Lessons learned from RMIS.
Software has had major benefits for the risk management profession. Using an Excel spreadsheet to record numbers and perform calculations is orders of magnitude easier than doing them by hand. And while paper files offered a certain sense of tangible comfort, it was very hard to e-mail them. Performing a text search to find the name of a witness required hours, assuming that one could find the file in the first place and that it had not been left in the mink of the employee who quit a week ago.
The benefits of software have extended beyond claims to the world of forecasting. Having large pools of data brought together allows one to calculate trends much more quickly. risk management information systems have brought this functionality to the insured so that one no longer has to rely on the insurers' calculations. It is very empowering to have access to data. Many systems today have built-in analyses that allow anyone with a basic understanding of the software to cream loss triangles, predict loss volatility and identify problem areas.
However, the picture is not entirely rosy. Those of you who were around when RMIS systems first arrived will recall that the promises of the software vendors were, to put it very kindly, insanely optimistic. While the systems might theoretically have been able to perform as promised, one still had to import data from multiple carriers. And those handy calculations that the program would perform for you, well, they were going to work as soon as the software vendor came out with the three new upgrades that they were working on, but somehow never got around to actually completing.
While RMIS products, through much trial and error, have evolved into solid tools, the newest risk management software products suffer from similar growing pains. Enterprise risk management platforms, which have multiplied exponentially in the past five years, are not yet perfected.
As with RMIS systems in their early days, the promises of many of these systems were sweeping. Several that I looked at promised to aggregate all of the data across the enterprise, quantify the risks and provide real-time updates in an attractive dashboard format. Upon closer inspection, I felt as if I had slipped back in time. Like the early RMIS sales pitches, those for ERM systems forgot one niggling detail: the data.
Aggregating the data across the enterprise sounds like a great idea. But in reality, most large enterprises do not have data in a single location. The data also resides on different platforms, in different languages and in incompatible formats. Gathering it together is about as simple as gathering up all of the sand on the beach.
The other problem they face is that a majority of risks am simply not yet quantified. There are no clerks furiously adding together the value of a bad strategic plan, multiplying by the sum of operational breakdowns and dividing by global warming to produce a nice, neat number.
Software that manages data well is not terribly useful when there is no data. And this is the Achilles' heel of the current software solutions on the market. No software, no matter how sophisticated, is going to help quantify intangibles. First we need to understand the methods for creating quantitative analysis. This is easy to do because the methods am not only available, but taught in numerous places. But first we have to get the order straight: first pants, then shoes. First data, then software.
BEAUMONT VANCE manages risk for Sun Microsystems Inc. He can be reached at email@example.com.
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|Title Annotation:||RISK MANAGEMENT|
|Publication:||Risk & Insurance|
|Date:||Sep 1, 2007|
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