Sergey Nivens - Fotolia


Compliance records provide fuel for big data analytics

Well-designed compliance records management can generate new business revenue for businesses by feeding big data analytics engines valuable data.

In nearly every business, in virtually every global region, compliance is considered an economic burden on a company's ability to create and deliver profits to the company. Compliance becomes even more expensive as companies expand into international trade and as developing economies continue to evolve their own regulatory systems to more closely resemble those of developed nations.

Quite simply, c-level executives resist making investments in compliance records management until the risk of fines, sanctions and reputational loss becomes unacceptable. Even then, the spending is restricted to the bare minimum considered necessary to satisfy regulators. The result is that compliance programs end up focusing on low-cost initiatives, such as training and cultural improvement exercises, rather than building and operating metric-intensive, continuous monitoring of performance management.

Of course, those management practices have compelling value for managing the production of goods and services, but their use in compliance is anecdotal at best. However, compliance executives are beginning to realize that well-designed regulatory management programs that connect to, and integrate with, progressive information governance programs have the ability to generate new revenues.

Discovering the analytic value of compliance

The key is to engineer compliance records so they are valuable to big data analytics engines. When done correctly, those records become a new product for the company that is capable of producing income that will offset a company's compliance expenses and perhaps even generate a positive return on investment. The essential strategy is to move the compliance function toward the front of the design lifecycle through which the business information assets and records are developed. Here are the initial key steps:

  • Recognize that the compliance records created and maintained in the ordinary course of business have the same value to the company as to the regulators: The information serves as documentation of the process controls, business practices and business performance.
  • As business becomes increasingly digitized, information governance programs and regulators are adopting many of the same standards and controls for assuring that records are created, preserved and accessible with consistent processes. Those processes are designed to protect the authenticity and integrity of the records, for the benefit of both internal operations and regulatory agencies. Areas of substantial overlap include information security, identity management, systems access controls and storage practices.
  • Connecting compliance and information governance enables those overlaps to be identified early in the design of new information systems and the ongoing management of the resulting records and data sets. When each business team arrives at the design table with a portfolio of their respective requirements, the resulting systems and records are improved. Conflicts between the rulesets can be flagged earlier, and every dollar spent on the new IT has a better chance of producing records that substantiate the compliance obligations of the company.

In other words, compliance is moved from being an afterthought into being part of the design process. This simple shift in how digital assets are designed can produce real savings in the operating costs associated with compliance. Compliance officers will not be required to veto designs or add additional requirements at the end of the process, both a major cause of the unfavorable expenses.

Access information markets for big data analytics

Analytics tools ingest information that allows massive volumes of comparable information to be evaluated so unexpected patterns, trends or relationships can be recognized. More and more, big data analysis firms benefit by collecting data sets from multiple players in an industry and building cross-industry analyses. They will pay for the data, and will often negotiate bartered arrangements in which data contributors receive back the industry analyses at discounted rates.

Healthcare, pharmaceuticals, automotive manufacturing, automated control systems (such as railroad trains without operating conductors), all benefit from these analyses. But the analyses are valid only if the inbound data can be mashed up together. Nonconforming data simply does not effectively fuel the process. The analytics engines evaluate inbound data and if the data does not conform, the data is embargoed or quarantined.

For many compliance executives frustrated by their quest for adequate funding, the revenue potential from well-governed performance records are potentially enormous.

As a result, it is simply less valuable. This is where information governance, integrated with compliance, can make such a difference. Well-designed compliance records have greater value to big data analytics because the rules that analytics engines rely on to evaluate inbound data are comparable, and often identical, to the rules being adopted for information governance and regulatory oversight. Connecting compliance to information governance enables the corporate data assets to produce new revenues by fueling big data analytics. The following are three realistic scenarios. In each case, the new revenues result from compliance and information governance working together:

  • A health fitness company, collecting personal fitness records subject to privacy and security regulations, creates revenue by producing analytic outputs to medical insurers, healthcare providers, fitness coaches, and even designers of health equipment.
  • A railroad transportation company, collecting performance, maintenance, and safety repair data subject to national transportation and environmental protection rules, creates revenues by producing analytic outputs that assist replacement part manufacturers, urban planners, and the designers of self-driving locomotives (yes, these really do exist).
  • A manufacturer of smart automobiles tracks and collects movement data, performance information, and driver behavior (music preferences, texting while driving, frequency of stops), all subject to privacy and federal transportation rules, and creates revenues by contributing to industry-wide analytics sold to automotive insurance companies, retailers (seeking to push coupons and other promotions to the driver), entertainment distributors, and regulators evaluating new rules on motor safety.

The next steps

For many compliance executives frustrated by their quest for adequate funding, the revenue potential from well-governed performance records are potentially enormous. The next steps are to investigate emerging big data analytics, research the economics and then prioritize how the existing compliance records can be retooled to immediately generate new revenues. Then, conduct a pilot study to find out if your existing records have value and, if so, how much. Learn whether there is a different value if the records reflected greater design quality.

Evaluate the cost of retrofitting that quality into your systems and, of course, the projected future revenues.

A successful outcome will set the stage for more strategic planning and improve integration of compliance requirements into all future IT projects. Businesses are inherently driven by the financial metrics of improved efficiency and controls. These are also the essential outcomes of big data analytics. Positioning your compliance records to be fuel for big data will inevitably create competitive advantage in future cycles of innovation.

Next Steps

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