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R&D Portfolio Management and the Black Swan – Enrich Consulting

Publicerad By Dr. Richard Sonnenblick

blackswanI recently read The Black Swan by Nassim Nicholas Taleb and found the book’s central tenets relevant to R&D portfolio management. I recommend you pick up a copy yourself, but until you do, I hope the following thoughts hit the mark for you as they did for me.

What is a “Black Swan?”

According to Taleb, a Black Swan is an event with three characteristics: 1) It has a low probability of occurrence; 2) It has remarkable (positive or negative) consequences; and 3) It creates an irresistible urge to retrospectively concoct a story explaining why the event happened and how it could easily have been predicted. The problem with Black Swans, says Taleb, is that they are far more common than those in the prediction business will admit, and that they have profound implications for the value of forecasting and sound decision making in a wide variety of disciplines.

To illustrate his point, Taleb creates two fictional countries, Extremistan and Mediocristan. Events in Mediocristan fit a normal distribution, with outliers obeying predictable patterns. Life in Extremistan is characterized by infrequent but earth-shattering events that change the course of history. The mistake made by so many is to confuse the Gaussian, predictable world of Mediocristan with the fundamentally unpredictable world of Extremistan. While the distribution of heights or weights of a group of people fits a Gaussian distribution, and thus represents Mediocristan, the distribution of personal wealth of that same population lies in the land of Extremistan, with a small number of people potentially responsible for a large proportion of the total. Similarly, Taleb avers that over the last 50 years, “the 10 most extreme days in the financial markets represent half the returns.”—a daunting assertion for forecasters if ever there was one.

Does your R&D portfolio live in Extremistan or Mediocristan?

Think back to the success stories of your firm over the last 10 years. Were they widely anticipated to be the successes they became, destined for stardom at their very genesis? How about the most expensive failures of your portfolio over recent years? Were the failure modes expected, or were they a surprise to most, if not all, involved? Try not to think about the ex-post rationalizations following the denouement; what was the accepted wisdom surrounding risk and opportunity just before the unveiling?

The challenge for those of us in high-risk R&D is that it is diabolically difficult to predict success or failure of any given product, product line, or technology. Often, we find ourselves further off the mark than we could ever have anticipated. Just last week, Pfizer pulled Exubera from the market, with quarterly sales of less than $2M following a $100M+ marketing campaign (and to say nothing of the nine-figure development costs). What if an employee of Pfizer had predicted sales at this level, shortly before launch? I’m sure they would have been laughed out of the lunchroom, or worse.

Thriving in Extremistan

If admitting that we live in Extremistan is the first step, where do we go from here? Taleb offers many interesting ideas, with some more actionable than others. Here are a few choice ones.
As Louis Pasteur once wrote, “Chance favors the prepared.” If you know that risk is unavoidable, structure your business so that you have as many opportunities to exploit as possible. While some feel serendipity is pure “luck”, Taleb asserts that serendipity can be the result of creating a business environment where unexpected connections are sought out and a large number of low probability high consequence leads are investigated with the understanding that only a small minority will bear fruit.

Beware the Narrative Fallacy: Our minds are hard-wired to explain and understand, even when no single true explanation is available. The inclination to create a narrative around Black Swans that have already occurred has two drawbacks: 1) It fools us into thinking we could have predicted the unforeseen event, and 2) It unduly narrows our focus as we look forward and try to anticipate the next Black Swan. R&D Portfolio management software that records your valuations is helpful in dispelling the myth that “we could have seen this coming if only…” but you also need to a healthy dose of skepticism to combat this aspect of human nature.

Don’t over-model your assets: If you invest in risky endeavors, it is tempting to increase the complexity of the models you build in an attempt to identify and mitigate risks. Taleb gives the example of a casino in Las Vegas who spends hundreds of millions on a state-of-the-art surveillance system (the losses due to employee and visitor cheating being perceived as their biggest risk), only to find their four most significant unforeseen events in the same period were 1) Loss of a $100M stage act when one of the duo was mauled by a tiger, 2) A disgruntled, injured contractor who almost succeeded in blowing up the casino, 3) discovery of an employee who had been hiding, rather than processing, IRS winnings paperwork for years, and 4) When the owner’s daughter was kidnapped, he illegally dipped into the corporate treasury to provide the ransom payment to the kidnappers. The moral is that no matter how sophisticated your valuation models, remember that it is almost always the unanticipated, off-model events that will define portfolio risk in Extremistan. Thus, keep in mind that increasing complexity in your valuation models reaches diminishing returns more quickly than you may realize. Instead, expand the definition of your portfolio in order to consider a broader perspective. For example, rather than simply including R&D projects in your portfolio, integrate research and licensing activities.

For more on Taleb, and the mixed success of his hedge fund, see this Wall Street Journal article (subscription required) and this profile in the New Yorker by Malcolm Gladwell from a few years back, when his first hedge fund was still operational.

Relaterade inlägg

Skrivet av Dr. Richard Sonnenblick Chief Data Scientist

Sonnenblick, Planviews Chief Data Scientist, har många års erfarenhet av att arbeta med några av världens största läkemedels- och life science-företag. Genom denna djupgående studie och tillämpning har han framgångsrikt formulerat insiktsfulla prioriterings- och portföljgranskningsprocesser, poängsystem samt finansiella värderings- och prognosmetoder för att förbättra både produktprognoser och portföljanalys. Sonnenblick har en Ph.D. och MS från Carnegie Mellon University i teknik och offentlig politik och en BA i fysik från University of California, Santa Cruz.