PATTERN BASED DIGITIZATION OF PRODUCT PORTFOLIOS - … · PATTERN BASED DIGITIZATION OF PRODUCT...

International Association for Management of Technology IAMOT 2018 Conference Proceedings

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PATTERN BASED DIGITIZATION OF PRODUCT PORTFOLIOS

M.SC. JULIAN ECHTERFELD University of Paderborn, Heinz Nixdorf Institute, Germany [email protected]‐paderborn.de (Corresponding)

PROF. DR.‐ING. JUERGEN GAUSEMEIER University of Paderborn, Heinz Nixdorf Institute, Germany

[email protected]‐paderborn.de

ABSTRACT

Digitization offers great potentials for product innovations and will change tomorrow’s product

landscape substantially. Companies have to exploit the innovation potentials of digitization in order

to secure future business success and stay competitive. However, a lot of companies still have massive

problems to manage the digital transformation of their product portfolio. One of the main reasons are

the manifold, almost incomprehensible options of digitization. To tackle this challenge, the paper at

hands presents a catalogue of digitization patterns which provide concrete options for digitizing

products and aid companies in generating innovative ideas for digital product features. The patterns

are part of an overall methodological approach for digitizing product portfolios.

Key words: digitization, digital transformation, digitization patterns, product portfolio, digitized

products, product portfolio management, future scenario

DIGITIZATION AS KEY DRIVER FOR INNOVATIONS

Digitization is the key innovation driver of the 21st century. It affects all areas of life and leads to far‐

reaching changes in nearly all industries. The disrupting force of digitization can already be witnessed

in numerous industries. Examples range from the retail sector (e.g. Amazon) to the media and

entertainment industry (e.g. Spotify, Netflix) through to the hospitality and travel business (e.g.

Airbnb). In all these industries incumbents were overturned and markets were reshaped by digital

solutions. But also in business‐to‐business‐industries like machinery and plant engineering industry or

electronics industry a fundamental digital change is currently unfolding, which is expressed by popular

terms like Industry 4.0 or Internet of Things (Kagermann et al. 2013). Bradley et al. employ the

metaphor of a digital vortex to describe the inevitable convergence of all industries towards a digital

centre in which offerings are digitized to the maximum extent possible. The speed with which the

industries converge to the vortex’ centre naturally differ – e.g. digital transformation in retail sector

obviously has progressed very much further than in machinery and plant engineering industry.

However, at the end of the day, no enterprise can evade the digital changes in its specific business

environment (Bradley et al. 2015). Zuboff’s laws which essentially state that everything that can be

digitized will be digitized have never been more relevant than today (Zuboff 1988).

Digitization generally is a broad and multifaceted term that drives innovations in manifold ways.

This makes it initially necessary to structure the different dimensions of digitization. Taking into

account the work of (Lichtblau et al. 2015), we elaborated a framework that is based on the two

aspects “object of digitization” and “nature of the object”. The “object of digitization” is distinguished


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into “product and service” and “product and service creation process”, the “nature of the object” in

“tangible” and “intangible”. In this way, five dimensions of digitization result (figure 1):

Digitization of the product portfolio: Digital product innovations that are based on new digital

product features (smart products), e.g. autonomous driving systems of cars.

Digitization of the service portfolio: Digital service innovations which rely on the collection and

analysis of large datasets (smart services), e.g. predictive maintenance of machines.

Digitization of the production system: Digital production system innovations which enable a

highly automated, decentral and self‐organized production (smart factory), e.g. plug and produce

of machines.

Digitization of the business processes and value chains: Digital process innovations that allow

highly automated business processes as well as horizontally and vertically integrated value chains

(smart processes), e.g. robot process automation.

Digitization of the business model: Digital business model innovations which change the entire

logic of a company’s business, e.g. performance based contracting business models.

Figure 1: Dimensions of digitization

The paper at hand focuses the dimension “digitization of the product portfolio”. Since the dimensions

“digitization of the service portfolio” and “digitization of the business model” can in no way be entirely

separated from this dimension, they are considered marginally as well. The other two dimensions are

not adressed within the paper. Subsequently, we give some examples how digitization is changing

today’s product world.

