If you read the newspaper, there's a good chance you've heard more about data recently than in previous years. Buzz-word
Vol. V No. 5
IN THE SPOTLIGHT Data Management: The Unsung Hero of Operational Risk Management By Rich Murnane
If you read the newspaper, there’s a good chance you’ve heard more about data recently than in previous years. Buzz-words like “big data” might seem like techno-babble, but the reality is that data has a significant impact across all operations. Operational Risk Management (ORM) is one area in particular where organizations can significantly benefit from mature data management practices and some of these new (or rebranded) technologies. ORM can be thought of as the practices and procedures you and your organization have in place to understand, plan for, and make decisions about the risks associated with doing day-to-day business. Most people think of risk in terms of financial risk; ORM goes further and includes things like physical security and duty of care for employees. Organizations with good ORM practices think in terms of “defense,” and know how do to identify and assess risks, make good decisions, and implement policies/procedures around the risks and hazards of doing business. Really successful and mature ORM practices allow organizations to not only think in terms of defense, but think in terms of offense as well. An example of this would be an organization that manages risks so well that it is able to do business in new and emerging markets. In the past, these markets may never have been considered, but now, because of a mature ORM program, this organization can enter - and achieve a significant competitive advantage as a result. So what does data have to do with managing operational risk? It’s simple, if you don’t have quality data about your critical assets, you have no way to confidently understand the impact of events on your operations; in essence, you have no way to gauge your exposure. And without knowing your exposure, how can you build successful risk management practices and procedures? Take as an example this simple hypothetical. Imagine you work for a large multi-national company and something bad happens in Spain. Here’s a (bare minimum) list of questions you may need to answer quickly and reliably: • Do you have employees on travel in Spain today? • Do you have expatriates there? • Do you know if travelers or expats have dependents with them? • Do you still have that facility open in Madrid or did it close when the business was shifted to Italy? • Does your major supplier still have their primary manufacturing plant in Madrid or did they move it to Asia? • Is the total number of people you need to contact in Spain 10, 12, or 14 people?
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Let’s just focus on the last question. If you’re concerned about the number of travelers in Spain today, and the right number is 12, and you think it’s 10, then you’ve just left two people from your organization exposed to risks during a potentially dangerous time. If you think it’s 14, now you might spend precious time and resources searching for those last two people, who don’t exist. That is time and resources that should have been focused elsewhere; time and resources that need not have been spent had the organization implemented mature data management practices prior to the event. For most organizations, investing time and resources on maturing data management isn’t the most exciting way to spend limited resources. But believe it or not, there can be major returns on these kinds of investments. Plus, the concepts behind mature data management are relatively straightforward, even for non-experts. In fact, these practices typically revolve around one big idea: data quality. Data quality practices include ensuring that data is correct, complete, and timely. At iJET we spend a significant amount of time helping clients transform previously unusable data into actionable information by doing just that. We have implemented a multiyear data quality program, using data profiling and data monitoring to drive results for major clients with mountains of
travel data. We have also developed a Master Database solution, allowing multiple sources to be mined and compiled into a single data repository for a holistic view. By profiling client data to determine correctness, we are able to continually monitor for data quality issues. When necessary, we deploy technology solutions to correct data quality issues and then circle back with profiling and monitoring to ensure the issues do not happen again. The result is a mature data management practice
that ensures data used in the iJET Worldcue platform is as correct as possible. This generates significant savings for clients, and allows them to implement strategies they would otherwise have avoided. So, is data management the “unsung hero” of ORM? I think there’s an argument to be made there, because if you want to have confidence that you are making the best decisions in your ORM program, you better have good data.
The Monthly Intelligence Forecast is produced by iJET® Intelligent Risk Systems. iJET is a leading provider of global intelligence and business resiliency services, helping multinational corporations and government organizations monitor, protect against and respond to global threats. Integrating world-class open source intelligence with patented technology, iJET’s award-winning Worldcue® solutions help clients monitor and assess global threats relative to their key people, facilities and supply chain assets; automatically track and communicate with travelers and expatriates; and deploy emergency response services throughout the world at a moment’s notice. Providing a unified view of threats to assets, iJET enables clients to mitigate risks, reduce corporate liability and prepare for and respond to crises. For more information on iJET solutions call 410-573-3860.
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Rich Murnane is iJET’s Director of Enterprise Data. As an active member of the data management community, Rich blogs about data management and is a member of the DataFlux Client Advisory Board. He holds a Bachelor of Science from Salisbury University with concentrations in computer science and mathematics.
