2014-10-11_Master PIC Thesis_Léonard&deChazal_SANOFI_Public version

CLARA LEONARD -‐ SOPH IE DE CHAZAL MASTER P IC – SANOF I M2 THES I S

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August 2014

Master PIC – M2 Thesis: The scale up of breakthrough innovations: the case

of eHealth solutions at Sanofi.

Students: Clara Léonard & Sophie de Chazal

Company tutors: Emma Garde & Bruno Leroy

Academic Advisors: Pr.Midler & Pr. Charue-Duboc


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TABLE OF CONTENTS

EXECUTIVE SUMMARY......................................................................................................... 6

1. INTRODUCTION: CONTEXTUAL ELEMENTS AND THE DEVELOPMENT OF EHEALTH SOLUTIONS AT SANOFI.................................................................................... 8

A. SANOFI’S STRAGEGY OF GOING “BEYOND THE PILL” ...........................................................................................8

B. EHEALTH – A BRIEF OVERVIEW ...............................................................................................................................9

i. What are eHealth solutions?............................................................................................................................. 9

ii. Contextual trends driving eHealth development ..................................................................................11

iii. Players and competitors in the industry .................................................................................................12

C. SANOFI’S TRACK RECORD IN EHEALTH SOLUTIONS...........................................................................................12

2. HOW THE SCALE-UP TOPIC BECAME THE FOCUS OF OUR RESEARCH ......13

A. SCALE UP AS THE NEW CHALLENGE FOR OPERATIONAL TEAMS .....................................................................13

B. DEFINITION OF SCALE-‐UP: A TWO-‐DIMENSIONAL CONCEPT ...........................................................................14

3. OUR EXPERIENCE AT SANOFI..................................................................................15

A. OUR POSITION WITHIN THE COMPANY WHEN WE JOINED SANOFI AND THE RE-‐ORGANIZATION OUR TEAM UNDERWENT ..........................................................................................................................................................15

B. OUR ROLES WITHIN THE CSI & INTEGRATED CARE SOLUTIONS COE TEAMS...............................................18

i. Our missions as junior project manager on eHealth projects ..........................................................18

ii. Strategic work in the context of the division reorganization and the creation of the Center of Excellence...................................................................................................................................................................19

4. LITERATURE REVIEW................................................................................................20

A. HOW WE STRUCTURED OUR LITERATURE REVIEW: APPROACH THE SCALE UP FROM THREE DIFFERENT PERSPECTIVES...................................................................................................................................................................20

B. LITERATURE ON ADOPTION BY END-‐USERS........................................................................................................21

i. The diffusion of innovations ............................................................................................................................21

ii. Do innovations have intrinsic features that improve their rate of diffusion and thus their scalability? ......................................................................................................................................................................27

C. LITERATURE ABOUT ADOPTION BY INTERNAL ACTORS ....................................................................................31

i. The role of affiliates or subsidiaries in multinational corporations..............................................31

ii. Organizational innovation processes: balancing innovation and scale-up ..............................35

iii. The effect of management tools on employee behavior...................................................................36

D. LITERATURE ABOUT ADOPTION BY OTHER STAKEHOLDERS: THE ECOSYSTEM ALIGNMENT.....................38


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i. The ecosystem: definitions and characteristics ......................................................................................38

ii. Strategies to innovate successfully in a complex ecosystems: The art of interessement according to Akrich, Callon and Latour.............................................................................................................40

iii. Innovate and deploy an innovation with a network of supplier or partners: The input from Charue-Duboc and Jouini (2004)...............................................................................................................41

5. EMPIRICAL MATERIAL: AN IN-DEPTH ANALYSIS OF FOUR EHEALTH PROJECTS AT SANOFI ....................................................................................................................................42

A. SELECTION METHODOLOGY ..................................................................................................................................42

i. Why four projects?...............................................................................................................................................43

ii. Selection criteria and elements of differentiation between the projects ...................................43

B. INSIGHT COLLECTION: INTERVIEWS AND SELF-‐EXPERIENCE ..........................................................................47

C. PROJECT MONOGRAPHIES ......................................................................................................................................48

i. Babushka SMS .......................................................................................................................................................48

ii. Phosphorus Mission ...........................................................................................................................................53

iii. Project MORE ......................................................................................................................................................60

iv. Diabeo.....................................................................................................................................................................65

6. RESEARCH RESULTS: NATURE, CLASSIFICATION AND OUTPUTS ...............71

A. EMERGENCE OF 9 KEY POINTS AND CLASSIFICATION METHODOLOGY .........................................................71

B. HOW WE ADDRESS EACH POINT AND OUTPUT ...................................................................................................72

7. RESEARCH RESULTS: NINE KEY POINTS TO WATCH OUT FOR AND RELATED TOOLS TO SUCCESSFULLY SCALE-UP EHEALTH SOLUTIONS IN AN MULTINATIONAL CORPORATION .....................................................................................................................73

A. KEY POINTS TO ENSURE ADOPTION BY END USERS ...........................................................................................73

i. Key Point 1: Intrinsic features of the solution have an impact on diffusion...............................73

ii. Key Point 2: Solution architecture and modularity can influence scale-up potential..........79

iii. Key Point 3: Solution must be monitored to ensure further adoption .......................................90

B. KEY POINTS TO ENSURE ADOPTION BY INTERNAL ACTORS ..............................................................................96

v. Key Point 4: Make individuals in the company feel involved on the project .............................96

vi. Key Point 5: Rationalize the choice of the first affiliate to ensure further deployment... 100

vii. Key Point 6: Communicate and make the solution visible internally ..................................... 107

C. KEY POINTS TO ENSURE ADOPTION BY OTHER STAKEHOLDERS IN THE ECOSYSTEM............................... 109


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i. Key Point 7: Build a relevant value proposition for all solution stakeholders ....................... 109

ii. Key Point 8: Elaborate a tailored promotion plan............................................................................ 116

iii. Key Point 9: Rationalize the choice of suppliers and partners when scaling-up................ 122

8. RECOMMENDATIONS FOR USE OF THE NINE KEY POINTS......................... 130

A. HOW PROJECT MANAGERS COULD USE THE NINE KEY POINTS .................................................................... 130

B. APPLICATION: SELECTION OF ONE PROJECT AND EVALUATION OF SCALE-‐UP POTENTIAL THROUGH OUR 9 KEY POINTS.................................................................................................................................................................... 131

9. CONCLUSION .............................................................................................................. 132

BIBLIOGRAPHY ................................................................................................................. 136

10. TABLE OF ILLUSTRATIONS................................................................................. 134


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WE WOULD LIKE TO ADDRESS OUR WARMEST THANKS TO:

• Emma Garde and Bruno Leroy, our company tutors, for their support and their trust,

and whose vision and pragmatism helped us orientate our research in the most

valuable way

• Florence Charue-Duboc and Christophe Midler, for their sound advices and

guidance all along our project

• Armelle Blaise, Jean-Yves Bailly, Corinne Monteil, Salah Mahyaoui, Antoine Barbot,

Jean-Marc Bourez for their availability and the time they took to answer our

multitude of questions

• The whole team of CSI and of the new Center of Excellence for Integrated Care,

who gave us the opportunity to participate in their projects and gave us important

responsibilities

• All of our teachers from the master, who provided us through their classes with

useful tools and mind frameworks to better analyze our experience in the company

• The IS Team for their friendly initial support

• All of our co-workers at Paris Sud who made that experience so enriching, both from

a professional and personal perspective


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EXECUTIVE SUMMARY

This thesis paper is the fruit of a collaboration between the Ecole Polytechnique’s

Master PIC – a Master’s program in which students carry out research on the management

of innovation in companies – and Sanofi, one of the largest pharmaceutical groups in the

world. As Master PIC students, we joined Sanofi during one year to simultaneously work on

the development of eHealth solutions and to analyze the innovation processes in place.

Sanofi is a large multinational organization that is organized in a matrix structure, with

both geographic and business line divisions. It is highly decentralized and innovations such

as eHealth solutions can be developed by a variety of entities within the company: R&D, a

corporate solutions development team that we were a part of, and local affiliates.

In the context of a decentralized organization that is present in a large diversity of

markets, understanding the mechanisms that are at work when an innovation such as an

eHealth solution is scaled up has proven to be a key issue. In particular, we found that

existing definitions and business literature on the “scale-up” topic did not reflect our

understanding of the scale-up mechanism at Sanofi.

Our Master’s thesis was written to examine the topic of scaling up innovations more

closely, and thus our research question is the following: “How to manage the scale-up of

breakthrough innovations? The case of eHealth solutions at Sanofi.”

To answer this question, we studied four eHealth solution projects at Sanofi through

the lens of management literature that focuses on the adoption of innovation by end users,

by internal actors in a company, and by external stakeholders a company relies on when

scaling up an innovation.

The result of our research is nine key points that have proven crucial to look out for

when scaling up an eHealth solution. Some points involve the application of existing tools or

frameworks we found in the relevant literature to our projects; other points introduce useful

conceptual frameworks to analyze scale up scenarios, or simply raise awareness on key

issues that should not be overlooked.

We proceed in the following order in this Master’s thesis:

1. First, we give contextual elements on the development of eHealth solutions at Sanofi,

detailing the company and the eHealth market history;


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2. Then, we clarify how the scale-up topic became the focus of our research, and we clarify

our understanding of the term, which articulates both notions of deployment and

diffusion;

3. We explain what role we played at Sanofi this past year;

4. We proceed by explaining the methodology behind our literature review before

summarizing the literature we rely on for our analysis;

5. We then carry out a detailed description of the empirical material we gathered for our

research during our time at Sanofi, namely the detailed descriptions of four eHealth

solution projects at Sanofi;

6. We then detail our research results, the 9 Key Points that closely analyze the challenges

that project teams are faced with when scaling up eHealth solutions.

7. Finally, we detail how project leaders who are trying to scale up eHealth solutions or

similar solutions can leverage these Key Points.


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1. INTRODUCTION: CONTEXTUAL ELEMENTS AND THE DEVELOPMENT OF EHEALTH

SOLUTIONS AT SANOFI

a. SANOFI ’S STRAGEGY OF GOING “BEYOND THE P I LL”

In 2013, Sanofi was ranked as the fifth biggest pharmaceutical group in the world with

net sales revenue of approximately €33 billion. Sanofi has over 110,000 employees around

the world, and is present in over 100 countries. Its main legacy companies are Sanofi-

Synthélabo and Aventis, which merged in 2004 to form Sanofi (Sanofi, 2013).

Starting 2009, Sanofi made a series of acquisitions within the healthcare industry in

order to become an integrated, diversified, global healthcare company. The company carried

out these acquisitions in order to decrease its reliance on “blockbuster drugs” (drugs with

over $1 billion in global sales) and to develop more stable and sustainable sources of

revenue and earnings growth. The issue with relying on “blockbuster drugs” is that sooner or

later, the company is exposed to a “patent cliff”: once the patents for the blockbuster drugs

expire, revenues decline sharply as the drug is faced with steep competition from cheap

generics, in an environment in which third party payers and healthcare authorities seek to

reduce costs(Sanofi, 2012).

Sanofi has since then invested in seven growth platforms – Emerging Markets,

Diabetes, Vaccines, Consumer Health Care, Animal Health, New Genzyme (which develops

treatments for rare and genetic diseases), and Innovative Products – which are less subject

to intense competition from generics and have diversified Sanofi’s activity and customer

base.

Furthermore, the company is moving away from a pure product-oriented perspective

and starts developing service-oriented solutions. The purpose of these solutions, also known

as Integrated Care, is to improve user satisfaction as well as access, quality, and efficiency

of care (WHO definition). When using new technologies to do so, we fall in the category of

eHealth.

The development of the BGStar® and iBGStar® glucose meters by Sanofi and its

partner AgaMatrix perfectly illustrates this development. These are the first FDA-cleared

glucose meters that seamlessly connect with the iPhone and the iPod touch, and are what

we call eHealth solutions. The solutions are exclusive to Sanofi and are synergetic with the

rest of its diabetes portfolio. They come with software that allows patients to improve and

simplify their diabetes management(Sanofi, 2012).


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Figure 1: Images of the iBGStar glucose meter

b. EHEALTH – A BR IEF OVERV IEW

i . WHAT ARE EHEALTH SOLUT IONS?

Nowadays, many terms are in use to talk about digital innovations in healthcare.

Concepts such as “telehealth”, “telemedicine” or “mobile Health” are now commonly used to

mention these new solutions. “Telehealth” and “telemedicine” refer more to solutions that

involve an actual medical act provided from the distance, while “mobile Health” refers only to

solutions that leverage mobile technologies such as smartphones. We prefer using the term

of eHealth, which in our sense encompass a broader spectrum of innovations.

By eHealth solution, we mean all solutions using information and communication

technologies aiming at improving health, wellness and autonomy.

Technologies

The technologies used for eHealth solutions can be very different from one solution to

another, and range from simple websites to complex systems with biosensors and highly

technological devices. Here is an overview of technologies that have already been used for

eHealth solutions, from the less complex to the most complex

-‐ Website

-‐ Mobile app

-‐ Call center

-‐ Automatic SMS reminders


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-‐ Smart packaging

-‐ Medical algorithm

-‐ Device

Type of solutions

The particularity of eHealth solutions lies in the fact that they can bring value all along

patient pathway and contribute to building an integrated care system, from prevention to

treatment follow-up.

Figure 2: the Patient Pathway

During our project at Sanofi, we have worked on a comprehensive segmentation of these

solutions, in order to classify them by type. From the reading of many reports trying to

analyze and segment the eHealth industry, as well as from our own experience at Sanofi, we

believe the following segmentation is the most relevant for Sanofi’s offer.

-‐ EDUCATION: solutions that educate patients on a specific pathology

-‐ COACHING: tailored educative solutions targeting behavior change

-‐ SCREENING & DIAGNOSIS: solutions that help screening and diagnose patients

-‐ ADHERENCE: solution or program that explicitly aims at improving patient’s

compliance to treatment.

-‐ REMOTE MONITORING: Solution that enables the patients to collect (manually or

automatically) data during his treatment

-‐ CARE COORDINATION: solution that aims at coordinating care among healthcare

professionals

-‐ DATA ANALITICS: Solution that analyzes collected data

Examples of eHealth solutions can be found in section 5.C, in which we describe in details

the features and development history of four of Sanofi’s solutions.

Prevention Screening Diagnosis Treatment administration

Treatment follow-‐up


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i i . CONTEXTUAL TRENDS DR IV ING EHEALTH DEVELOPMENT

Along with corporate strategic concerns, external factors are pushing companies like Sanofi

to develop eHealth solutions.

Social and demographic trends

-‐ Aging population (more people being dependent and requiring care)

-‐ Increasingly more people suffer from chronic diseases (eHealth solutions can

improve treatment follow-up)

-‐ Medical desertification and inequality in access to care (eHealth can help providing

care from the distance)

Global transformation

-‐ Urbanization (increased connectivity, interconnected networks)

-‐ Value shift from manufacturing to services

-‐ Rise of emerging markets with inequality of access to care

Economic trends

-‐ Budget constraints for medical authorities (eHealth can contribute to decreasing

healthcare cost for payers)

Consumer empowerment

-‐ Switch from passive patient to active health consumer

-‐ Peer to peer communication

Health practices

-‐ Compliance issues

-‐ Switch from healthcare (treatment) to health management (prevention and early

intervention)

Technological trends

-‐ Increased adoption of technology for health-related purposes

-‐ Acceptability of Self-Measurement

-‐ Development of the internet of things

-‐ New market players coming from the telco industry, bringing efficient new

technologies

-‐ Innovation in electronics and textile industries (nanotechnologies, flexible chips, smart

textiles …) that can be used in eHealth solutions


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i i i . PLAYERS AND COMPET ITORS IN THE INDUSTRY

Traditional healthcare players such as pharmaceutical companies have to deal with

new entrants coming onto the market of eHealth solutions. These newcomers entered the

healthcare industry even though it was not originally their core industry, yet they master a

know-how or technology that is necessary to build, develop and run eHealth solutions.

Because eHealth solutions are made of a wide variety of components (cf. chart below), a

multitude of actors, each of which is specialized in one or more components, are now playing

on the market. Dealing with other actors is now necessary if one wants to develop a

complete solution, and partnership becomes the rule.

Players on the market can be segmented as follows. Examples of companies are listed

below each category.

Sorin

(pacemakers)

Google (Google

lenses)

Philips

Withings

Orange

Business

Services

Docapost

Santech

Voluntis

Manzalab

Be-Patient

Voluntis

Biomouv

Liquidweb

Europe

Assistance

AXA

Handle my

health

Patientys

Janssen

Novartis

Alere

Sanofi

Roche

Figure 3: eHealth market players’ segmentation

c. SANOFI ’S TRACK RECORD IN EHEALTH SOLUT IONS

Sanofi has a track record in the development of eHealth solutions; we’ve identified

roughly one hundred solutions or patient programs that include a digital element within

Sanofi. This list is not necessarily exhaustive, because there is currently no comprehensive

global database of eHealth initiatives within Sanofi.

The solutions we identified vary in complexity, geography, and development stage.

Indeed, solutions developed by Sanofi teams can be as simple as a website giving

information on a disease and the corresponding Sanofi treatment, and as complex as

Diabeo, a mobile application that can help Diabetes patients adjust their insulin doses

Hardware / Sensors

Data Hosting /

transmission Software /

App Smart medical systems

Call centers Integrators


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according to their reported diet, exercise, and glucose levels with the help of a proprietary

algorithm (cf. section 5.C.iv for more details on Diabeo). Digital solutions have been

launched in all Sanofi geographic areas, though the majority of solutions are in Europe.

Finally, as can be seen in the graph below, some solutions are only at the ideation stage –

the very beginning of the project – while other solutions have been scaled up to new

subsidiaries.

Figure 4 : Illustration of the state of advancement of the Sanofi eHealth solutions we identified

The above graph brings to light the fact that Sanofi has actually been quite successful

in bringing eHealth solutions to the launch stage, as is shown by the fact that Sanofi has

launched about one hundred solutions in the past couple of years and has many other

projects in the pipeline.

2. HOW THE SCALE-‐UP TOPIC BECAME THE FOCUS OF OUR RESEARCH

a. SCALE UP AS THE NEW CHALLENGE FOR OPERAT IONAL TEAMS

In our view, the graph of Sanofi’s track record in eHealth solutions in the previous

section highlights the fact that scaling up – launching solutions across several geographies

or therapeutic areas to reach more patients – is the next big challenge for the company. The

graph shows that Sanofi has been successful in launching eHealth solutions, but that for the

time being we have only identified two solutions that have been scaled up throughout the

company. Scaling up is a challenge the company is only facing now because Sanofi only

started developing eHealth solutions in the past couple of years, and so hadn’t yet reached

the scale-up stage of development.


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b. DEF IN IT ION OF SCALE-‐UP: A TWO-‐DIMENS IONAL CONCEPT

When reviewing management literature for a definition of scale-up that we could base

our research on, it appeared that very few articles were actually dealing with the concept of

scale-up itself, and when they were, a parallel with our experience in project management for

eHealth solutions could not easily be done. For example, the WHO published guidance to

scale-up health services innovations(World Health Organization, Department of Reproductive

Health and Research, 2009). Even though similarities exist between both types of

innovations (eHealth and services or programs), the later only concerns public health

initiatives, for which challenges differ greatly from those encountered by a multinational

company like Sanofi in the launch of a new solution.

The WHO defines scale-up as “deliberate efforts to increase the impact of health service

Innovations successfully tested in pilot or experimental projects so as to benefit more people

and to foster policy and programme development on a lasting basis”.

Although the aim of reaching more end-users on a long-term basis is similar to the

one of a multinational corporation (MNC) in the case of eHealth solutions, an important

dimension is missing. Unlike public health initiatives that are usually tested in a very specific

location and then scaled-up on a larger scale in the same country or region, eHealth

solutions are tested or launched in a given country and then scaled-up in other geographical

areas. This raises the issue of the optimal internal organization and relationships between

corporate structures and affiliates to successively launch a solution by different entities. Yet

this aspect is overlooked in the WHO definition.

Therefore, we elaborated a definition for scaling-up that matches with our own

experience at Sanofi. This definition is composed of two dimensions, internal and external

adoption.

Internal adoption: DEPLOYMENT.

As defined by Charue-Duboc and Jouini (Charue-Duboc, Le déploiement d’innovations inter-

filiales au sein d’une multinationale, 2014), deployment is the process by which affiliates

located in different geographical areas successively adopt and commercialize an innovation

while adapting it to local specificities.


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Scale-up depends indeed from the adoption of the solution by affiliates internally, which

adapt and launch it in their region. In the case of breakthrough innovations, deployment can

be a tedious process, as local managers can show reluctance to take the risk of launching an

innovative solution that greatly differs from their usual core business.

External adoption: DIFFUSION

Everett Rogers’ definition (Rogers, 1983) is appropriate to define the diffusion as a process

of external adoption: “Diffusion is the process by which an innovation is communicated

through certain channels over time among the members of a social system”.

The success of scaling-up thus depends also on the pace of adoption of the solution by end-

users in a given geographical area.

The concept of scaling-up can therefore be illustrated as follows:

Figure 5: Scale-up concept graph

This segmentation in two dimensions, internal deployment and external diffusion, will

structure our research and help us analyze some critical points for scale-up.

3. OUR EXPERIENCE AT SANOFI

a. OUR POS IT ION WITH IN THE COMPANY WHEN WE JO INED SANOF I AND THE RE-‐

ORGANIZAT ION OUR TEAM UNDERWENT

When we joined Sanofi in 2013, we were integrated into the Customer Solutions &

Innovation (CSI) team. The team’s mission was to develop healthcare solutions that are


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either complementary to the division’s pharmaceutical offerings or marketable as separate

commercial opportunities. These solutions could include services or medical devices, or

combinations of the two. Following a healthcare services landscape study that the CSI

carried out in collaboration with the Sanofi Information Solutions (IT) team in 2012, the CSI

team decided to focus its efforts on developing the three following types of solutions,

because they are most promising in terms of potential profitability, patient engagement, and

potential market growth:

• Coaching apps & casual games (games that are designed to educate patients

about their disease and help them make better choices): they will be designed to provide

relevant disease treatment information to patients. The solutions that have already been

developed are available free of charge to patients. It is unclear what impact these solutions

will have on Sanofi revenues, but the main objective is to add value to Sanofi medications by

eventually pairing these solutions with them. These solutions could indirectly increase patient

adherence to treatments, which could in turn potentially increase medication sales and offset

development costs.

• Adherence solutions: are designed to have a direct impact on patients’ adherence

to medications. They will initially be provided free of charge to patients using Sanofi products.

Some adherence solutions incorporate devices, like connected pill bottles, which makes the

development costs higher than those of coaching & serious game apps. Because non-

adherence to medications is a very wide spread phenomenon, and because pharmaceutical

companies carry a significant part of the economic burden of non-adherence (in the form of

foregone medication sales), it makes sense for Sanofi to develop and commercialize

adherence solutions.

• Telemonitoring solutions: these are solutions and devices that allow healthcare

providers to remotely monitor patients. These solutions are costly and difficult to put in place:

they involve feedback loops from patient data, they are often considered as ‘medical devices’

by regulatory authorities and require official approval, and their impact on adherence still

needs to be proven. These solutions could eventually be proposed to patients as stand-alone

healthcare solutions and be reimbursed by payers, once their medico-economic rational is

proven.

Our team was a part of the broader Patient Centered Solutions (PCS) division. The

PCS division’s scope mainly covered the following treatment areas: cardiovascular health,

renal health, bio surgery, and fibrosis & inflammation. The solutions that the CSI team

developed were thus geared towards these therapeutic areas rather than those of other

divisions, such as diabetes or oncology. The PCS division also included corporate functions


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that worked across all divisions (notably the market access and pricing teams). The PCS

division itself was part of the Global Operations entity, which includes all the corporate

commercial divisions (PCS, Diabetes, Oncology, CHC, Generics).

Figure 6: Sanofi Organization Matrix 2013 (simplified)

At the start of 2014, the Global Operations team reorganized its divisions. The

principle change was to remove the support functions within each division and to group them

into Centers of Excellence (CoE) that will work across all divisions. This led to the creation of

the following Centers of Excellence:

- Chief Patient Officer CoE: this is a new function dedicated to better understanding

patient needs and their healthcare experience, in order to find new ways to

improve the Sanofi offering

- Marketing CoE: this marketing support function will work across all divisions

- Value Development & Market Access CoE: this team consists of cross-division

Market access and pricing teams

- Integrated Care Solutions CoE: This CoE includes our former CSI team, as well

as some new members both in the US and France who have extensive medical

devices and services development experience. The integrated care solutions

COE will have a scope that spans across all divisions.