NEW PRODUCTS IN A DIGITAL WORLD

Digitization opens up fascinating opportunities for product innovations. Many companies have already

started to digitize their products by equipping them with information and communication

technologies and connecting them via the internet. Figure 2 shows six examples in which enterprises

from different industries have innovated their products by adding new digital features: The tyre


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manufacturer Hankook has developed an intelligent tyre which is able to brake automatically in case

of black ice or aquaplaning. Moreover, it can vary its air pressure depending on the street conditions

to enhance traction and rolling characteristics. The consumer electronics company Samsung launched

a smart refrigerator which provides online ordering of food, remote observation of the food inside the

fridge as well as additional app‐based functions that can be controlled by a touchscreen (e.g. weather

service, calender, etc.). The tennis outfitter Babolat integrated sensors and networking components

into the grip of its tennis rackets which make it possible to record and evaluate the ball speed, spin

and point of contact. In this way, players are supported in improving their game. The bed

manufacturer sleep number recently presented a smart bed which automatically adjusts the bed’s

headboard if a person starts snoring. Moreover, it varies the hardness and supporting force of the

mattress depending on a person’s lying position. The healthcare company Novartis and Google are

working on intelligent contact lenses that are able to permanently measure and control a diabetic’s

blood sugar level based on the lacrimal fluid. Last but not least, the machine tool manufacturer DMG

MORI developed an app‐based machine control and operating system which also provides digital

production workflows on shopfloor level.

Figure 2: Examples for digitized products

The extensive changes in the product world can also be expressed in figures: A study conducted by

the business consultancy PwC predicts that the share of highly digitized products will almost triple

until 2020. This will lead to an expected increase in revenues of nearly 2.5% per year (PwC 2014). A

survey conducted by the German Association for Information Technology, Telecommunications and

New Media (BITKOM) reveals that 40% of the companies interviewed plan on digitizing their product

portfolio within the next years (Dirks 2017).

Both the examples and the figures show that digitized products will have an ongoing massive

impact on tomorrow’s global innovation landscape. For companies, it will therefore be crucial to bring

out a continuous stream of digital product innovations to defend or even strengthen their competitive

position and ensure future business success (Porter and Heppelmann 2015).


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PATTERNS FOR DIGITIZING PRODUCTS

Digitized products have been broadly discussed in scientific literature for several years and referred

to by miscellaneous terms (Novales et al. 2016). Rijsdijk and Hultink see a shift towards smart products

(Riijsdijk and Hultink 2009). Porter and Heppelmann state that traditional products evolve to smart,

connected products (Porter and Heppelmann 2014). Gausemeier et al. observe a change towards

intelligent technical systems (Gausemeier et al. 2014). Lee speaks of cyber‐physical systems (Lee

2008).

The terms to label digital products are as varied as their attributed characteristics. Rijsdijk and

Hultink define seven characteristics of smart products: autonomy, adaptivity, reactivity,

multifunctionality, ability to cooperate, humanlike interaction and personality (Riijsdijk and Hultink

2009). Gausemeier et al. specify four characteristics: Adaptivity, robustness, foresightedness and user‐

friendliness (Gausemeier et al. 2014). Noll et al. mention six characteristics: Data‐centricity,

intelligence, connectivity, communication ability, extensibility and individualization (Noll et al. 2016).

Following the work of (Novales et al. 2016), we carried out a synthesis of the characteristics mentioned

in literature and defined eight constituting characteristics of digitized products (Ahram et al. 2012),

(Rijsdijk and Hultink 2009), (Sabou et al. 2009), (Yoo et al. 2012), (Gausemeier et al. 2014), (Porter and

Heppelmann 2014), (Noll et al. 2016):

• Adaptivity: Digitized products interact with and automatically adapt to their environment.

• User‐friendliness: They take into account and automatically adapt to different users’ behaviour.

• Robustness: In an ever‐changing environment, they cope with even unexpected situations that

were not considered by the developer.

• Foresightedness: They use knowledge gained through experience to anticipate the effects of

different factors.

• Connectivity: Digitized products are connected with other products and devices and are able to

exchange information.

• Autonomy: They independently solve complex tasks within a certain application domain without

involvement of the user.

• Extensibility: They are extensible along their lifecycle, e.g. by digital updates.

