Today I continue my exploration of big data in a best practices Foreign Corrupt Practices Act (FCPA) compliance program. Yesterday, I considered how you might use big data in a best practices compliance program. Today I want to explore how visualization of data can assist you in a wide variety of ways in both the detect and prevent prongs of your compliance program. The topic of this series of blogs is based upon an eBook, entitled “Planning for Big Data – A CIO’s Handbook to the Changing Data Landscape”, by the O’Reilly Radar Team, with a series of authors each contributing a chapter. Today I will focus on a chapter by Julie Steele, entitled “A Picture is Worth a 1000 Rows”.
Joe Oringel, co-founder of Visual Risk IQ, is often heard saying, there is a reason his company is named Visual Risk IQ. It is because his company specializes in visualizing the results of the transactions they monitor or analyze. Steele asks “How are you going to make sense of all that information efficiently so you can make a good decision?” She believes “Data Visualization is an important answer to that question.” Put another way, visualization allows you to see the data.
Recognizing that not all visualizations are helpful, Steele writes, “The best data visualizations are ones that expose something new about the underlying patterns and relationships contained within the data. Understanding those relationships – and so being able to observe them – is key to good decision-making. The Periodic Table is a classic testament to the potential of visualization to reveal hidden relationships in even small data sets. One look at the table, and chemists and middle school students alike grasp the way atoms arrange themselves in groups: alkali metals, noble gasses, halogens.” All of this means “If visualization done right can reveal so much in even a small data set like this, imagine what it can reveal within terabytes or petabytes of information.”
Steele says there an “important distinction lies between visualization for exploring and visualization for explaining.” She explains that while visualization for exploring can be imprecise, it is “useful when you’re not exactly sure what the data has to tell you, and you’re trying to get a sense of the relationships and patterns contained within it for the first time. It may take a while to figure out how to approach or clean the data, and which dimensions to include. Therefore, visualization for exploring is best done in such a way that it can be iterated quickly and experimented upon, so that you can find the signal within the noise.” She concludes by noting, “Software and automation are your friends here.”
Steele believes that “Visualization for explaining is best when it is clean.” This is because paring down information to its simplest form, by removing as much noise as is as possible, will allow the “efficiency with which a decision maker can understand” the data. She notes this is the preferred approach “to take once you understand what the data is telling you, and you want to communicate that to someone else.” Moreover, “Visualization for explaining also includes infographics and other categories of hand-drawn or custom made images.”
Incumbent throughout these blogs posts on big data is embedded the concept that the customer base of any company’s compliance function is its employee base. So if you consider that “Many kinds of data visualization, from complex interactive or animated graphs to brightly-colored infographics, can help” to explain to your employee base many of the key issues around compliance. This can allow your employees to better understand your company’s values, the expectations under your Code of Conduct and compliance program and their obligations going forward. It can also be a useful teaching tool to help prevent inadvertent actions that may become more nefarious later. Steele believes that “As Big Data becomes bigger, and more companies deal with complex data sets with dozens of variables, data visualization will become even more important.”
Here is another area where the compliance function can draw upon other talents in a company as Steele suggests you should work with an in-house designer or better yet a team of designers to help you put together visualizations. This is because “Visualization for explaining works best when someone who understands not only the data itself, but also the principles of design and visual communication, tailors the graph or chart to the message.”
Such a designer can work as your translator “Since data visualization is like a foreign language, in the same way, hire an experienced designer for important jobs where precision matters. If you’re making the kinds of decisions in which your customer, product, or profit hangs in the balance, you can’t afford to base those decisions on incomplete or misleading representations of the knowledge your company holds.”
In the concluding chapter in the eBook, entitled “The Future of Big Data”, Edd Dumbill noted, “Visualization fulfills two purposes in a data workflow: explanation and exploration. While business people might think of a visualization as the end result, data scientists also use visualization as a way of looking for questions to ask and discovering new features of a dataset. If becoming a data-driven organization is about fostering a better feel for data among all employees, visualization plays a vital role in delivering data manipulation abilities to those without direct programming or statistical skills.”
The ability to put disparate pieces together in a way that company employees, from top management to the business development person in the AsiaPacific region, understand and see the connections is an important method that should be used by any Chief Compliance Officer (CCO) or compliance practitioner. Consider such analysis as buying patterns of foreign governments in the context of charitable donations. In both the Schering-Plough and Eli Lilly Securities and Exchange Commission (SEC) FCPA enforcement actions, the SEC simply put in a table showing the date of donation to the decision maker’s personal charity and the date of obtaining or retaining business by the company in question. Imagine if the CCO had had that data visually displayed, it might have detected an issue that could have then been prevented before it became a full-blown FCPA violation. It might have led to remediation. It might also lead to additional investigation to see if the charitable donation met the company’s internal requirements or if any exceptions were granted and if so were they properly vetted.
I hope that this series on big data has given you some ideas on what might be available to you, hiding in plain sight, in your own company data.
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