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Cognitive Biases in Private Equity Health Sector Investments


Mankind in its hubris and for motivational reasons defines itself by its reliance on reason. But let cite Mark Twain’s words to puncture our pomposity “Man is the Reasoning Animal. Such is the claim. I think it is open to dispute. Indeed, my experiments have proven to me that he is the Unreasoning Animal”.

The human brain for all its wonders is “a flawed belief machine”. Errors in judgment are the product of the interplay of the necessary shortcomings in information-processing strategies and motivational factors.  Processing time and memory space need to be conserved both in computers and human minds, except computers advance at a phenomenal rate, increasing to once unthinkable levels. It takes millions of years of evolution to produce changes in the brain, and the brain could not be shut down for renovation. Evolution relies on jerry rigging. Unlike a computer, we have motivational biases so we function like a government run press. All new information is filtered, interpreted and censored to confirm our prejudices, pre-conceived notions and dogmas to make us reflect positive at affirming our decisions.  Combined with processing limits, this well explains much about Private Equity banker decisions.

All this is equally true in risk management. Risk management is older than Homo sapiens.  Our early ancestors did not have to ponder how best to invest in international emerging markets and consequently did not require medical device market analysis, but how to hunt game and not become game themselves.

Consider these items listed below on how human cognitive biases can increase risk in the arena of investment banking.

1. Illusionary correlation- we see chance occurrences happening together as related and then notice whenever they occur together again. This is an evolved cognitive fallacy of attributing meaning and significance to coincidences. Today most even intelligent and educated people still do not believe in “coincidences”. Quantitative analysis is a vehicle where we can defend against illusionary correlation by mathematically using the concept of randomness.

2. Confirmation bias-We notice and recall events that support our beliefs more than events which contradict them.

3. Planning fallacy – One of our most significant cognitive biases.  We function on “Objective Probability”, ergo “X” number of events have happened before and therefore I can put percentages against the times it failed and the times if succeed and calculate the probability of success as indicated by a formula; (E(x) = Pr1X1 + Pr2X2 +………PrnXrn).  This can provide us least squares or variances when calculating capital requirements against a subjective Marketing managers business plan if there are similar products that have come before. In the instance of new technology being introduced and not replacing an existing technology but breaking new frontiers, investment bankers should be using a different calculation for the set of variables, regression analysis to consider how closely the financial requirements fit with the reality of the variables in its business plan assumptions; a best fit line of progression (R = 1).  Measuring one event against previous events without the proper quantitative analysis can underestimate how long it will take, and how hard it will be to do a task. Such planning fallacies often lead to falling short on the required amount of capital to be raised and again can be mitigated by using quantitative economic analysis.

4. Omission bias- We notice an action more than a failure to act. We judge an action that produces harmful consequences more harshly than harmful consequences produced by failing to act.

5. Illusion of control- We believe we are in control of events that actually occur by chance. In a sublime example, Dice players have been found to believe they can control dice outcomes by talking to dice!  This is why lotteries allow people to pick their own numbers, instead of having assigned numbers.

In summary, Cognitive behavior biases should be considered when calculating risk more frequently than not as they can be mitigate risk by quantitative predictive statistical analysis which in the end can protect your brand value as an investment banker.  The extra step may be worth twice your investment if your equity players are risk adverse.

Written by Alexander Nussbaum PhD, Statistical consultant to Analytic Medtek Consultants and Professor at St. John’s University and edited notes by Ken Peters PhD, Principle Analytic Medtek Consultants and Professor of Economics Baruch College, CUNY

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