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Figure 7: Sanofi Organization Matrix 2014 (simplified)

Unfortunately, as of August 2014 we cannot detail how the changes will effectively

change the team’s missions (beyond widening the therapeutic area scope) because the re-

organization has yet to be fully implemented.

b. OUR ROLES WITH IN THE CSI & INTEGRATED CARE SOLUT IONS COE TEAMS

i . Our MISS IONS AS JUNIOR PROJECT MANAGER ON EHEALTH PROJECTS

During our time at Sanofi, we gained operational, first-hand experience on some of

the eHealth solutions that the integrated care team was working on by taking on the roles of

junior project managers. Sophie worked principally on the Babushka SMS project, while

Clara focused on the MORE project, both of which are described in detail in projects

monographies (5.C). As junior project managers, we were responsible for coordinating the

efforts of all team members – affiliate teams, colleagues in the global corporate team, and all

the third parties we might have hired or have been partnering with. Furthermore, we ensured

that the set timeline was followed as closely as possible, did troubleshooting when

necessary, and gave our input on different aspects of the projects. This first-hand experience

allowed us to gain a rich understanding of what obstacles a project team is faced with when

trying to scale up a solution or when trying to build a scalable solution.


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Furthermore, we carried out research on the CSI focus areas that were assigned to

us – Clara carried out extensive research on the telemonitoring solution market while Sophie

focused on adherence solutions.

i i . STRATEGIC WORK IN THE CONTEXT OF THE D IV IS ION REORGANIZAT ION AND

THE CREAT ION OF THE CENTER OF EXCELLENCE

CREATING A DATABASE OF EX IST ING INTEGRATED CARE SOLUTIONS

WITHIN SANOFI

In order to work on the new Center of Excellence for Integrated Care’s strategy, our

team wanted to analyze the integrated care solutions within Sanofi. Indeed, until the Global

Operations reorganization, the team had been limited to developing solutions for the

therapeutic areas covered by the PCS division, and was not fully aware of what other

projects were being carried out in different divisions and geographical areas.

Our team thus proceeded to collect information on existing solutions within Sanofi,

and then we cleaned the data and classified all the entries, according to about a dozen

criteria. Some examples of sorting criteria are the technology used, the place the solution

was launched and the therapeutic area. This exercise allowed us to identify several work

packages for the new Center of Excellence for Integrated Care.

ASSESS ING THE MAIN CHALLENGES EHEALTH SOLUTION PROJECT TEAMS

FACE & DEVELOPING RECOMMENDATIONS FOR THE COE

The above database analysis helped determine the six following areas that the

Center of Excellence for Integrated Care could work on:

- Business Models: almost all solutions developed are free, and the vast majority

target only patients (vs physicians, payers)…The CoE for Integrated Care could

help affiliates refine their business models and develop processes for solutions

targeting reimbursement.

- Medium & Technology: The CoE for Integrated Care can scout technologies on

the behalf of affiliates looking to develop solutions.


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- Integrated care & value proposition: support the affiliate and brand teams as

they work on demonstrating the positive impact of their solutions.

- Partnerships: support teams by scouting and proposing partners with whom to

develop solutions.

- Internal organization and synergies: improve data collection on projects, serve

as a catalyzer to share and spread best practices throughout Sanofi.

4. L ITERATURE REV IEW

a. HOW WE STRUCTURED OUR L ITERATURE REV IEW: APPROACH THE SCALE UP FROM

THREE D IFFERENT PERSPECT IVES

When we began our literature review, we realized that very little material is available on

on the notion of scaling up itself. We therefore came back to our definition of scale up

(defined in 2.b) to orientate our research. We had indeed defined scale up as a combination

of two dimensions, the adoption by external users (diffusion) and the adoption by internal

actors (deployment). We therefore segmented our review according to the perspective

considered when looking at adoption (external vs. internal). On the topic of deployment, we

focused on literature about internal organization. As for the topic of diffusion, we mostly

found general literature on the diffusion of innovation, as well as material on the

characteristics an innovation should have to be quickly and easily diffused in a given

population. However, this literature only considers the process of adoption from the end-user

outlook. Yet in our sense, the very specificity of launching breakthrough innovations in the

healthcare industry, is that the adoption by a wide multiplicity other external stakeholders is

required to ensure diffusion. We therefore dig into literature about ecosystem alignment, in

order to better understand the notion of ecosystem, the relationship between actors and the

way of reaching out to them when scaling up a solution. Our literature review is therefore

structured as follows:

Literature on adoption by end-users

-‐ General literature on the diffusion of Innovation


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-‐ Do innovations have intrinsic features that improve their rate of diffusion and thus

their scalability?

Literature on internal adoption -‐ The role of affiliates or subsidiaries in multinational corporations

-‐ Organizational innovation processes: balancing innovation and scale-up

-‐ The effect of management tools on employee behavior

Literature on adoption by other stakeholders: understand the ecosystem -‐ The Ecosystem: definitions and characteristics

-‐ Strategies to innovate successfully in a complex ecosystems

-‐ Innovate and deploy an innovation with a network of supplier or partners

b. L ITERATURE ON ADOPT ION BY END-‐USERS

i . THE D IFFUS ION OF INNOVATIONS

THE BASS MODEL (1969) : THE TRAD IT IONAL D I FFUS ION MODEL OF INNOVAT ION

FOR A PHARMACEUT ICAL COMPANY

Diffusion-of-innovation theory includes a set of models that aim to represent or predict

the adoption patterns of new technology, products or ideas by society. To analyze models

that would be applicable to the diffusion of eHealth solutions, we considered that the first

step was to look at the diffusion models a pharmaceutical company might use for its core

business, which is drug production and marketing. In a study conducted in Australia in the

frame of the BMC Health Service Research(Dunn & Al, 2012), Dunn & Al applied the Bass

diffusion model to explain the adoption of new medicine. Dunn explains that clinical evidence

is not the only factor to influence the adoption rate of new drugs by Healthcare Professionals;

this diffusion process is also strongly influenced by a complex set of social interactions and

regulation forces.

The Bass Diffusion Model, which is probably the most common mathematical

representation of diffusive adoption, can to some extent, be used in the case of drug diffusion.

This model describes the number of new adopters over time, by distinguishing the adoption

through external and internal forces.

In this model, Bass considers that adopters of a new product can be classified in two

categories: the innovators, who have a high degree of innovativeness, and the imitators (as

shown in the graph below)


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Figure 8: Bass diffusion model

The innovators are individuals that are attracted by novelty per se, and can be easily

convinced to adopt the new products. They are in fact interested in the intrinsic

characteristics of the new product or service. The imitators, on the other hand, only adopt

innovation once they are convinced of the value or effectiveness of the new product, after

having seen or heard innovators who already adopted it. In other words, the model is based

on the assumption that potential adopters of an innovation are influenced by two types of

factors: the exogenous, or external factors which are directly related to the innovation itself,

and the endogenous, or internal factor, which can be understood as social contagion.

Figure 9: Bass diffusion model according to Dunn

In the case of the diffusion of new medicine, as Dunn states, exogenous factors can

be external regulation concerning a drug or the clinical evidence produced during former

official clinical trials, whereas endogenous factors can be word-of-mouth between Healthcare

professionals, bottom-up pressure by patients who heard about the new drug, mass-media

communication about the positive effect of a new medicine etc… Even though quantitative

and population wise analyses about adoption rate and speed of new healthcare practices are

rare, this model is a good basis to understand how new drugs have traditionally spread in the

medical population.


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However, eHealth solutions are not the core activity of pharmaceutical companies

and another model might be necessary to describe their adoption process. Because eHealth

products are new digital technologies that healthcare professionals or patients are not

familiar with in the frame of their daily care activity, the process of adoption and diffusion is

more complex. In this sense, the models proposed by Rogers and Moore give us some

complementary elements to better understand the reality.

THE MECHANISM OF D I FFUS ION ACCORD ING TO ROGERS AND MOORE

Both Rogers and Moore present the mechanism of diffusion of an innovation as a

dynamic process of adoption by successive groups of the target market, defined by specific

characteristics. Rogers defines the diffusion as a process by which an innovation is

communicated through certain channels over time among the members of a social system.

Rogers (Rogers, 1983) also describes the innovation as a sequenced diffusion by 5 sub-

groups of users, which seems more appropriate than Bass’ model to deal with digital

technologies, which are completely new to the health Industry, known to be pretty

conservative and a slow sector to move. The classification is the following (graphic

representation is presented below)

-‐ The innovators (risk takers): They are the “nerdy” ones, always keen on trying new

technologies. They are not price sensitive and have few regards for the actual

evidence concerning the innovation (which could be clinical evidence for eHealth

solutions).

-‐ Early adopters (hedgers): They are visionaries and perceive the innovation and the

technology as a way to gain a competitive advantage. In the case of eHealth

solutions, they are the ones arguing the fact that these new health innovations are a

solution to tackle issues such as medical desertification, the rise of public healthcare

expenses, or population aging. They see these innovations as a potential solution to

the industry’s problems, and are ready to heavily invest in it, without having

exaggerated expectations. Early adopters are usually opinion leaders and are well

socially connected in their local environment.

-‐ Early majority (waiters): They are the pragmatic ones. They watch the early

adopters and will only adopt the technology when its effectiveness and added value

has been proven. They are much more risk-averse than those in the two previous

categories.


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-‐ Late majority (skeptics): They are more conservative, averse to the risk and very

price sensitive. They usually adopt the innovation once it has become a real

commodity and has been simplified for use as much as possible. They will adopt the

innovation when it appears to be the new standard of practice (in the case of

healthcare).

-‐ Laggards (slowpokes): They are the last group, for whom, as Rogers says, “the

point of reference…is the past.”

If this model seems to be in line with reality as far the different groups are concerned, it

presents the diffusion a continuous and self-evolving process. Yet, in the case of disruptive

innovation like telemedicine solutions, which have the potential of completely transforming

the way care is delivered and healthcare practice is carried out, the innovation requires

action and energy to spread from one group to the other. In Moore’s conception, the real

challenge is to move from early adopters to early majority: to cross “the chasm”.

Continuing Rogers’ work on the diffusion, Moore (Moore, 1991) uses the same

classification of adopters. However, the real challenge in the diffusion of an innovation lies in

what he calls “the chasm”. Moore actually noticed that many new products or services were

adopted quite easily by the first two groups (innovators and early adopters), but failed to

reach the wider part of the population, the more pragmatic one that did not see the value

present in the innovation. In these cases, companies failed to transform an innovation or high

tech product that attracted innovation-friendly people into a comprehensive and convenient

solution that met the needs or expectations of the majority.

Figure 10: Moore's diffusion chasm

In order to successfully cross the chasm, Moore gives several recommendations:

- Focus before all on a niche market and become a leader on this market.

- Then deploy from niche markets to other niche markets, using one’s leading position

on one market to convince the population on other niche markets. This is, according


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to Moore, the ‘Bowling Alley” phenomenon. Only this technique can, according to him,

make a company successfully cross the chasm.

- This leads afterwards to “the tornado”, which is the massive adoption by the market,

followed by the commoditization of the innovation.

Yet, in the case of Sanofi, the concept of niche market is not clearly defined for

innovative solutions, and it would be interesting to find a way to apply Moore’s theory to the

diffusion of eHealth solutions. We see several ways to interpret it:

The diffusion model could apply to the diffusion of the innovation inside Sanofi by

successive affiliates. The adoption would then refer to the acceptance of the affiliate to

launch the innovation on its territory. Just as in Moore’s model, some affiliates can serve as

example and be “key opinion leaders” and can lead and promote the innovation diffusion in

other affiliates. A “niche” could thus be understood as a specific division or territory.

In the healthcare sector, a niche can also refer to a specific pathology, or even directly to

a drug (since some of the eHealth solutions are directly linked to specific medicines). A

company can become the leader on a defined pathology with a specific technology, and then

either transposes the technology to another pathology (if the technology is pathology-

agnostic) or adapt the solution so it can fit the needs and care-patterns of another pathology.

This could be a good illustration of the application of the concept of “bowling alley” applied to

the Healthcare industry. But we will have the opportunity to discuss this possible analysis

based on experimental research on Sanofi’s projects.

Other authors have analyzed, in the continuity of Rogers and Moore, the specific topic of the

healthcare industry. This is in particular the case of Berwick, who theorized the process of

dissemination of innovation in Healthcare.

BERWICK: D ISSEMINAT ING INNOVAT IONS IN HEALTHCARE

A very slow pace of adoption characterizes the sector of Healthcare. As Berwick

(Berwick, 2003) writes, “in healthcare, invention is hard, but dissemination is even harder”.

Even when an evidence-based innovation is brought to market, its diffusion is far from being

assured. Thus, Berwick proposes seven recommendations to succeed in disseminating

innovations in health care:

1. Find sound innovations: in healthcare, more than in other industries,

innovators tend to publish their work and scientific journals have a great


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influence. Medical communities are dominated by early and late majority

clusters (to use Rogers classification), which need to have solid evidence and

do not trust remote and unknown sources of authority.

2. Find and support innovators: Innovators are crucial, because they are the

hooks in the target market. Yet, they may not be the easiest individual to deal

with, as they are, in the case of physicians, usually not very invested in local

networks, can be abrasive, are not renowned as top-tier doctors …

3. Invest in early adopters: Because they are the key opinion leaders and the

rest of the medical community watches them, early adopters are of great

value. They are often the likeliest target of pharmaceutical companies, since

the latter have a direct access to them through sales rep – an advantage that

Sanofi can definitely develop. The aim is thus to foster communication and

interaction between early adopters and innovators, so that Early adopters can

try the new solution and inform the rest of the Healthcare community about it.

On the contrary of Moore, Berwick do not assume that focusing on a niche is

necessary. The important is to concentrate on the right people at the right

moment.

4. Make early Adopter activity observable: Because the interface between

early adopters and early majority is crucial, companies that try to spread their

innovations should encourage social interaction between these two groups,

since academic publication is not enough to enhance the pace of diffusion.

Thanks to the power of one-on-one detailing of new drugs to physicians,

pharmaceutical companies have the possibility to build face-to-face network

and foster interactions between the groups directly.

5. Trust and Enable reinvention: The principle lying under this rule is simply

that an innovation must be adapted locally to be successful. Berwick quotes

Van de Ven on this topic “An initial idea tends to proliferate into several

divergent and parallel ideas during the innovation process”. To do so, leaders

should also accept a lean project management and mere resistance if

products or services need to be “reinvented”. Berwick also believe that

individuals inside the company should be incentivised to take ideas from

elsewhere, transform them and adapt them for a new market or purpose.

Rogers or Moore did not describe this theory on internal organization and

management tools, though it is a key element for a successful diffusion.

6. Create Slack for change: The diffusion of an innovation is not an

autonomous process and requires a real amount of time and money, which is


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a real challenge in healthcare given current cost pressure in the industry.

“Leaders who want innovation to spread must make sure that they have

invested people’s time and energy in it”

7. Lead by example

It seems that Berwick’s recommendations are specifically suited for innovation

targeting Healthcare professionals in particular. EHealth solutions however can be sold

directly to patients in order to make them manage their own health. In that case, the rules

need to be adapted, and the diffusion model to follow might actually be closer to Moore’s and

Rogers’, who works in the frame of B to C diffusion of innovations.

i i . DO INNOVATIONS HAVE INTR INS IC FEATURES THAT IMPROVE THE IR RATE OF

D IFFUS ION AND THUS THE IR SCALABIL ITY?

In this section, we delve into existing literature on the effect that an innovation’s

intrinsic characteristics can have on its rate of diffusion. We hope that this literature review

will provide us with a framework to analyze the eHealth solutions developed at Sanofi, as we

try to understand what leads to the successful scale-up of a digital health solution.

In order to highlight the impact that the way an innovation is perceived can have on its

diffusion, Berwick(Berwick, 2003) cites Everett Rogers’ Diffusion of Innovations(Rogers,

1983), in which Rogers claims that between 47% and 87% of the variance in the rate of

spread of an innovation can be predicted by how the innovation is perceived by potential

adopters. Berwick then presents Everett Rogers’ “five factors”: the five perceived

characteristics of an innovation that most influence the speed at which it spreads. These five

perceived attributes are listed below.

1. the perceived benefit of the innovation: an innovation will spread faster when potential

adopters believe that using it will help them;

2. the compatibility of the innovation with the “values, beliefs, past history, and

current needs of individuals”: innovations must be compatible with the existing

practices of users, must resonate with their needs, and must be in line with their belief

systems;

3. the complexity of the proposed innovation: innovations which are difficult to

understand and implement tend to have a slower rate of adoption;


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4. the trialability of the innovation: whether it can be tested on a small scale before full

implementation, like taking a car for a test-drive;

5. the observability of the innovation: how easy it is for potential adopters to observe

others using the innovation first.

While these five intrinsic characteristics of innovations pertain to the rate of diffusion of

innovations rather than their scalability – the latter topic being the focus of this paper – we

believe that using Rogers’ five factors could help us analyze the ‘intrinsic potential’ each

solution has to be successfully scaled up.

In “Explaining Diffusion Patterns for Complex Health Care Innovations”, Jean-Louis

Denis et al(Denis & Al, 2002) study the dissemination processes of four different health care

innovations, these four different cases having been selected according to whether they were

adopted by healthcare professionals rapidly or slowly, and whether scientific evidence of

effectiveness was available before or after the solution was adopted (“leading evidence”

versus “lagging evidence”).

Following the analysis of these four different cases, Denis & al propose an alternative

conceptual framework of the diffusion process, which is illustrated in the figure below.

Figure 11: Denis et al's conceptual model of the diffusion process

Denis & al suggest that innovation is not a linear process, but rather an interaction

between the innovation (with its key characteristics) and the adopting system that is made up

of heterogeneous actors who have different sets of values, interests and power

dependencies. To illustrate this, we can take the example of an innovation that is meant to

be used in a hospital setting, such as a new surgical tool, a new procedure. The adopting

system would be the hospital as a whole, and the actors within the system could be hospital

administrators, physicians, and patients. The actors have different criteria when deciding to

adopt the solution or not, and their preferences carry different weights when it comes down


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to the hospital’s decision to adopt the innovation or not. The innovation has characteristics

that bring different benefits and risks to the different actors. Thus, the rate of diffusion

depends on how well the innovation characteristics ‘map’ onto the adopting system.

Denis and al describe this relationship in the first proposition of their paper:

“Proposition 1: the more the pattern of benefits and risks surrounding the innovation maps

onto the distribution of interests, values, and power of the actors in the adopting system, the

easier it is to create a coalition for adoption and the faster the adoption process.”

Thus, an innovation will have more chances of spreading if it brings high benefits to the most

influential actors in the adopting system rather than to actors that don’t have much decision-

making power.

Regarding the intrinsic characteristics of innovations, Denis & al suggest that

innovations are made up of two different components: a ‘hard core’ that corresponds to

everything in the solution that is relatively fixed and cannot be adapted, and a ‘soft periphery’

related to all the different ways in which the hard core can be implemented. To illustrate this

concept, we can take the example of a drug. The hard core consists of the drug itself (the

molecule), while the soft periphery includes, among other things, the indications (who the

drug is prescribed to, for which reasons, in which quantities), the organizational

arrangements (where the drug is made available, whether a prescription is required or not)

and the follow-up process. This distinction between hard-core and soft periphery gives way

to the third proposition Denis and al make in their paper:

“Proposition 3. Negotiation of the meaning of an innovation in a particular context occurs in

the soft periphery of its definition, enabling a variety of pathways to adoption.”

This means that because innovations are in part defined by a malleable soft periphery, often

times the balance of benefits and risks can be adapted for the actors within the adopting

systems and the solution can be implemented in a variety of ways that increase the chances

of it being successful adopted and disseminated. Thus, when innovations have a wide soft

periphery, the characteristics of the innovation can be tweaked so that the benefits/risk

balance can be optimized for all the actors within the adopting system… There will thus be

several “pathways” for the adoption of the innovation. In the example of the hospital, this

could mean that the price makes the administrators want to adopt it, but the simplicity makes

the physicians want to adopt it.

Using the “hard core vs soft periphery” distinction of innovation characteristics could

be a fertile path for us to explore as we investigate what makes an innovation easier to scale-

up.


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In 2009, the World Health Organization published “Practical Guidance for scaling up

health service innovations”(World Health Organization, Department of Reproductive Health

and Research, 2009) in collaboration with ExpandNet, an international network for

professionals working on the scale-up of public health services. The document is primarily

aimed at public health program managers, with the aim of providing them with an applied

framework for scaling up, and with best practices and recommendations for scaling up

projects. The guide is derived from both from academic literature and from field experience.

The framework, pictured below, presents scaling up as a system composed of five

interacting elements: the innovation, the user organization, the environment, the resource

team or organization and the scale-up strategy.

Figure 12: The WHO/ Expandnet's framework for scaling up

For the “innovation” element, the WHO document gives a list of seven attributes that

enhance an innovation’s potential for a successful scale-up. This list is made of the five

characteristics proposed by Everett Rogers (relative advantage, compatible, not too complex,

testable and observable), plus the two following characteristics:

1. Credible: based on sound evidence or advocated by respected persons or institutions.

While sound clinical evidence isn’t enough for an innovation to spread throughout the

healthcare system, credibility and proven effectiveness is important in the health sector,

and will be required if public funds are being used for the scale-up.

2. Relevant: for addressing persistent or sharply felt problems. The WHO authors probably

added this because in the public health sector, projects compete for limited resources of

time, people and money. Only the most relevant ones will get the required support.


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Now that we have studied literature that help us understand the process of diffusion

among targeted end-users, we will dig into the internal corporate side, in order to understand

the challenges at stake when trying to deploy a breakthrough innovation in different

geographies.

c. L ITERATURE ABOUT ADOPT ION BY INTERNAL ACTORS

The ability of a firm to develop, implement, and scale-up innovations depends in part

on its internal organization. The structural organization, the processes, and the management

tools in place all have an influence on the willingness of employees to develop and test new

ideas, and on how employees bring these innovations to the market.

Given that Sanofi is a multinational corporation (MNC) with affiliates in nearly 100

countries, that digital health solutions can be developed either by affiliates or the head office,

and that the scale up of solutions implies the deployment of these solutions in Sanofi

affiliates, it is pertinent to look at the existing academic literature on the management of

multinational organizations.

i . THE ROLE OF AFF IL IATES OR SUBS ID IAR IES IN MULT INAT IONAL

CORPORATIONS

In “Managing Across Borders: the Transnational Solution”, Christopher Bartlett and

Sumantra Ghoshal argue that multinational companies should be seen as “portfolios” of

“differentiated yet interdependent subsidiaries”. The affiliates are “differentiated” because

each affiliate commands a distinct set of internal resources and external resources, and

plays a different strategic role for the company: it would be a mistake to perceive affiliates as

identical miniature copies of the head office. Bartlett and Ghoshal also stress that the

affiliates are interdependent in order to debunk the hypothesis that affiliates are solely

dependent on the main office; in fact, their actions affect and influence each other and the

head office. To understand the different roles that subsidiaries can play within a multinational

corporation, Bartlett and Ghoshal propose a typology of subsidiaries according to their

external resources, which they call “the strategic importance of the local environment”, and

according to their internal resources, which are interpreted as “the competence of the local

organization”.

Bartlett and Ghoshal explain that the strategic importance of the local environment of

a subsidiary usually depends on the market’s size and sophistication (for example, the


32

market’s appetite for technologically complex products). The competence of the local

organization is assessed by looking at a subsidiary’s skills and strong points (which could be

marketing, production or a range of other activities).

From these two dimensions, Bartlett and Ghoshal defined four generic subsidiary

roles, pictured in the figure below: a subsidiary can be a “strategic leader”, a “contributor”, an

“implementer”, or a “black hole”.

Figure 13: Bartlett and Ghoshal's classification of subsidiary roles in multinational corporations

Strategic leaders are subsidiaries that are both highly competent and are located in a

strategically important environment. These subsidiaries are capable of developing valuable

innovations on their own, innovations that can then be adopted by other subsidiaries within

the MNC. Contributors are subsidiaries that might be very competent in one of the MNC’s

activities or functions, but that aren’t located in a strategic market. Implementer subsidiaries

have neither strong competencies nor an important market; they are good recipients for

innovations and products developed elsewhere in the firm. Finally, black holes are

subsidiaries that do not have the skills to match the very competitive market they located in;

they do not have the capacity to learn from their environment.

As Mathis Guérineau (Guérineau, 2013) argued in his Master’s thesis, Bartlett &

Ghoshal’s typology of affiliates is interesting because it shows the different ways affiliates

can develop a multinational corporation’s capabilities and knowledge, but it is not a typology

that clearly and directly shows the roles that affiliates can play in the deployment of

innovations. Guérineau actually developed a 2x2 typology matrix of affiliates in terms of their

capacity for innovation, which we believe is an interesting tool to use to analyse Sanofi

affiliates.


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Guérineau argues that an affiliate seeking to adopt and deploy an innovation developed by

global corporate faces two main constraints: the market demand for innovation, which is an

external environment factor, and the affiliate’s internal capability to adopt and deploy the

innovation. This being the case, he proposes a matrix that runs along the two following axis

(Guérineau’s definitions below):

1. The value of the local innovation system: The characteristics of an affiliate’s

external environment that can influence the affiliate or the group’s strategy. This

axis is used to describe the affiliate or its market’s need for innovation, and

highlights why the affiliate might be important for the group.

2. The affiliate’s capability-set for innovation: this refers to all the capabilities and

resources an affiliate can dedicate to understanding and deploying an innovation

developed by corporate – time, money, necessary expertise…

Guérineau then proposes lists of objective criteria to help readers place affiliates

along the two axes. To assess the value of an affiliate’s local innovation system, one would

want to look at the affiliate’s country’s ranking in the global innovation index, and the

affiliate’s competitive position on its market. To assess an affiliate’s capability-set for

innovation, one would want to determine the affiliate’s knowledge, its means, and its desire

to innovate (or to adopt and deploy innovations).

