This is part 6 of 10 from the 2013 Data & Analytics Global Executive Study and Research Project.
While many companies are beginning to cultivate benefits from their use of analytics, organizations that are getting the most value have a distinct approach. In this section, we introduce the Analytical Innovators, contrast their behaviors with other companies and discuss how these differences matter to organizational performance.
The concept of Analytical Innovators emerged when we combined responses to two of our survey questions, one about creating a competitive advantage with analytics and one about using analytics to innovate.15 We then grouped respondents into three distinct levels of analytics sophistication according to how they responded to both questions. (See Figure 2: Analytical Innovators — A Small Group of Analytics Leaders.)
Figure 2: Analytical Innovators — A Small Group of Analytics Leaders
Analytical Innovators are those respondents who strongly agree that analytics has helped improve their organizations’ ability to innovate and say that analytics has helped create a competitive advantage to a great extent. Analytics Practitioners are utilizing data, mostly to address tactical and operational issues, but are not innovating with analytics at the same level as Analytical Innovators. And Analytically Challenged organizations are struggling to use data beyond basic reporting and marketing applications.
Analytical Innovators are distinguished by several key characteristics: their mindset and culture, their actions and their outcomes.
Mindset and Culture
More than other companies, Analytical Innovators have developed an analytical mindset that supports the use of data and analytics across a wide range of corporate activities. They tend to view data as a core asset; they challenge the status quo; they believe in the possible; and they are open to new ways of thinking.
Data as a Core Asset: It’s Cultural Several executives in our interview series described data as a core asset — in their companies, analytical insights are part of the culture of the organization and are utilized in strategic decisions, both large and small. Analytics determines products and services, project success or failure, and the allocation of resources. Employees, whether data-oriented or not, utilize these insights in their decision-making processes.
Neel Sundaresan, senior director and head of eBay Research Labs, describes the role of analytic insights at eBay:
Everybody in the organization — whether you are a technical person, a researcher or an engineer, a product manager, a businessperson, or an analyst — has to be data-driven. Now, not everybody has to look at data, but everybody has to understand data at some level. A lot of data is coming from the behavior of millions of people on our site. So, being able to understand and get your head around that data is really important. You can think of it as an attitude change in all grades of people.”
Michael Johnson, director of the utility for care data analysis at Kaiser Permanente, describes how analytics permeates healthcare delivery:
With our electronic medical record system, we’ve become much more data driven and analytics oriented. Pretty much every actor in the care delivery system is using the same record and entering information in the same place. That allows us to do some remarkable things with regard to thinking about where and how members should receive care, and how to improve the flow of information, while at the same time lowering costs.
New Ways of Thinking Sixty percent of Analytical Innovators “strongly agree” that they are open to new ideas that challenge the status quo, a view that is weakly represented among other companies. (See Figure 3: Open to New Ideas.)
Figure 3: Open to New Ideas
A perfect example of an Analytical Innovator company with this mindset is online dating service Match.com. The evolution of analytics has changed how the company thinks about everything it does, according to its CEO, Mandy Ginsberg:
Everything that we do is driven by analytics. We literally test every page, every new feature — there’s nothing that we do where we don’t understand the impact of what we’ve done.
Match.com has become much smarter in the past four years. We’ve grown the data and analytics team considerably compared to some of the other areas of our business. We realized that we needed to double down in this area, and we started getting smarter and smarter about decisions.
Match.com has been around for 18 years, and that is both a benefit and a curse because we had old infrastructure and old ways of doing things, and had to adapt, versus a company like Zynga who is so fresh and new and everything they do is as a data driven company. In fact, I would say a company like Zynga is a data company that happens to do games. We’re a dating company that happens to be good at analytics, but it went in that reverse order. It’s shocking how far we’ve come.
Analytical Innovators use different language than other types of companies to talk about analytics. In response to an open-ended survey question, Analytically Challenged managers often referred to their analytics capabilities in terms of “we can’t” or “we don’t.” Analytics Practitioners frequently described their analytics capabilities in practical terms, such as solving problems or increasing efficiencies. In stark contrast, Analytics Innovators describe their analytics capabilities in terms of “reimagining” or “rethinking.”
