Business Implications Data Culture

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Accenture

TechnologyVision2012

Business Implications SeriesData culture


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Business Implications Data culture Technology Vision 2012 trend: Converging data architectures


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Business Implications Data culture

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Fostering the new data culture

Google, Facebook, and Amazon already run on datalots of it, from

outside their respective four walls as well as inside. They sift the datain ways that deliver rich insights and lead to faster, more assureddecision making. But how is this different from a decade or two ago,when companies began investing in business intelligence solutions?Facebooks recent public offering gives a clue: its valuation owedmuch to its storehouse of consumer data. The broader answer:were entering an age in which data drives every decision. Data has

become a strategic asset, and a companys success will depend onhow well and how often its employees, at every level, use that asset.

Converging data architectures

Business implication drivers Accenture

Technology Vision 2012 technology trends

Industrialized data servicesContext-based services

Accenture Technology Vision 2012


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Fans of the AMC series Mad Men

will get it, but the rest of us needto be reminded of a time, not solong ago, when businesses hadentire service functions to producememos, type letters, make copies,and create presentations.

Today, basic ofce-productivity applications mean that these tasks

are expected to be part of everybodys workplace literacy. Its an

essential part of how people do their jobs.

Not too far in the future, business leaders will recall an era when

data literacy was the province of only a few specialists. For now,

it is the trailblazers among business leaders, eager to outgrow

and out-innovate their competitors, who are creating a new

corporate culture; one where acquiring insights and making

decisions using data sources and data analysis is the rule and not

the exception. Their efforts are directed toward a host of business

benets: pushing for deeper cost savings and greater operational

efciencies, striving for revenue growth by identifying new market

opportunities and accelerating new-product launches, improving

nancial models, mitigating supply chain risks, and much more.

But whats really new here? Havent businesses been recognizing

and treating data as a valuable asset for decades? Yes, but

something signicant has changed: the costs associated with

that data.

Ten years ago, data was expensiveexpensive to gather; expensive

to aggregate; expensive to access, report on, analyze, process, and

store. In addition, as more data was added to the mix, the costs

grew exponentially. To deal with those realities, organizations

had no choice but to build systems and cultures for treating data

as a scarce resource. That meant that only the highest priority

decisions have been able to rely extensively on data; essentially,

everything else has been priced out of the data equation.

The new newsand something that most business leaders

have not yet realizedis that innovative tools and maturing

technologies now allow IT to change that cost equation. Data

volumes are exploding; today, more data is being collected

than ever before, internally, within businesses, and externally,

among the organizations networks and in the wider consumer

world. Horizontal-scaling technologies now allow the storingand processing of that data in ways that do not exponentially

raise costs. Chief information ofcers can now architect data

platforms that enable their organizations to tap structured and

unstructured dataeverything from blog posts and Facebook

data to e-mail trafcand to industrialize their data services (see

Accentures Technology Vision 2012 report) so that companies can

quickly access and share data across the organization, at minimal

incremental cost.

But implementing a data platform to change that cost model is

only half of the equation. To get tangible results, its necessary to

start modifying the organizations objectives too. Companies mustmove from the current modelthe implicit strategy of maximizing

the benet of a set amount of data usageto an explicit model

where all employees are expected to maximize data usage to drive

business benets. That represents a cultural shift that can have a

dramatic effect on how the organization is run. In the new model,

data becomes central to innovation and to all decision making,

fueling growth and making the organizations operations more

efcient at every level. Data skills spread beyond IT, becoming part

of every business function and business activity. This new culture

not only allows all employees to ask what data would allow me

to do my job better? but also makes the necessary data availableto them. Like the managers who were the rst to realize what the

proliferation of Lotus 1-2-3 and Microsoft Ofce would mean

for ofce productivity, farsighted executives today are starting

to realize that data is becoming a strategic asset for the future

growth of their business. In essence, data is en route to becoming

every organizations next core competency.

Business Implications Data culture Accenture Technology Vision 2012


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Silicon Valleys latest approach todecision making

Think about this scenario: a customer service manager has

a hunch that the company could win more repeat sales if its

customer service reps (CSRs) were to proactively contact all

customers who have bought more than $500 worth of products

in the last month to see if those customers have encountered

any issues that the company could help with. In an ideal scenario,

the service manager makes this decision by weighing the potential

benets against the cost of having the CSRs do this. If that cost is

less than the incremental revenue that is driven through increased

sales, the service manager will do it; if not, they wont.

