Oracle’s Paul Sonderegger On How CFOs Can Grapple ‘With The Valuation Of Intangibles’

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As Oracle’s big data strategist, former Forrester Research analyst Paul Sonderegger is a leading proponent of the idea that big data is a source of wealth creation on par with financial capital. In his role at Oracle, Sonderegger helps organizations tap into huge reserves of data to create profitable new products and services. And he draws on these real-world experiences to influence the future direction of Oracle’s big data solutions.

In the early 2000s, Sonderegger was a principal analyst at Forrester Research. He then spent eight years as an evangelist and strategist at Endeca, the pioneer in big data and information discovery, before joining Oracle in 2011.

At a time when an increasing number of companies are realizing the value of cloud, and using evolving analytics tools, we asked Sonderegger why CFOs should embrace the concept of data capital—and how they can harness data to drive value both within and beyond the finance department.

Q. How do you define data capital?

A. First, let me say that “data capital” is not a metaphor. We’re not saying data is like gold that you can mine, or oil you can drill for. We’re saying data literally fulfills the economic definition of capital—a produced good (as opposed to a natural resource) that, in turn, is a factor of production in other profit-making goods or services.

Imagine a retailer who wants to enter a new geographic market. To do so, they need to make significant financial investments to construct new facilities, to build out the supply chain, and so on. The same principles apply when the same retailer creates a dynamic pricing algorithm. To function, that new service requires data in the same way a geographic expansion requires financial investment.

Q. Financial data has been finance leaders’ principal “raw material.” How does the rise of data expand the CFO’s purview beyond financials?

A. CFOs are already grappling with the valuation of intangible assets like brand sentiment, human capital, and customer relationships—all of which require non-financial data collection, reporting, and analysis. In fact, intangibles comprise 84% of corporate valuations on the S&P 500 index, according to intellectual property merchant bank Ocean Tomo—up from just 17% in 1975.

But now, the value of data itself is beginning to show up as a form of capital in quarterly meetings with analysts.  Cloud companies like Oracle are reporting on the number of web sessions in their cloud or the number of candidate records in their HCM cloud. We can also expect to see more traditional industries follow suit—retailers boasting about average number of data points collected per customer, usage-based auto insurers citing aggregate data collected annually, or logistics firms emphasizing the total number of package scans captured.

Q. How does the concept of data capital apply to traditional financial functions like budgeting?

A. The real world is a messy place, and no amount of data or analysis is going to deliver a perfect vision of the future. But CFOs can draw on their data capital to quickly envision and plan for multiple potential futures. This enables them to decrease the time and costs of budget planning—and react much more quickly and effectively as reality unfolds.

Q. You’ve described data capital as an “embarrassment of potential riches.” Please explain.

A. Unlike financial capital, which you can only invest in one opportunity at a time, data capital can fuel multiple analytic or algorithmic investments at once. Even when focusing on the highest-priority opportunities for cutting costs or increasing revenue, a CFO can combine a dizzying number of possible data sets to uncover new insights—and an equally large number of possible ways to act on the correlations and connections they discover.

Q. As you say, the possibilities are dizzying. How can CFOs take the lead in transforming data into a form of capital—without losing their balance?

A. CFOs are uniquely positioned to increase the productivity of traditional capital by using data capital in new ways. They possess the analytical, data-driven mindset necessary. Just as important, they have a unique purview into the breadth of the company’s operations.

However, CFOs need to both expand the technology tools at their disposal and make them simpler to use. That doesn’t mean just purchasing the latest, greatest solution on the market. They must ensure these new technologies integrate into their existing enterprise architecture. Cloud plays a big role here, but so do people. CFOs need to build data science teams to quickly create and test new hypotheses about the business.

Q. Where can CFOs begin the process?

A. The leaders are moving to cloud-based platforms that offer reporting, planning, forecasting, and analytics all in one. New approaches like robotic process automation (RPA) can further speed and automate high-volume, repetitive tasks, such as account reconciliation. This kind of platform gives you a consistent, highly available foundation of financial and operational data.

But the real magic is in letting data science teams mix and match that financial and operational data into new combinations. This will offer innovative managers the alternative perspectives on the business they’ve craved for years but couldn’t produce for themselves.

Robert Landon is a New York-based writer who has covered leading-edge business technologies for more than two decades.



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