These two axes yield the following typology matrix, with four different “ideal-types” of

affiliates.

considerable Potential New Big Historic Big Value of the

local

innovation

ecosystem average Implementer Accelerator

low high

Local organization's capability-set for innovation Figure 14: Guérineau's classification of subsidiary roles in relation to innovation deployment


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Guérineau’s description of the four ideal-types of affiliates:

1. Historic Big:

-‐ Definition: Can take risks and lead by example, but can also be bogged

down by its size and organizational complexity, which makes rapid

innovation deployment impossible. Can share resources, experience and

expertise with other affiliates.

-‐ Strengths: High level of expertise, established marketing methodologies

and large financial resources.

-‐ Weaknesses: The big size leads to complexity, pressure from corporate,

and a need to have innovations that are tailored to the local market 2. Accelerator:

-‐ Definition: Can quickly deploy targeted innovations according to market

specificities and available affiliate expertise in some areas. Leads to rapid

client feedback to prepare the innovation deployment in other zones.

-‐ Strengths: Average size in terms of revenues and number of employees

reduces the pressure coming from corporate; expertise in same areas; good

innovation ecosystem (in at least some areas)

-‐ Weaknesses: weak financial resources. 3. Implementer:

-‐ Definition: These affiliates and their markets have only started growing.

They have a demand for innovations that are easy and fast to deploy, in

order to keep up with market growth

-‐ Strengths: growing markets, good platforms for deploying “ready-to-launch”

innovations, small or medium sized affiliates that reduces the pressure

coming from corporate.

-‐ Weaknesses: weak human and financial resources, no internal expertise,

and rapidly changing and volatile environment.

4. Potential New Big:

-‐ Definition: large and fast growing affiliates in new markets in which the

company’s traditional business models don’t work. There is an internal

capability gap in these markets that needs to catch up with a market that is

hungry for innovation.


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-‐ Strengths: Plenty of growth opportunities, support from corporate, and good

platforms for deploying “ready-to-launch” innovations

-‐ Weaknesses: fast growing workforce that makes it difficult to build internal

capabilities; very little internal expertise; rapidly changing and volatile

environment.

Guérineau also proposes a list of objective criteria: affiliate size according to sales

revenue, market share, and evaluation in internal innovation scoreboards.

i i . ORGANIZAT IONAL INNOVATION PROCESSES: BALANCING INNOVATION AND

SCALE-‐UP

While the matrixes provided by Bartlett and Ghoshal and by Guérineau can help us

understand the impact that affiliates can have on the scale-up of a digital health solution

within Sanofi, the analytical model of organization innovation processes developed by

Christian Seelos an Johanna Mair(Seelos, 2013), which is pictured below, gives us a clearer

understanding of how both internal and external factors can help or hinder a company’s

ability to bring innovations to the market, from the initial exploration of innovations to their

scale up. Seelos and Mair suggest that an organization’s continuous capacity for innovation

(OCCI) depends on its ability to simultaneously explore innovations (develop and test them;

increase knowledge) and bring these innovations to scale. The authors explain that there is

an underlying tension between exploring and scaling innovations, since exploring innovations

involves challenging the norm and thinking outside the box, while scaling innovations

involves standardization, the creation of routines and processes, and a commitment to the

current way of doing things.

Figure 15: illustration of Seelos & Mair's OCCI Model


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While Seelos and Mair are focused on social innovation and designed this model with

social-sector organizations in mind, we believe that this model is generic enough to be of use

to us as we analyze a private sector MNC such as Sanofi.

In their paper “Innovate and Scale: a tough balancing act”, Seelos and Mair suggest

that their OCCI model can be used to identify what are the factors that are hindering an

organization’s capacity to innovate; they propose a set problems that can occur at each

stage of the innovation process, and specifically whether these issues occur more at the

individual level (an single employees motivations, incentives, skills), the group level (the way

a team/division is organized) or at the organizational level – (the way the organization as a

whole is structured and functions). Since our research is focused on the scale up of

innovations, we will only quote Seelos on Mair on what they suggest are the barriers to the

formalization and scaling of innovations:

“Formalization and scaling—organizational level: Do innovations remain invisible to

headquarters, for example in very decentralized organizations? Does a power and leadership

vacuum prevent successful innovations from being formalized and adopted? Do

organizations have inadequate critical execution competencies? Do rapid cycles of

innovation prevent sufficient development of the outcomes of innovation processes?”

i i i . THE EFFECT OF MANAGEMENT TOOLS ON EMPLOYEE BEHAVIOR

From the Seelos and Mair paper, it is apparent that the tools a company uses to

manage its activity – things like balanced scorecards, quarterly financial reports, employee

performance evaluations with fixed criteria – will have an impact on the organization’s ability

to innovate and scale-up that innovation, since these management tools affect the behavior

of everyone in the organization.

Michel Berry clearly exposes the role that management tools can play within an organization

in his 1983 paper “Une technologie invisible? L’impact des instruments de gestion sur

l’évolution des sytèmes humains”(Berry, 1983). In this paper, Berry develops the idea that

while management tools are commonly conceived to be tools that employees can use to help

them keep track of their actions and guide their reasoning, in fact these tools often end up

dictating the behavior and choices of the employees, and often on a sub-conscious level.

The employees are used to using these tools every day, and know that their performance will

be judged in relation to these tools, and so the employees end up having highly automated

behaviors that conform to the processes in place. Berry suggests looking at the whole of


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these tools as an “invisible technology” that plays a crucial role in the way an organization

functions. Berry also argues that internal resistance to reform, innovation, and change in an

organization can be in large part explained by the formal processes in place, which become

engrained in people’s minds after a while.

It follows from Berry’s paper that, as we move onto the case studies of different digital

solution launches within Sanofi, we should look at the processes the main actors have to

conform with and how their performances was formally evaluated, to see if that could have

impacted the scale-up of the solution.

Finally, in considering how internal organization can affect the success of a project

scale up, we can refer again to the WHO’s “Practical guidance for scaling up health service

innovations”(World Health Organization, Department of Reproductive Health and Research,

2009). In the framework, two of the major elements are the user organization – an

organization that intends to adopt and implement an innovation – and the resource team –

the team that is working for the scale up and dissemination of the innovation. Translating this

framework within Sanofi, we could see “user organizations” as affiliates, and the “resource

team” as global teams such as Customer Solutions & Innovation, a team that is pushing for

the development and scale-up of digital health innovations.

The qualities that the WHO recommends user organizations and resource teams should

have in order to increase the chances of a successful scale-up are listed below.

“Successful scaling up is facilitated when the user organization has the following

characteristics:

-‐ The members of a user organization perceive a need for the innovation;

-‐ The user organization has the appropriate implementation capacity;

-‐ The timing and circumstances are right;

-‐ The user organization possesses effective leadership and internal advocacy;

-‐ The resource and user organizations are compatible.”

“Resource teams are more likely to be successful in attaining scaling-up goals if they

possess the following features:

-‐ effective and motivated leaders who command authority and have credibility with the user

organization;

-‐ a unifying vision;

-‐ understanding of the political, social and cultural environments within which scaling up

takes place;

-‐ the ability to generate financial and technical resources;

-‐ in-depth understanding of the user organization’s capacities and limitations;


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-‐ relevant technical skills, including research and evaluation skills;

-‐ capacity to train members of the user organization;

-‐ capacity to assist the user organization with management interventions needed to

implement the innovation;

-‐ skills and experience with scaling up;

-‐ compatibility with the user organization.”

Looking at these practical criteria established by the WHO field book, we see that the two

dimensions of subsidiaries defined by Bartlett and Ghoshal come up again – that is, most of

the criteria listed above relate to either to an affiliates local environment or to its

competencies. Thus, it seems that these guidelines validate our use of the Bartlett and

Ghoshal matrix when analyzing affiliates to understand their role in the scale-up of

innovations.

d. L ITERATURE ABOUT ADOPT ION BY OTHER STAKEHOLDERS: THE ECOSYSTEM AL IGNMENT

i . THE ECOSYSTEM: DEF IN IT IONS AND CHARACTERIST ICS

Adner (Adner, 2006) who considered as the most recognized author on ecosystems

when dealing with innovation processes, defines the innovation ecosystem as the

collaborative arrangements through which firms combine their individual offers into a

coherent, customer-facing solution. Collaboration is thus a key element to success when it

comes to innovation implementation and diffusion, because, according to Adner, effective

ecosystems can create a lot more value than a single firm could have created alone.

Iansiti and Levien (Iansiti, 2004) point out that actors in today’s ecosystems are

becoming increasingly more heterogeneous in a given industry, and that most companies are

present in ecosystems that extend beyond their own and traditional industries. They explain

that ecosystem members can be of a wide variety: suppliers, distributors, outsourcing firms,

makers of related or substitute products etc. In their conception, the ecosystem is led by one

central player, “the focal firm”, that ensures the sustainability of the ecosystem. However, in a

multi-player field like healthcare that mixes public and private interests and where the market

is built around many firms (should they be medical or technological), we believe the concept

of “focal firm” does not really apply.

The approach of Koenig (Koenig, 2012) seems therefore more appropriate: he differentiates

4 types of ecosystems based on two main criteria: the level of centralization/or


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decentralization of critical resources within the ecosystem, and the form of independence

between the members. He suggests the following typology:

Figure 16: Koenig's typology of business ecosystems

• “A tender system” : one leading firm has access to key resources and relies on

partner to develop a tailored offer for its own business

• “Platform”: One of the actors has one key resource that made available to other

players.

• “Community of fate”: This corresponds to an ecosystem where resources are

decentralized, even if some leading players exist. Solidarity and co-innovation is

essential in this kind of ecosystem where each player needs the skills or other

resources for another firm to develop an innovation

• “Fuzzy community” refers to an ecosystem with a multitude of actors, whose

contribution can be easily isolated and that evolve in an open-source development

model.

We believe the ecosystem in which eHealth solutions are being launched nowadays can fit in

the category “community of fate”. Resources are indeed highly decentralized (some have the

medical knowledge, other the technical skills; some have the right to access patient data

when other do not, but have a direct access to the medical community etc.) and actors have

to work in tight collaboration to develop innovative solutions.

In our research, we will also consider the characteristics of a business ecosystem presented

by Charue-Duboc and Jouini (Charue-Duboc, 2013) that is:

• Heterogeneous members contributing together directly or through indirect impact

(political, legal…) to the delivery on an overall offer or a complete solution


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• A leader firm, who “co-envisions” and “co-manages” the collaboration and evolution

between all members in order to align the interests of all players. For the healthcare

sector however, the status of “leading firm” can in our opinion only be given in the

frame of a specific project management / innovation launch, since the industry per se

is not clearly led by one player.

• Rules and interface

Even if this literature on ecosystems definition will not be used as such in the rest of

our research, we believed it was important to gather these elements to be able to

embrace the notion of ecosystem later on. This helped us understand the context in

which Sanofi is evolving, and the way it could interact with other stakeholders depending

on the issues at stake. How to innovate in such complex ecosystem in a topic we will

address in the next paragraph.

i i . STRATEGIES TO INNOVATE SUCCESSFULLY IN A COMPLEX ECOSYSTEMS: THE

ART OF INTERESSEMENT ACCORDING TO AKRICH, CALLON AND LATOUR

Akrich, Callon and Latour (Akrich, 2002) challenge two basic and common

assumptions on innovation:

i. The pace of diffusion of a, innovation is determined by its intrinsic characteristics

ii. The adoption of an innovation is the result of a mutual adaptation between a

defined product and a defined target market.

These statements are not false, but are not sufficient to fully understand the

deployment process of an innovation. A product cannot indeed be defined without taking into

account every interaction it implies, as well as the variability of the social and economic

environment in which it is released.

While Moore and Rogers have theorized a model of diffusion, where the innovation is simply

launched into a market that is more or less receptive, and where the social and economic

context is not a key element, Akrich, Callon and Latour present a model of interessement.

In their conception, when developing an innovation, every single player that is

connected somehow to the innovation should be taken into account while developing and

launching the product or service. The innovation should result from an aggregation of the

interest of all stakeholders in order to have the highest probability of success. As the authors

say, “Innovation is the art of interesting an increasing number of allies who will make you

stronger and stronger ».


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In order to do so, they first recommend to drive continuous negotiations with all

members of the ecosystem to make sure they become allies and will be ready to accept and

adopt the innovation, and secondly recommend to have a lean development, that enables

the company to adapt the innovation (what they call “socio-technical compromise”) after

several experimentations aiming at testing the level of “interessement” of the ecosystem.

The mechanism, which in their conception, enables the “interessement” of each player is an

act of translation: the challenge is to translate a commercial object and strategy into a

research question that is relevant for each player of the ecosystem.

Such an approach is very interesting for Sanofi, as it can be easily used in the case of

innovation in healthcare, where each player has different needs and expectations (patient,

healthcare professionals, social security, private insurance, hospitals, pharmaceutical

companies etc…) and failing to onboard only one these players in the innovation deployment

could lead to a complete fiasco.

A very specific stakeholder to manage in the case of eHealth industry is the partner

one is developing the solution with. As explained in the section about eHealth definition,

solution development mostly imply partnering with an external actor that master a needed

know how. We tried to put the concept of partnership in the perspective of scaling up, and

find in an article written by Charue-Duboc and Jouini (Charue-Duboc, 2014) some elements of

response to help us understand the causality in the relationship between the two notions.

i i i . INNOVATE AND DEPLOY AN INNOVATION WITH A NETWORK OF SUPPL IER OR

PARTNERS: THE INPUT FROM CHARUE-‐DUBOC AND JOUINI (2004)

Charue-Duboc and Jouini, in their paper « Le déploiement d’innovations inter-filiales au

sein d’une multinationale » (Charue-Duboc, 2014) address the question of the deployment of

an innovation by a multinational company, and how to overcome the paradox of globalizing

an innovation while having to adapt it locally. They list 5 key success factors for the

deployment of innovation between affiliates in a multinational company and one of them is

contracting successively with local suppliers to deploy the innovation. Charue-Duboc and

Jouini confronted several cases of deployment of innovations inside a multinational gas

company. In all cases, they have been changes of suppliers during the scale-up depending

on the geographies the innovation was commercialized in, and the company partnered with

local players. Key takeaways from their research are the following:


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• The success of the first commercialization of a solution in a given geography highly

depends on the level of implication of a partner/supplier which already has good

relationship with the affiliate launching the innovation, and which is already well-

known among targeted customers.

• Partners/suppliers do not always share the multinational’s scale-up strategy.

Therefore, multiplying the partnerships and contracts with local players enables the

MNC to follow its initial scale-up strategy without having to deal with other players’

interests. Acting so ensures a higher rate of success than incentivizing one player to

invest time and money in geographies that are not essential to him.

• However, it should not be overlook that such a partnering strategy requires specific

contacting processes and confidentiality agreements.

These key success factors can easily be applied to Sanofi’s case, whose solutions often

requires to contract with specific suppliers. We will come back on point later on in our paper,

and analyze it in the light of empirical case studies at Sanofi.

After having presented the literature review, that orientated our research and gave us a

good overview of what aspects had to be taken into account when dealing with the challenge

of scaling up innovation in complex ecosystems, we will detail our empirical material for this

research. At Sanofi, we had the chance to be at the heart of project management, and

contribute to solutions development on a daily basis. We thus had access to very concrete

empirical material: existing eHealth projects at Sanofi.

5. EMPIRICAL MATERIAL: AN IN-‐DEPTH ANALYSIS OF FOUR EHEALTH PROJECTS

AT SANOFI

a. SELECT ION METHODOLOGY

As explain in paragraph 3, we had two different types of missions, both of which

enabled us to discover and understand eHealth solutions at Sanofi and how they were

carried forward. On one hand, through our roles of projects managers, we led projects on the

field by being in charge of tasks such as launching a pilot, coordinating teams internally,

doing the promotion of the solution etc. Thanks to this position at the very heart of the

project, we were able to analyze projects with an internal point of view. On the other hand,

we listed all integrated care solutions at Sanofi, and elaborated a classification so that the

database could be exploited easily for further analysis. Not only did this work gave us a

comprehensive overview of the eHealth projects at Sanofi, it also helped us develop criteria


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to differentiate and segment projects. This has been a helpful tool to select projects for our

research project.

In order to deepen our research on scale-up, we selected 4 projects at Sanofi that we

could draw lessons from either by analyzing them on their own, or by confronting them to one

another to extract key takeaways and best practices. We selected the following projects,

which will be detailed in project monographies:

• Babushka SMS

• Phosphorus Mission

• MORE

• DIABEO

We explain hereafter our selection methodology, by detailing the criteria we retained to build

a relevant sample to analyze.

i . WHY FOUR PROJECTS?

Out of the approximately 120 eHealth projects listed at Sanofi, we decided to select

four projects which were already consistent enough to conduct a research on (projects at the

stage of ideation or Proof of Concept were therefore excluded from the beginning). Picking

four projects enabled us to analyze each of them in depth by going back to the genesis of the

project and investigating the entire development process, as well as comparing the projects

with one another.

i i . SELECT ION CR ITER IA AND ELEMENTS OF D IFFERENT IAT ION BETWEEN THE

PROJECTS

Our selection was driven by 3 main criteria: 1-Different technology used, 2-Different

types of solutions, 3-Different stages of maturity. By doing so, we chose 4 projects that

turned out having other differentiating elements (such as therapeutic areas, geographical

footprint and internal process development)

Criteria 1: Different technology used

As explained in 1.b, eHealth solutions can be composed of very diverse technologies

with various level of technical complexity. Although Sanofi’s eHealth activity is quite young,

teams have worked on solutions based on technologies ranging from the simple website to

complex solutions combining medical devices, medical algorithm and mobile app. We


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considered that choosing solutions with different technical infrastructure could help us

evaluate the impact of the technology used on scale-up potential.

Figure 17 : Selected projects for monographies in relation to corresponding technical infrastructure

Criteria 2 Different types of solutions

EHealth solutions answer different needs, have different purposes and can imply different

level of patient engagement. Questioning scale-up potential from the perspective of the type

and purpose of a solution can also be an interesting path to follow. It is easier to scale-up a

simple education tool than a complex real time monitoring solution that can modify

treatment? And if so, confronting the 4 solutions will help us determine what can deeply

impact scale-up.

• Phosphorus Mission is a casual game requiring little patient engagement and

aiming at inform the patient about the pathology, as well as indirectly change his

behavior toward his disease. It is ranked as an education and coaching solution

• Babushka SMS is a solution based on automatic educational and reminding SMS

sent to the patient, aiming at improving adherence to treatment.

• MORE is a remote monitoring solution that enables HCPs to improve patient’s follow-

up.

• Diabeo is also a remote and real time monitoring solution that helps the patient

adjusting his treatment depending on his lifestyle and physician’s prescription


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Figure 18: measuring level of patient engagement and eHealth solution purpose

Criteria 3: Different maturity stage

The idea is to understand, for each project and at different stage of development, how

project leaders handle the scale-up question. Is the question of scaling-up only rising once

solutions are launched? Are solutions prototyped and tested with the objective of being

scaled-up in the mid-long term?

Phosphorus Mission is already launched in several geographical areas, whereas Babushka

SMS has been launched this year in Indonesia. As for Diabeo, it is currently being tested in

real life in a clinical trial. Finally, MORE is at the moment going through a user test to assess

the value of such a solution and define the best business model.

Figure 19: eHealth solutions selected for the monographies in relation to development stage


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Element of differentiation 1: Therapeutic areas

In terms of therapeutic areas, Sanofi has established 12 priorities it is at the moment

active in. Choosing solutions dealing for different pathologies could enable us to deal with

different patient pathways, for which gaps in care can vary, as well as the answer offered by

the eHealth solution.

It is therefore enriching for our research to take solution from different therapeutic areas, in

order to analyze:

- If the complexity of certain patient pathways for given pathologies can impact the

scalability of a solution

- If, from a corporate perspective, launching and scale up a solution in a therapeutic

area where the company is strongly active in its drug business (such as Diabetes) is

easier than in a therapeutic area which is not core to the company (such as Renal –

Specialty Care)

Figure 20: eHealth solutions selected for monographies in relation to therapeutic area

Element of differentiation 2: Geographical footprint

• MORE is currently being tested in Ireland.

• Diabeo is currently being test in France.

• Babushka SMS has been launched in Indonesia.

• Phosphorus Mission has been launched in many countries around the globe.


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The geographical spread of the projects we picked can enable us to investigate several

points, such as the role of the local affiliate in charge of the launch or the impact of local

context (healthcare systems, regulatory constraints etc.) on the rate of diffusion.

Element of differentiation 3: Internal process development

Three of the solutions we chose (Phosphorus Mission, Babushka SMS and MORE)

have been developed by CSI, the global entity we joined at the beginning of our project. They

were thus projects initiated at a global level, and then pushed down to affiliates for

implementation. On the other hand, Diabeo is a project fully originated and led by the French

affiliate.

This raises the challenge of internal organization for project follow-up in the case of

scale-ups, and comparing the four projects have helped us understand the different paths a

solution could follow inside Sanofi to complete scale-up.

b. INS IGHT COLLECT ION: INTERV IEWS AND SELF-‐EXPER IENCE

Among the 4 solutions, 2 are projects we have worked on as junior project managers

(Babushka SMS for Sophie and MORE for Clara). Thanks to this role, we can base our

research on our experience, the difficulties we encountered and the opportunities we faced.

However, since we took over the projects at a moment where they were already at an

advanced stage of development, we led interviews with the project leader to better

understand project roots and history.

For the 2 others however (Phosphorus Mission and Diabeo), we led several

interviews with project team members in order to gather data and insights about the project.

INTERVIEWS

Babushka SMS Emma Garde Project leader

Phosphorus Mission Corinne Monteil Project leader

Salah Mahyaoui Project coordinator

MORE Emma Garde Project leader

DIABEO Armelle Blaise Project leader

Jean-Yves Bailly Project leader

Antoine Barbot IS Business Partner

Figure 21: monography interview table


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C. PROJECT MONOGRAPHIES

All projects described hereafter will follow the same presentation structure:

-‐ A solution overview, in which we detail the therapeutic needs the solution is

answering, as well as a technical description of the solution

-‐ A solution history, in which we establish the whole chronology of the project to

understand, all along project development, what could have influence the decision

and success of scaling up

-‐ A list of opportunities and challenges that the project team has encountered

during project development, which can help us understand what aspects might

foster or impede scale up.

i . BABUSHKA SMS

1. SOLUT ION OVERV IEW

Therapeutic needs & detection of gaps in care

According to the World Health Organization, up to 50% of patients suffering from chronic

diseases do not take their medication as prescribed by their doctors; they might skip doses,

take extra doses, delay the start of their treatment, or prematurely end their treatment.

This non-adherence to medications can have serious consequences on the health

outcomes of patients. For instance, just in the United States, it is estimated that at least 10%

of hospitalizations and 125,000 deaths per year are a direct result of poor medication

adherence (McCarthy, 1998). This medical burden is probably magnified several times over

in developing countries, where access to health resources is often much more limited than in

the US, and where medication adherence rates are assumed to be lower by the WHO (WHO,

2003).

The babushka SMS solution is designed to help patients adhere to their medications. In

this case, the solution has been designed for patients in Indonesia who suffer from Acute

Coronary Syndrome (ACS) or who have undergone Percutaneous Coronary Intervention and

need to take antiplatelet medication.


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Technical description of the solution

Figure 22: Babushka SMS flow diagram

Babushka SMS is an automatic, adaptive and interactive text-messaging solution that

sends reminders, educational and motivational messages to ACS & post-PCI patients who

are prescribed Plavix in Indonesia. The text message content and frequency is based on

verified behavioral science principles.

A patient who wants to use Babushka SMS must go to the www.pillmessage.com

website to sign up to the service. The patient fills out a questionnaire giving his or her basic

contact information, answers questions on his or her usual medication taking habit, selects

the type of reminder message he or she finds most inspiring out of a list of sample

messages, and can choose to involve a caregiver (friend or family member) who will also

receive messages and support the patient throughout the duration of the program.

Once the patient is signed up, tailored automated reminders and motivational messages

are sent to the patient. The content and frequency of the messages sent to the patient varies

according to the responses the patient sends back. The patient also receives two-way

messages asking him to or her to confirm he or she is sticking to the regimen, and a report

via email once every two weeks. This report gives the patient a quick overview of her

adherence history (e.g. “During the past three weeks, we asked you 8 times whether you had

taken your Plavix, and you replied yes 5 times”).


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The SMS program lasts six months, though patients can renew it once for total twelve

months duration. They can unsubscribe from the service at any time. Finally, the Sanofi

Indonesia medical team receives reports from the services provider once a month. These

reports, which only include aggregated and anonymized data, let Sanofi know how many

patients are signed up, how many responses are being sent back.

