It�s Time to Put Data Mastery in the Driver�s Seat
Data mastery, which has been a priority for insurance companies for almost a decade now, is commonly pursued in terms of leveraging internal and external data to gain business insight into increased revenue, decreased expenses, or improved ease of doing business. In spite of this focus, most insurers still struggle with creating a mature enterprise business intelligence (BI) and analytics program.
Why? Many insurers have internal deficiencies in executive ownership of data-related initiatives, enterprise data strategies, and governance. Further, knowledgeable and trained resources are hard to come by, and easy access to the requisite data is typically not. These factors have led to bad alignment between data programs and business goals, which is complicated by a lack of good, accurate enterprise data, outdated and unused reports, and, basically, a lack of trust in the data itself.
Insurers understand the business value of data to a certain degree, but most have yet to understand the full implication of getting the most value from an enterprise data mastery program. To put data mastery in the driver’s seat requires most insurers to turn their whole approach upside down. The traditional approach is to put as much data into a data warehouse as possible, and then run reports and analyses that have been around since the company began. This would be analogous to an insurer creating every product imaginable and then seeing which ones were most profitable -- but still keeping all the non-profitable programs because “we always did it that way.” No one would consider such an approach to product development, but, strangely, it is completely acceptable for data mastery initiatives.
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Companies need to primarily focus their attention on identifying which reports and analyses will best help achieve strategic business goals, which are most likely closely aligned with the purpose of data mastery stated above. Not all reports and data are created equal, so it stands to reason that not all data should receive the same treatment. Data that feeds into helping an insurer understand operational performance and areas for improvement -- product performance, claims fraud, and claims leakage, for example -- is far more important than data used for reports not required for decision-making. Since not all data is created equal or used for equally important purposes, not all data needs to be of the highest quality or managed at the same level. This simple fact was the bane of most large data mastery and data management initiatives that failed during the 2000s.
Insurers that have garnered the biggest benefits from data mastery programs are those that quickly realized the necessity for current, accurate reports and analyses to enable decisions on a real-time and daily basis. While admittedly few and far between, insurers that can provide the right data to the right people at the right time are far ahead of the competition. Most insurers, in fact, struggle with enterprise data that is weeks or months old, untrusted, and difficult to access. Due to these hurdles, as well as the large cultural data fiefdoms that have traditionally existed, insurers have long thirsted for better information but settled for outdated data.
This is now beginning to change. Technology vendors are providing more integrated solutions with mature insurance data models, out-of-the-box reports and analyses relevant to the business, and easy-to-create reports and analyses. Most importantly, they are creating strong, automated governance models. Regardless of how easy it is to interact with the data, if an insurer cannot trust it or understand its true semantics, it is the old garbage-in/garbage-out principle.
The biggest hurdle for most insurers is internal culture. In other words, insurers are their own worst enemies. To overcome this simple truth, insurers must break down the data fiefdoms that have long permeated the insurance industry and create a culture in which the enterprise owns and controls the data, not the departments that generate it. There must be enterprise ownership of data mastery programs to enable and create a thriving mature data mastery culture, thereby allowing a carrier to achieve the highest business value from data mastery investments.
— Ben Moreland is the senior business architect for Innovation Group. He can be reached for further comment or information via email at [email protected].
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