Part 1 in a two-part series.
While many finance groups are still behind in implementing Big Data projects, finance executives and experts argue that the tide is turning. At organizations like Providence Health & Services and Payless ShoeSource, Big Data is already making a big difference.
In conducting research for an upcoming FP&A Guide to be published April 6, 2016, by the Association for Financial Professionals (AFP), How Finance Can Get Ready for Big Data, AFP found that many finance departments are considering how Big Data projects can help them support better business decisions. The use of Big Data in finance is not a question of whether, but of when.
Certainly, there are many challenges ahead; a lot of financial planning and analysis (FP&A) teams are still struggling to get their heads around larger sets of small data and continue to rely on spreadsheets. Even the term “Big Data” can intimidate some executives. There are also real issues around data integrity and governance, the adoption of the right integration and analytics tools, and a necessary shift in FP&A’s mindset and skill set.
Nevertheless, Big Data has the potential to transform the role of finance. “It’s a lot easier to access all this new information,” said Larry Maisel, president of DecisionVu and a former Columbia University professor. “For organizations, [Big Data] presents both an opportunity and a challenge, particularly for the FP&A function,” he said. “The challenge today is not how to access it, but what information to access and how to use it productively to gain insight into trends and inflection points.”
Big Data in action
Providence Health & Services is going live with a Big Data project in April 2016. Michael Trzupek, vice president of systems finance, has been trying to pull together data to better serve and understand the hospital system communities. The project, led by the FP&A team, is designed not to look just at transactional data (number of admissions, visits, and so on), but also how the health system is evolving over time. FP&A is driving the systems and organizational change. At the same time, the company is looking at benchmarking similar activities across locations and at standard deviations in performance. The new system will link up the data into both forecasting and long-range planning.
Big Data, once it’s refined, allows companies to know where to invest and what business actions to take to help optimize processes. According to Trzupek, those who excel at it will have better advice for IT, marketing, and operations regarding what decisions to make to achieve desired outcomes. He believes finance should be the owner of Big Data financial projects and define the requirements and desired outcomes, while IT figures out how to deliver the technology to deliver those outcomes.
At Payless ShoeSource, CFO Michael Schwindle focuses his team’s time on supporting the company across the entire enterprise. He sees data and formalized analysis as the “collective mind” of the organization. As a company gets larger and more complex, the need to synthesize and simplify grows. Finance’s modern challenge is to deliver concise meaning from mountains of data to support decisions. At Payless, what FP&A strives to understand is what company actions drove the customer across the threshold of a decision. The data surrounding these different intersections of customers’ activity is huge and requires that Payless look at it at the individual customer level vs. the tyranny of averages. Instead of taking a single number and assuming that everyone is the same, Big Data allows FP&A to look at real patterns down to each customer level to arrive at a more precise conclusion regarding drivers of behaviors and behavioral patterns.
The key is to move beyond correlation to causality. In one recent sales campaign, for example, a first look at high-level data showed that purchases of sale items and regular-priced items both increased. The first assumption was that the customers who came in to pick up sale items also bought regular-priced items. After looking closely at customer and transaction-level data, however, it turned out that different customer groups bought sale items than the ones who paid regular price. That distinction will affect decisions about future sales and marketing initiatives. Schwindle’s personal mission is to take all that rich data and use it to inform all parts of the organization – marketing, merchandising, real estate, and supply chain.
A new role for FP&A
No matter what term one uses, Big Data or predictive analytics, companies like Providence and Payless demonstrate that finance is already adding value by implementing Big Data projects. To do so, according to Philip Peck, VP of financial transformation at Peloton, “FP&A needs to retool so they can thrive in this new era. While it presents great challenges, it also contains phenomenal opportunities to elevate FP&A’s game and drive greater insight and become indispensable business partners.”
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For more on tapping data to drive greater value, see Algorithms: The New Means of Production.