2. SOLUT ION H ISTORY

How the Babushka SMS project took off

The Babushka SMS project kicked off in the summer of 2012. At the time, the CSI team

had just piloted Babushka App, a tablet specially designed for seniors that included a mobile

application designed to help poly-medicated seniors take their medication as prescribed, with

the help of their pharmacist. The Babushka App pilot had not been carried out with the goal

of preparing a market launch of Babushka App; the goal was to confirm that there was a

market appetite for adherence solutions for seniors that leveraged technology, and that

Sanofi could create a solution that patients would appreciate. When the pilot results for

Babushka App came in and turned out to be very positive; patients found the tablet and app

very useful, and they reported two points to improve: the app should have more flexible

scheduling features, and should also be available on technological devices patients already

use, rather than a tailored tablet. The CSI team decided to capitalize on the experience and

to use the feedback to create an economically viable solution that could be made available to

the wider public.

During the same summer, the CSI team leader visited Sanofi Singapore to present the

Babushka App at an internal summit on innovation. After the conference, the regional head

of marketing approached him, explaining that poor adherence to medications was in fact a

proven issue in the region, and that he would be happy to work on the development of an

adherence solution in Asia. The existence of a real patient need for adherence solutions and

of an internal champion for adherence solutions in the region led the CSI team to agree to

launch a solution with the Asia region. This was the start of Babushka SMS.

The decision to develop an SMS-based solution:

The decision to develop a solution that relies on automated text messaging stemmed

from the following elements:

• Positive feedback and lessons from the Babushka App pilot


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• Proof of effectiveness: several published articles concluded that sending text

message reminders is an effective way to improve patient adherence to medication;

• Interviews with adherence experts, who suggested working on an SMS-based

program

• Relative low cost, accessibility and simplicity of text messaging: more patients can be

reached via SMS than by smartphone or tablet, especially in developing countries

(adapted to market needs).

The decision to develop the solution for Plavix-using patients in Indonesia

To develop the solution, the team needed to find a brand and a market to launch in.

Indonesia was selected because it has one of the largest populations in the Asian region,

with many aging patients suffering from coronary diseases who need help adhering to their

medication. The Indonesian team chose the Plavix brand because it is a medication that is

commonly taken by cardiac patients.

Services provider selection

The CSI team consulted an expert in adherence to create a benchmark of potential

solution providers before interviewing a short list of potential providers and launching a bid.

The final vendor selected, based in the United States was selected because of their

expertise in behavior change projects and their previous work on similar projects.

The Babushka SMS development

The development of Babushka SMS lasted between late spring and early September

2013. Making Babushka SMS ready for launch required:

• Preparation of contracts and other legal document

• Building a website and ensuring it is in line with all of Sanofi’s digital communications

guidelines

• Translating & approving all website copy and message content & frequency at local,

regional & global levels;

• Ensuring compliance with the internal Patient Support Program procedure;

• Ensuring that an adequate adverse events reporting process for solution users;

• Preparing the solution launch with the Sanofi Indonesia team

• Determining KPIs for solution follow-up

It could be argued that the most challenging and lengthy part of the solution development

process were to understand how existing internal and external regulations could be applied

to an innovative project such as Babushka SMS. For instance, existing Patient Support


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Programs included call centers or in person visits, and rules were drafted to monitor live

patient-provider interactions, which do not occur in Babushka SMS since it is an automated

texting program. As a consequence, the CSI and Sanofi Indonesia teams had to work closely

with regulatory teams to understand how to ensure that the project followed the spirit of the

existing rules.

The launch

Babushka SMS launched in Indonesia in December 2013. At the time, the team did

not have the necessary resources to launch the solution throughout all of Indonesia. This

being the case, the team decided to launch Babushka SMS solely in Jakarta as a pilot until

end of April 2014, and to ask their general manager for the resources for a scale up in May if

the patient and physician feedback during the pilot phase was positive.

While patient subscriptions during the pilot phase were lower than the pilot objective,

the Sanofi Indonesia team still decided that they wanted to scale up the project. Indeed, it’s

possible the team simply overestimated how any patients a single physician could recruit into

the program over a month. Furthermore, the feedback from physicians on babushka SMS is

very positive.

The Sanofi Indonesia now wants to scale up the solution throughout Indonesia at the

start of fall 2014. The scale up will be challenging for the local team. The CSI team paid for

the solution development and first year operational costs, but Sanofi Indonesia will have to

cover maintenance and promotion costs. These costs might be too high for the affiliate; even

if the business case is strong, the affiliate has limited resources and the funds might get

funded to a more urgent or immediately profitable project.

3. OPPORTUNIT I ES & CHALLENGES FOR THE SCALE UP OF THE SOLUT ION

Opportunities

-‐ A theoretically effective solution that affiliates want: Sanofi affiliates are interested in

SMS-based adherence solutions – after launching Babushka SMS in Indonesia, the CSI

and Sanofi Indonesia received spontaneous requests for more information from brand

managers in the US and in France. The fact that it is a simple and cheap solution for

patients to adopt and understand makes it attractive, as is the fact that several studies

have proven that SMS programs similar to Babushka SMS have proven to effectively

improve patient adherence in clinical studies.


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-‐ Positive feedback from patients & doctors enrolled in the program: The Sanofi

Indonesia team collected feedback from the 9 physicians who participated in the pilot,

and their survey responses were very positive. The fact that only one patient has

unsubscribed from the program also suggests that patients are satisfied with the

program, since it is very easy to unsubscribe. This positive feedback has proven to be a

key element in deciding to scale up in Indonesia.

Challenges

• Existing Sanofi procedure not adapted for this kind of solution: The existing Patient

Support Program procedures and pharmaco-vigilance (PV) management requirements

are not drafted for programs that use mobile technologies – Babushka SMS is the first

program the company has launched which includes automated text-messages. Until

these requirements evolve, the project teams must act with prudence and work with the

regulatory teams, which can be time-consuming.

• The cost associated with a babushka SMS scale up: The current cost of Babushka

SMS is probably too high for many Sanofi affiliates that would be interested in adopting

the solution. The team needs to evaluate how the costs could be brought down.

• No hard evidence of effectiveness –YET: a randomized controlled trial to measure

Babushka SMS’ impact on patients’ adherence to medication in Indonesia has been

commissioned, and patient recruitment into the study began in July 2013. The results of

this study are key, because affiliates who are interested in the solution will have hard

proof that it is an effective and valuable. For the time being, the lack of this proof has

slowed down scale up efforts.

i i . PHOSPHORUS MISS ION


Phosphorus Mission is an educational casual game for chronic kidney disease (CKD)

patients undergoing dialysis. The game is designed to improve patients’ CKD awareness,

dietary choices and phosphorus management by helping them understand their condition

and the important role nutrition and proper treatment play in their disease management.


54

Phosphorus Mission is available on Google Play, on the iTunes App Store and on PC via

CD-ROMS.

Therapeutic needs & detection of gaps in care

Phosphorus is the second most abundant mineral in the human body after calcium

and it is necessary to build strong bones. While a phosphorus deficiency can cause fatigue,

having excessive phosphorus levels is more worrisome as it can cause serious bone and

cardiovascular diseases.

Healthy kidneys can eliminate excess phosphorus levels from the blood stream, but

patients living with CKD need to take extra care to manage their phosphorus levels since

their kidneys don’t function properly. In order to control their phosphorus levels, CKD patients

need to manage their nutrition and know which foods are rich in phosphorus and must be

avoided. Dialysis also helps. Finally, patients can take phosphate binders (such as Renvela

which is produced by Sanofi) that can help control the amount of phosphorus absorbed by

the body. Thus, patients can best control their phosphorus levels by understanding their diet

and their treatment.

Technical description of the solution (with screenshots)

A serious game developer, created Phosphorus Mission for Sanofi. The game is

designed to help CKD patients improve their nutrition knowledge and understand the role

that phosphate binders play in their disease management.

Figure 23: Phosphorus Mission screenshot

The game is designed to be simple enough for casual gamers to play and enjoy. After

selecting a meal and learning how much phosphorus it contains, players must shoot


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phosphate binders towards a string of nutrients in order to capture excess phosphorus balls.

The players must also group together balls of the same color in sets of at least three – the

different colors represent different proteins, carbohydrates & fat that the body must also

absorb in the right proportions. The game is composed of sixteen levels of increasing

difficulty, as the meals contain higher levels of potassium each time. Between every level,

users are coached & quizzed on the role of nutrition and medication for their CKD

management.

Figure 24: Phosphorus Mission screenshots


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2. SOLUT ION H ISTORY:

The start of the project:

In 2011, Sanofi’s Business Excellence & Innovation team – which would become the

CSI team in 2012 – worked on improving existing innovation processes in Sanofi. The team

carried out multiple market studies to understand what effective innovation processes other

corporations had in place in order to determine what innovation processes might work well

within Sanofi, a pharmaceutical group looking to develop services for patients.

The team also created an innovation board, which is constituted of eight recognized

experts in innovation who all have very different backgrounds – most of the board members

are external to the health sector and can thus bring Sanofi insights from different industries.

With the innovation board’s input, the Business Excellence & Innovation team developed a

services innovation process framework (see graph below) to guide the nascent integrated

solution development process at Sanofi.

Figure 25: The services innovation framework developed and applied by the CSI team

At the end of 2011, the Phosphorus Mission project kicked off. The goal was to create

an integrated solution that would address gaps in care that patients are faced with along their

care pathway in an innovative way by following the services innovation process framework.

The solution concept development:


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The decision to develop a solution for Chronic Kidney Disease patients:

The team first chose to focus on chronic pathologies, because patients who suffer

long term diseases are more likely to experience serious gaps in care, and are thus more

likely to need or want integrated solutions that address these gaps (e.g. difficulty adhering to

medication regimen, coordinating care etc.) Then, the Business Excellence & Innovation

(BE&I) team decided to focus on developing solutions for renal diseases. At that moment, the

Sanofi renal team had already gathered patient insights and clearly identified gaps in the

care of renal patients, and so was receptive to developing a solution for patients.

Furthermore, the renal and BE&I teams were part of the same larger Sanofi entity (the PCS

division), so working on a project together would be simpler from a logistic and budgetary

point of view. Finally, the Renvela brand – a phosphate binder for CKD patients – was facing

an upcoming patent loss, and developing an integrated solution could perhaps help boost the

brand.

Selecting the casual game concept:

In order to develop good concepts for the solution, the project team leader hired

Valerie Casey to lead an ideation session at Sanofi. Casey is a renowned designer and

innovator who is at the head of an online design thinking community of over 100,000

members. She is now VP of innovation art Samsung.

A wide variety of people were invited to this ideation session: members from the

Sanofi corporate, from legal teams, IT, brand teams, members of Sanofi subsidiaries etc.

The group discussed CKD patients’ insights and the gaps in care they face before

brainstorming on possible solutions. The group came up with dozens of ideas, which they

then grouped into clusters. A handful of concepts were retained and later discussed with the

legal and IS teams to assess the feasibility of the proposed ideas.

Finally, in Q1 2012 the project team which was led by Corinne Monteil decided to go

ahead with the concept of a casual game. Several studies had already proven the positive

impact well-designed video or casual games can have on patient outcomes. A casual game

would thus be an effective way to address CKD patients’ lack of awareness and need for

disease education. Furthermore, developing such a solution would allow Sanofi to

differentiate itself from its competitors who had not developed such solutions.

Developing the game

After a standard Request for proposal process and with feedback from Sanofi’s R&D

department, a game developer was selected to develop the game. The first step was to

gather patient insights, to understand patient needs patient attitudes toward their disease,


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their treatment, and toward mobile technology. The team built on the insights gathered by the

renal division by carrying out patient interviews in dialysis and self-dialysis centers in Paris

and Bordeaux.

Two game concepts were then developed and tested: a Zuma-like (Z-like) concept,

and an Angry Birds-like (AB-like) concept. Two testing sessions were carried out in the fall of

2012: the Z-like game was tested in France, and both the Z-like and AB-like versions were

tested in Singapore. After analyzing the test results, the chose to go forward with the Z-like

version, and took into account patient feedback to improve the solution. The game was

named Phosphorus Mission.

The game launch:

An iOS (Apple version) of the game was launched in Singapore in May 2013. The game was

subsequently rolled out to 10 other countries, with a similar version of the game released on

Google Play for Android users. The scale-up to 10 countries was a mix of push and pull – up

to 25 different Sanofi subsidiaries spontaneously asked for information on the game. The

game is set to also be launched in the Middle East in the summer of 2014.

3. OPPORTUNIT I ES & CHALLENGES FOR SOLUT ION SCALE UP :

Opportunities

-‐ External & internal recognition: The game has been recognized as valuable both

within Sanofi and by external organizations. Within Sanofi, the solution has been

featured by the connecting nurses’ platform, a worldwide nurse’s network supported

by Sanofi. Outside of the company, the game was rewarded by the Economist in Asia

and received accreditation by the European Dialysis and Transplant Nurses

Association (EDTNA). This recognition can be very positive for the scale up of the

solution, as official recognition from influential entities such as nurse networks can

really legitimize the solution in the eyes of important users and promoters of the

solution such as physicians, nurses, and patients.

-‐ Preliminary user feedback is positive: In mid-2014, IPSOS was commissioned to

carry out a market study to measure user satisfaction and self-reported impact of

solution on patient adherence to phosphate binders. While the final numbers aren’t

out yet, the first results are promising. This can help promote the game internally to


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more Sanofi subsidiaries and externally to more patients and patient/nurse/renal

associations.

-‐ The game has proved to be a “door opener” for some sales representatives.

Indeed, in certain subsidiaries med reps see this game as a “door opener” – a new

offering to present to doctors, which allows them to visit new physicians or physicians

that they hadn’t seen in a long time because they had nothing new to present to

them. This fact may have positively influenced the deployment of Phosphorus Mission

throughout Sanofi affiliates.

Obstacles

-‐ Cost of deployment: it can cost up to twelve thousand euros to deploy Phosphorus

Mission in a new affiliate. While for some affiliates this is an easily absorbed costs, for

many others this is a prohibitive cost, especially since it usually has to be paid for

using the renal marketing or medical budgets. One solution has been to split the cost

between countries that share the same language and a similar culture when possible.

This however points to a need to develop more frugal innovations, or to find a new

way of financing the scale up besides asking affiliates to cover the cost.

-‐ Departure of key project sponsors within Sanofi: Over the course of the

Phosphorus Mission project, two key project sponsors in the global renal team and

one regional leader in Singapore who had enthusiastically supported the project left

the company. Losing these allies might have slowed down the scale up process, as

the CSI team had to build new relationships within the organization.

Project timeline:

Date

Market studies & benchmarking of corporate innovation processes 2011

Project kick-off (ideation session) Q4 2011

Customer Solutions & Innovation team created 2012

Decision to develop an educational casual game Q1 2012

Game developer selected to develop the game Q2 2012

Game developer delivers patient insights & game concepts Q2/Q3 2012


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First testing phase (France, Z-like game, carried out by game developer) Q3 2012

Second testing phase (Asia, Z-like and AB-like games) Q4 2012

Selection of Z-like concept and game development finalized Q1 2013

First launch (in Asia) Q2 2013

Roll out to 10+ countries Q4 2013

Figure 26: Phosphorus Mission project timeline

i i i . PROJECT MORE


MORE is a telemonitoring solution for patients suffering or likely to suffer from Atrial

Fibrillation (cardiovascular disease). The solution is based on the use of a device, namely

electrodes embedded in a smartphone case, supplied by an American provider. The device

enables the end user (most likely the patient) to record ECG with his phone and possibly

send it to someone else (most likely the HCP) for continuous follow-up. Global teams

developed this solution. Yet several business models are possible and we are currently

running a pilot test to assess the most appropriate one.

Therapeutic needs and detection of gaps in care

Atrial Fibrillation (AF) is before all a medical burden. (Sanoski, 2009)

-‐ 2.2 million patients have AF in the US in 2009

-‐ AF prevalence is expected to increase by ≥2.5-fold by 2050 in the US

-‐ AF is associated with an increased long-term risk of hospitalization, stroke, heart

failure and all-cause mortality

It is also an economic burden: (Sanoski, 2009)

-‐ Hospitalization with AF is frequent, long lasting and severe, associated with reduced

quality of life and is highly predictive of death

-‐ In 2009, cost of AF care was estimated to $6.65 billion per year in the

-‐ Beyond rhythm and rate control, guidelines recommend establishing goals to reduce

stroke, hospitalization & mortality


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In this context, many challenges and “gaps in care” have been spotted by Sanofi’s teams:

Screening: Under/late diagnosis (due to lack of symptoms or lack of ECG)

Monitoring: Lack of access to definitive data when symptoms are present

Treating: inappropriate discontinuation and poor adherence

Educating: Poor awareness of patients (i.e. stroke vs. risk of hospitalization)

From our analysis, MORE is a solution that could therefore:

-‐ Increase early diagnosis of AF and increase in timely diagnosed population

-‐ Educate on the disease

-‐ Improve adherence to treatment

-‐ Increase detection of AF events through regular ECG monitoring

-‐ Enhance the communication between the patient and the HCP

The pilot currently running will help us fine tune our analysis and validate these assumptions.


MORE is a solution composed of a device (electrodes that can be attached to a smartphone

to record ECGs) and an app.

The technology has been clinically validated, with a sensitivity of 99.7% sensitivity in

comparison to a standard full machine.

The utility of device is recognized in literature for

-‐ Community screening

-‐ Detection before acute medical issues

-‐ Access to definitive data when symptoms are present

The technology obtained FDA approval and is CE marked. The device provider developing

the technology has already commercialized it in several countries.

The solution can be used by different end-user for different purposes. The aim the pilot test is

to determine which use case brings the most value, (not only financial benefits for Sanofi, but

increased value for all users).


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Figure 27: MORE flow diagram

1) The solution can be used by the HCP, during consultation, to screen patients by

checking their pulse, as a routine process, or for patients complaining of abnormal pulse (as

all HCPs do not always have a fix ECG recording machine at their disposal during

consultation). This corresponds to the (1) displayed on the patient pathway shown above.

If the abnormal pulse in confirmed, the GP refers the patient to the cardiologist for the rest of

the diagnosis. Cardiologists can also use the solution during consultation for screening (even

though they have more advanced technology at their disposal, MORE has the advantage of

being convenient and user friendly).

2) The solution can be prescribed by HCP and used by patients, and then be used as

a remote monitoring solution. As explained on the patient pathways, some patients need

to record their ECGs during 7 days for the cardiologist to be able to make a correct diagnosis

(2). The HCP can then provide his patient with the MORE solution. This way, the patient can

record ECGs according to his doctor’s recommendation and send it to him regularly.

Both of the scenarios are currently being tested in pilot.


The project of MORE came from 3 different streams that came out simultaneously

-‐ The brand team, in charge of the marketing for a cardio product, was investigating to

find a new solution. They wanted to develop services around their products to bring


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more value (in existing market, and in market they were about to launch their product

in).

-‐ The global team CSI already had an experience on a remote monitoring project in

cardio. However this project was highly complicated to put in place and they were

looking for an easier project to roll-out.

-‐ Sanofi scouting team spotted the technology in 2013. Further discussions with field

experts confirmed the benefits such a device could bring.

From the combination of these three parameters emerged the project MORE.

Since the technology was already on the market, the idea of the project team was to quickly

set up a user test to evaluate the value of such a project. However, important questions were

still pending:

What model must be tested?

The MORE project could target HCPs to provide them with a device simple to use, that could

help them screening patients. But it could also target patients in a remote monitoring

perspective, where patients could record their ECG and send it to their cardiologists, so that

the latter can follow-up on them from the distance.

Where should we do the user test?

From the type of model chose must be determined where to roll out the test.

Optimal conditions for the screening model were: - Remote areas - With average revenues (out of pocket business model) - HCP not very well equipped

Asia was then considered as an appropriate location to test this model

As for the remote monitoring model, the conditions to gather were: - High level revenues - Health-conscious population - Tech friendly

Scandinavian countries were therefore considered to test this model.

For the sake of simplicity, it was decided to test both tests in one location: Sweden.

However, due to cultural and regulatory reasons (required certification and data hosting

regulation) it turned out to be complicated to organize the test in Sweden.

Global teams therefore turned to the Irish affiliate, which was known for its sense of

innovation and offered the project and where the device was already commercialized. Not


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only were the very keen on doing the project, they also proactively took the lead on the

operational part of the project. As of today, the user test has started and we are waiting for

first feedbacks on the technology usage by the end of the summer, to help us build the most

relevant value proposition.

3. OPPORTUNIT I ES AND CHALLENGES

Opportunities

An attractive project that arouses interest internally. The device provider is well known

by Sanofi internally and even the top management is aware of their activity. Their technology

can be easily understood and stands a relevant example for mobile Health technologies, and

how it can improve healthcare and the way care is delivered.

A solution based on a technology already launched on the market that has already

proved its efficacy. This enabled the project team to act faster than if the solution still

needed to be certified and be approved by the medical community.

Strong implication of all stakeholders internally. Both global and local teams committed

to the project. The Irish affiliate proactively took care of the operational side of the project on

the field. Global teams coordinate all stakeholders successfully.

First feedback very positive. We see a strong interest and curiosity of the healthcare

professionals for that solution. Plus, the latter so far declared to be very satisfied with the

solution. We should gather more detailed and valuable feedback by the end of the summer.

Challenges

Defining the right business case. As described in the “history of the solution”, the aim of

the user test in Ireland is before all to define the best model for the solution between:

A solution targeting physicians that help them in the screening of patients

A solution targeting patients to help them monitor their heart activity and educate them on

their disease, improve patient-provider relationship and enable the cardiologists to better

follow up on patients.


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Elaborate the right financial model. This of course depends on the business case chosen

above, but it remains a consistent challenge for the future. Will the service be free, based on

a fee for service model? Or can even a reimbursement be considered?

The relationship with the device provider. So far, the latter is only a supplier for Sanofi.

Should the solution be a success, can a stronger partnership be put in place for future

developments?

Gather relevant and accurate insight from users to understand their use of the

solution. The whole point of the test is to understand how HCPs and patients use, or would

want to use the device. It is critical to be able to collect the right data and accurate feedback

to be able to adjust the solution and better meet their needs with the final version of the

solution.

Deploy the solution. Should the test be a success and the solution officially launched, what

other geographies would be appropriate for that solution? Many constraints exist on this

project: the brand must be active in the area, patients must follow the same pathway as in

Ireland, etc…

iv . DIABEO


Diabeo is a medical device with a telemonitoring service inside for diabetic patients that are

following a complex insulin therapy. It is the result of the collaboration of the following three

players:

-‐ Sanofi Diabète France, the Diabetes Business Unit in the French affiliate

-‐ A software editor specialized in medical and healthcare related applications

-‐ A French research institute for Diabetes.

Diabeo has not yet been launched and is at the moment being tested in France on a large

scale (TELESAGE study) to evaluate the clinical and medico-eco impact of the solution.


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Therapeutic needs and detection of gaps in care

Type 1 and advanced Type 2 diabetic patients* need to follow a complex insulin

therapy and are often under what is called a “basal-bolus” insulin regimen. In other words,

this mean taking both slow-acting insulin for usual blood sugar control and fast-acting insulin

right after or just before meals. The combination of the two enables the patient to maintain a

low and stable blood sugar level at all times. However, this therapy requires an accurate and

regular monitoring of blood sugar levels, as well as a precise follow-up of meals and

exercises in order to adjust the insulin dose that needs to be taken.


Diabeo has been developed to help these patients dealing with their disease on a daily basis.

The objective is twofold:

-‐ Helping them calculate the dose of both fast- and slow- acting insulin they need to

inject themselves with, depending on their medical prescription, their physical activity

and their nutritional behavior.

-‐ Strengthen the patient-provider relationship by automatically and frequently

transmitting the patient’s results to the healthcare professional, enabling this way a

better follow-up.

The solution is composed of:

-‐ A mobile app, compatible with iOs and Android, for the patient’s use only

-‐ A self-learning medical algorithm, embedded in the mobile app

-‐ A web application that offers a dashboard to healthcare professionals with automatic

analysis to follow-up on patients

-‐ A call center, hosted by specialized nurses formed in tele-diabetology.


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Patients interface

Form to fill in Insulin dose calculation Patient history Healthcare Professional interface

Figure 28: Diabeo user interface


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2004: The Research Institute contacts the software editor to develop a solution that could

help patients in the insulin titration process. The editor had by then already developed

Medpassport, a full web application that were used in various therapeutic areas. Sanofi

supports the project financially.

After successfully testing the concept on 20 patients, they decide to move forward with the

project.

2009-2011The software editor and the Research institute launch a second study in order to

demonstrate on a larger scale the benefit of the solution, with a part of the solution dedicated

to the patient in mobility. By then, the technology has evolved, and the solution is now a

PDA-based titration tool, coupled with a web-based application.

A study (TELEDIAB 1) is carried on among 180 patients (suffering from type 1 Diabetes)

during 6 months to demonstrate the clinical benefits, and suggest other benefits of the

solution.

TELEDIAB 1 results

Proved clinical outcomes: Better control of blood sugar level with no augmentation of

hypoglycemic risk (HbA1c –typical biomarker used to evaluate the efficiency of a solution

aiming to reduce or stabilize blood sugar levels) -0,9%)

Suggested economic outcomes: lower transportation costs

Suggested organizational outcome: increase in medical productivity due to a better

control and follow-up without additional time of medical practice.

2011: In a context where the regulatory framework becomes clearer (HPST law in 2010 that

officially defines telemedicine), Sanofi, The software editor and the Research Institute sign a

tripartite contract. Sanofi is primary in charge of the overall project management, the

promotion, and business plan elaboration.

