At first it was me, and I didn’t even realize it. Data, claims data—I have worked with it literally for decades, but why did I never see it this way before? I created strategies, dashboards, reports, peer comparisons, reviewed stewardships, and even on occasion was mesmerized by a new fancy gauge chart, but now I see it. Data is not one-dimensional.
What do I mean?
Let me think back to the world of Workers Compensation metrics, a world where averages rule:
- average paid
- average incurred
- average lag time
- if not averages, then ratios (paid to incurred, per 100 FTEs)
Don’t take me wrong; these still are fantastic metrics, and we should not underestimate their power even in today’s market. They can drive risk and claims management, invoking action based upon trends, driving behavior to correct spikes in locations or jurisdictions, and communicating successful strategies to senior management.
Is “big data” one-dimensional?
But, is this enough? Is the world of “big data” really this one-dimensional? Is it flat, should we “captain” our own vessel and explore if there are other dimensions out there? Some of you may already have begun your journey, did you make it to the other side or was your ship not prepared so you came back to port disappointed?
In the world as we know it, risk management suffers from being ill-prepared to journey into the open waters and chart new routes in data and metrics. We are happy creating bigger and better ships but then never leave port. The risk management information systems (RMIS) are getting more complex and sophisticated. Recently, I even witnessed an Amazon Echo interface with a RMIS to create a claim. There are even newer and more robust visualization tools that can interface with all of the claims data.
But, even with all of these advancements, we still are presenting the data from the one-dimension “ship” safe in port.
So, how does an organization begin to open its eyes to the multiple dimensions of data?
I have often begun the conversation that in order to present better metrics within an organization, the organization first needs to understand how each area within that organization measures and understands risks.
From the CEO to the floor supervisor, each area has different business questions, goals, and metrics. Interestingly, at this point the data is not complicated; in fact, it is the standard fields available in any risk system. A CEO may focus on total incurred and change in projected ultimate reserves, whereas the line supervisor may focus on the DART rate (OSHA days away from work). Both come from the same source of data. If not, that is a topic for another discussion.
Now we know that different areas within an organization have different metrics to measure success from a claims perspective. We typically have stopped, right at the cusp of exiting the bay into open water. We are hesitant. Just like the Santa Maria, a ship is more than just her captain, Columbus.
Not only did I need to understand the metrics from a claims perspective, but I also needed to know the metrics from other areas within the organization and how they measured success; more importantly and through escaping the one-dimension, how do those metrics that govern and drive their area impact the claims data?
For example, logically there is an impact in turnover and worker compensation claims. Have you measured it? Does it impact claims within the first year of service? You say of course, but do you measure it? Do you know where it is higher or lower? Do you know why? Does the human resources department understand the cost to the organization from a claims perspective? Are you making your metrics multi-dimensional? Do you integrate other metrics into your claim metrics?
The world is no longer flat, data is no longer small and self-contained in its own systems. A RMIS is much more than consolidated claims reporting. It is your world, so is yours flat or round?
Guest blogger R. Duane Pifer is Senior Consultant, Data Analytics Lead for Integrated Casualty Consulting at Willis Towers Watson.