Compared to the other groups, Analytical Innovators report that they use more of their data, use it to obtain more timely answers, collaborate more with analytics and are more effective throughout the information value chain. In short, Analytical Innovators use data and analytics much differently than everyone else.
Getting Real-Time Answers and Developing Products More Quickly We asked respondents to rank the top three uses of analytics in their organizations and found that the groups diverged on several key applications. For Analytical Innovators, the No. 1 use of analytics is to make real-time decisions. For other groups, the top answer was reducing costs. The next top use of analytics among Analytical Innovators is increasing customer understanding, followed by accelerating the development of new products. (See Figure 4: Analytical Innovators Use Analytics Differently Than Other Companies.)
Figure 4: Analytical Innovators Use Analytics Differently Than Other Companies
Sam Hamilton, vice president of data at PayPal, describes how analytics has influenced that company’s real-time decision making:
We have gone from report creation that takes weeks or months to deliver, to self-service, real-time data analysis. And we have gone from data analysis done by a small group of analysts to data-driven decisions throughout PayPal, done by most of the staff. All of this has progressively shrunk the latency of time to value of data.
In our interviews, we asked executives from companies that had many of the earmarks of Analytical Innovators how analytics was influencing their product development life cycle. The comments of eBay’s Neel Sundaresan were typical:
Increasingly (Internet-based) products are getting improved and improvised as they get used. As these products get used at scale, they generate a lot of user behavioral data. This provides the opportunity to enhance these products as users use them and create analytics-driven learning products.
Think about the product life cycles now and those from a few years ago. Before you would probably have a product release every year, every two years, and you’re waiting for the next revision to be released with enhancements, whereas now it’s just happening all the time. Releases? There is no well-defined product release.
Use More of Their Own Data Analytical Innovators use more of their data than other companies. They are nearly three times more likely to say they use a great deal or all of their data than Analytically Challenged organizations do, which are the least effective at using analytics for competitive advantage and innovation. More generally, we saw a strong correlation between how much a given company uses analytics to create competitive advantage and advance innovation, and how much of their data that company uses. (See Figure 5: Analytical Innovators Use More of the Data They Collect.)
Figure 5: Analytical Innovators Use More of the Data They Collect
LinkedIn is among the few companies that utilizes virtually all of its data. Every web request the company gets generates a transaction, and every transaction has some information and value associated with it, according to Deepak Agarwal, LinkedIn’s director of relevance science:
While carefully respecting the privacy of our LinkedIn members’ data, every single bit of information is eventually used. The raw data gets transformed in very complex ways, allowing for members’ data to remain private and anonymized. There are many different analysts and data scientists who analyze this data, create different groupings of the data, create different aggregates of the data, look at different kinds of numbers on different user subpopulations and then glean insights from them. That’s what ultimately goes into improving the relevance of our products.
More Effective Throughout the Information Value Chain Analytical Innovators are also more effective than other companies at each step of the information value chain. (See Figure 6: Effectiveness Across the Information Value Chain.) Compared to Analytically Challenged organizations, Analytical Innovators are more than twice as effective capturing information, nearly three times as effective at analyzing information and three times as effective at using insights to guide strategy.
Figure 6: Effectiveness Across the Information Value Chain
Beyond the basics of capturing and analyzing information, Analytical Innovators are much more likely to support their analytics activities with an integrated approach to information management that disseminates insights to customer-facing employees and to partners and suppliers. Analytical Innovators bolster their efforts to share knowledge and insights through champions who promote best practices. And they are much more likely than other groups to have these key supports in place. (See Figure 7: Analytical Innovators Have More Supports for Analytics.)
Figure 7: Analytical Innovators Have More Supports for Analytics
Outcomes: Power Shifts to Those with Insight
One distinguishing characteristic of Analytical Innovators is also a compelling theme that emerged during our research: Analytical Innovators report a power shift in their organization because of their use of analytics. This is a significant finding, in that power shifts can be disruptive. They often call into question experience and intuition that managers and employees have built up over years. We found that the more an organization uses analytics to build competitive advantage and to innovate, the more likely it is to say analytics has shifted its power dynamics.