Diabeo becomes the solution described in 1.2. (Mobile app + medical algorithm + call center

+ web based application + automatic analysis).

With the objective of asking a reimbursement to the French social security, a larger study

(TELESAGE) is being organized in France: 24 months, in 12 regions, with 700 patients, 200

diabetologists and 6 nurses formed in tele-diabetology.

So far, near half of the patients have been recruited.


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Commercialization was originally planned in 2014, but is now postponed in 2017 due to

several difficulties that have been encountered when setting up the TELESAGE study.

3. OPPORTUNIT I ES AND OBSTACLES

Opportunities

A mature project that already benefits from a good medical credibility. The concept of

the solution has already been clinically proved during the study Telediab 1, which has

highlighted clear positive medical outcomes when using Diabeo. The study currently running

(TELESAGE) should confirm these results. Moreover, since Diabeo was developed in

partnership with a recognized research institute in diabetology, the solution benefits from the

very beginning from the support of Key Opinion Leaders in the medical population.

Diabeo obtained the required official certifications. The solution is indeed CE marked,

which indicated the compliance with EU legislation. Diabeo is also the first software in France

to be classified as a medical device with IIb risk by the European Commission (IIb: Device

with “medium risk”).

Diabeo gained in visibility internally and in the ecosystem. This solution is indeed the

reference internally when talking about eHealth at Sanofi (i.e. an entire page was dedicated

to Diabeo in the last Activity Report of the Group). The Diabeo team receives a good support

from top management, since the project is considered as having a great potential, and

because it is developed within the core therapeutic area Sanofi is active in Diabetes.

Furthermore, Diabeo is already well-known in the ecosystem – in the medical community, as

well as bloggers, VCs, etc…

The Diabeo team succeeded in making the legislation evolve for the sake of the

project and created a whole new delegation protocol for telemedicine. For the project to

be carried on, physicians and nurses have a sign a tasks delegation contract (since some of

the tasks which were previously done by the physician will now be done by the nurse by

phone). It is a great step forward to have managed to build the protocol from scratch and

have it authorized on a national level.

A dedicated team that can invest the required time and resources on the project


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Launching Diabeo led to the creation of a new job status: nurses specialized in

telediabetology. This will probably serves as example for future projects.

Obstacles

Having to deal with a regulatory framework still in construction. No delegation protocol

existed in the case of telemedicine in France before Diabeo (it only existed for medical

practice in hospitals). This protocol had to be elaborated from scratch, and validated by each

ARS successively. Moreover, this lack of standardization also led to a very heave contracting

process. Indeed, for the TELESAGE study currently running, each nurse had to sign a

delegation contract with each physician, which was highly time and effort consuming.

Following the fast pace of technology evolution. The first version of Diabeo has been

developed for specific smartphones and operating systems. However the latter upgrade at a

rhythm that is complicated to follow. And new versions had to be developed and tested to

keep up with that rhythm in order to stay compatible with the systems and the smartphones

present in the population.

Future users need to be trained to use Diabeo, as it is an innovative and unusual solution.

Anticipate payers’ expectations concerning clinical and medico-eco outcomes. As the

team is targeting a reimbursement by the social security, evidence has to be gathered, but

the level of expectation is still unclear. Very few telemedicine solutions have so far obtained

an agreement for reimbursement, and none in diabetes. A high level of proof is expected by

the payer.

The status of pharmaceutical company prevent from collecting valuable data. Sanofi

has no access to the patient’s clinical information directly through the solution. The only data

they can collect is about how the patient uses the app (frequency of use), and some

anonymized transversal data. This is a real obstacle as such data could provide relevant

evidence and could help improve the solution itself.

Launching a solution with a 3-side partnership. The interest of each party should be

taken into consideration at all steps of the process. This also raises issues concerning


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Intellectual Property (Sanofi owns the brand Diabeo, but The software editor is the owner of

the software)

A complicated solution deeply rooted in France that seems complicated to scale-up.

Other affiliates are waiting for clear evidence before wanting to adapt and launch the solution

in their geographies. Diabeo is a project completely owned by the French affiliate, and no

global division has yet considered bringing it to scale.

6. RESEARCH RESULTS: NATURE, CLASSIFICATION AND OUTPUTS

a. EMERGENCE OF 9 KEY POINTS AND CLASS IF ICAT ION METHODOLOGY

Based on the observation of our cases, we rapidly came to the conclusion that project

teams, regardless of the project, were confronted to similar challenges for scale-up. Several

items appeared redundant and were raised as crucial elements to look out for in the scale up

of a solution, either directly by project leaders, or came out of our own analysis. The literature

review helped us organize these points in relevant clusters. We realized indeed that what

matters was the point of view taken when analyzing a breakthrough innovation. Rogers,

Moore and Berwick tackle the issues from the perspective of the end-user whereas Bartlettt

& Ghoshal takes an internal point of view, by analyzing the adoption of the innovation by

affiliates and other corporate entities. As for Akrich, Callon and Latour, they widen the

question to all other stakeholders in the ecosystem. As this segmentation matched with our

field observations, we articulated our key points to watch out for in the scale-up of a

breakthrough innovation as follows:

• Key points to watch out for adoption by end-users

Key point 1: Intrinsic features of the solution have an impact on diffusion

Key point 2: Solution architecture and modularity can influence scale-up potential

Key point 3: Solution must be monitored to ensure further adoption

• Key points to watch out for adoption by internal actors

Key point 4: Make individuals in the company feel involved on the project

Key point 5: Rationalize the choice of the first affiliate to ensure further deployment

Key point 6: Communicate and make the solution visible internally


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• Key points to watch out for adoption by other external stakeholders

Key point 7: Define a clear value proposition to interest all stakeholders

Key point 8: Elaborate a tailored promotion plan

Key point 9: Rationalize the choice of suppliers and partners when scaling-up

These key points will be analyzed in details individually in section 7.

b. HOW WE ADDRESS EACH POINT AND OUTPUT

Depending on the Key Point, we have adopted different research scenario:

• Found in literature tools or framework to help us analyze our cases. We then evaluate if

all elements of the literature selected are relevant for us and raise new points to the light,

which did not exist in the bibliography we used (Key Point 1, Key Point 2, Key point 5)

• Analyzed our cases on a given topic, raised major issues, and supported our arguments

by ideas found in the literature. (Key point 3, Key point 7, Key point 9)

• Analyzed our cases, raised major questions and found elements of response in

literature. (Key point 4, Key point 6, Key point 8)

Our research on each point led to 3 different types of outputs, for use of project managers

wanting to scale up a breakthrough innovation:

• We built actionable operational tools,

• We developed/collected conceptual frameworks to help decision making

• We raised vigilance on major issues that should not be overlooked

Perspective End users Internal actors External stakeholders

Key Point 1 2 3 4 5 6 7 8 9

Operational tool • • Conceptual framework • • • • • • Raise vigilance • • • •

Figure 29: Outputs by Key Point


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7. RESEARCH RESULTS: NINE KEY POINTS TO WATCH OUT FOR AND RELATED

TOOLS TO SUCCESSFULLY SCALE-‐UP EHEALTH SOLUTIONS IN AN

MULTINATIONAL CORPORATION

a. KEY PO INTS TO ENSURE ADOPT ION BY END USERS

i . KEY POINT 1: INTR INS IC FEATURES OF THE SOLUTION HAVE AN IMPACT ON

D IFFUS ION

1 . THE NEED FOR A TOOL TO EVALUATE A SOLUT ION’S SCALE -‐UP POTENT IAL

As the Customer Solutions & Innovation team has been integrated into the new Center of

Excellence for Integrated care, the team’s objectives and scope of action are destined to

evolve as well. Two topics of interest for the Center of Excellence for Integrated Care (among

others) are:

1. Identify, among the existing eHealth solutions within Sanofi, which solutions should

be scaled-up throughout the organization, and help with the scale-up process;

2. Continue exploration activity and solution development, with the objective of

developing solutions which will be scalable.

Given these two points of interest, we set out to build a tool that would be helpful for:

1. Assessing which existing solutions have the best potential to be successfully

scaled up throughout Sanofi;

2. Guiding the solution development process, keeping the issue of solution

scalability in mind from the very beginning of the solution design process.

2. ACADEMIC L I TERATURE ON HOW AN INNOVAT ION’S ATTR IBUTES CAN HAVE AN

IMPACT ON I TS D I FFUS ION RATE

In order to develop our tool, we turned to literature that investigates what can affect

the diffusion rate of innovations. We focused on Everett Rogers’ description of five perceived

attributes of innovations that affect their rate of diffusion in The Diffusion of Innovations, and

on the WHO’s “Practical Guidance for scaling up health service innovations”, which contains

a short chapter on the attributes of innovations that improve the potential for scale up.


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Everett Rogers’s five perceived attributes of innovation

According to Everett Rogers (1995), the following five perceived attributes explain

between 49% and 87% of the variance in the rate of adoption of innovations. They are listed

below, along with Rogers’ definition:

-‐ Relative advantage: “is the degree to which an innovation is perceived as being

better than the idea that supersedes it”;

-‐ Compatibility: “is the degree to which an innovation is perceived as consistent with

the existing values, past experiences, and needs of potential adopters”;

-‐ Complexity: “is the degree to which an innovation is perceived as relatively difficult

to understand and use”;

-‐ Trialability: “is the degree to which an innovation may be experimented with on a

limited basis”;

-‐ Observability: “is the degree to which the results of the innovation are visible to

others.”

The WHO’s “CORRECT” features of an innovation that enhance scale up

potential

The WHO and ExpandNet co-published a guidebook on scaling up health service

innovations, in which the authors describe seven features of a health service innovation that

improve the probability of a successful solution scale up in a new area, by a new health

organization… The criteria are based on literature on the diffusion of innovations, as well as

on additional empirical evidence on health service scale ups.

The criteria are listed and described below:

-‐ Credible, in that they are based on sound evidence or advocated by respected

persons or institutions;

-‐ Observable, to ensure that potential users can see the results in practice;

-‐ Relevant for addressing persistent or sharply felt problems;

-‐ Relative advantage over existing practices so that potential users are convinced that

the costs of implementation are counteracted by the benefits;

-‐ Easy to install and understand, rather than complex and complicated;

-‐ Compatible with the potential users’ established values, norms and facilities; fit well

into the practices of the national program;


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-‐ Testable without committing the potential user to complete adoption when results

have not yet been seen.

When comparing the two lists, we see that the WHO Guidelines re-state Everett Rogers’ five

attributes, and then add two attributes – credibility and relevance – which seem to be

necessary in the world of public health. Indeed, in healthcare, innovation adopters are more

likely to ask for evidence of effectiveness or to be swayed by key opinion leaders’ actions

(credibility). Furthermore, public healthcare innovations are often carried out in a context of

limited means, so there is an expectation that innovations should be prioritized and

developed to deal with the most important problems.

3. DEVELOP ING A SCALE UP POTENT IAL EVALUAT ION GR ID

After our literature review, we wanted to see if the seven attributes listed above

(Rogers’ five factors and the WHO’s two additional features) would be relevant “scale-up

potential” evaluation criteria for eHealth solutions developed within Sanofi.

We proceeded by first estimating the scale up potential of the four eHealth solutions

we have chosen to study in depth. By “scale up potential”, we are mainly referring to a

solution’s diffusion potential rather than to its deployment potential.

This estimation is based on our personal appreciation. We have decided to use a

simple scale: a green light means that the solution is considered simple to scale up, an

orange light means that the solution can be scaled up but the process will be slow and/or

difficult to carry out in certain regions, while the a red light means that the solution will be

extremely difficult, if not impossible, to scale up as is.

Figure 30: eHealth solution scale up potential assessment

-‐ Babushka SMS: we have observed that there is certainly a demand for cheap and

simple solutions like Babushka SMS from Sanofi subsidiaries, physicians and patients.


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However, the diffusion of the solution in Indonesia and the deployment to different

subsidiaries has been slower and more difficult than planned. Patient sign ups in

Indonesia to this service are not up to expectations, and while several Sanofi subsidiaries

have shown interest in developing this service, none has followed through for the time

being because of regulatory questions that vary in each country.

-‐ MORE: we have not graded this solution because its scale up potential will be

determined following the pilot results.

-‐ Diabeo: this solution has not yet been launched, but we feel comfortable rating is as

“very difficult to and slow to scale up” because the market access strategy will vary from

country to country, depending on the local health system and legislation, which in many

countries does not yet exist for this type of solution.

-‐ Phosphorus Mission: After much debate, we chose to rate this solution as orange

(difficult) rather than green. What we have observed is that the game was deployed

rather quickly throughout Sanofi, but we do not have data on patient downloads.

The next step was to “grade” each solution according to the seven criteria we wanted to test

in order to determine whether these results were positively correlated with our assessment of

the solutions’ scale up potential, and to verify if all seven proposed attributes were relevant.

Figure 31: Draft table for assessing an eHealth solution's scale up potential


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After completing this evaluation grid, we determined that the “relative advantage” and

relevance” attributes were not relevant evaluation criteria to compare Sanofi eHealth

solutions. We have chosen to remove these attributes from our evaluation grid for three

reasons:

1. Lacking predictive power for scale up potential: While all four solutions were rated

green in the relative advantage and relevance categories, we have assessed none of

the solutions as “easy” to scale up;

2. Lacking comparative power: All four solutions were rated green in the relative

advantage and relevance categories; this does not allow us to compare them. We

believe that most Sanofi solutions will come out as green in these two categories,

which makes them ineffective for comparing solutions.

3. While all criteria refer more to an end-user point of view, “relative advantage” is a

much wider concept that encompasses all external stakeholders. This will in our

research be treated as “value proposition” and be analyzed in a separate point (cf.

Key point 7 : Build a relevant value proposition for all stakeholders)

Finally, with the feedback of Sanofi project leaders, and going from our own experience as

junior project managers at Sanofi, we decided to add an additional evaluation criterion to our

grid:

-‐ Inter-operability, defined as “the ability of a system or a product to work with other

systems or products without special effort on the part of the customer”1

Inter-operability is important for the scale-up of e-health solutions because the solutions

need to be compatible with whatever device, operating service or telecom system the

users (physicians, nurses, patients) use, wherever they are. The more inter-operable the

initial solution is, the faster the scale-up process will be.

Result: the scale-up potential evaluation grid Our final scale-up potential evaluation grid contains six criteria:

-‐ Inter-operability;

-‐ Complexity;

-‐ Compatibility;

-‐ Trialability;

-‐ Observability;

-‐ Credibility.

1 http://searchsoa.techtarget.com/definition/interoperability


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We tested this grid again on our four selected solutions; the result seems satisfying as the six

selected attributes predict the scale-up potential of the solutions rather well.

Figure 32: Final table for assessing an eHealth solution's scale up potential

Criticism and qualifications of results

Our analysis of the four solution’s scale up potential and of how they measure up to

proposed attributes is based on our personal appreciation, rather than on objective

measurement criteria. To strengthen the pertinence of this evaluation tool, further research

should be carried out on which objective criteria could be used to measure:

-‐ Inter-operability;

-‐ Complexity;

-‐ Compatibility;

-‐ Trialability;

-‐ Observability;

-‐ Credibility;

It should be noted that objective criteria for the attributes proposed by Everett Rogers

(complexity, compatibility, trialability, observability) might be difficult to find given that Rogers

defined them as perceived attributes by users. These attributes are thus subjective and the

measurement criteria will have to vary according to which users are targeted.


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Furthermore, it seems that some of the attributes carry more importance when

determining the scale up potential of a solution. For instance, Phosphorus Mission was rated

as “green” for all but two criteria (observability & credibility), however overall it is rated as

somewhat difficult to scale-up (orange). Thus, further investigation would be required to

determine whether these two criteria are particularly important for scale up, or whether we

are simply missing some extra criteria or have misevaluated the solution.

i i . KEY POINT 2: SOLUTION ARCHITECTURE AND MODULARITY CAN INFLUENCE

SCALE-‐UP POTENTIAL

After comparing the diffusion and deployment rates of Phosphorus Mission and

Babushka SMS, we decided to explore whether the architecture of the solutions (mobile

application versus automated SMS system) had an impact on the scale up rate, and if so

how.

Reading Denis et al’s “Explaining diffusion patterns for complex healthcare innovations”

(2002) allowed us to apply a conceptual framework to analyze the solutions and understand

how their structure can impact their diffusion within an organization.

1. L I TERATURE REV IEW: DEN IS ET AL ’ S “EXPLA IN ING D I FFUS ION PATTERNS FOR

COMPLEX HEALTHCARE INNOVAT IONS

Denis et al’s methodology

The authors of “Explaining diffusion patterns for complex healthcare innovations”

(2002) selected four different cases of innovation dissemination in order to study what affects

the diffusion rate of innovations in hospitals and medical settings. The four cases were

selected by using a two-axis matrix with the following criteria:

• Leading versus lagging evidence: was solid evidence of the innovation’s

effectiveness available before or after the diffusion process began?

• Rapid or slow adoption: this refers to how quickly the innovation diffused

throughout the medical community.

The matrix featured below thus contains four cells that correspond to four different types of

diffusion scenarios:

1. Over-adoption: when solutions with lagging evidence are rapidly adopted;

2. Under-adoption: when solutions with leading evidence are slowly adopted;

3. Successful adoption: when solutions with leading evidence are rapidly adopted;


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4. Adoption with prudence: when solutions with lagging evidence are slowly adopted.

Denis et Al then selected four different innovation diffusion cases (featured within the graph

below) within the Quebec region that correspond to these scenarios, and studied what

factors had affected their dissemination rate.

Figure 33: Table 1 in Denis et al's "Explaining diffusion patterns for complex healthcare innovations" (2002)

Denis’ conception of the structure of innovations

According to Denis, complex innovations can be understood as being made up of:

• A hard core, which is the well-defined part of the innovation which cannot be adopted

to meet the needs of the adopting system (patients, doctors, hospital administrators

etc.); in the case of a drug, the hard core would be the molecule.

• A soft periphery, which is the less clearly defined part of the innovation that can be

more or less easily altered to fit the adopting system’s needs; in the case of a drug,

the soft periphery would consist of who the drug is prescribed to, the dosing, the cost

etc.


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Figure 34: an illustration of hard core and soft periphery taken from "How to spread Good Ideas" (2004)

The effect that the clarity of an innovation’s hard core & soft periphery has

on its diffusion rate

Denis et al explain that, depending on the type of health care innovation, it can be

more or less simple to differentiate between the innovation’s hard core and its soft periphery.

For instance, the distinction is clear for a drug molecule, the hard core simply being the

molecule itself; the distinction is much more vague for sets of practice standards, such as the

ACT innovation which is Denis’ example of an under-adoption. ACT stands for Assertive

Community Treatment, and is an approach to treating psychiatric patients. It is a set of

actions, of guidelines to follow. While there is good evidence that taken together, all the

proposed actions are an effective method of treatment, it is not clear whether some actions

are more effective than others, or whether practitioners can effectively implement just a

subset of the proposed guidelines. There is thus a lack of clarity over what constitutes the

hard core of the ACT innovation, the part that may not be altered for it to stay effective.


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Figure 35: Table 3 in Denis et al's "Explaining diffusion patterns for complex healthcare innovations" (2002)

Denis’ research on the diffusion rate of the ACT innovation suggests that the lack of

clarity over the hard core and soft periphery actually engendered confusion and debate

among practitioners interested in the innovation, and may have contributed to the solution’s

under-adoption.

At the same time, Denis et al stress the importance of this soft periphery in the

diffusion process, arguing that the “negotiation of the meaning of an innovation in a particular

context occurs in the soft periphery of its definition, enabling a variety of pathways to

adoption”; this implies that the more the solution can be tweaked and altered to

simultaneously satisfy the needs of different actors in the adopting system, the more likely it

is to be adopted.

2. SANOF I CASE STUD IES : LOOK ING AT PHOSPHORUS MISS ION & BABUSHKA

SMS UNDER THE LENS OF THE HARD-‐CORE/SOFT PER IPHERY D IST INCT ION

Phosphorus Mission

i. A game with a fairly clear distinction between hard core and soft periphery:

Phosphorus Mission is a casual video game designed to educate CKD patients on their

disease and treatment, with the aim of helping them improve their adherence to the nutrition

and medication regimen their disease requires. Distinguishing between the game’s hard core

and soft periphery isn’t obvious, so we proceeded to analyze it by levels, from the nucleus,


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the most hard and unalterable part, to the most soft and malleable aspects of the game:

Figure 36: Phosphorus Mission structure

Looking at the chart above, it is difficult to draw clear line between the game’s hard core and

soft periphery. Does it stop at the line between geographic adaptation and key messages &

game structure, or at the line between key messages & game structure and pathology &

targeted users? One could perhaps argue that it stops even earlier – it could be adapted for

a different pathology.

ii. The hard core / soft periphery distinction in practice and its impact the

game deployment throughout Sanofi

As the Phosphorus Team began to scale up the game throughout the organization, the

distinction between care core and soft periphery was clarified:

-‐ Hard core: everything up to key messages and game structure – the game’s

purpose, key messages and the way the game looks and is played could not be

changed;

-‐ Soft periphery: the game interfaces and geography could be altered according to

affiliate needs.


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Figure 37: Phophorus Mission - distinction between hard core and soft periphery

This distinction simply stems from the fact that while it is relatively simple to change items

related to the interfaces and geography, changing anything else required going through all of

the game development processes and costs again; it would involve creating a similar but

different solution. Thus, the distinction between hard-core and soft periphery is actually quite

clear for Phosphorus Mission.

1. Ways the clear distinction between hard core and soft periphery

accelerated the scale up of Phosphorus Mission

By defining the hard core of the game so clearly, the Phosphorus Mission project

team gave a very clear definition of the game, to whom it is addressed and for what purpose.

This clarity probably simplified the communication effort toward potential adopters (Sanofi

affiliates eager to present the product to their patients).

Furthermore, limiting the scope of what parts of the game can be adapted for affiliates

limits the cost related to these adaptations, and makes the game more affordable to scale up

than it would have been with a larger soft periphery.

2. How this distinction can limit the Phosphorus Mission scale up


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By definition, Phosphorus Mission is only addressed to CKD patients who want or

need to learn about their condition and treatment. The game would have a larger scope of

potential adopters if it had a wider soft periphery.

In fact, the Phosphorus Mission team is working on the development of a new game

that is addressed for patients within a different therapeutic area. This could be considered a

re-invention of Phosphorus Mission, a widening of its soft periphery in order to adapt to new

users.

Babushka SMS

i. A game with a vague distinction between hard core and soft periphery:

Babushka SMS is an automatic text-messaging program designed to help patients

adhere to their prescribed medication treatment. Currently, it is only launched in Indonesia,

where it is designed for cardiac patients who are prescribed Plavix. We will analyze it by level

in the same way we looked at Phosphorus Mission.

Figure 38: Babushka SMS structure

Distinguishing between the hard core and the soft periphery of Babushka SMS is difficult,

because even relatively small changes to the program – for instance, the language –

demand replacing the message content. And while adapting the messaging to certain


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pathologies can be simple if the treatment schedule is similar to that of Plavix (once a day),

adapting the system to other treatments required adapting both message content and

frequency…

ii. The hard core / soft periphery distinction in practice and its impact on the

solution deployment throughout Sanofi

While Babushka SMS is for the time being only launched in Indonesia, the project

team is working with new affiliates and brand teams to scale up the solution throughout

Sanofi. These efforts have revealed that potential adopters perceive the hard core of the

program as “sending automatic text message reminders to patients”, all other aspects

(pathology, language, preferred message content) being negotiable and adaptable according

to adopting teams’ needs.

Figure 39: Babushka SMS - distinction between hard core and soft periphery

3. Ways the vague distinction between hard core and soft periphery

can accelerate the scale up of Babushka SMS

The lack of clarity over what exactly constitutes the hard core of Babushka SMS was

beneficial in the sense that, when in doubt, potential adopters assumed that the hard core


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was small and that the solution could be adapted to their needs. In other words, the

vagueness led to the program having a large soft periphery and thus having a very wide

base of potential adopters, since the pool of Sanofi teams who could adopt the solution was

not restrained by pathology or geography.

4. How this distinction can limit the Babushka SMS scale up

Launching the Babushka SMS solution in a new country requires time to translate the

solution, buying a different local license from the vendor to launch the solution, and time to

gain local regulatory approval. Adapting the Babushka SMS solution to new pathologies

means adjusting the message content and frequency. Doing both of these things at the same

time (trying to scale up Babushka SMS to a new country for a new pathology) has proven

very challenging; the process ends up being nearly as costly as the initial Babushka SMS

development, and takes the economies of scale out of the scale up process. If there was less

scope in what could be changed, perhaps the scale up process would be a bit faster or

simpler.

3. TAKEAWAY FROM THE CASE STUD IES

a. Most eHealth solutions seem to have a vague distinction between their

hard core and soft periphery, which can slow down the scale up process

For both Phosphorus Mission and Babushka SMS, the distinction between hard core

and soft periphery is hardly clear-cut. This might actually be the case for most eHealth

solutions, especially those that only consist of software. This is because, like the ACT

intervention described by Denis above, many eHealth solutions are actually a set of different

interventions: for instance, Babushka SMS includes reminders, but also motivational

messages and the possibility to connect with a caregiver. Adopting affiliates might want to

cherry-pick which parts of the solution to keep, but then will be left unsure of the re-invented

solution’s effectiveness, since only the solution as a whole set of interventions will have been

tested. This vagueness and uncertainty can open up debates between different actors within

the adopting system and thus slow down the adoption process. In comparison, scaling up the

launch of a new drug (Sanofi’s traditional activity), which has a very clear hard core, doesn’t

pose this type of problem.