Why arent managers acting on hunches like this every day?The answer is often distressingly simple: in most companies,

they lack access, expectations, and time. To begin with, groups

dont have easy access to the necessary data, even though

the components of the data almost certainly exist in pockets

throughout the companythe cost per hour of the CSRs time,

the number of customers whove spent more than $500 in the last

12 months, the current rate of repeat purchases within 3 months,

and so on. Also, there is no expectationfew if any metrics or

incentivesto help make this type of experimentation a part

of someones job. And few people are given the time to act on

these ideas. Too often, there simply isnt a minute to explore the

possibilities; immediate concerns override such experimentation

to the point of complete exclusion. The consequence: managers

make decisions on gut feel, or, more often, they dont act on

their hunches and instead just move on to their next tasks.

Thats whats typical today. But a new corporate model is

emerging: young companies that arent dogged by heavyweight

legacy IT systems and that are infusing data into many more of

the decisions their managers make every day. Amazons chief

technology ofcer, Werner Vogels, has stated that Amazons

free-owing data-services model enables the company to respondvery quickly to new ideas. At companies such as Amazon, LinkedIn,

and Facebook, data is the new lingua franca: managers are expected

to come to meetings with proposals, but those that arent backed

by hard data are unlikely to get a hearing.

The advantage that these companies have is this: without

existing IT systems to contend with, theyve implemented a data

architecture that is focused on data sharing (see Industrialized

Data Services in Technology Vision 2012). In essence, through

data services, their data is not tied to this or that software

application; for the most part, its free to roam, and can be

moved, shared with alliance partners or suppliers, divided up,analyzed every which way, blended with other datawhatever

it takes to unlock more of its potential value.

With data more easily available, this new breed of companies

has gone one step further and created a new corporate data

cultureone that regularly requires data to back up managers

choices. Essentially, these companies have achieved a pervasive

form of data-driven decision making. They can be quicker and

more condent in their decision making; they can explore more

ideas more easily and with more conclusive results; they can cut

costs more quickly, more easily, and more effectively; and they

are better able to evaluate and enter new markets and deneand launch new products.

Data culture starts to trickle outward

Most businesses are following a different path toward data-driven decision making. For them, changing ITs data infrastructure

is hardly a given; it is neither inexpensive nor done all at once. It is,

however, just as important, and some of the more forward-looking

companies are already building up their data competencies.

One standout is Procter & Gamble: chief executive ofcer and

president Robert McDonald is behind a company-wide push

to digitize as much as possiblefrom tracking sales of shampoo

in the United Kingdom to developing a digital skills inventory

of its employees. The companys well-publicized Business Sphere

presents its top executives with a weekly array of granular, up-to-

the-minute dataalmost all of it actionable. In the next few years,

P&G expects to be able to identify, absorb, and get value fromseven times the amount of data it gathers constantly today.1

While large-scale transformations are rare, some companies

are further along with discrete initiatives. Several leading oil

and gas companies are using emerging software tools to review

massive amounts of their raw exploration data and predict the

economic viability of new reserves. And utilities are using the

same tools to analyze large volumes of data from smart meters

and to help optimize energy generation based on predictive

patterns of consumption.

Its fair to say that most organizations are low on the datalearning curve. For many, their forays into leveraging data are

just that; those initiatives are notor not yetintegrated into

an overarching strategy. The end goal of such a strategy is clear,

though. A recent study of 179 companies, led by an economist at

the MIT Sloan School of Management, suggests that companies

that adopted data-driven decision-making have productivity

levels 5 to 6 percent higher than could be explained by other

factors, including investment in technology.2



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What the C-suite needs to do now

Get a clear sense of the organizations datainventory and how it is being cataloged.

Determine how the data is being valued and prioritized.

Establish what data needs to be shared and how,and what needs to be collected and how.

Revisit relationships with suppliers, serviceproviders, and other partners with the focus ondata: what data each party can access, who owns

what, how its used, and how its shared. Assess your organizations data-skills gap;

determine where the gaps are greatestand draft plans for how to ll them.

Begin identifying the characteristics of a data culturefor your organization; how would your companysignal that data is becoming a core competency?

Consider a new management role: a chief data ofcer.

