I’ve written before on the importance of people sharing data as broadly as possible in an organization. A company may have hundreds, or even thousands, of people with “analyst” in their job titles, but if you keep access to data centralized, you’re also keeping the capacity for innovation centralized — and limited.
At the same time, simply opening up the data floodgates to your workforce, without a solid strategy, will create more confusion than success. The better approach is to package up the complexity into accessible tools — analytical applications — to leverage the most valuable asset of all in your workforce: curiosity. In other words, business analysts need an environment to follow that spark of curiosity on data issues (“Hmm, there’s a spike over here … an aberration over there. Let’s experiment a little to figure out why.) without having to know all the complex processes happening underneath the application.
Expanding Insight Across the Organization
Such an “Analytical Application Platform” — as the Northwestern Kellogg School of Management’s Mohan Sawhney and I call it in our Sentient Enterprise model for big data agility — is a self-serve, on-demand environment for users to follow their hunches. Put more pragmatically, as the chief data officer at a major international bank recently told me, analytical apps help “people to stop submitting tickets and get them to start thinking more analytically on their own. A business manager needs to understand the levers to pull, but not necessarily know all the engineering.”
This executive is absolutely right. And in the process of building analytical apps, we’re not just expanding data access — we’re also expanding the company’s seedbed for analytic insight and value. When designed and implemented correctly, analytic applications can foster curiosity in the user community and provide a framework for that curiosity to lead to scalable solutions.
This framework holds up even in the face of tough and demanding business challenges. I know of cases where analytical applications have taken CRM sentiment data — not all of it positive — to fuel analytic solutions allowing companies to anticipate consumer concerns more proactively and thereby boost overall customer satisfaction. In fact, critical business challenges are often where analytics leaders find valuable internal partners — lighthouse customers, as I’ve come to call them — who welcome the assistance to create solutions and, ultimately, showcase for the rest of the company the value of agile analytics.
Supporting Analytic Success
Keep in mind that, just as we shouldn’t simply open up the data floodgates to your company without a strategy, neither should we simply crank out analytical apps without some support systems in place. While it’s important to keep bureaucracy to a minimum, analytical apps do need to operate within a certain organizational framework.
The banking executive I mentioned, for instance, has a system for “insight governance.” This involves deploying relationship managers to gauge analytics needs within the organization and coordinate quick development of the apps, as well as super users within the various company divisions to help ensure ongoing and self-service functioning of those apps. Advanced data scientists are always available to help when roadblocks or deeper analytic challenges arise; the beauty of the system is the workload for these experts is naturally skewed toward these tougher challenges, where they’re needed most!
You’ll likely find that some departments and job functions may be more receptive than others: Mobile and online divisions, for instance, tend to be familiar already with the value of data. Marketing departments also typically lend themselves to analytic solutions to help with intensive, time-boxed product campaigns that often have clear measures of success. Adoption might be a bit more difficult, however, for an HR, legal or physical asset management department. But even in these areas, the value of analytics becomes clear once you demonstrate, for example, digital analysis of server usage shows how to optimize load more efficiently and save the company money.
By now, it’s probably clear that fostering both access and curiosity around data has to do not just with technology, but also corporate culture. Fortunately, the insight governance measures I mentioned earlier can help people share expertise more easily within the company. Another important way to promote culture is to recruit talent who are data-literate from their previous training or work experience and already “get” the value of analytics. All of these steps, together with cutting-edge technology, contribute to an environment of analytic curiosity that can help any given insight grow from interesting finding to a significant trend to that big cost-saving or profit-generating solution!
For more on the Sentient Enterprise, watch my video overview on our website.
Mr. Ratzesberger has a proven track record in executive management, as well as 20+ years of experience in analytics, large data processing and software engineering.
Oliver’s journey started with Teradata as a customer, driving innovation on its scalable technology base. His vision of how the technology could be applied to solve complex business problems led to him joining the company. At Teradata, he has been the architect of the strategy and roadmap, aimed at transformation. Under Oliver’s leadership, the company has challenged itself to become a cloud enabled, subscription business with a new flagship product. Teradata’s integrated analytical platform is the fastest growing product in its history, achieving record adoption.
During Oliver’s tenure at Teradata he has held the roles of Chief Operating Officer and Chief Product Officer, overseeing various business units, including go-to-market, product, services and marketing. Prior to Teradata, Oliver worked for both Fortune 500 and early-stage companies, holding positions of increasing responsibility in technology and software development, including leading the expansion of analytics during the early days of eBay.
A pragmatic visionary, Oliver frequently speaks and writes about leveraging data and analytics to improve business outcomes. His book with co-author Professor Mohanbir Sawhney, “The Sentient Enterprise: The Evolution of Decision Making,” was published in 2017 and was named to the Wall Street Journal Best Seller List. Oliver’s vision of the Sentient Enterprise is recognized by customers, analysts and partners as a leading model for bringing agility and analytic power to enterprises operating in a digital world.
Oliver is a graduate of Harvard Business School’s Advanced Management Program and earned his engineering degree in Electronics and Telecommunications from HTL Steyr in Austria.
He lives in San Diego with his wife and two daughters.
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