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b. Having a wide soft periphery expands the base of potential adopters but

complicates the scale up process

When we compare the above Phosphorus Mission and Babushka SMS case studies,

we see that Babushka SMS has a wider soft periphery that allows it to have a wider potential

base of adopters within Sanofi. While Phosphorus Mission is designed solely for renal

patients, Babushka SMS can be altered to fit the needs of a variety of patients and thus of

Sanofi brand teams.

However, we can see from the Babushka SMS project team’s efforts to scale up the

solution across Sanofi that the deployment process has proven to be more difficult for

Babushka SMS than for Phosphorus Mission, in part because Babushka SMS is supposed to

be more adaptable to both brand and affiliate needs. While adapting Babushka SMS to both

a new country and a new pathology at the same time is possible and not necessarily much

more costly than doing just one of those two things at a time, operationally it is similar to

starting from scratch:

-‐ Launching the solution in a new affiliate can require developing new protocols for

adverse events reporting, since what is possible in one affiliate might not work in

another. It also requires ensuring compliance with country-specific legal

requirements.

-‐ Adapting Babushka SMS to a new pathology involves designing and approving new

messages and a new message sending frequency, which can be time consuming and

requires the active involvement of the new brand’s medical team. Adapting to a new

pathology also means that whatever proof of effectiveness that exists for Babushka

SMS in Indonesia for cardiac patient adherence might not transfer over to a new

treatment. It can be likened to testing a new technology again.

Is there a scale-up strategy that could effectively deal with the deployment challenges

that Babushka SMS and similar solutions have faced? We believe that the bowling alley

market development strategy proposed by Geoffrey Moore in Crossing the Chasm:

Marketing and Selling High-Tech Products to Mainstream Customers (1991) could be a good

model off which to base the deployment strategy within Sanofi.

The bowling alley market development model is the strategy that Moore suggests for

attacking the “Early Majority” part of the market, which is typically made up of pragmatists

who are not interested in innovation, but in a solution that cost-effectively answers their

problems. This is a large share market, made up of different niches. Moore suggests that the


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most effective way of reaching this early majority is to proceed by niches, instead of

approaching it as a homogeneous group.

The group marketing the innovation must first find a niche market that is willing to adopt

the innovation because it is the only product on the market that answers their needs, even if

it has yet to be fully proven. In the case of Babushka SMS, that initial niche would

correspond to the Sanofi Indonesia affiliate. Then, once the initial niche is happy with the

solution, propose the same solution to a different niche that could benefit from the exact

same solution. This would correspond to launching Babushka SMS as is (except maybe

changing the language) in another Sanofi Affiliate that wants an adherence solution for

cardiac patients. The fact that the solution has already been successfully launched and

proven, and might benefit from brand team support, will make the launch in a new affiliate

simpler. At the same time, the Babushka SMS project team could develop a new version of

Babushka SMS for a different pathology in Indonesia; since the local team has already had

experience adopting new solutions, the process should be smoother than starting in a new

affiliate.

In conclusion, our case study helped us developing a new approach to Denis’ theory.

Whereas in his conception, the wider the periphery, the faster and wider the adoption by end-

users, we propose a more ambiguous and paradoxical approach. A large periphery is

certainly a way to broaden the target market, as the solution can be adapted to answer a

wider spectrum of needs. However, it may slow down the scale-up process as it requires

many heavy and costly modifications that affiliates are sometimes not ready to make.

Similarly, a fixed and restraint periphery obviously limits the possible applications of the

solution and therefore restricts potential targets. Yet, because only limited alterations have to

be made to these soft components to adapt the solution, it simplifies scale up process.


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Figure 40: Graph illustrating the Bowling Alley strategy, available on Prof. Kenneth E. Homa's website

i i i . KEY POINT 3: SOLUTION MUST BE MONITORED TO ENSURE FURTHER

ADOPTION

The importance of monitoring the innovation came out from two different sources: on

one hand, from a report of the WHO about Practical guidance for scaling up health service

innovation, and on the other, from our direct observations of CSI projects and the necessity

of monitoring the solution.

1. L I TERATURE REV IEW: THE IMPORTANCE OF MONITOR ING IN THE GU IDANCE

FOR SCAL ING UP E LABORATED BY THE WHO

In the healthcare sector, scaling up innovations requires time and effort. That is why

the WHO published a practical guidance to scale up health service innovations, in which it

develops a concrete scaling up strategy to follow. This strategy refers to the plans and

actions necessary to fully establish the innovation in policies and programs and relies on 5

pillars, among which: Monitoring and Evaluation


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Figure 41: Expandnet's and WHO's scale up strategy for healthcare innovations (2009)

Before going further in details in the content of this pillar, it should be noted that the report

exclusively refers to public health initiatives, and not corporate business solutions. While

some aspects at stake are common between the two as they both try to implement change in

a complex industry, they differ on many points. The proposal of the WHO must therefore be

understood in this perspective. It is however an interesting basis for us to understand the

importance of tracking an innovation when launch to ensure further diffusion.

The WHO starts by listing several questions that need to be raised during scale up.

- What are the pace and coverage of scaling up?

- What are barriers to expansion and how can these be addressed?

- Is the innovation being institutionalized at local, regional or national levels?

- What are the barriers to vertical scaling up and how can these be addressed?

- Are the essential features of the innovation intact as scaling up proceeds?

- If essential features are not consistently implemented, what remedial action can or

should be taken?

- Is the innovation still producing the same results, especially in those regions of the

country where it is being adapted to suit local environmental conditions?

- Is the innovation being appropriately adapted to new conditions resulting from

changes over time, or from regional differences?

- Is scaling up becoming swifter and more efficient over time? Are economies of scale

being reached?

- Does scaling up produce the anticipated impacts?


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However, existing systems for monitoring are rarely capable of providing answers to these

questions, and special procedures have to be put in place.

Monitoring the solution can, according to the WHO, have two major benefits for scaling up

innovations:

1. It gathers evidence that proves the value of new approaches and can therefore

motivate managers and communities to implement change

2. It gather scientific knowledge on success factors for scale up

Methodologies to monitor the innovation should stay simple, and should before all be

compatible with existing systems and procedures. By building too complex tracking

processes, one takes the risk of demotivating people to implement them, and in the end

failing to gather valuable data.

Monitoring the innovation also implies having established, in line with the entity in charge of

the implementation (in our case the affiliate), a clear planning defining milestones, target to

achieve, and indicators to track. As it results from a join decision, monitoring the evolution

will not be perceived as an external intrusion judging the project, rather more as a way to

evaluate project progress.

As for the indicators to track, the WHO differentiates 3 types of indicators:

- Indicators for monitoring the scaling up process

Example: extent to which essential features of the innovation (e.g. training,

management, facility construction) are being implemented

- Indicators for capturing the outputs and outcomes of the innovation

Example: client and community satisfaction with services that include the

innovation

- Indicators for examining the results and impacts of the innovation

Example: number of people with access to quality services over time has

increased

The WHO also underlines the fact that both qualitative and quantitative methodologies must

be used to monitor innovations, since only the combination of the two will provide teams with

an exhaustive and realistic overview of how the project is progressing.

Even though these recommendations primarily target public health initiatives, we believe

they can all be applied to the field integrated care solutions. The analysis of two case studies

hereafter will similarly underlines the importance of tracking and monitoring data, while

bringing additional elements to take into account.


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2. CASE STUD IES & OBSERVAT IONS

Babushka SMS

Babushka SMS, the adherence solution based on automatic SMS reminders, has

been launched in Indonesia. The solution is considered within Sanofi to be a Patient Support

Program (PSP), which is defined as a program to improve patient’s adherence to treatment

with a Sanofi marketed medicinal product or to improve patient’s use of a Sanofi marketed

medical device, in agreement with the treating physician.

Since Sanofi launched the solution, a limited amount of data has been collected and

gathered on the solution and its diffusion. This data is provided on an aggregated and

anonymous level. The reasons that can explain why the CSI team is not able to gather more

information today are the following:

Regulatory reasons: Because Babushka is a Patient Support Program, specific rules and

procedures must be carefully followed, especially for solution monitoring and data collection.

Only the relevant Sanofi medical team (in this case, the Plavix medical team in Indonesia)

may have access to a limited amount of patient data that is collected by service providers (cf

frame below).

Organizational reasons: The global Sanofi entity and the Indonesian affiliate agreed on a

clear list of KPIs prior to launch, but failed to ensure that the monthly reports sent by the

services provider included all these data.

Every month, the CSI team receives a report from its services provider with the following

data:

• Number of patients enrolled

• Number of Healthcare Professionals enrolled

• Drop-out rate

• Number of text messages sent

• Response rate

As of today, the data that has been gathered is difficult to compute and analyze. For

example, we know how many patients are enrolled, how many reminders have been sent

out, and how many responses (saying if yes or not the patient took his medicine – on a

declarative basis) have been received. Yet, we do not know what proportion of patients

responded, if it is always the same patients who answer text message, the reasons why


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some patients don’t answer, etc. We are for the moment lacking qualitative data about users’

satisfaction that could help us assess the acceptation of the reminder solution by patients

and HCPs. Satisfaction market research should be rolled out in the coming months.

All these data would be highly valuable to evaluate the effectiveness and the actual diffusion

of the solution among a given population.

However, the lack of collected data has been a notable obstacle to the solution scale-

up. In the Indonesian affiliate, the management is reluctant to promote and extend the

solution at a higher scale in the country without more data to prove that the program is

successful (at the very least, appreciated by patients and doctors), especially because the

money to scale-up Babushka would be drawn from the affiliate’s budget. Being able to collect

relevant and comprehensive data on a solution therefore brings direct evidence that can

encourage scale-up. The issue remains the same with other affiliates: they will not be willing

to deploy a solution in their geographies if they do not have the evidence that patients and

HCPs are satisfied with the solution or that the solution significantly impacts patient’s

adherence to treatment.

Phosphorus Mission

Similarly, until recently a limited amount of data has been collected for Phosphorus Mission

the educational game for CKD patients. So far, only the number of game downloads per

geographic zone (corresponding to a given online store – such as the Apple Store) was

available. While the project leader eventually commissioned a detailed study on patient

engagement with the game, she could not do so earlier in the process because carrying out

a study right after the game launch would not be in line with the lean development approach

espoused by the team’s management.

The study is currently running among 70 patients in 4 different countries. The aim is to

evaluate:

• Overall satisfaction of the solution

• Get patients feedback on pros and cons of the game

• Knowledge of patients about the pathology

• Suggest an impact on adherence to phosphate binders (based on patients’

declaration)

Like for Babushka, gathering this data will have a strong impact on scale-up:


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if the solution proved to be effective in the selected countries, other affiliates that have so far

been quite cautious or skeptical concerning Phosphorus Mission will be more likely to adopt

the solution and launch it in their geographies in the future. The solution deployment rate can

be significantly accelerated this way.

Moreover, getting users’ feedback enables the project team to understand what

needs to be changed or improved in the solution. Having tested the first version prior to

launch and the second version in real life has led to useful conclusions that constitute a

constructive basis for developing a second version of the game. This next version would

better meet patients’ needs and could supposedly diffuse at a higher rate among the

population. For example, according to the first feedback we received, patients were overall

pretty satisfied with the game but some found it redundant and repetitive in the long run.

Should the game be upgraded and a new version released, the project team would make

sure the games stays entertaining longer. The game could therefore gain in attractiveness,

becomes more viral and be adopted by a larger amount of patients.

Finally, monitoring the solution helps steer the scale up in the right direction.

Gathering data is in the case of scaling up a necessary tool for project management. As

explained before, the market research was undertaken in 4 different countries. If for example

the data collected when monitoring the solution shows a mitigated success in Korea

compared to the United States, then this would help the project management tailor their

solution and marketing approach to the country, and therefore reach a wider target market.

3. LEARN ING FROM THE CASE STUD IES : WHY I S I T NECESSARY TO TRACK &

MONITOR THE INNOVAT ION?

These observations from real case studies inform us on the importance of tracking and

monitoring the solution for the process of scale-up:

• Monitoring the solution once launched enables the project team to collect valuable

evidence of the effectiveness of the solution, and therefore to convince other affiliates

to adopt the solution and launch it in their geographies. This can therefore strongly

influence the deployment axis of the scale-up.

• Monitoring the solution can highlight the pros and cons of a solution in order to build a

better second version of the solution, and in the future create product lineages.


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• Monitoring the solution is essential to gather data about the actual cost of the solution

in the long run and build an appropriate business case

• Monitoring the solution once launched is a key management tool in order to

constantly adapt solutions features and marketing strategy to better fit in the target

market.

The two last points cover the diffusion axis of the scale-up, as they show how tracking and

gathering data about a solution can help develop a lean market approach and therefore

reach more end-users in a given country.

b. KEY PO INTS TO ENSURE ADOPT ION BY INTERNAL ACTORS

v. KEY POINT 4: MAKE INDIV IDUALS IN THE COMPANY FEEL INVOLVED ON

THE PROJECT

In the case studies the support of crucial actors internally appeared key in the decision

and the success of the launch or scale up afterwards. In a large, decentralized, multinational

corporation such as Sanofi, garnering internal support and interest at all levels of the

organization could is essential to ensuring a successful eHealth solution launch and scale

up. Plus, this support must exist from the very beginning of the project for it to be really

effective when the challenge of scale up occurs.

We will firstly analyze the cases Phosphorus Mission and Babushka SMS to understand

the nature of the internal alignment and support for these projects. Based on these learnings,

we will then develop recommendations for project teams, to ensure the existence of this

support from the ideation of their solution.

1. CASE STUD IES & OBSERVAT IONS

Phosphorus Mission case study

The Phosphorus Mission team realized the importance of ensuring internal interest

early on in the game development. When the Phosphorus Mission team started developing

their solution, one of the first things they did was approach the Renal brand team in order to

determine:


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-‐ What insights had already been gathered by Sanofi on Chronic Kidney Disease

patients;

-‐ What was the business strategy of the Renal brand;

-‐ What challenges the brand was facing – in this case, upcoming patent loss and

the need to add-value to its medication.

The Phosphorus Mission then used this information to guide the development of the

solution and of the promotion strategy. In other words, the team worked hard from the

beginning of the project to ensure the interest of the Renal team, which had been identified

as a key stakeholder for the promotion and scale up of the solution, even if the Renal team

wasn’t paying for the solution development. The support the Phosphorus Mission project

team received from the Renal brand team proved to be invaluable at later stages, when

seeking internal approval of the solution or promoting it to Renal brand teams in various

Sanofi affiliates.

One other point that benefited the scale up of the Phosphorus Mission game is that it

proved to be a “door-opener” for sales representatives: some sales reps were actually sought

ought by nephrologists wanting to learn more about the game. Since most sales

representatives usually have to work very hard to obtain even five minutes of a doctor’s time,

promoting this game has actually turned out to be in the interest of sales representatives,

and this has positively influenced the promotion efforts and thus the game diffusion. IT

should be noted that sales reps who did not perceive the game as a “door-opener” probably

did not see it as in their interest to promote the solution, since their incentives are not linked

to the number of game downloads, and since they have too little time with physicians to

discuss all Sanofi products that they cover.

Finally, one point that has probably negatively affected the scale up of Phosphorus

Mission is the fact that many Sanofi affiliates have limited budgets to dedicate to renal

pathologies. Even if local Renal product leaders are interested in the solution, they have

limited means and are not incentivized to adopt the solution and promote it in their market.

Babushka SMS case study

The Babushka SMS project team decided early on to partner with the Indonesia affiliate.

This choice was driven by several reasons:


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-‐ Indonesia is a large market, with a large cardiac population, and a large portion

of cellphone users

-‐ The local marketing and medical directors were very interested in the solution,

and ready to champion it:

o The local cardiac team had already noticed that a good portion of the

patients had difficulties adhering to their prescribed Sanofi medication;

o The medication in question was also going to stop being fully reimbursed

by local authorities as generics were going to arrive onto the Indonesian

market, so providing a service that adds value to the Sanofi medication

could be beneficial;

This strong local interest in developing the Babushka SMS solution was the key to

bringing it to market and scaling it up within the country. They dedicated time and resources

to the project even though it wasn’t part of their official job missions, and did trouble-shooting

to determine the best method of promotion (they identified nurses as key promoters of the

solution).

The regional team’s interest in the project also proved to be of high importance; when the

organization of the randomized controlled trial designed to test the effectiveness of the

Babushka SMS solution ran into some hurdles, the regional team dedicated several

experienced personnel to ensure successful trial management. This is because they saw

adherence as a key issue for themselves and Sanofi.

Babushka SMS has also faced the same challenge as Phosphorus Mission, namely lack

of dedicated resources. As motivated as the local team has proven to be, its time is limited

and its incentives are not linked to the Babushka SMS project; this means that when local

team members have had to choose between giving time to the Babushka SMS project or

another issue they are evaluated on, as rational people they have systematically prioritized

the other issues.

2. CASE STUDY LESSONS

The above case studies have highlighted how important it is for the eHealth solution

project team to garner interest at all levels of the organization in order to ensure a successful

solution launch and scale up.


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Furthermore, in a decentralized organization such as Sanofi, we believe that the eHealth

solution project team should apply what we will call a horizontal and a vertical approach to

assessing interest for the project within the organization:

• Horizontal approach: Assess who are the key stakeholders for the projects across

the Sanofi divisions (global brand team, global regulatory team etc.) Having a project

champion in one of these divisions can prove very useful, because brand teams have

members in almost every Sanofi affiliate and could thus prove to be very effective

ambassadors for the project;

• Vertical Approach: Study every member of Sanofi involved in bringing the solution

to the patient, hierarchically. If we take the example of the Babushka SMS project, this gives

the following “chain of command”

-‐ Center of Excellence for Integrated care, practically on par with

-‐ Local Marketing & Medical directors

-‐ Local Product Manager

-‐ Local sales and area manager

-‐ Local sales representatives.

The idea would be think of how developing, promoting and scaling up the solution is in the

interest of each of these stakeholders. If promoting the solution isn’t actually in their interest,

avenues to explore could include:

-‐ Reworking the criteria according to which employees are evaluated to

encourage employees to work on these kinds of innovative projects. As Michel

Berry explained in “Une technologie invisible? L’impact des instruments de

gestion sur l’évolution des sytèmes humains” (1983), management tools often

end up heavily, and often unconsciously, influencing the behavior of employees.

If the management controls in place dissuade workers from participating in new

projects that incorporate a risk of failure, than it will of course be difficult to

stimulate an interest in such projects.

-‐ Creating incentives for employees: In chapter 6 of Everett Rogers’ Diffusion of

Innovations (1995), Rogers analyzes the different types of incentives that exist

and their effect. According to Rogers, incentives work by modifying the

perceived relative advantage of an innovation, by making it more beneficial to


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adopt or diffuse it because of a cash or gift reward. Furthermore, citing Rogers’

1973 work on family planning innovation, Rogers states that incentives do in fact

speed up the rate at which innovations are adopted.

vi . KEY POINT 5: RAT IONAL IZE THE CHOICE OF THE F IRST AFF IL IATE TO

ENSURE FURTHER DEPLOYMENT

1. KEY PO INT OVERV IEW

The comparative analysis of the four project monographies above (section 5.C) brings to

light the opportunities and challenges that projects can be faced with in the first affiliates in

which they are developed.

We will illustrate this key point by comparing and contrasting the Diabeo and Babushka

SMS projects and by drawing on the works of Bartlett and Ghoshal (Ghoshal, 1989) and of

Guérineau (Guérineau, 2013), which we synthesized in our literature review (section 4.c).

This analysis will lead us to highlight two key components – the affiliate’s internal

environment and its external environment – to be considered in the scale-up because they

can affect how to choose the sequence of countries in which the innovation is launched. The

goal if this analysis is two-fold:

1. Highlight the opportunities & challenges an eHealth solution will face during rollout. In

practice, it isn’t always possible to choose the affiliate according to its capacity to deploy

innovations. Other factors must take precedence: the affiliate’s budget, whether the

affiliate has a team of motivated people with enough time to dedicate to the launch of a

new solution, whether launching the solution is in line with the affiliate’s (or one of its

brands) overall strategy… Often, the decision is whether to launch an innovation in a

less-than-ideal affiliate or not to launch at all. In this kind of situation, the categorization of

the different types of roles affiliates can play would not serve to select the affiliates, but

rather to highlight what types of opportunities and challenges the project team will face.

2. Guide the selection of the first affiliate in which an eHealth solution is launched.

Categorizing affiliates according to their innovation-deployment capabilities could

theoretically help the Center of Excellence for Integrated Care (CEIC) select the most

appropriate affiliate for the launch of a new eHealth solution.


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2. MANAGEMENT L I TERATURE ON THE ROLE OF AFF I L IATES W ITH IN MNCS

In order to develop this key point, we relied heavily on Bartlett and Ghoshal (Ghoshal,

1989) and of Guérineau (Guérineau, 2013), which we synthesized in our literature review

(section 4.c).

In particular, we used Guérineau’s two dimensions of affiliate analysis – internal

environment and external environment – and his four “ideal types” of affiliates, which we shall

briefly redefine here for the reader.

• Internal environment: the affiliate’s capabilities to deploy innovations, its human and

financial resources.

• External environment: the affiliate or its market’s need for innovation; the external, market

forces that drive an affiliate to deploy innovations.

These two axes yield the following typology matrix, with four different “ideal-types” of

affiliates.

considerable Potential New Big Historic Big

Value of the

local innovation

ecosystem

average Implementer Accelerator

low high

Local organization's capability-set for innovation Figure 42: Guérineau's classification of subsidiary roles in relation to innovation deployment

• Guérineau’s description of the four ideal-types of affiliates:

o Historic Big: Can take risks and lead by example, but can also be bogged down

by its size and organizational complexity, which makes rapid innovation

deployment impossible. Can share resources, experience and expertise with

other affiliates.

o Accelerator: Can quickly deploy targeted innovations according to market

specificities and available affiliate expertise in some areas. Leads to rapid client

feedback to prepare the innovation deployment in other zones.


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o Implementer: These affiliates and their markets have only started growing. They

have a demand for innovations that are easy and fast to deploy, in order to keep

up with market growth

o Potential New Big: large and fast growing affiliates in new markets in which the

company’s traditional business models don’t work. There is an internal capability

gap in these markets that needs to catch up with a market that is hungry for

innovation.

3. CASE STUDY: D IABEO IN FRANCE , BABUSHKA SMS IN INDONES IA

Diabeo:

Diabeo is being developed and launched in France simply because it is the French

affiliate that initiated, funded, and developed the project. While this ambitious project is for

the time being entirely French-affiliate-led, the Sanofi global corporate team is carefully

following the project development. Indeed, Sanofi corporate has even demonstrated its

interest and support by dedicating an entire page of the “Rapport d’Activité 2013” to the

Diabeo project.

When we look at the affiliate-related factors that have helped or hindered the project

development, we see that they can roughly be grouped under external environment related

factors and internal environment related factors.

Factors that positively affected the Diabeo development:

Factors that have slowed down the Diabeo development:

Inte

rnal

env

ironm

ent:

• Strong business development and technology

scouting & partnering capabilities: Sanofi France’s

business development team supported the project

from 2004 onwards and co-drafted and signed a

tripartite cooperation agreement that allowed Sanofi

to develop a commercial project around the solution;

• The French affiliate has a relatively large budget

compared to most Sanofi affiliates: this allowed

Sanofi France to commit to financing the Diabeo

project

• Strong support from top affiliate management

Strong development capabilities: product

development, market access, clinical trial teams.

• Existence of a “project champion” (Nicolas Cartier)

who pushed Diabeo forward at the early stage

n/a


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Exte

rnal

env

ironm

ent:

• Strong local innovation ecosystem: the fact that

Sanofi France could meet and partner with

innovative organizations such as the Research

Institute and The software editor allowed the

project to emerge.

• Existing regulatory or legislative restrictions on

how telemedicine can be carried out: Current

French legislation requires the patient’s

diabetologist and Diabeo call center nurse to

sign a contract located in the same region

this constraint could seriously hinder the

Diabeo launch

• The legal framework for this kind of project is

nascent and evolving slowly: French legislation

over telemedicine has only begun being

drafted. In fact, projects such as Diabeo are

spurring the legislation to evolve, but in the

meantime they must operate in an undefined

legal environment.

Figure 43: Diabeo - internal and external affiliate factors that affected the solution launch

Looking at the graph above, we can see that factors which have most slowed down

the launch of Diabeo are those that are related to the external environment.

Babushka SMS:

The decision to develop Babushka SMS, an automated text-messaging service

design to improve patient adherence, stemmed from the global CSI (now part of the CEIC)

team. The team decided to fund the project and to partner with Sanofi Indonesia to develop

the solution. The decision to work with the Indonesia affiliate was driven by the following

factors:

-‐ External environment: Indonesia has a large cardiac patient population. A

large part of this population includes cellphone users. Furthermore, the local

medical and marketing teams knew it had a patient adherence to medication

problem (physicians reported patients dropping out of treatment or

decreasing adherence drastically four months after it had begun). On a

macroeconomic level, it made sense to launch in Indonesia.