Think through how to embed data prociencyin the organizations business teams and howbest to integrate existing data specialists withthose teams in order to extract insights.

Looking at how data literacy will need to change talentmanagement efforts; Updating metrics, incentives,evaluations and rewards to encourage the use ofdata will play a part in building a data culture.

Investigate the concept of data exchanges throughwhich data can be shared internallyand maybeeven bought and sold with external partners.

Map out ways to ratchet up expectations about howto better analyze dataand how to better report on it.

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Driving toward a data-driven corporate culture

Rome wasnt built in a dayand established organizations dont

become data-centric overnight. So, a rst, concrete step is to

recognize that the shift toward data is indeed a journey. It is also

a team effortnot a next-quarter program that can be handed

off to an executive sponsor but an ongoing commitment that

demands the wholehearted involvement of the CEO and concrete

actions and accountability from most of the members of the

companys top team.

This is not the place to list the kinds of software solutions that can

help produce insights at scale across an organizationthats for

the CIO to evaluate and recommend. But it will take more than just

a change in technology to maximize the advantages derived fromdata. It is appropriate here to address key factors that are under

the remit of the CEO. As the CIO makes progress in providing the

foundation capabilities that will allow the business to access and

manipulate data, the rest of the C-suite needs to start adapting

the business so that it can take advantage of the CIOs initiatives.

Three factors cry out for immediate attention:

1. Reskilling the organization.

A recent study by EMC, a leading data-storage company, notes

that only one-third of companies are able to effectively use the

data they are collecting to assist their business decision making,gain competitive advantage, drive productivity growth, yield

innovation, and reveal customer insights. One of the most pressing

reasons for that gap: the business demand for data expertise has

quickly outpaced the supply of data-savvy talent.3

If organizations are to take on a data-centered mindsetif there is

to be a corporate culture that understands and reveres datathen

intimate understanding of data must be embedded in the skills

and characteristics of all employees at all levels, especially within

the business. Its as simple as this: if its expected that data is

used to drive decisions, then the teams that make those decisions

must have the skills to utilize the data. This will require a new

conversation about talent management. Human Resources must

explore and conclude what data literacy means, how it can be

evaluated and rewarded, how it can be woven into future hiring

criteria and training programs, and how it can be widely regardedas a driver of career progress. But recruiting data scientists to

lead data efforts is just the start. There is already a scramble for

these scarce data resources, and it will only accelerate. Meeting

the data-skills gap will require companies to go beyond recruiting;

rather, they must develop the capability to train and build those

data skills themselves throughout their business.

It goes without saying that data literacy has to become a core

competency among the executive team, but it is a characteristic

that must also be evident at every level of the organizationfor all

business decisions. Reskilling raises real issues of organizational

structure. For instance, should all data specialists reside within



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IT, or should they be integrated with line-of-business functions?

And how do we start cross-pollinating the data skills and deep

knowledge of the business processes that will be necessary toget concrete insights into our companies opportunities and

challenges? Those are the kinds of conversations that CIOs,

together with the CEOs ofce, must be having now.

2. Appointing a data champion.

The more that data is shared within and outside of the

organization, the more there is a case to be made for a chief data

ofcer (CDO) position. Last December, Bank of America appointed

John Bottega as its CDO.4 Bottega had been hired into a CDO role

at Citigroup in 2006, a popular move by banks and other nancial-

services providers at that time, as banks wrestled with disparate

data sources market reference data, customer data, risk data,

transaction data, and moreand as they struggled to reconcile

data from other companies they had bought. The CDO role

appears in state and federal government, too; at the U.S. Federal

Communications Commission (FCC), there is a CDO for each

bureau and each ofce.5,6 The FCCs data chiefs are responsible

for the policies and practices that make FCC data available

internally and externally as an asset for daily use.

John Bottegas appointmenthe is responsible for data

management strategy, policy, and governance, and he reports

to enterprise CIO Marc Gordonis seen as a signal moment.

Bank of America may be the rst bank to appoint a truly

enterprise-wide chief data ofcer, Mike Atkin, managing director

of the Enterprise Data Management Council, a group of data

management professionals, told American Banker. This is anindication that Bank of America takes data management seriously.

The size of Bank of America, the reach of the nancial institution,

and the elevation of this position to C level is a great sign.

However, the CDO role needs to be added to the C-suite lineup

in industries ranging from retail to industrial manufacturing.