• Multifunctionality: Through the application of information and communication technology in

physical products, digitized products fulfill multiple functions.

The characteristics provide helpful orientation and can aid the digitization of products, e.g. by serving

as search fields for new digital product features. However, scholars unanimously give evidence that

the majority of companies still have massive problems to manage the digital transformation of their

product portfolio. One of the main reasons are the manifold, almost incomprehensible options of

digitization (VDMA and McKinsey 2016), (Kempf and Frese 2015).

To tackle this challenge, we analyzed what companies concretely did to digitize their products in

order to find universal patterns that can be used within product innovation management. The basic

idea of patterns is reusing solutions that are documented generally and abstractly in order to make

them accessible and applicable to others. In this way, patterns seek to contribute to reducing

complexity and increasing efficiency in problem‐solving processes (Alexander, 1979), (Cloutier and

Verman, 2006). Patterns are used across several domains, e.g. in software engineering (Gamma et al.,

1995), (Buschmann et al., 1996), product engineering (Roth, 1982), (Altschuller, 1984), and business

model development (Gassmann et al., 2014), (Echterhoff et al. 2017). As far as we know, patterns for

digitizing products yet do not exist.


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Our analysis included a comprehensive literature study on the one hand, and an exploration of best

practice examples on the other hand. In sum, we developed a catalogue currently containing 50

digitization patterns. Figure 3 exemplarily shows the digitization pattern “Digitization of the human‐

machine interface (hmi)”. According to this pattern, analogue display instruments and input devices

are substituted by digital ones. Best practice examples reach from Volkswagen over Lenovo and to

Apple. For each pattern it is marked, which characteristics of a digitized product it mainly affects.

Figure 3: Digitization pattern “Digitization of the human‐machine interface (hmi)”

The patterns are sorted by six overarching categories (figure 4). The categories describe the general

objective which is pursued with each containing pattern:

• Substitution of analogue technologies (No. 1): Analogue technologies that fulfill existing

functions are replaced by digital technologies. This category e.g. includes the pattern “Digitization

of the human‐machine interface (hmi)” shown above.

• Increasing intelligence (No. 2): Products are equipped with additional digital functions which

impart intelligence to them. Some patterns of this category are illustrated in figure 4 in a simplified

form.

• Development of data‐based services (No. 3): Through an intelligent evaluation of data from or

around the product, product‐related, beneficial services are developed.

• Outsourcing of product functions (No. 4): Existing or new product functions are outsourced to

smart devices (e.g. smartphones, wearables, etc.) or other external IT‐infrastructure (e.g. cloud).

• Building product systems (No. 5): Individual products are connected and are able to interact with

each other. New functions are realized which emerge from the cooperation of two or more

products.

• Creating ecosystems (No. 6): Product systems are connected with other systems and form so

called system of systems. New functions are realized which emerge from the cooperation of two

or more systems.


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Figure 4: Catalogue of digitization patterns (Category “Increasing intelligence”)

The catalogue provides concrete options for digitizing products and supports companies in generating

innovative ideas for digital product features. The categories give impulses for digital solutions with

different innovation levels and complexity – from simple substitution to complex ecosystems.

In the following, we present a methodology for planning digitized product portfolios using the

elaborated patterns. The methodology takes into account a company’s current digital position,

possible future scenarios for the portfolio, digitization strategies for each product group of the

portfolio derived from the scenarios and concrete digitization measures for each product group.

METHODOLOGY FOR PATTERN BASED DIGITIZATION OF PRODUCT PORTFOLIOS

Up to now, product portfolio planning has been intensively tackled by researchers. To the best of our

knowledge, methodologies that explicitly address the digitization of product portfolios are rather rare

in literature, however. Approaches for general product portfolio planning were already developed in

the 1950s (e.g. Abromeit 1950). Since then many further approaches were drawn up, though without

special focus on digitization (e.g. Day 1977, Procter and Hassard 1990,). Within the last few years,

several management frameworks (e.g. PwC 2014, Roland Berger and BDI 2015) and maturity level

models for digitization (e.g. Schuh et al. 2017, VDMA 2016) were developed. Nonetheless, a holistic

approach for digitizing product portfolios yet does not exist. To bridge this gap, we subsequently

introduce a pattern based methodology designed to enable companies to digitize their product

portfolio systematically. The methodology follows the four‐phase process shown in figure 5.