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-‐ Internal environment: The marketing and medical directors at Sanofi

Indonesia were very enthusiastic about the project, and the CSI team

considered it key to develop the solution with an affiliate that was excited

about it.

Babushka SMS launched in Jakarta in December 2013, and the project will be scaled up to

the rest of the Indonesia in the fall of 2014. The CSI team is also working on scaling up the

solution to different affiliates.

Below, we will classify the affiliate-related factors that have helped or hindered the

project development, just as we did for Diabeo.

Factors that positively affected the Babushka

SMS development:

Factors that have slowed down the Babushka

SMS development:

Inte

rnal

env

ironm

ent:

• Strong support from affiliate top management:

the affiliate GM, marketing director and medical

director were very enthusiastic about the project

and willing to push it forward to launch.

• The Indonesian affiliate has a relatively small

budget compared to most Sanofi affiliates: the

local team has scarce resources to devote to

solution promotion

• Existence of a capabilities gap: the Babushka

SMS was the team’s first experience in

developing and launching an eHealth solution,

so the local team didn’t have the appropriate

processes in place.

Exte

rnal

envi

ronm

ent:

• Large cardiac population with a need for

adherence solutions: Indonesia is the third most

populated country in Asia after China and India,

with a large portion of patients who have cardiac

issues. The local affiliate also reported patient

adherence issues. Thus, Babushka SMS

answered a local need.

• Local cellphone habits: The majority of cellphone

users in Indonesia have pay as you go plans;

this can dissuade the most cost-sensitive from

enrolling in Babushka SMS, even if the program

itself is free

Figure 44: Babushka SMS - internal and external affiliate factors that affected the solution launch

Looking at the graph above, we can see that factors which have most slowed down

the launch of Babushka SMS are those that are related to the internal environment.


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4. ANALYZ ING SANOF I ’ S AFF I L IATES W ITH GUÉR INEAU’S FRAMEWORK

a. France: A Historic Big with a challenging but valuable local ecosystem

According to Guérineau’s matrix, Sanofi France could mostly be described as a

Historic Big: it is a large, complex affiliate, it has important financial and human resources,

strong internal expertise, a thriving innovation ecosystem, and a strong market demand for

innovation. It is probably one of the few Sanofi affiliates that could carry a project as complex

and expensive as Diabeo. However, no affiliate fits perfectly into one “ideal type”, and France

is no exception: its external environment, while overall quite beneficial, can also be a

challenge because of slowly evolving legislation.

b. Indonesia: a Potential New Big

Sanofi Indonesia might be best described as a Potential New Big. After all, it has the

largest market in Asia, after China and India and is in a growing but economically and

politically volatile market. The local team has limited financial resources, and had no

innovation development expertise when the Babushka SMS project began, which was a

challenge for the project team. Furthermore, the affiliate team and local market have a strong

appetite for frugal innovations, which are in rupture from the traditional Sanofi business

model in developed countries.

c. The internal and external characteristics of affiliates that affect eHealth

solution deployment

i. Internal environment factors:

• Internal capabilities:

o Strong Business Development and Scouting capabilities are important –

especially for the first affiliate – in order to pick the best partners (especially local

ones) and the best and most adapted technology available;

o Strong product development capabilities – operational market access, clinical trial,

and marketing teams – that can be applied to eHealth solution development

(rather than medication) can also have a positive impact on eHealth solution

launches;

• Financial Resources: choosing an affiliate that can at least co-finance an innovation and

maintain it after global is no longer involved is helpful


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• Support from top management: it is important for the affiliate’s top management (General

Manager and Marketing and Medical Directors) to be onboard for the solution

development – if they are, the project team will be able to dedicate the necessary time

and resources to the eHealth project.

• Presence of a project champion: Picking an affiliate with one or two people that are ready

and willing to champion the solution within the local and regional offices is invaluable.

Since the Center of Excellence for Integrated Care is solely a global entity, the team

needs local ambassadors, or champions, to push projects to launch stage.

ii. External environment factors:

• Innovation Ecosystem: are there innovative local organizations (research funds, start-

ups, software developers…) with whom to partner, to develop the solution with, or to

promote eHealth solutions with?

• Legislation, regulation: Existing legislation (or the lack of it) can have a significant impact

on the time it takes to bring an eHealth solution to the market.

• Local demand and/or readiness for new technologies: by definition, most eHealth

solutions leverage new technologies, such as mobile phones, smartphones or devices. Is

the local market ready to use and adopt these devices? And is their use of these devices

compatible with the eHealth solution use?

• Local need for the eHealth solution: the eHealth solution should answer a real local

patient need.

5. CONCLUS ION OF THE KEY PO INT

No affiliate will fit perfectly into one of the ideal-types described by Guérineau.

However, his matrix is useful in the sense that it forces it’s user to assess affiliates both in

terms of external environment and internal capabilities, and helps anticipate some of the

potential strengths and weaknesses of affiliates. This can allow project teams to better deal

with the challenges they will inevitably be faced with. Comparing affiliates in the same

categories could also lead to the development of context-based best practices. Also, the

typology could potentially be used not just to pick the first affiliate with whom to launch the

eHealth solution, but also the following sequence of affiliates in which to scale-up.

Finally, using the matrix can also bring to light the dynamic nature of Sanofi’s

affiliates. Their internal and external contexts can evolve and so the ideal-type to which an

affiliate most corresponds to can change through time. This could for example inspire

affiliates (or corporate) to invest more in certain affiliates to see their internal capabilities


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grow. For instance, Sanofi Indonesia developed valuable capabilities during the development

of Babushka SMS, as it received training from the regional clinical excellence unit and from

the Center of Excellence for Integrated Care. This development could make Sanofi Indonesia

an Accelerator affiliate, at least for certain types of innovation.

vi i . KEY POINT 6: COMMUNICATE AND MAKE THE SOLUTION V IS IBLE

INTERNALLY

1. THE CONTEXT

As a large multinational corporation, Sanofi is a matrix of regional divisions and

therapeutic area divisions. The regional divisions benefit from a lot of autonomy in their

management. Likewise, the therapeutic area divisions act more or less independently from

one another. This structure gives regional teams the flexibility they need to react

appropriately to their markets, and at the same time allows brands to have a coherent

strategy internationally. However, this structure does complicate the flow of information

across divisions and geographic areas. While the Key Point 4 concentrates on how to get

internal support and onboard teams internally, this Key Point focuses on an issue much more

upstream in the scale up process: how do I make sure people know about my solution inside

the company? The goal is here not to convince people, but rather to create visibility around

the solution in a silo-organized company, in which it is difficult to bring light on one’s projects.

2. OBSERVAT IONS

As we worked on developing a database of eHealth solutions within Sanofi, we realized

that information about these projects wasn’t flowing effectively enough across the company.

First, many of these projects were unknown to the Center of Excellence for Integrated Care

team, even though some projects could be deemed quite successful in terms of patients

enrolled and could perhaps be scaled up to new geographies. This is because until recently

there was no central database of eHealth solutions within Sanofi; now we’ve created one, but

it is probably not exhaustive. Secondly, we noticed that very similar projects were launched

in different geographic areas, with different project leaders & vendors: we wondered whether

the project leaders had developed everything on their own, or if they had managed to get in

touch and work on key issues together.


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In our day-to-day work at Sanofi, we noticed the impact of internal communication on the

creation of scale up opportunities. For instance, following the launch of Babushka SMS, a

short article on the solution was published on Sanofi’s internal website; this article led to

several brand managers contacting the project leader for more information. Anecdotally, we

also saw that brand managers we worked with were interested in hearing about successful

solutions that had been launched by other Sanofi teams, but that they often did not have

easy access to this information.

3. ANALYS I S & POSS IBLE SOLUT IONS

In the article “Innovate and Scale: A tough balancing act”, Christian Seelos and Johanna

Mair(Seelos, 2013) list factors that can negatively affect an “organization’s capacity for

continuous innovation” (OCCI), which refers to an organizations ability to continually come up

with innovative ideas while simultaneously standardizing and scaling up successful

innovations. At the organizational level (by which Seelos and Mair principally mean an

organization’s leadership, strategy, and culture), the authors cite the following stumbling

block: “Do innovations remain invisible to headquarters, for example in decentralized

organizations?” We believe that as a decentralized organization, Sanofi does in fact face this

challenge.

In 2010, the Sanofi Business Excellence and Innovation team realized this was a

challenge for Sanofi. To respond to this challenge, the team designed the Mylinks awards.

The MyLinks Awards are an annual internal challenge designed to reward and showcase the

best user-centric innovations of the year. In fact, the Mylinks awards and the corresponding

MyLinks website – a website accessible to all Sanofi users on which all submitted project

descriptions are displayed – has most probably played a key role in encouraging services

and eHealth innovation within Sanofi. However, certain adjustments could be made to further

improve the visibility of eHealth projects:

- Improve the search function: currently, it is difficult for website users to easily sort

through all the posted projects to find those that can potentially interest them. Creating a

more user-friendly database of solutions on the website, rather than a list of projects,

might revive interest in the website

- publicize the website internally: if the website was promoted more internally, perhaps

more project leaders would upload their projects to the website or consult it to find best

practices


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- implement a mandatory eHealth solution reporting process? One avenue to explore

might be creating a standard questionnaire all eHealth project leaders must fill out. If

implemented, this would facilitate the upward flow of information in the organization.

c. KEY PO INTS TO ENSURE ADOPT ION BY OTHER STAKEHOLDERS IN THE ECOSYSTEM

i . KEY POINT 7: BUILD A RELEVANT VALUE PROPOSIT ION FOR ALL SOLUT ION

STAKEHOLDERS

1. WHY I S VALUE PROPOS IT ION SO IMPORTANT?

“Value Proposition” should be understood as all benefits a solution can bring to all

stakeholders concerned, directly or indirectly, by the solution. Because eHealth integrated

care solutions are relatively new in the healthcare sector, in which it takes time for

breakthrough innovations to be accepted by all stakeholders, project managers are often

confronted with situations where they need to explain the value proposition behind their

solutions. It is indeed complex to establish a clear value proposition, due to the following

reasons:

-‐ Because these breakthrough innovations are so radical compared to the company’s

original activity and that they are services and no longer products, traditional tools

and conceptual frameworks do not work to evaluate their concrete value

-‐ Value proposition can vary from one stakeholder to another. The challenge is

therefore to be able to define what the solution can bring to each and every one of all

stakeholders.

Many brand teams inside Sanofi or healthcare professionals in the ecosystem still

consider these types of innovations as simple communication tools for drugs. The true

impact of eHealth solutions on healthcare delivery, organization, costs, patient experience,

medical outcomes etc. still need to be demonstrated. “Demonstration” here does not refer to

any type of evidence gathered during an organized user test or clinical trial. By

demonstration, we rather mean the clear explanation of how the solution work and what

added value it brings to each stakeholder.


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The challenge is therefore not so much to prove the efficacy of the solution by

concrete evidence, which requires time and effort, but at least for project leaders to clearly

explain internally and externally how the solution answers unmet needs of patients or HCPs,

and which clear benefits it can bring. It might seem obvious to do so, but it is a step that

cannot be overlooked. During our experience as junior project leaders, we observed a real

discrepancy between what we believed our projects could bring to all stakeholders, and what

was understood from the presentation of our solution, internally and externally.

Moreover, when listing of all integrated care solutions for the Center of Excellence, we were

asked to classify the solutions by “value proposition”, having the choice between

-‐ Experience

-‐ Medical outcome

-‐ Cost reduction

This task turned out to be quite difficult, as the value proposition of a solution was, although

not clearly asked, rarely explained in the definition field. This shows that some project

leaders do not present their solution by the value they can bring, but rather by the technology

used or its functionalities.

2. ANALYZ ING THE NOT ION OF VALUE PROPOS IT ION THROUGH THE MODEL OF

INTERESSEMENT DESCR IBED BY AKR ICH CALLON AND LATOUR (2002)

When looking in the literature to find elements that could feed our research on this Key

Point, we found the model of interessement exposed by Akrich Callon and Latour in their

article The Key to Success in Innovation Part 1: the Art of Interessement (Akrich, 2002) very

close to our conception of value proposition in the case of eHealth solutions. Traditional

literature on the diffusion of innovation mostly links the rate of diffusion to the intrinsic

features of the solutions. For Akrich, Callon and Latour, this conception is very limited. In

their opinion, an innovation cannot be understood outside of the economic and social

environment it evolves in, and has to be defined through all interaction it implies. All actors

that may directly or indirectly be concerned by the diffusion of the innovation have to be

taken into consideration.

To the traditional model of diffusion, the authors oppose their model of interessement.

Whereas the diffusion model clearly separate the innovation and the environment, and

pictures the diffusion process as the launch of a technical object in a population more or less

receptive, the model of interessement stages all actors of the ecosystem. A successful

diffusion of an innovation results from the aggregation of interests of all actors. For each

actor should be listed the points of contact with the innovation, as well as the interest they


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may have in adopting the solution. “The innovation is the art of interesting an increasing

number of allies that makes us stronger and stronger”. This is in our sense very close to the

conception of value proposition defined in the first paragraph of this Key Point, as many

stakeholders have to be “interested” by the innovation in the case of eHealth.

Moreover, Akrich defines the mechanism that enables the “interessement” of each player

as an act of translation: the challenge is to translate a commercial object and strategy into a

research question that is relevant for each player of the ecosystem. An easy parallel can be

done between the act of translation, and the act of defining the value proposition. Both of

them are difficult to elaborate in a multi-stakeholder ecosystem, and need to be tailored to

each actor’s interests for him to have the highest probability of adopting the solution.

3. CASE STUDY: MORE

For some projects however, the value proposition definition is at the heart of the activity.

The case of MORE stands out perfectly in this perspective. As explained in the monography

(cf 5.C.iii), the project MORE is a solution based on an innovative technology: a device

(electrodes that can be attached to a smartphone to record ECGs with the mobile) and the

related app. Sanofi’s objective is to use this technology to create more value for patients

and/or caregiver and/or payers. Two models with different value propositions are at the

moment under assessment (via a pilot) in Ireland to define which one best fits market needs

and expectations.

The two models and their value proposition are the following:

1) In the first model, the solution can be used by HCPs, during consultation, to screen

patients complaining about abnormal pulse (as HCPs do not always have a fix ECG

recording machine at their disposal during consultation).

If the HCP is a General practitioner and that the abnormal pulse in confirmed, he can refer

the patient as usual to the cardiologist for the rest of the diagnosis, and usual care is not

disrupted by the use of the solution.


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Figure 45: MORE flow diagram – Model 1

Value proposition for each stakeholder

GP: Enable systematic screening

Strengthen the relationship with the cardiologist as he can refer patient with

tangible evidence

Cardiologist: Device more convenient than fixed machine. Improved experience as a

practitioner

Device can easily be used on the go to screen patients. The solution enables

him to widen its spectrum of action

Less useless consultation: Patients referred from GPs are more likely to be

at risk

Patient: Improved patient experience as their ECG can be recorded with the first

practitioner they visit (feeling to be better taken in charge)

More patients suffering from or at risk of AF screened and diagnosed

Payers: More patients diagnosed which leads to a diminution of risk of AF event. For

payers, this means an important cost reduction thanks to reduction of

hospitalization

2) In the second model, devices are given or prescribed by HCPs to specific patients so that

the latter can record their ECG during a given time period and regularly send their recordings

to their cardiologist. This remote monitoring solution can therefore enable the HCP to:

-‐ Fine-tune his diagnosis

-‐ Have a close follow-up on patients already diagnosed.


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Figure 46: MORE flow diagram - Model 2

Value proposition for each stakeholder:

GP: Improve screening of patients (no longer a “one-shot” recording during

consultation)

Enhance relationship with patients

Cardiologist: Fine-tuned diagnosis

Better follow-up of existing patients – Better reactivity if something goes wrong

Less consultation for one specific patient, which means more room for more

patients

Enhanced relationship with patients

Patients: More likely to have a better diagnosis on his therapeutic condition

Increase patient-awareness – feels more health-conscious

Feels more confident as he is followed from the distance

Enhance relationship with the caregiver

Payers: More screening & better follow-up which likely leads to a decrease in AF

events. For payers, this means an important cost reduction thanks to reduction

of hospitalizations.

Defining the value proposition of a solution is, as shown above, not always simple and not

necessarily clear to explain. We therefore asked ourselves it was possible to better present

it, and elaborate tools that could contribute to mapping the value proposition of a given

eHealth solution.


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4. MAPP ING OF THE VALUE PROPOS IT ION: FOOD FOR THOUGHTS IN EX I ST ING

L I TERATURE

The “Triple Aim”

The Institute for Healthcare Improvement (IHI) has developed an approach to optimizing

healthcare performance (Institute for Healthcare Improvement, 2009). Each initiative aiming

at optimizing healthcare (among which eHealth solution) should pursue three dimensions:

CARE, HEALTH and COST. This concept is called “The triple Aim”. In other words, an

innovative solution should bring value by

-‐ Improving patient experience and the way care is delivered

-‐ Improving medical outcomes

-‐ Decreasing costs related to healthcare

“In most health care settings today, no one is accountable for all three dimensions of the IHI

Triple Aim. For the health of our communities, for the health of our school systems, and for

the health of all our patients, we need to address all three of the Triple Aim dimensions at the

same time.”

This can help us think the concept of value proposition for our solution at Sanofi: does our

solution address the three dimensions? What dimension do we focus on? How?

HAS Matrix : expected impacts of telemedicine

The HAS is an independent public authority that contributes to regulate French

healthcare system and improve its quality and effectiveness. Innovative solutions such as

Figure 47: The IHI triple aim


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eHealth projects therefore fall directly in its scope, since they participate in empowering

patients and improving the way care is delivered.

Since 2010 (year where the law HPST on telemedicine was adopted), the HAS

published reports and tools to help the development of eHealth project on French territory as

well as to regulate their applications. From literature review on telemedicine, to practical

steering guides, several documents and tools have been put at the disposal of industrials as

well as healthcare institutions or professionals, who would like to carry on eHealth projects.

Among these tools, the HAS developed a matrix(Haute Autorité de Santé, 2013) , which goal

is to map the impact of expected effects of a given telemedicine project. Even though,

according to our definition, telemedicine is only a subpart of eHealth as a whole, we believe

this matrix could help project managers assess the benefits of their solution and build a

relevant value proposition.

Based on the observation that unlike other health services, an economic evaluation of the

impact of telemedicine (and more generally eHealth) solutions was very difficult to make,

alternative evaluation must be realized in order to be able to precisely assess the value

brought by these type of solutions to all stakeholders. That is why the HAS created this

matrix with a double objective:

- Improve evaluation quality, and particularly homogenize evaluation methods for

telemedicine projects

- Take into account the specificities of telemedicine project for which traditional

methods for medico-eco evaluation are not appropriate Figure 48: The HAS matrix

Accessibility Professional

practices and care coordination

Quality of care Costs

Patients, family

and caregivers

Healthcare Professionals

Health institutions

Social security,

insurance, state


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The matrix is an interesting tool to evaluate, for 4 main groups of stakeholders, the

impacts (negative or positive) of the solution on 4 different dimensions: Accessibility,

Professional practices and care coordination, Quality of care and Costs.

Filling up this table can be a fertile exercise for project managers in the sense that it

contribute to clarify value proposition and thus help them communicate about the benefits of

their solution for each actor of the ecosystem.

i i . KEY POINT 8: ELABORATE A TA ILORED PROMOTION PLAN

1. OBSERVAT IONS AND STATEMENTS

Promotion of a service such as eHealth solutions: a new challenge for Sanofi

Promotion and communication are key elements to ensure diffusion. The definition of the

diffusion given by Rogers (Rogers, 1983) highlights that aspect:

“Diffusion is a process by which an innovation in communicated by a variety of channels

over time within members of a social system.”

A right promotion is therefore at the very heart of a successful diffusion, yet its

importance is often overlooked. However, the term of promotion is very broad and embraces

many variables. An overview of the literature about communication helped us defining the

various components of communication. Mac Donald (Macdonald, 2002) sets out the key

input and output variables of communication that can be considered as the basis of any

promotion action and are listed below.

Key Variables in communication ((Macdonald, 2002))

Input Variables

Source of the message (credibility, likeability, power, quantity and demography) The message itself (appeal, style, organization, quantity) Communication channel (mass media, one-to-one, spoken/written …) Receiver (characteristics, personality traits, attributes …) Destination (intended behavioral targets, intended outcomes…)

Output Variables

Exposure to the message Perception of the information Encoding Acceptability of the message Behavior Change (in line with the intention of the sender) Post-behavioral consolidation


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For a pharmaceutical company, these variables are clearly defined for its core business:

sales of drugs. If we apply McDonald’s variable to this case, we will obtain:

-‐ The source of the message: Sanofi, a recognized player in the pharmaceutical

industry

-‐ The message itself: evidence-based promotion, focus on clinical outcomes, product

oriented promotion

-‐ Communication channel: mostly one-to-one through sales representatives, or by peer

reviews

-‐ Receiver: healthcare professionals that are specialized in a given therapeutic area

-‐ Destination: More prescriptions of the drug, and indirectly sales increase for the

company

This model is well mastered by pharmaceutical companies as they have been doing so for

decades, and there sales force is trained this way.

Yet, when it comes to eHealth solutions, new challenges are rising up. Promoting this

type of solution is a brand new activity for Sanofi, and we can try to explain it by re-using Mac

Donalds variables to show how it differs from traditional drug selling.

-‐ The source of the message: Sanofi has a good credibility for medical field but is not

recognized as a core player for digital innovation

-‐ The message itself: Rarely evidence-based promotion, focus on overall benefits of the

solutions, service-oriented promotion

-‐ Multi-channel Plan Communication channel: one-to-one promotion through sales

representatives, Use of a third party (patient association), conferences,

-‐ Receiver: healthcare professionals, patients, hospitals, nurses, dieticians

-‐ Destination: Incorporation of the service into their usual practice, change of behavior

to use digital new technologies in treatments

Because promotion of eHealth solutions is so different from drug promotion, we

considered that promotion was itself a point of vigilance important enough to discuss it

separately.

In order to understand how promotion was done for existing eHealth projects, we will analyze

the case of Phosphorus Mission, the educational game for patients suffering from chronic


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kidney failure. This is indeed the only solution (out of the 4 cases that we selected) that out

rolled significant promotional efforts.

2. CASE STUDY: THE PROMOT ION OF PHOSPHORUS MISS ION

As a reminder, Phosphorus mission is an educational gaming solution for smartphones

and tablets that has been developed to educate and coach patients suffering from kidney

failure. This is the first solution of this type to be developed by Sanofi and thus the first time

the operational teams had to promote a serious casual game. Here are the key takeaways of

the promotion of Phosphorus Mission.

Sales Force training is necessary: sales representatives had first to follow specific training

sessions to learn how to promote the game. Sales representative traditionally visit

healthcare professionals (in this case mostly nephrologists) to sell phosphate binders (typical

drug used in treatments for patients suffering from kidney failure). They are therefore used to

promote a specific product that have been clinically tested and for which they can bring

concrete evidence of effectiveness. However, the arguments are different in the case of a

service like Phosphorus Mission. Key benefits of the solutions are:

-‐ Awareness: Patients know more about their disease

-‐ Behavioral changes: Patient change their eating habits in order to reduce their

phosphorus intake and optimize the treatment follow-up

Sale force has then been trained on conveying these messages to promote the solution.

Promotion is done by affiliates: The CSI team (at the global level) developed the solution,

but the promotion is under regional & affiliates’ responsibilities. Global teams proposed the

launch strategy and the multichannel plan. They provided templates of documents to help in

the promotion process and gave some guidelines to local marketing teams but are no longer

in charge of operationalizing the promotion on the field. This therefore means that promotion

of the same solution can vary from one country to another, depending on each country’s

particularities. There is indeed no global recommendation on how to promote eHealth

solutions that could be used by local marketing teams as general guidelines to follow. Yet,

global teams usually put in place best practices sharing and provide the promotional material

(questionnaire, KPI and survey’s methodology) to affiliates


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Promotion often relies on a 3rd party: One-by-one promotion through medical visit is a

tedious process, and very time-consuming. One way of increasing the speed of the process

is to onboard a 3rd party that can play the role of the promotional actor. This has been done

in Saudi Arabia for Phosphorus Mission: it is in this country legally compulsory to partner with

a patient association to be allowed to launch the solution. Sanofi managed to partner with the

Saoudi dialysis association. This partnership turned out to be a great asset to receive Health

Authorities validation and in a second step should help to leverage promotion on a higher

scale. Promotion of educational tools is not only done by med reps, but can also be indirectly

done by the association, which already benefits from a solid credibility among the medical

community. Direct promotion to patient can be done, depending on countries regulation

This can have a tremendous impact on the rate of diffusion of eHealth solutions. Due to other

priorities, this kind of partnership has not been conducted in France for example, despite the

recommendations of the global team, and we assume this could have been nice to have in

order to ease the process of diffusion of this solution that a lot of professionals and patients

are still reluctant to use.