Our survey revealed that Analytical Innovators “strongly agree” or “somewhat agree” four times more than Analytically Challenged organizations that analytics has shifted the power structure within their organizations. (See Figure 8: Analytics Shifts the Power Structure. )
Figure 8: Analytics Can Shift the Power Structure
That power shift can take a number of forms. A C-suite champion may give new analytics talent the power to innovate. Or analytics and analysis may start to influence investment decisions, shifting power from one group or executive to another. For example, at Neiman Marcus, analytics was once consumed exclusively by midlevel managers. Now, with consistent project successes, analytics outcomes are regularly reported to the board and senior executives. According to Jeff Rosenfeld, vice president of customer insight and analytics at Neiman Marcus, this has created a shift in the all-important funding decision process:
Having a culture, which has evolved over the last couple of years, based more on data, has caused us to make smarter decisions. No question. There is a long list of examples of changes we’ve made to the website, or customer experience, or changes we’ve made to promotions that were based on rigorous analytics and tests to understand what’s most profitable for the business. How we choose to allocate our marketing dollars has shifted by substantial dollar figures, based on analytics.
Those who have control over data, and the ability to analyze that data, move to the forefront in the organization — in fact, it is suddenly very cool to be the geek. (Researchers Tom Davenport and D. J. Patil peg data scientists as having, “The Sexiest Job of the 21st Century.”)16
Chief marketing officers are among those who are benefitting from data analytics. In a 2012 survey of 100 CMOs,17 over 89% say that social data has influenced their decisions. The authors of the study offered a particularly intriguing conclusion: CMOs are using social data to drive discussion in the C-suite and thereby elevate themselves “as owners of the brand-consumer relationship.” This suggests that CMOs are using social data to enhance their influence and improve their personal brand within the organization. For CMOs, social data is not merely about insight; it is a new source of legitimacy in the C-suite.
Many executives focus on the question of how to get more value from their data. But for some companies — perhaps even many companies — this approach emphasizes the wrong issue. It misses a key part of the relationship between data and value: the connection between how much data is valued and how much value data can deliver.
Indeed, the more data is valued by an organization, the more value it can usually deliver. This is not merely about making investments in analytics (which can go wrong), but about conferring power on analytics and creating a culture in which analytics is part of how decisions get made. At Wells Fargo Company, this means that the organization is relying more on analytics to make decisions, a significant shift, according to Pascal Hoffmann, former vice president of digital banking strategy:
When you look at the decision making process, it has become more quantitative and more scientific than it used to be a few years back. It’s a slow transition triggered by smart people along the way, where you have existing processes and established thinking. Some people want to challenge the status quo and look harder at the evidence on how the decisions are made, and what decisions are made. They come up with evidence that shows that there is a better way to go about making decisions; that there is a better decision than the one that was made in the past. And because they have the evidence and they can build a case with hard science and data, they get paid attention to.
Senior management support is almost always critical to developing the kind of data-driven culture that embraces evidence-based ideas that run counter to the status quo. At casino giant Caesars Entertainment, for example, analytics is being driven through the organization by a team of analytics missionaries who are being integrated into senior management teams at the property level. This has been a difficult change in management process that has required support from corporate executives at headquarters.
Summing up the Analytical Innovators
Analytical Innovators exist across industries, vary in size and differ in how much data they collect. However, they share several important characteristics. Most share a belief that data is a core asset that can be used to enhance operations, customer service, marketing and strategy. Across the information value chain, they are more effective with their analytics than other groups. They use this effectiveness to act more quickly: to deliver faster results, to make real-time decisions and to accelerate the development of products or services. They also tend to have strong management support for analytics-based decision making, which undoubtedly supports (or reflects) a greater willingness to accept data-driven ideas that challenge the status quo. In turn, this creates more opportunity for managers with valuable ideas to advocate for their organization’s success — and to enhance their own career prospects.