In a modern world of endless data and seemingly unlimited risks, the job of a risk manager is often an unenviable one.
Today's risk managers have long understood the power that data can possess, but few managers actually have the tools or insight needed to truly reach their end goal of reducing workers' compensation risk. This means many risk managers are not properly filtering and using the critical data at their disposal that could very well save their companies millions in claims costs.
In order to combat this problem, forward-thinking companies are beginning to adopt predictive analytics solutions that combine the power of incident-management and claim risk systems into an all-in-one package. The end result is what we in the risk management world refer to as "actionable data." That actionable data is what will ultimately ensure your company is protected from excessive risk exposure for years to come.
For any company looking to adopt an integrated incident and claim management solution, your solution must have three things:
- Access to incident data to help foster instant corrective and preventive action (which will ultimately foster increased ROI) because comprehensive root-cause analysis and contributing factor data are the critical source of actionable data
- Full integration with a third-party administrator (TPA) to help fully automate the process of filing incident claims
- A data intelligence/analytics platform to integrate, correlate and provide actionable insight as it relates to identifying which incidents and root causes are creating the greatest liability, and most importantly, to prevent incidents and resulting claims from occurring in the first place.
The question then becomes how do we get to that point of risk protection? And what is the actual efficacy of these solutions?
To answer this, we need to examine what we really mean when we refer to "actionable data." In the context of claims management, actionable data is the end-product derived from analyzing claims data received from the claims system of a carrier or TPA. This data is then "acted upon" in some fashion — usually for underwriting and pricing as opposed to learning and trending.
From reactive to proactive
This distinction is key: When you marry the analytics behind the incident management process with those of the claims management process, it enables end-users to actually influence the data instead of reacting to a given result. In other words, you aren't just relying on a program that spits out a command, you are instead digging deeper into the root causes and contributing factors of the claims and receiving solutions for how to prevent those incidents in the future. Simply put, you're moving from reactive to proactive.
This process is best illustrated via a real-world example. Let's say you own a trucking company, and you're receiving complaints that your trucks have been hitting parked cars. With an actionable data solution, the interplay of incident and claims management could be leveraged to know exactly how and when your trucks are hitting parked cars, along with insight into why the incidents keep happening.
This illustrates the efficacy of actionable data. If you don't capture the actual reason the cars are being hit — perhaps drivers are being distracted by something in the street — you won't be able to put a process in place to ensure that future losses are avoided.
Enterprise-wide safety culture
And, of course, integrated incident and claims management systems aren't just about bottom-line protection. Ultimately, the system should be designed to enable an enterprise-wide safety culture to keep employees safe. This is especially relevant to companies working in high-risk industries such as construction, manufacturing, logistics, oil, energy and many others. When the nature of the job puts employees' lives at risk, it's imperative to employ a solution that doesn't just tell you what caused an incident, you need the how, why and in what ways do we prevent this from happening again to be answered as well.
Looking ahead, "actionable data" is a key component of a much larger technological transformation happening in the claims space. Companies today are already looking to the Industrial Internet of Things (IIoT) as one method for helping boost the quality, quantity and reliability of the data they gather to help guide safety and improve decision-making. Imagine a world in which every piece of equipment a company owns is connected to the internet and capable of producing real-time risk mitigation.
Ultimately, the best claims to manage are those that never occur. Having the right information at the right time, and the supporting proactive data intelligence platform provides the path to a safer organization and reduced incident claims exposure.
Jeff Faiello is vice president, Business Intelligence and Analytics at ProcessMAP. He can be reached at jfaiello@processmap.com.
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