It is imperative that companies large and small begin to move

beyond IT data managementactivities such as remediation,

data cleaning, and compliance with regulations. The CDOs role

is to become the champion for the strategic use of data at every

level. The role serves as the bridge between IT and the business,

providing guidance to maximize the value that can be derivedfrom data. If data is truly going to become a part of a companys

new culture, there will have to be a signicant transformation

of technology, organization, talent, incentives, and more. That

transformation will require the full support of the C-suite and

a dedicated champion to drive it forward.

3. Rethinking relationships with

partner organizations.

If data now has a measurable value, why are you sharing it so

freely with partners? Who owns the data, anyway? If youve

outsourced your HR function, do you still own the data? Do youhave access to it? It is Accentures belief that companies now

need to rethink their partnership agreements in relation to data,

reevaluating current arrangements in light of the value of the

data already being shared. The rethinking will extend to issuessuch as what data the organization is going to collect and from

where, and how its going to be collected and how it will be used.

In some cases, the answers will materially affect the nature of

the relationship.

A prerequisite step is to put a value on data. The more widely

a data set is used, the more valuable it becomes. But how do you

assign worth to it when it is combined with other data? Or split

up? Or used multiple times over many years? New data-valuation

approaches will also inuence the ways that data is stored,

shared, published, secured, and destroyed. Do we save everything,

assuming it will be useful to somebody somewhere? Or do wesave just the data that we guess will be most valuable? What

rules govern the deletion of data? A plant supervisor cant simply

archive machine data from a production line if its now critical

for other business processes, such as new-product engineering

or analysis of product recalls.

However, there isnt yet much concrete guidance for how

to value data across a companylet alone across the ecosystem

of suppliers, customers, and other stakeholders that may need

to use it, at least at some time or another.



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Companies like Google, Amazon, and Procter & Gamble are showing

what must happen next. Their recognition of the value of data, andtheir wholesale commitment to extracting more and more valuefrom growing volumes of data, must become the model for otherbusinesses to follow.

But its not just a question of handing off the issue to the CIOwith a mandate to somehow accelerate the use of data across

the organization. Nor is it just a budget sign-off for new analyticsor reporting software. Ensuring that data becomes a pivot pointfor long-term competitiveness calls for a strategic effort thatis galvanized and led from the top. It is at least as much aboutmindset and culture as it is about technology. It is certainly moreabout the business functions than it is about IT. And it is absolutely

about new skills and new levels of accountability.

Are those themes part of the conversations atyour company yet?

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1. Forbes.com, August 3, 2011

At Procter & Gamble, Toothpaste Is Datahttp://www.forbes.com/sites/quentinhardy/2011/08/03/at-procter-gamble-toothpaste-is-data/

2. Erik Brynjolfsson, Lorin Hitt, and Heekyung Kim, April 22, 2011

Strength in Numbers: How Does Data-Driven Decision Making Affect Firm Performance?

3. EMC press release, December 5, 2 011

New Global Study: Only One-Third of Companies Making Effective Use of Datahttp://www.emc.com/about/news/press/2011/20111205-02.htm

4. American Banker, December 14, 2 011

Does John Bottegas Hire as B of As Chief Data Ofcer Mean the CDO is Back?http://www.americanbanker.com/issues/176_241/John-Bottega-appointed-chief-data-ofcer-Bank-of-America-1044859-1.html

5. FCChttp://www.fcc.gov/data/chief-data-ofcers

6. ACM Queue, May 1, 2006

A Conversation with Werner Vogelshttp://queue.acm.org/detail.cfm?id=1142065

Sources: Contacts:

Dr. Gavin Michael

Chief Technology Innovation Ofcer

[email protected]

Michael Biltz

Director, Accenture Technology Vision

[email protected]

Scott W. Kurth

Director, Accenture Technology Vision

[email protected]

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About Accenture

Accenture is a global management consulting, technology services and outsourcingcompany, with more than 244,000 people serving clients in more than 120 countries.Combining unparalleled experience, comprehensive capabilities across all industries andbusiness functions, and extensive research on the worlds most successful companies,Accenture collaborates with clients to help them become high-performance businessesand governments. The company generated net revenues of US$25.5 billion for the fiscalyear ended Aug. 31, 2011. Its home page is www.accenture.com.

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