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Figure 5: Methodology for digitizing product portfolios

In the following, the methodology is going to be outlined in detail. To provide a better understanding,

the phases are presented using examples from an industry project conducted with a leading German

manufacturer of household appliances. Focus of the project was the digitization of the company’s

product portfolio for vacuum cleaners. Due to confidentiality, the results have been alienated.

Portfolio analysis

Within the first phase, the company’s product portfolio is analysed to determine its current degree of

digitization. As an initial step, all product groups of the portfolio are scanned and formally described

by their characteristics (Schuh et al. 2012). Figure 6 depicts a simplified description of the company’s

present portfolio of vacuum cleaners based on three characteristics: “appliance category”, “particle

absorption” and “energy supply”. Product groups with the same characteristics are aggregated. This

procedure allows a reduction of the product groups to a manageable number on the one hand, and

because of the abstract description a comparison of the product groups with competition on the

other. In the considered example, five different product groups result.

Figure 6: Product portfolio for vacuum cleaners


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In the next step, the existing digital product features are determined for each product group. The

features are sorted by the eight categories “adaptivity”, “user‐friendliness”, “foresightedness”,

“robustness”, “connectivity”, “autonomy”, “extensibility” and “multifunctionality” (chapter 3). The

robot vacuum cleaner, for instance, currently has an indoor positioning system and a touch user

interface. It can be operated in different modes and by remote control. Moreover, it can clean

autonomously in auto mode and has an obstacle and fall detection. The user can set a timer to define

at which time the robot is supposed to clean the floor (figure 7).

Figure 7: Specification of product groups with regard to digital product features

Having specified the digital features for each product group of the portfolio, the digital features of the

competitive products are analyzed. First of all, all relevant competitors are identified. Since in the

course of digitization often new competitors with innovative, disruptive products enter the market

(Porter and Heppelmann 2015), attention should particularly be paid on those companies. The market

for vacuum cleaners, for example, was entered by many startups like Neato Robotics or iRobot in

recent years. Subsequently, the competitor’s products are scanned and examined with regard to their

digital features. Within the considered industry project, it became evident that many competitors

already offer a greater amount of digital features as well as more innovative features. In case of robot

vacuum cleaners, digital features like home monitoring are available, for instance. The user can use

the camera of the robot to monitor his home, e.g. as protection against burglars. As an additional

feature the robot creates a digital map of the home which can be displayed on the smartphone. The

user can follow the robot’s track on the map so that he sees where the robot cleaned the floor and

where not.

Based on the company’s and the competitor’s digital product features, the degree of digitization

is calculated for each product group (figure 8). The value ranges from digital beginner to digital

pioneer. The robot vacuum cleaner in the given example possesses 8 out of 22 digital features that

currently exist on the market. Thus, it has a degree of digitization of 36% and can be classified as a

digital follower. Taking into account the degree of digitization of all product groups, the degree of


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digitization for the overall portfolio can be determined. This is done by taking the average value

weighted with the respective sales share of the product group.

The results are illustrated in a digitization cockpit. The cockpit reveals the company’s digital

position in the market. As it can easily be seen, the considered company can generally be classified as

a digital beginner. This means a serious risk for the company. It is threatening to lose touch with the

competitors and needs to act urgently in order not to lose market shares and competitiveness.

Figure 8: Digitization cockpit for the product portfolio of vacuum cleaners

Portfolio alignment

The second phase aims to strategically align the product portfolio with digitization. Since digitization

can lead to disruptive changes of products, markets and competition (Porter and Heppelmann 2015),

(Bradley et al. 2015), (Kreutzer and Land 2014), it is absolutely necessary to have an idea about the

digital future. In order to think ahead of how the product portfolio might develop in the context of

digitization, a foresight analysis is conducted using the scenario technique. A scenario is a

comprehensible description of a possible situation in the future based on a complex network of

influence factors. Examples for influence factors in the case of vacuum cleaners are “smart home

integration” or “energy supply”. For a detailed description of the scenario technique please refer to

(Gausemeier and Plass 2014), (Gausemeier et al. 2011). In the course of the project, four thinkable

scenarios for vacuum cleaners for the year 2030 were developed (Echterfeld and Gausemeier 2017):

• Keep it simple (scenario 1): In this scenario, the digitization of vacuum cleaners fails to appear

due to low customer acceptance and willingness to pay. Only very simple digital product features

are integrated.


