A Markovian Approach to Risk Management
If recent years have taught us anything at all regarding assessing risk, it’s that a myopic approach to risk and risk management is, in itself, a risk. When it comes to HR and compliance, we can’t afford to be nearsighted. Instead, we must look far into the future to be prepared for whatever comes our way. Consider the poor guy above. Is the leaky boat, the sharks, or the approaching storm the biggest risk? Can you address them all, and if so, in what order?
RISK MANAGEMENT AND THE MARKOVIAN PROCESS
In the past few years, we have all heard more than once that we need to “trust the science.” When it comes to risk in this context, the science is what is referred to as a Markov Chain, or Markovian Process. The short definition is this: the Markovian Model is a mathematical process that uses observations to predict an approximation of future events.
You may be wondering how this applies to you as an HR or compliance professional, not a mathematician. And it is true that you don’t need to know all the ins and outs of this process, but someone or something that you work closely with, such as your risk management software, should understand this concept. Still, it is helpful to have a basic understanding of the processes being used in the risk management world, so let’s dive into it and learn something new.
The three observations in our example (the leaky box, the sharks, and the approaching storm) exist in what is known as the “observed state layer.” A risk management professional could use those observations of the situation to predict what will happen in the future. Will the man safely make it to shore, or will the sharks catch up to him before then? Using the Markovian Process, you can estimate just how likely each of those outcomes would be.
It all starts with the purpose of the Markov Model – the probability of transitioning from one state to another. One of the main appeals to Markov is that the future state of a stochastic variable, which is dependent on the outcomes of random occurrences, is only dependent on its present state. In the HR and Compliance world, those occurrences would be workplace incidents.
PAST EVENTS, FUTURE BEHAVIOR
The Hidden Markov Model, or HMM, is specifically relevant to the HR and compliance world. The HMM differs from the standard Markov Model in that it acknowledges that the observed state and the estimated state cannot be seen directly. We have all heard the phrase that past events can be used to predict future behavior, and this is the premise here.
The past events (observable) can be used to predict the future event (not observable and therefore hidden). The observable state lives in the observable layer, and although the relationship between the two exists, the estimated state lives in the hidden layer as it is yet to be revealed. The man is trapped in a box in the ocean and sharks are chasing him, but we cannot know for sure what the outcome will be.
The world is a complex place with lots of “observed state” phenomenon that can be used to drive estimated future states. In fact, one of those predictable future states is the application of nuanced mathematical analysis to risk avoidance and mitigation – using the Markovian Process!
Is the past really a prelude to the future? I believe it is in the world of risk management, and the analytics associated with risk mitigation strategies will continue to evolve past theoretical and into mainstream HR, compliance, and risk management strategies. You might not even know it. You might not have the analytics team to apply these, but the software you use will. The next generation of solutions will have these models built in. Simply a surface understanding of Markovian Process will allow you to leverage groundbreaking technology to make your organization more resilient and risk resistant than ever before.
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MEET THE AUTHOR
J Rollins is the co-founder and CEO of ETHIX360. J is a well known leader and innovator who has served on senior leadership teams ranging in responsibility from Chief Revenue Officer, Chief Marketing Officer, SVP of Product Strategy and Chief Operating Officer.
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