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Business Implications - Data culture

In recognition of IT’s increasingly large impact on business, Accenture Technology Labs is augmenting its annual Accenture Technology Vision with a series of Business Implication companion pieces. The Accenture Technology Vision sets out to determine the emerging IT developments that will have the greatest impact on enterprises, government agencies and other organizations in the next three to five years.

Business Implications - Data culture
In this first in the series of Business Implications, Accenture Technology Labs looks at the significance of emerging data culture.

Business changes, Technology catalyst

Each year, the Technology Vision team at Accenture Technology Labs sets out to determine the emerging IT developments that will have the greatest impact on enterprises, government agencies, and other organizations in the next three to five years. These efforts produce a handful of robust hypotheses, which have been synthesized into the six overarching technology trends in Accenture’s Technology Vision 2012 report, with the goal of guiding CIOs in their strategies to leverage and drive new opportunities based on an evolving technology landscape.

But, times are changing. With each passing year, the rapid rate of innovation within IT is having an increasingly larger impact on businesses beyond the CIO organization. To address this new reality, this year we have created Business Implication companion pieces to Accenture’s Technology Vision 2012. These pieces walk through opportunities and issues driven by the vision technology trends and start the C-suite discussions about what needs to be done now to prepare for and take advantage of these changes. Technology is playing a key role in reshaping how companies do business. Some of you are already having these conversations with your IT colleagues. For those of you that aren’t, are you ready?

Fostering the new data culture

Google, Facebook, and Amazon already run on data—lots of it, from outside their respective four walls as well as inside. They sift the data in ways that deliver rich insights and lead to faster, more assured decision making. But how is this different from a decade or two ago, when companies began investing in business intelligence solutions? Facebook’s recent public offering gives a clue: its valuation owed much to its storehouse of consumer data. The broader answer: we’re entering an age in which data drives every decision. Data has become a strategic asset, and a company’s success will depend on how well and how often its employees, at every level, use that asset.

Today, basic office-productivity applications mean that these tasks are expected to be part of everybody’s workplace literacy. It’s 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 benefits: pushing for deeper cost savings and greater operational efficiencies, striving for revenue growth by identifying new market opportunities and accelerating new-product launches, improving financial models, mitigating supply chain risks, and much more. But what’s really new here? Haven’t businesses been recognizing and treating data as a valuable asset for decades? Yes, but something significant has changed: the costs associated with that data.

Ten years ago, data was expensive—expensive 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 news—and something that most business leaders have not yet realized—is 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 storing and processing of that data in ways that do not exponentially raise costs. Chief information officers can now “architect” data platforms that enable their organizations to tap structured and unstructured data—everything from blog posts and Facebook data to e-mail traffic—and to industrialize their data services (see Accenture’s 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, it’s necessary to start modifying the organization’s objectives too. Companies must move from the current model—the implicit strategy of maximizing the benefit of a set amount of data usage—to an explicit model where all employees are expected to maximize data usage to drive business benefits. 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 organization’s operations more efficient 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 available to them. Like the managers who were the first to realize what the proliferation of Lotus 1-2-3 and Microsoft Office would mean for office 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 organization’s next core competency.

Silicon Valley’s latest approach to decision 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 benefits 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 won’t.

Why aren’t 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 don’t have easy access to the necessary data, even though the components of the data almost certainly exist in pockets throughout the company—the cost per hour of the CSRs’ time, the number of customers who’ve 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 expectation—few if any metrics or incentives—to help make this type of experimentation a part of someone’s job. And few people are given the time to act on these ideas. Too often, there simply isn’t 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 don’t act on their hunches and instead just move on to their next tasks.

That’s what’s typical today. But a new corporate model is emerging: young companies that aren’t dogged by heavyweight legacy IT systems and that are infusing data into many more of the decisions their managers make every day. Amazon’s chief technology officer, Werner Vogels, has stated that Amazon’s free-flowing data-services model enables the company to respond very 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 aren’t 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, they’ve 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, it’s free to roam, and can be moved, shared with alliance partners or suppliers, divided up, analyzed every which way, blended with other data—whatever 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 culture—one 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 confident 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 define and launch new products.

Data culture starts to trickle outward

Most businesses are following a different path toward datadriven decision making. For them, changing IT’s 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 officer and president Robert McDonald is behind a company-wide push to digitize as much as possible—from tracking sales of shampoo in the United Kingdom to developing a “digital skills” inventory of its employees. The company’s well-publicized “Business Sphere” presents its top executives with a weekly array of granular, up-tothe-minute data—almost all of it actionable. In the next few years, P&G expects to be able to identify, absorb, and get value from seven 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.