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• Digital variants (scenario 2): Here, only high‐prized premium products are fully digitized. Basic

products are only occasionally equipped with digital features due to cost pressure.

• Focused digitization (scenario 3): In the context of this scenario, digitization mainly concentrates

on robot vacuum cleaners due to the high innovation appeal of autonomous systems.

• Maximum digitization (scenario 4): Within this scenario, all vacuum cleaners are digitized to the

maximum extent possible. The biggest trigger for digitization are integrative smart home systems.

The scenarios help to broaden the view for possible future developments. Thus, they build a solid basis

for the strategic orientation of the product portfolio. In order to elaborate a strategic direction for

digitization, a reference scenario needs to be selected, on which the strategy is focused. Therefore,

the scenarios are evaluated with respect to their probability of occurrence and strength of impact on

the business with vacuum cleaners. In the considered example, scenario 4 was chosen as reference

scenario.

The reference scenario draws a probable and radical picture of the future of vacuum‐cleaning in

the year 2030. However, digitization is not a revolution that happens overnight, but an evolutionary

process that takes place gradually (Kagermann 2015). In order to describe the stepwise development,

a scenario roadmap is worked out. The roadmap describes the migration from the current situation

into the future picture of the reference scenario (Reymann 2013). Figure 9 depicts the scenario

roadmap that was developed within the project.

Figure 9: Scenario‐Roadmap for scenario 4 “Maximum digitization”

The roadmap shows for each influence factor of the scenario how it might develop until certain points

in time. From today’s perspective, an integration of vacuum cleaners into smart home systems

(influence factor 3) has not imposed because of the low technological progress. For 2020, it is assumed


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that some first features for the integration into the smart home will be available on the market. Until

2025, the connection of vacuum cleaners with other devices via smart home will have greatly

increased. Incompatible devices will hardly have a chance then. In 2030, the connection with other

household and entertainment devices via smart home will have become a standard practice.

Against the background of the reference scenario and its migration steps, the future validity of the

current product portfolio can be evaluated. In figure 10, the evaluation for the product portfolio of

vacuum cleaners is shown.

Figure 10: Evaluation of the future validity of the product portfolio

It is supposed that all product groups except upright vacuum cleaners will be relevant at least until the

year 2020. From the year 2025 onwards, it is expected that nearly all cable‐based vacuum cleaners

will be substituted by battery‐powered models. The portfolio should therefore be extended, especially

by “battery‐powered, bagless canister vacuum cleaners” and “battery‐powered, bagless stick vacuum

cleaners”. Furthermore, all product groups will only have market success if they are equipped with

innovative digital features and are integrated into the smart home in the long run.

Based on the current digital position and the digital reference scenario, a promising strategic

direction for each product group of the portfolio is derived. Figure 11 exemplarily shows the strategic

direction elaborated for product group no. 5 “robot vacuum cleaners”. The strategic direction is based

on a chance/risk analysis and a norm strategy, which is formulated with the aid of a portfolio. The

portfolio is spanned by the two dimensions “digitization need of the product group” and “medium‐

term importance of the product group”. The first dimension stems from the digitization cockpit

(figure 8), the second dimension from the future validity check (figure 10). Four characteristic norm

strategies result:

• Attack: If a product group is weakly digitized compared to competition (digital beginner) and has

a great importance for the medium‐term future, the company should promptly launch a

digitization offensive and attack its competitors. Otherwise it is threatening to lose its acclaimed

market position.

• Defense: Product groups which are highly digitized compared to competition (digital pioneer) and

have a great importance for the medium‐term future, provide a strong starting position.

Nevertheless, the company should not lean back and rest on this position, but proactively defend

it by developing new innovative digital features.


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• Skimming/Discontinuation: For weakly digitized product groups (digital beginner) with a low

importance for the medium‐term future, either a skimming strategy should be pursued or the

product group should be discontinued. Investments regarding digitization are not worthwhile

here.