A large scale partnership is currently pursued by the global CSI team with a leading Dialysis

professional organization: EDTNA. As part of educational mission, EDTNA is interested in

eHealth solutions and educational tools in particular. EDTNA and Sanofi have accepted an

independent audit of the game which resulted in very positive results …opening discussion

for accreditation discussion. If this process ends up with an accreditation, this will accelerate

uptake of the game through EDTNA network and communication channels. As a

consequence Sanofi CSI team would then have an additional argument to convince affiliates

to partner with local associations (Patients, academic or professional).

Before doing the promotion of a specific solution, make sure the target audience is

educated to be receptive to the conveyed message. What was striking in this project was

to see that many people, internally and externally, could not be receptive to the promotion of

an educational game for renal pathologies, because they were not aware of how mobile

technologies could significantly help in improving healthcare and patient pathways or

experiences. So before talking in depth about the benefits of a given solution, general

education about technologies and their usage in healthcare should be made upstream, to

ensure that the targeted people have all the tools they need to understand the full value of

the solution we are offering.


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3. E LABORAT ION OF A THEORET ICAL PROMOT ION MODEL

Based on these observations, we believe it could be interesting to map the promotion

process depending on market segmentation order to differentiate the targets and the

messages to convey. The aim is not to provide a step-by-step guidance of how promotion

should be done, but more to explain how the issue of promotion could be looked at in the

case of breakthrough innovations in healthcare.

Berwick, through his works on innovation dissemination in healthcare, helped us in this way.

Use of Berwick’s recommendations for promotion

In his paper, Berwick (Berwick, 2003) insists on the slow pace of dissemination for

innovations in the healthcare sector. “In healthcare, invention is hard, but dissemination is

even harder […] mastering the generation of good changes is not the same as mastering the

use of good change”. Therefore, succeeding in implementing breakthrough in the healthcare

sector is a tedious process that requires effort and time. Among Berwick’s 7 rules for

disseminating innovation healthcare, some can be looked at through the prism of promotion.

Find and support innovators: even though innovators might not be the toughest market

segment to convince to adopt the innovation, failing to reach to them in the first place might

be a crucial mistake. Promotion should therefore pay a specific attention to these precursors

eager for change in order to secure this target market. For that market, promotional message

will focus on the “innovatiness” of the solution: new features, technological features, design

… They will for the most part make their mind on the efficacy of the solution on their own,

and do not need solid clinical evidence for buying the solution. However, as Berwick

explains, innovators may be tough individualities to deal with, are sometimes considered as

mavericks and are not so invested in local network. Therefore, additional promotional effort

has to be done among other groups, and more specifically among early adopters.

Invest in Early adopters: early adopters, unlike innovators, are deeply rooted in local

networks. They are no innovation-freaks, but are rather curious and keen on trying new

changes. However, as Berwick explains, “early adopters need the slack time and resources

to try out new things and to reduce their uncertainty through small-scale trials.” In fact, they

will be likely to adopt the solution, but only after a trial and evaluation period. This, in our

sense, should also be part of promotional processes. Getting early innovators to openly try


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out the solution is key to success, and promotion teams should dedicate a significant amount

of time to make potential users try and discover the solution: display actual prototypes at

conferences, organized trials with motivated healthcare professionals, go through hospitals

and clinics to promote the solution and leave it there for people to try… This non-exhaustive

list of options only serves as an example for methods to effectively promote the solution

among early adopters.

Moreover, Berwick believes that increasing the ease and frequency of interaction between

innovators and early adopters can have a significant impact on the dissemination pace of the

solution. Organizing meetings and conference to make the two groups meet and collaborate

can therefore also be another element of an effective promotion.

Make the Early Adopter Activity observable: For the innovation to diffuse to the “Early

majority” segment, the crucial interface between early adopters and early majority must be a

top priority in promotional efforts. Berwick statement is the following: “The early majority

watches the early adopters, but they cannot watch them if they cannot see them”. The real

challenge is therefore to raise awareness among the early majority about what other

healthcare professional have been curious enough to try and have eventually adopted. In

Berwick’s conception, the most efficient channel to do so is to improve social channels

between the two groups, because memoranda or publications will have a small impact in this

situation. To spread the innovation, social interactions have to be established (here once

again through meetings, conferences and so on). However, the feasibility of that kind of

measure in a promotion plan can be argued as it is costly, requires moderators to animate

reunions… An alternative option raised in our case study of Phosphorus Mission is to partner

with Key Opinion Leaders associations (either patient or professional association in a given

therapeutic field). KoL, experts recognized by peers, mostly belong to the “Early Adopters”.

Partnering with KoL or patient associations can therefore be understood as a promotional

action. By doing so, teams gain a solid argument for further promotion among the early-

majority as they can say “Early Adopters have tried it, evaluated it and adopted it”. Therefore,

instead of putting much effort in creating social interaction between the two groups, building

a partnership with a relevant association help crossing the gap existing between them. And

this is all the more true for pharmaceutical companies, which can easily rely on their one-to-

one detailing sales processes already existing. When visiting HCPs from the “early majority”

segment, they can advertise the partnership they established with KoL associations. The

idea is here for pharmaceutical companies not to improve the interfaces between the groups

and improve social interactions, but rather to act itself as the interface.


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Figure 49: Graphic representation of theoretical promotion model inspired by Berwick's rules for dissemination

i i i . KEY POINT 9: RAT IONAL IZE THE CHOICE OF SUPPL IERS AND PARTNERS

WHEN SCAL ING-‐UP

1. REMINDER: THE IMPORTANCE OF PARTNERSH IP FOR EHEALTH SOLUT IONS

As a reminder of what has been explained in 1.b, most eHealth solutions have been

developed based on a partnership with multiple parties, or at least through a supplier-

customer contract. The key point to understand is that very few players in the industry are

capable of developing and launching an eHealth solution on their own. There are indeed

many composites of an eHealth solution, from the service provided to the biosensors. Here is

an overview of the possible composites of a solution:

-‐ Medical Device : data capture, biometric sensors

-‐ Data management (hosting and transport)

-‐ Human to Machine interface: apps, PC software, Web service

-‐ Algorithms: Smart medical systems

-‐ Human-to-human services: call centers, HCPs interaction, coaching

Usually, players in the eHealth industry are specialized in one of these components, and

several players will partner to build and develop a comprehensive solution. Sanofi often acts

as an integrator on the market.

The more complicated the solution, the more partners are usually involved in the

development process.


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We therefore chose to analyze the most complicated solution among our 4 cases that is

DIABEO, to deal with a complex partnership pattern and draw learnings from it.

2. CASE STUDY: D IABEO – ANALYS I S OF A PARTNERSH IP FOR TELEMED IC INE

SOLUT ION

Overall description of the partnership

The Diabeo project, a software that helps diabetic patients calculate their insulin doses,

was from the start a co-innovation project between three parties: A research institute in

diabetology, a French software editor with a good track record in medical software, and

Sanofi, that has a strong footprint in the Diabetes area. This partnership was officialized with

a tripartite contract in 2011. The task repartition can be described as follow:

Research institute in diabetology: the implication of the research institute was for the most

part the work of one man, Dr Charpentier, who contacted the software editor. As a key

opinion leader, he played an important role in getting the medical community engaged in the

project, and gave a solid credibility to the solution in the ecosystem, as it could be said that

recognized diabetologist was at the genesis of the project. Dr Charpentier, along with other

healthcare professionals from the institute, participated in the elaboration of the algorithm, by

bringing the necessary medical knowledge to the solution.

The software editor: This company is a pioneer for therapeutic companion software. They

developed a full web application, which enables healthcare professionals to follow up on their

patients in many therapeutic areas. After being contacted by Dr Charpentier, they started

working on a solution focused on Diabetes. With the help of the research institute, they

developed the medical algorithm that they incorporated in 2011 in a mobile app. The

software aims at supporting patients across the insulin pathways and is CE marked since

December 2013.

SANOFI: the implication of the group was at the beginning limited to the Diabetes division of

the French Affiliate. Sanofi brought heavy financial support to the project, its recognized

brand image in the field of Diabetes, project management skills and a considerable strike

force (should the project be launched at a higher scale). Sanofi took over the responsibility of

project management (business plans, promotion and distribution), and allocated a team to

the project.


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Even though these three players are the key actors for Diabeo, other companies are

involved in the project. These service providers however operate under a supplier contract,

and cannot be per se considered as partners. They are listed below:

Data hosting player: This player has been the preferred supplier of the software editor

quoted above for data hosting and management. The editor was indeed already working with

this player for Medpassport, and continued to do so for Diabeo. This firm was indeed at that

time (and actually still is) one of the only companies allowed to host and transport health data

in France. It was therefore in charge of building a data hosting platform for the solution, and

to take care of the data transmission between patients and HCPs.

Call center: The final version of the solution (the one being currently tested in clinical trial)

includes a call center with nurses trained in telediabetology. The nurses have all signed a

delegation procedure with each diabetologist enrolled in the clinical trial, as they will support

and advise diabetic patients from the distance.

Figure 50: Diabeo's partnership framework

If we look at this partnership from a scale-up perspective, what are the key takeaways from

this case study?

The question of the scale-up for Diabeo has not been at the top of the agenda so far,

since the team in charge of the project (in the French affiliate) is for the moment focused on

the roll out of the clinical study to gather evidence. Yet, some other affiliates have shown

interest for the solution, and are already considering launching it in their geographies. In


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order to anticipate the difficulties that might be encountered for the scale-up of the solution in

other countries, we discussed that issue with project leaders to understand what could be the

main challenges concerning the partnerships and suppliers in the case of a scale-up.

The main challenge: adaptation to local specificities.

Firstly, Diabeo includes a data-hosting platform. Regulations are strict when it comes to

health data management, and in certain geographies, official certifications are compulsory to

host and transport health data. In France, approximately 50 companies or healthcare

institutions have that certification for the moment. Yet, these 50 companies do not

necessarily comply with rules in other countries and ministers in other countries have

sometime developed their own certification process. This means that compliance to local rule

in terms of health data management could be a real challenge for scaling-up eHealth

solutions.

Moreover, the circle of influence of given Key Opinion Leaders is often very limited to a

certain geographical area. The Research Institute is indeed famous in France and

recognized for its expertise. However, should the solution be deployed abroad, another

partnership with a local medical association or research institute would be necessary to gain

in visibility and ensure diffusion among local healthcare professionals.

A solution like Diabeo is highly tailored to a given healthcare system, patient pathway

and a specific pattern of care coordination. All of these can widely vary from one country to

another. It is therefore paramount to deal with professionals that are familiar with the local

healthcare system and would be able to adapt and adjust the solution and service provided,

depending on the particularities of the country. In the case of Diabeo for example, the nurses

present on the call center that the patients can call anytime need to be familiar and confident

with local healthcare system, diabetic patient pathways and types of treatment. A local

service provider to handle the call center would therefore be more likely to recruit local

nurses.

In order to manage local adaptations, a governance of the solution needs to be setup.

Before different level need to be identified in the solution to be addressed by the right level of

governance:

-‐ Core Model: Core Solution managed by global team with a strong process to

incorporate local requirements that could benefit to all countries


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-‐ Customizing: adaptions possible identified by the global team and specify by the local

team (e.g.: languages, forms…)

-‐ Local developments: local adaptation managed by each country (e.g. specific

reports…).

Most of the medical requirements must be in the Core model. Possible requirements to adapt

the algorithm would be considered as a local customizing of the solution.

3. KEY LEARN INGS FOR THE CHO ICE OF PARTNERS TO ENHANCE SCALE -‐UP

The choice of partners is important for the two dimensions of the scale-up defined previously

(cf. 2.b), which are diffusion and deployment.

• The choice of partners can have an impact on the diffusion rate of the solution

(Diffusion Axis)

• Local contracting and partnership is often necessary to successfully deploy a solution

(Deployment Axis)

a. The choice of partners can have an impact on the diffusion rate of the solution

(Diffusion Axis)

Even though Sanofi is well known in the healthcare industry, it is paramount for them to

contract with the right partners to gain credibility in various fields:

Medical credibility. To ensure that the solution has a real medical added value, it is key to

partner with medical associations, healthcare institutes or research associations. The idea is

to onboard Key Opinion Leaders that can tremendously influence the pace of diffusion of the

solution.

Usage credibility. The goal is to show that end-users have tried, validated and adopted the

solution. Partnering with patient associations is a way to show that the solution is user-

friendly and matches with patient’s needs.

Technical credibility. For complex technical eHealth solutions, it can be an advantage to

partner with a player that is already recognized as a leader in a technical field. This

contributes to gaining patients and HCPs’ trust in the solution, and speed the diffusion. For

example, patients would be less reluctant to use a telemonitoring solution, for which a

famous telecommunication provider makes the telecommunication part, since the in this case

the provider obviously has the know-how and professionalism required to handle this task.


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b. Local contracting and partnership is often necessary to successfully deploy a

solution (Deployment Axis)

Such an assertion may seem counter intuitive when thinking about scale-up. One may

instinctively think: “the more global the partners, the easier the scale-up”. The case of Diabeo

prove us wrong to think this way, and highlights the necessity of paying close attention to the

partners we chose to scale-up an innovative solution, especially in healthcare.

Yet, do all eHealth solutions require to build local partnership to be successfully

scaled-up? For Phosphorus Mission for example, the serious casual game for renal patients,

it is not necessary to build new partnership in each country. The game simply has to be

adapted to local patients’ lifestyle. Plus, can some partners stay global while other have to be

locally picked in each new country in which the solution in launched? And if so, what defines

which partners need to be local and which can stay global?

4. RESULTS – GU IDEL INES FOR CHOOS ING PARTNERS

a. Understand the differences between solutions depending on two axes to

highlight the need for local partners:

We previously asked the question: “do all eHealth solutions require to build local

partnership to be successfully scaled-up?” The obvious answer to that answer is no, but it is

complicated to clearly explain why. Therefore, we decided that it could be interesting to

elaborate a clear framework to distinguish solutions based on 2 criteria in order to better

understand the rationale behind the partnership that needs to be built. This is no decision

tool, as it does not help concretely in the decision process, but it explains and theorizes a

general intuition.

We considered two criteria:

-‐ The level of medical complexity of the solution

-‐ Market access difficulty (device certification, data management certification etc.)


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Figure 51: Partner selection depends on the deployment strategy

The stronger the medical service provided, the more it has to be given by local actors

that are familiar with local healthcare systems and local practices. Similarly, the more strict

the regulatory environment, the more it is interesting to partner or contract with local players

that have obtained these certifications and comply with local rules. By local players, we mean

player that are familiar with the local industry and local process. It can therefore be a MNC,

as long as it has an affiliate with a rooted footprint in the given geographical area, whose

business is in line with local rules.

A very similar point is highlighted by Charue-Duboc and Jouini in their paper « Le

déploiement d’innovations inter-filiales au sein d’une multinationale » (Charue-Duboc, Le

déploiement d’innovations inter-filiales au sein d’une multinationale, 2014). As explained in

the literature review, one of their key success factors for the deployment of innovation is

contracting successively with local suppliers to deploy the innovation. Charue-Duboc and

Jouini confronted several cases of deployment of innovations inside a multinational gas

company. In all cases, they have been changes of suppliers during the scale-up depending

on the geographies the innovation was commercialized in, and the company partnered with

local players. Key takeaways from their research are the following:

• The success of the first commercialization of a solution in a given geography highly

depends on the level of implication of a partner/supplier which already has good

relationship with the affiliate launching the innovation, and which is already well-

known among targeted customers. In the case of Diabeo, the Research Institute is


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used to working with a French Affiliate, and is highly recognized for its expertise in

France.

• Partners/suppliers do not always share the multinational’s scale-up strategy.

Therefore, multiplying the partnerships and contracts with local players enables the

MNC to follow its initial scale-up strategy without having to deal with other players’

interests. In the case of Diabeo, the player in charge of data hosting has a strong

focus on European countries, and it is unclear if they would have a real interest

investing time and resources to continue hosting data, should Diabeo be deployed in

other geographies.

• However, it should not be overlook that such a partnering strategy requires specific

contacting processes and confidentiality agreements. This point applies perfectly to

Diabeo, for which local contracting to put in place the medical call center was a

tedious task, and is likely to be as difficult in other geographies as well.

In a nutshell, all three points can apply to the case of Diabeo, where local adaptation is

crucial for success and requires tailored and new contracts for each new deployment.

c. What defines which partners need to be local and which can stay global?

The second important question concerns the need for local contracting depending on the role

of the partner in the solution. As explained before, eHealth solutions often results from a

complex contracting process with many players, which all have different core businesses.

Which ones need to be picked locally? Which one can be global player and stay along Sanofi

for the whole scale-up process?

Sanofi IS team partly answered this question, and started by segmenting the architecture of

a solution in 3 parts: SENSORS – CLOUD – TRANSACTION

While sensors and and cloud are tasks that can be developed and managed globally, the

transaction businesses and to some extent a part of the cloud business (such as data

hosting) have to be tailored to local specificities (such as regulations or the healthcare

system). This therefore leads to a partnership patters that can include both local and global

players, depending on the part of the solution they are responsible for.


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Figure 52: eHealth solution architecture segmentation

We chose not to dive in too much detail into this segmentation, but we believe it can be a

good basis for further investigation on partnerships analysis for scale-up.

8. RECOMMENDATIONS FOR USE OF THE NINE KEY POINTS

a. HOW PROJECT MANAGERS COULD USE THE N INE KEY POINTS

We believe that the nine points that we developed above can be of use to project

managers in several ways.

During the ideation stage, as the project manager sorts through a large amount of

interesting ideas, we think it could be beneficial to have the key points in mind, in order to

focus on the ideas which would have most potential for being scaled up.

Secondly, at the prototype stage we think that the team should keep our criteria in

mind and try to satisfy a majority of the as the proto-solution is being built. That is, we think

that at the prototype stage the team should be assessing potential internal and external

interest in the solution, and if possible adjusting the solution to gain support. They should be


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thinking of how to choose the best internal and external partners to work with for a future

scale-up, and our points could be a starting point to guide the thought process.

At the testing stage, the project team could use criteria inspired from some of our

key points. For instance, they could as users to assess the innovation in terms of

Interoperability, Complexity, Compatibility, Trialability, Observability and Credibility, by

following the ideas developed in Key Point 1 (characteristics of innovations).

Finally, our nine points could be used to create selection criteria, when trying to

determine which solutions out of those already launch have most potential for being scaled

up. Existing external partners, solution characteristics and internal support are all items that

in our opinion should be assessed when choosing a solution for scale up.

b. APPL ICAT ION: SELECT ION OF ONE PROJECT AND EVALUAT ION OF SCALE-‐UP POTENT IAL

THROUGH OUR 9 KEY POINTS

After achieving this work, we decided to apply our results on a concrete case, once

again based on Sanofi’s solutions. Starting from the 120 solutions we listed during our

project, we wanted to extract relevant projects that would be the most appropriate for a rapid

scale-up. The first selection was made on very simple criteria: we only selected solutions that

were already launched, and that were not too simple from a technological perspective (so we

excluded all websites) and not too complex either (medical devices which require

certification. We ended up with 15 solutions.

The major difficulty we encountered for further selection was the lack of data

available provided in the database. We therefore used this issue as criteria, to only select

solutions for which we had an understandable and comprehensive description. We were at

that point left with 7 solutions.

As the 7 solutions seemed to have a certain potential for scale-up, we chose one for

which we could have a significant amount of data, to further analyze it in the light of our 9 key

points for success. For confidentiality reasons, we will not disclose the solution’s name.

Solution description

The solution is targeting patients suffering from Chronic Kidney Disease on dialysis.

Patients have to pay very close attention to their food intake and often follow a very specific

diet. The app gives the patient a quick view of his daily intake for six key nutritional values


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that are important for patients with CKD on dialysis: phosphorus, calcium, potassium,

sodium, protein, and fluids. He also has the option to track your daily intake of carbohydrates

and calories

Methodology and learnings

We put ourselves on purpose in the position of an external manager who is not familiar

with the project, as it could happen in real life when evaluating projects for potential scale up.

When applying our 9 points to the project, we drew out many positive points and points to

improve, should we decide to further scale up the solution. This can therefore be used as a

basis for future management of that project.

Figure 53: Application of the 9 key points to an example solution

9. CONCLUSION

Breakthrough innovations raise new and complex management challenges. The notion of

scale up, however, is often discounted in literature, and we hope our research brings

elements of comprehension in that sense.

For the whole duration of our project, we held a delicate yet stimulating position. We were

indeed constantly sitting between two chairs. On one side, we were searching through

academic papers to enlighten us on multifaceted concepts, and on the other, we had to

perform pragmatic operational tasks to achieve ambitious projects. Juggling between the two


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was no easy business. Theoretical abstract models rarely matched what we were

experiencing on the field, and our everyday concerns were a far cry from the ones developed

in literature. With distance and hindsight, we understand today that it was in fact from this

very discrepancy that our project found its meaning and relevance. We managed to find the

right balance and from this tricky positioning emerged constructive work. Throughout our

research, however, we remained firmly committed to the goal of delivering results that could

be valuable for both sides, and that could help people sitting on both chairs dealing with the

scale up of breakthrough innovations.


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10. TABLE OF I LLUSTRAT IONS

Figure 1: Images of the iBGStar glucose meter .......................................................................................................................... 9

Figure 2: the Patient Pathway .........................................................................................................................................................10

Figure 3: eHealth market players segmentation.....................................................................................................................12

Figure 4: Scale-‐up concept graph...................................................................................................................................................15

Figure 5: Sanofi Organization Matrix 2013 (simplified)......................................................................................................17

Figure 6: Sanofi Organization Matrix 2014 (simplified)......................................................................................................18

Figure 7: Bass diffusion model........................................................................................................................................................22

Figure 8: Bass diffusion model according to Dunn.................................................................................................................22

Figure 9: Moore's diffusion chasm ................................................................................................................................................24

Figure 10: Denis et al's conceptual model of the diffusion process................................................................................28

Figure 11: The WHO/ Expandnet's framework for scaling up..........................................................................................30

Figure 12: Bartlett and Ghoshal's classification of subsidiary roles in multinational corporations ................32

Figure 13: Guérineau's classification of subsidiary roles in relation to innovation deployment ......................33

Figure 14: illustration of Seelos & Mair's OCCI Model ..........................................................................................................35

Figure 15: Koenig's typology of business ecosystems..........................................................................................................39

Figure 16 : Selected projects for monogrpahies in relation to corresponding technical infrastructure ........44

Figure 17: measuring level of patient engagement and eHealth solution purpose ................................................45

Figure 18: eHealth solutions selected for the monographies in relation to development stage........................45

Figure 19: eHealth solutions selected for monogrpahies in relation to therapeutic area ....................................46

Figure 20: monography interview table .....................................................................................................................................47

Figure 21: Babushka SMS flow diagram .....................................................................................................................................49

Figure 22: Phosphorus Mission screenshot ..............................................................................................................................54

Figure 23: Phosphorus Mission screenshots ............................................................................................................................55

Figure 24: The services innovation framework developed and applied by the CSI team.....................................56

Figure 25: Phosphorus Mission project timeline ....................................................................................................................60

Figure 26: MORE flow diagram.......................................................................................................................................................62

Figure 27: Diabeo patient interface ..............................................................................................................................................67

Figure 28: Outputs by Key Point ....................................................................................................................................................72

Figure 29: eHealth solution scale up potential assessment ...............................................................................................75

Figure 30: Draft table for assessing an eHealth solution's scale up potential............................................................76


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Figure 31: Final table for assessing an eHealth solution's scale up potential ............................................................78

Figure 32: Table 1 in Denis et al's "Explaining diffusion patterns for complex healthcare innovations" (2002) ..............................................................................................................................................................................................80

Figure 33: an illustration of hard core and soft periphery taken from "How to spread Good Ideas" (2004).............................................................................................................................................................................................................81

Figure 34: Table 3 in Denis et al's "Explaining diffusion patterns for complex healthcare innovations" (2002) ..............................................................................................................................................................................................82

Figure 35: Phosphorus Mission structure..................................................................................................................................83

Figure 36: Phophorus Mission -‐ distinction between hard core and soft periphery ..............................................84

Figure 37: Babushka SMS structure..............................................................................................................................................85

Figure 38: Babushka SMS -‐ distinction between hard core and soft periphery ........................................................86

Figure 39: Graph illustrating the Bowling Alley strategy, available on Prof. Kenneth E. Homa's website ....90

Figure 40: Expandnet's and WHO's scale up strategy for healthcare innovations (2009)...................................91

Figure 41: Guérineau's classification of subsidiary roles in relation to innovation deployment ................... 101

Figure 42: Diabeo -‐ internal and external affiliate factors that affected the solution launch ........................... 103

Figure 43: Babushka SMS -‐ internal and external affiliate factors that affected the solution launch ........... 104

Figure 44: MORE flow diagram – Value proposition 1 ...................................................................................................... 112

Figure 45: MORE flow diagram -‐ value proposition 2........................................................................................................ 113

Figure 47: The HAS matrix............................................................................................................................................................. 115

Figure 48: Graphic representation of theoretic promotion model inspired by Berwick's rules for dissemination ............................................................................................................................................................................ 122

Figure 49: Diabeo's partnership framework ......................................................................................................................... 124

Figure 50: Partner selection depends on the deployment strategy............................................................................. 128

Figure 51: eHealth solution architecture segmentation ................................................................................................... 130

Figure 52: Application of the 9 key points to an example solution.............................................................................. 132


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