As they tend to do, CATs highlight areas of needed improvement in our industry, and the recent winter storm across unprepared areas of the country was no exception. Observing how both carriers and IA firms managed through it left me with a singular phrase echoing in my head: master data management (MDM).
Most firms have some active effort in progress to wrangle their data. If MDM is a new concept to you, it refers to creating a uniform data structure across all systems. Have you ever had to know what the same thing is called in two different systems? With a properly implemented MDM, that goes away. Conceptually, it’s easy. In practice, it can be quite challenging. Carriers generally have a patchwork of home-grown and off-the-shelf core business systems (HR, FNOL, claims management) alongside various SaaS products. The concept of MDM came along well after many of those systems were deployed, so now it’s an exercise of retro-fitting a data structure across what’s in place. Adding to that, M&A activity is a driving force in insurance, and with each new acquisition comes a whole new grab bag of tech and data to incorporate.
MDM principles have been around quite some time, but they really entered the realm of criticality with the broad adoption of AI/ML technologies. From a business perspective, if you can’t sort your data across systems, you can’t draw meaningful business insights from the interrelationships between data sets. Doing so requires taking (likely) .csv data from at least one system, exporting data in another format from another system, finding a common identifier (assuming there is one; I’ve seen companies have to create them for these purposes), and then finally correlating the two. Who’s got time for that? And forget about trying to correlate 3 or 4 data sets. Need another business insight next week? Same manual process, over & over. Strategically, this is a problem for post-hoc analysis & planning. Operationally, this bears out in the inability to act on that data in real time. Competitors who can have an immediate edge.
So, how does MDM relate to a CAT? Simply put, in this last CAT, we saw that companies with a workable MDM in place had field adjusters wrapping up before others had even assigned claims to the field. Why? When the demand surge hit, they had a top-down, categorical data structure in place that works across systems to make quick changes en masse without disrupting business. If you’re not already working to enable MDM, it definitely needs to be part of your overall strategy that informs every tech decision, from creating new claims attributes to assessing acquisition costs.