• Skimming/Recycling: If a product group is highly digitized (digital pioneer), but has a low

importance for the medium‐term future, a skimming strategy is advisable, as well. Further

digitization would not lead to long‐term commercial success. Existing digital features can though

be recycled and integrated in other or newly planned product groups.

For the company’s robot vacuum cleaner, the norm strategy “Attack” is recommended since this

product group will be of vital importance in the future and was barely classified as digital follower

(figure 8). If the company does not digitize it in due time, it will run the risk of being left behind by the

competition and losing its positon as premium supplier.

Figure 11: Strategic direction for digitization (product group robot vacuum cleaners)


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Apart from that, the planned product generations of the product groups are synchronized in time with

the migration steps and strategic goals for each generation are formulated. With the next generation

of robot vacuum cleaners (RX2), the company seeks to catch up with its competitors through

integrating common digital features with improved quality. By means of the subsequent generation

(RX3), an ascent to digital pioneer is envisaged and some first features for the integration into smart

home are supposed to be integrated. For the following generation (RX4), full autonomy is ought to be

achieved by intelligent features and complete integration into smart home.

In order to reach the goals, concrete specifications for the product groups are made as far as this

is already possible. The specifications are oriented on the six categories of digitization presented in

chapter 3. The next product generation RX2 is scheduled to be equipped with new interface

technologies, for example. In addition, the indoor navigation system shall be improved and the robot

is to be controlled by a smartphone app.

Idea finding

The third phase aims to find promising ideas for digitizing the product groups of the portfolio according

to the previously formulated strategic directions. Starting point is a profound analysis of the

customers’ pains and gains. This is due to the fact that digitization is not meant to be an end in itself,

but is supposed to be of genuine benefit to the customers. Following the approach of (Osterwalder et

al. 2014) the customer jobs are initially identified. Therefore, the customer process is scanned as it is

also propagated by the design thinking approach for example (Plattner et al. 2016), (Brown 2009).

Along the customer process, pains and gains are determined through customer observation and

customer interviews. For deeper analysis, the pains and gains are decomposed and structured in a

hierarchy. Figure 12 illustrates the hierarchy of the customer pains. First, the overall pain is

formulated: ”Customer is unsatisfied”. After that, the overall pain is decomposed into sub pains until

the actual reasons are found.

Figure 12: Hierarchy of customer pains

For the unresolved pains and gains, innovative digital product features are sought. For this purpose,

the digitization patterns introduced in chapter 3 are used. Since the patterns and the strategic

directions are based on the same structure (the six categories of digitization), a strategy‐conform


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digitization of the product groups is provided. In order to find digital features, the patterns can be

applied in two different ways that are inspired by the works of (Gassmann et al. 2014):

Pain‐and‐gain‐induced‐search: Here, a suitable pattern is being searched for a formerly identified pain

or gain. Figure 13 shows an example. The underlying customer pain is that the vacuum cleaner drowns

out ambient noises, so that the customer can’t hear when the mobile rings or the doorbell chimes. A

suitable pattern for tackling this problem is number 2.6 “Elimination of disturbing factors”. According

to this pattern, a product recognizes possible disturbances and adapts its behavior, so that the

disturbances are eliminated or reduced. Transferred to the vacuum cleaner this could mean that it

switches off automatically when the mobile rings or the doorbell chimes.

Figure 13: Example for the pain‐and‐gain‐induced‐search

Pattern‐induced‐search: With this variant, a digitization pattern is selected more or less randomly. On

the basis of the pattern, ideas for new digital product features are generated that address a customer

pain or gain. Taking the pattern 2.1 “Analysis of input factors”, an idea for a new digital product feature

for vacuum cleaners might be an analysis of the composition of the indrawn dust. The vacuum cleaner

warns the user in case of mold spores, for example, and gives the recommendation that he should air

more frequently (figure 14). The corresponding customer gain is the minimization of health risks.

