Dave Frankel was recently boarding an American Airlines flight in London when he heard a song come over the intercom. Although it was a Muzak version of the tune, he recognized it as one by a group he liked.
When he reached his seat, he tweeted his appreciation of the airline’s interesting choice of music. “And then I got a response on Twitter from American Airlines in a second saying, ‘I’m glad you liked it,’” Frankel, the president of EDGAR online, says. (He has since forgotten the name of the song.)
To be sure, he got a less positive answer when he tweeted back a request for a seat upgrade. Though the request was playful, the airline might well have considered compensating him, since it had received something valuable in return.
Frankel tells the story to demonstrate the second-by-second, almost exponential growth of potentially actionable business information under the rubric of Big Data — not only via Twitter, but also Facebook, Amazon.com, Yahoo and similar sites, as well as email. He marvels that “just by sitting on a tarmac and tweeting something,” he had provided American Airlines with data it could potentially use to improve its marketing and customer services. Other fliers, after all, might like such songs, and the company might subtly help boost its revenues by playing them more frequently.
Such opportunities are generated by the growing ability of companies to aggregate and draw correlations from huge amounts of unstructured data. Accompanying them, however, is the threat to corporations and accounting professionals of falling behind. “If companies don’t wake up and understand that this isn’t going away, that it’s only going to get bigger, then they’re going to put themselves at risk,” Frankel warns, adding that “the accountants and [financial] reporting managers are still not there yet.”
Indeed, outside of accountants and finance executives who actually work for companies in businesses that provide or deliver data products and services, few such professionals have reportedly been able to catch the wave. A big reason may be that those involved with internal and external financial reporting are limited, by training and inclination, to working with structured data – the kind that can fit readily into tables, Excel spreadsheets and, ultimately, financial statements.
The problem for accountants is that the future belongs to unstructured data — the kind that can be dug out of tweets like Frankel’s, as well as videos, photographs and the vast amounts of text floating free on the Internet. “Unstructured data represent the largest proportion of existing data and the greatest opportunity for exploiting Big Data,” according to a recent editorial in the Journal of Information Systems (published by the American Accounting Association).
Such unstructured data includes the plain text found in the Management’s Discussion and Analysis (MD&A) sections of company 10-Qs and 10-Ks, and in corporate press releases and interviews with corporate executives, the authors of the editorial note.
Valuable as such data may be, they’re outside the grasp of most accountants and finance executives. Thus, while traditional corporate accounting and auditing “are essential for economic production activities and will continue to be performed,” the authors write, “current accounting and auditing methods are in danger of becoming anachronistic”
in the face of an economy increasingly being driven by Big Data.
In short, reality is swiftly outpacing the ability of accountants to gauge it. What needs to happen for them to start to catch up?
To some, the future evoked by the editorial’s writers might appear dark. Referring to employees and management as “nodes,” they suggest that accountants “must view the possibilities associated with Big Data, of knowing much about a corporation, including knowing a substantive amount about who works in a corporation.”
Granting that many questions still need to be answered about the propriety of surveillance of employees, they wonder if such employee metrics as time on the Internet, sites visited, telephone calls made and geographical location should be created and reported.
Yet although “it seems objectionable and invasive that a stranger could know virtually everything about another person, knowing as much as possible about a corporation is much more palatable,” they write, noting that employees have less privacy protection than exists for individuals outside a corporate setting. Speech, documents and email generated during work and via corporate resources may be fair game for the Big Data gathering efforts of corporate accountants.
Swimming in Big Data
Yet before diving into such difficult waters, finance and accounting professionals might do better to learn from peers who actually work in the world of data analytics. While Nina Tan, CFO of Trax Technology Solutions, for example, is involved in the valuation of her company’s data assets, she also uses unstructured data in more traditional accounting and finance functions.
At Trax, a Singapore-based firm that provides an image-recognition mobile application that gathers data from photos taken of shelves at retail stores, Tan is “moving finance from a reporting-centric to analytic-centric financial function,” she wrote in a recent email in response to questions from CFO.
Thus, Tan pores over data to unearth the causes behind the company’s sales, costs and profits and to create budgets and provide input to rolling forecasts. Via analytics, Tan, a CPA, gets an overview of the data that drive revenues and operating and sales expenses, including when, where and by which salespeople different products are sold. When she needs to, she can also drill down into more granular information underlying financial statement line items.
Beyond such fairly traditional “dashboard” type information, Tan is working with other senior managers to set key performance indicators (KPIs) for use in aligning employee motivations with company strategy. To confirm that the KPIs are leading the company where it wants to go, the executives will analyze the correlations between the success of certain salespeople and the performance indicators.
In one recent example, to find out whether the firm was using its people wisely, Tan used data analytics to measure why Trax’s website experienced certain peak and trough periods. She first found correlations among traffic, time of day and location. With Australia about three hours later than Asia, the firm’s site traffic builds to a peak in Asia’s morning and Australia’s afternoon. The trough occurs during Asia’s afternoon, as Australia knocks off from work.
The question she was attempting to answer was: “Does it makes sense to hire additional headcount to handle the peak, but leave them idle during the trough?” Employing what she calls her “cause and effect analysis” of time zones and traffic data, respectively, she “suggested a practical solution that requires only use of our existing headcount. Basically, it only requires overlapping of two different shifts during the peak hours.” The analysis enabled Trax to trim its headcount costs and capital spending, she said.
From her perch in a firm that uses data analytics on day-to-day basis, Tan waxes bullish on the ability of the accounting and finance functions to expand their roles to encompass huge amounts of unstructured data. “In three to five years’ time, I see the finance function as a strong, formidable strategic partner to operations and sales. Finance is the natural gatekeeper of data, as information normally flows through the function,” she says.
Accountants still need to become more familiar with statistics and decision science in order to grasp how Big Data can enhance their skills and vice versa, she thinks. Ultimately, however, they can play a part in enabling companies “to separate the wheat from the chaff and focus on the information that counts — not on the information overload,” Tan adds.