It’s fair to say that most organizations are low on the data learning curve. For many, their forays into leveraging data are just that; those initiatives are not—or not yet—integrated 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)

What the C-suite needs to do now

- Get a clear sense of the organization’s data “inventory” 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, service providers, and other partners with the focus on data: what data each party can access, who owns what, how it’s used, and how it’s shared.
- Assess your organization’s data-skills gap; determine where the gaps are greatest and draft plans for how to fill them.
- Begin identifying the characteristics of a data culture for your organization; how would your company ignal that data is becoming a core competency?
- Consider a new management role: a chief data officer.
- Think through how to embed data proficiency in the organization’s business teams and how best to integrate existing data specialists with those teams in order to extract insights.
- Looking at how data literacy will need to change talent management efforts; Updating metrics, incentives, evaluations and rewards to encourage the use of data will play a part in building a data culture.
- Investigate the concept of “data exchanges” through which data can be shared internally—and maybe even “bought” and “sold” with external partners.
- Map out ways to ratchet up expectations about how to better analyze data—and how to better report on it.

Driving toward a data-driven corporate culture

Rome wasn’t built in a day—and established organizations don’t become data-centric overnight. So, a first, concrete step is to recognize that the shift toward data is indeed a journey. It is also a team effort—not 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 company’s top team.

This is not the place to list the kinds of software solutions that can help produce insights at scale across an organization—that’s for the CIO to evaluate and recommend. But it will take more than just a change in technology to maximize the advantages derived from data. 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 CIO’s 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 mindset—if there is to be a corporate culture that understands and reveres data—then intimate understanding of data must be embedded in the skills and characteristics of all employees at all levels, especially within the business. It’s as simple as this: if it’s 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 regarded as 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 organization—for all business decisions. Reskilling raises real issues of organizational structure. For instance, should all data specialists reside within 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 to get concrete insights into our companies’ opportunities and challenges? Those are the kinds of conversations that CIOs, together with the CEO’s office, 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 officer (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 financialservices providers at that time, as banks wrestled with disparate data sources— market reference data, customer data, risk data, transaction data, and more—and 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 office. (5),(6)
The FCC’s data chiefs are responsible for the policies and practices that make FCC data available internally and externally as an asset for daily use.

John Bottega’s appointment—he is responsible for data management strategy, policy, and governance, and he reports to enterprise CIO Marc Gordon—is seen as a signal moment. “Bank of America may be the first bank to appoint a truly enterprise-wide chief data officer,” Mike Atkin, managing director of the Enterprise Data Management Council, a group of data management professionals, told American Banker. “This is an indication that Bank of America takes data management seriously. The size of Bank of America, the reach of the financial 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 management—activities such as remediation, data cleaning, and compliance with regulations. The CDO’s 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 derived from data. If data is truly going to become a part of a company’s new culture, there will have to be a significant 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 you’ve outsourced your HR function, do you still own the data? Do you have access to it? It is Accenture’s 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 issues such as what data the organization is going to collect and from where, and how it’s 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 influence 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 we save just the data that we guess will be most valuable? What rules govern the deletion of data? A plant supervisor can’t simply archive machine data from a production line if it’s now critical for other business processes, such as new-product engineering or analysis of product recalls.

However, there isn’t yet much concrete guidance for how to value data across a company—let alone across the ecosystem of suppliers, customers, and other stakeholders that may need to use it, at least at some time or another.

Companies like Google, Amazon, and Procter & Gamble are showing what must happen next

Their recognition of the value of data, and their wholesale commitment to extracting more and more value from growing volumes of data, must become the model for other businesses to follow.

But it’s not just a question of handing off the issue to the CIO with a mandate to somehow accelerate the use of data across the organization. Nor is it just a budget sign-off for new analytics or reporting software. Ensuring that data becomes a pivot point for long-term competitiveness calls for a strategic effort that is galvanized and led from the top. It is at least as much about mindset and culture as it is about technology. It is certainly more about 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 at your company yet?

1. Forbes.com, August 3, 2011
“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, 2011
“New Global Study: Only One-Third of Companies Making Effective Use of Data”
4. American Banker, December 14, 2011
“Does John Bottega’s Hire as B of A’s Chief Data Officer Mean the CDO is Back?”
5. FCC
6. ACM Queue, May 1, 2006
“A Conversation with Werner Vogels”

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

Lundi 1 Octobre 2012

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