Figure 14: Example for the pattern‐induced‐search


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In the context of the project, over one hundred ideas for new digital product features for vacuum

cleaners were generated by means of the patterns. In the last step of the third phase, the features are

evaluated to select the most promising ones. The evaluation is made with the help of a portfolio that

is based on two dimensions: (1) Benefit of the feature for the customer and (2) Costs of the feature

for the company. There are three characteristic segments in the portfolio (figure 15):

Sure‐fire success: Features in this segment, have a great benefit for the customer and don’t cause

substantial costs for the company. They should be implemented. Feature no. 4 “Automatic

adaptation of the vacuum power to the ground” is an example for this category of features.

Arithmetic game: This segment contains features that either generate a large benefit for the

customer and extensive costs for the company or are of little use for the customer and rather cost‐

efficient for the company. In this case, a feature’s profitability should be checked in detail, e.g. by

creating sales scenarios, harnessing cross‐selling potentials or identifying ratio‐potentials. One

example for this category is feature no. 3 “Automatic retightening of the cable within the vacuum‐

cleaning process”.

Losing deal: Features in this segment, will not bring significant benefits for the customer but

involve considerable costs. They should not be implemented. This applies for feature no. 2

“Analysis of the composition of the indrawn dust” for example.

Figure 15: Evaluation of digital product features (excerpt)

Portfolio definition

The fourth phase aims to define the digitized product portfolio. It is specified, which product group of

the portfolio gets equipped with which digital features.

In order to reduce variants and complexity, features that have been selected for implementation

are grouped into packages in the first instance (Schuh 2005). In the context of this paper, we define a


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feature package as a combination of digital product features that provide the same or a similar benefit

for the customer (e.g. reduction of effort, motivation, etc.). Following this definition, the digital

features are evaluated in terms of their customer value. This is done using the 30 elements of value

proposed by (Almquist et al. 2016). Based on the evaluation, the similarity of each pair of features is

calculated. The similarity is high if two features address the same elements of value. The final outcome

is a similarity matrix which can be transferred into a multidimensional scaling (MDS) (Borg and

Groenen, 2005). The MDS visualizes the features in a two‐dimensional space regarding their similarity

to each other. Features with a high similarity value are positioned in close proximity. Figure 16 shows

the MDS elaborated within the project. We call it a feature map (Amshoff et al. 2014). By means of

the map, 15 different feature packages have been defined.

Figure 16: Creating feature packages with the help of a feature map

The feature packages contain various features that differ with respect to their degree of innovation,

development effort, development time, implementation cost, etc. For this reason, homogenous sub

packages are defined for each packet based on the different criteria. Following the idea of the Kano

model (Kano et al. 1984), a basic package, performance package and premium package is determined.

Figure 17 exemplarily shows the sub packages for feature packet no. 9 “comfort due to process

simplification”.


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Figure 17: Definition of basic, performance and premium packages

In a final step, the sub feature packages are assigned to the product groups of the portfolio on the one

hand, and the product generations on the other hand according to the strategic directions. Due to the

different feature packages, the product groups can be digitized to different extends. The result of the

methodology is a portfolio roadmap which shows the planned development of the portfolio in the

light of digitization. Figure 18 depicts an excerpt of the roadmap developed in the project. As a matter

of course, the roadmap should be reviewed and updated regularly.

Figure 18: Digital portfolio roadmap (excerpt)

SUMMARY AND CONCLUSION

Digitization leads to far‐reaching changes of products in all industries and has a massive impact on the

global innovation landscape. For manufacturing companies, it is crucial to bring out a continuous

stream of digital product innovations in order to strengthen their market position and remain


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competitive. In the paper at hand, we introduced a pattern based methodology for digitizing product

portfolios. The methodology aids companies to strategically align their product portfolio with

digitization and transfer their product portfolio into the digital age. In the course of our research,

several sub‐outcomes could be obtained: (1) The digital transformation of product portfolios must be

implemented gradually since the digitization is an evolutionary process. Companies need to have a

clear idea of the digital future and its migration steps. The migration steps should be synchronized

with the product generation plan. (2) Companies from different industries use the same principles to

digitize their products. These principles can be abstracted and documented in the form of digitization

patterns. We developed a structured catalogue currently containing 50 digitization patterns. They

support companies in generating innovative ideas for digital products. (3) When it comes to

digitization, companies have different starting points with regard to their specific market, customers

and competitors. Depending on the digital position, different digitization patterns are applicable.

Moreover, digital product features only have commercial success if they address concrete customer

pains or gains.

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