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Leveraging Existing Resources to Make Effective Risk-Related Decisions

By Sonny Blackwell, Vice President, BXS Insurance

Sonny Blackwell, Vice President, BXS Insurance

I am an accidental data scientist. As a risk management consultant for a regional insurance broker, my clients tend to be “middle market” companies or public entities. Relatively few have Information officers, and almost none employ true data scientists. Almost all are budget-challenged and overwhelmed with competing time demands created by their own organizational issues and by sales consultants with solutions in search of problems. Sophisticated marketing techniques are designed to take advantage of emotions, and it’s easy to make a less than an ideal decision under the influence of stress and time constraints. Objective, unbiased advice with solution-neutral motives are often valued by decision makers.

As an undergraduate Criminal justice major, I was required to take criminology classes. The purpose was to learn how crime is distributed within communities in order to deploy law enforcement and crime prevention strategies. In graduate school, I took courses in epidemiology and biostatistics. This taught me to recognize patterns of disease outbreaks, risk factors, correlations and cause-and-effect of diseases within communities so that public health resources could be most effectively utilized to improve the overall health of the population. As a risk management consultant, I found myself relying instinctively on those methods. In order to determine the most practical and cost-effective countermeasures for my clients facing rate increases or cancellation, I had to first identify possible sources of poor performance and then collaborate with them to make decisions regarding the best course of action. I learned to blend the objectives of solving urgent problems with long term strategy to maximize Return on Investment.

"Investment expenditures and various types of results data, including claim costs and associated costs, can be measured to calculate Returns on Investment."

It’s been said that “a problem well defined is half solved.” In 1854 Dr. John Snow mapped cholera fatalities in London and determined that a disproportionate number of victims drank water from the Broad Street pump. Then, he convinced town officials to remove the handle from the pump so that people could no longer draw water from it. Fatalities from cholera dropped significantly and immediately. That same basic approach can be used today to identify concentrations of accidents and injuries within workplace populations and liability claims against organizations. Effective, focused solutions can often be developed once a common understanding is reached. Investment expenditures and various types of results data, including claim costs and associated costs, can be measured to calculate Returns on Investment.

Fortunately, most organizations already have valuable information from which to develop basic a data-driven decision approach to decision making. Data exists throughout organizations. But in the real-time fog of doing business, decision makers forget to take advantage of data they’ve already collected or assume that because they lack an expensive state-of-the-art RMIS system, they can’t take advantage of that data. Such systems are very beneficial to many organizations. It’s challenging to collect, organize, combine with other relative metrics and finally, develop understandable visualizations or tables so that multiple stakeholders can collaborate on a common issue and understand how their specific interests affect strategic priorities.

Sophisticated systems and highly trained analysts can add value to certain organizations, but if your organization is faced with the need to make important risk-related decisions, there is most likely a way to use existing data in existing systems with people you already know, to reach better decisions and lower your cost-of-risk.

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