Sometimes I just feel a roll coming on and this week it seems the word operationalization is stuck in my head. To honor that instinct, I am going to make this week’s theme on operationalization of your compliance program. There are many different and unique ways to operationalize a best practices compliance program and today, I would ask you to consider forecasting as an approach not usually thought of as a mechanism to more fully integrate compliance into the very DNA of your organization. However, I think it can be a powerful tool for the compliance practitioner and many more in your organization.
Operationalizing your compliance program requires rigor around risk management. This means moving beyond simple risk assessments into a full risk management process. This is a three-step process of forecasting, risk assessment and risk-based monitoring. Many compliance practitioners fail to begin the risk management process with the critical step of forecasting.
At its heart, every business tries to plan for its future. It is a critical aspect of any management of any organization, non-profits, privately owned and, of course, publicly traded companies. It is important that management can set out what it opines will happen in the next three, six, 12 and 24 months. Ben Locwin has said this “is really something that the businesses try to wrap their heads around in such a way that they can shunt resources where they think is appropriate in order to meet these future demands. Forecasting really at its heart is an educated guess and really as much as it becomes a reliable model more so and less so a guess, is based on the quality of the input data.” It is a process through which you are attempting to “prognosticate what the future will bring to you”. Unfortunately, forecast models are only as good as the data which are put into them or the GIGO (Garbage In, Garbage Out) Principal.
Locwin notes that forecasting “should be broadly defined as a technique to estimate future aspects of any sort of business or operation.” He divided forecasting methods into two major categories; qualitative and quantitative. While both methods use past or historical data, in the quantitative method, “you would use time series analysis, for example, to see how certain trends appear in the data in the past.” Contrasting the qualitative method, which Locwin said is “a more subjective, and you’re using less collective data which has been, let’s say, put into some sort of time series plot. It could be finances fluctuating over time or maybe it’s various incidences. In the context of anti-corruption compliance specifically, this would include various instances of bribery and corruption that have been occurring. How would you document similar events over time? When were there spikes? Those spikes, related to what types of actions by your organization?”
Under either approach, whether you are using the qualitative or quantitative method for forecasting, Locwin notes “what you’re really trying to do is say that, “We expect that the trends that we’ve seen will be somewhat predictive of future behavior.” Otherwise, if you don’t consider that past behavior is in some ways indicative of future performance, you would not engage in any forecasting whatsoever.” Rather it is simply predicting.
Forecasting, typically, will raise risks (and opportunities) which you might consider going forward. However, it does not assess or monitor these risks. Those are handled by risk assessments and risk monitoring. Locwin cautioned that simply because something is forecast does not mean will occur. He cited to Nobel winning physicist Niels Bohr for the following, “Prediction is difficult, especially about the future.” Locwin further explains, “Whenever you’re trying to say how something will go, really the best you can do is try to look at past data and try to say what’s going to happen with that. In my prior probabilities, my prior knowledge tells me this, and therefore what will that mean for the final outcome?”
This last point led Locwin to note, “what we can all do as an industry to insulate ourselves from overly adverse outcomes is to be more agile and adaptable in how we respond to the changes that are coming. Standing immutable behind hardline policies can make the necessary operational changes difficult to absorb and lead to more variance and extended costs in the long run. This concept is known as anti-fragility, where the idea isn’t to become more impervious to change and market forces, but to be more adaptable to these changes. The ancient philosopher Heraclitus of Ephesus said, “Change is the only constant.” This is true in pharma as well. Closing our eyes, covering our ears and hoping the changes will pass us over are not viable strategies. However, expecting the change and being adaptable and resilient to its effects are strategies for success. Just ask Charles Darwin.”
Consider the research by Guy Mayraz, who ran a series of experiments at Oxford University’s Experimental Social Science center. The first lesson is the bias towards predicting what people hope will happen. If you want your business to increase, you must believe your transaction/investment/deal will always make money. After all, have you have ever seen a business plan that was designed to lose money?
The second lesson, derived from Phillip Tetlock’s Good Judgment Project almost sounds like someone channeled the well-worn Howard Sklarism that water is wet, is that “self-critical, open-minded forecasters do a better job than narrow-minded overconfident ones.” Tetlock notes, “dwelling on our own fallibility is not something people do very well; whether it involves hanging out with our friends or on cable news”. The result is that “Confident, eye-catching forecasts are the snack food of analysis”. Unfortunately, this is even more true in the business world.
Finally, forecasters must always remember that more than one outcome is possible. A strong possibility may be a possibility but it is not a certainty. One way to overcome this bias is to develop alternative scenarios. Richard Lummis, host of the podcast 12 O’Clock High – A Podcast on Business Leadership, has called this the “devil’s advocate” role at the business planning table and that every scenario-planner should create at least two contradictory alternatives to their rosier, positive scenario. Superforecaster Tetlock has noted that “Superforecasting Requires “Counterfactualizing””.
The ultimate point is that in any forecast there must be preparedness for contra-events. Elizabeth Holmes, now disgraced founder of Theranos Inc., famously said “if you have a Plan B as a back-up, you have already lost”. I find that to be worse than not helpful in any setting, particularly the business setting. She had no Plan B and now she has no role in Theranos or will not in any other public company for the next 10 years. No matter what your forecasting or scenario planning model shows, prepare for other results. For any Board of Directors overseeing a compliance program or managing any type of risk, it all begins by asking questions.
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