I recently attended a conference of insurance professionals and the conversation centered around “Big Data.” It was a captivating presentation that only a risk and insurance professional could love. It certainly got my attention and it got me thinking about how I collect and use data to identify exposures in my work.
Risk management sets itself up to be the poster child for big data. As risk professionals we’ve been using big data for decades.
Through modeling, trending, forecasting, and claims management we have been on the forefront of what just now seems to be getting everyone else’s attention. And with the cost of technology so cheap, the ability to collect all types of data is mind boggling.
But this lends itself to the question, “Just because I can measure and model it….do I need to?”
Let me explain.
It was during this conference that a data specialist discussed the use of big data and how his company had applied it to a model to validate the impacts of water run-off and flooding. After collecting their data and running it through a model they were able to say definitively that water tends to pool at the lowest elevations.
Further, if a building is constructed in these low zones it is more likely than not that they will be adversely affected by floods versus building on higher ground.
Really? You needed to model that theory?
Now to be fair their work wasn’t finished. They are still working on positive impacts of a variety of options for engineering controls. Clearly, that will be useful when it comes time to design, budget, and build in these areas.
Through modeling, trending, forecasting, and claims management we have been on the forefront of what just now seems to be getting everyone else’s attention.
We are all working hard each day to identify and control risks to our company. And big data has a place, a very important place, in our work.
But as I listened to this presentation I wondered if maybe we are becoming too dependent on technology, models and big data and losing a skill that is just as important.
I call it battle scars but you know it as real experience. It has been said that we don’t learn from success; we learn from failure.
Now that doesn’t mean we have to experience a total loss in a flood zone to learn it’s not a good idea…especially if high ground is just down the block. But the lessons learned from battle scars can be invaluable.
That’s why I think, in addition to the collection and use of big data, it is just as important to set up environments where it is safe to experiment. Try new things. And know that you will fail. But failing is learning. It’s a good thing.
Just try to fail fast, fail cheap, and fail forward.