How Pharma is Subservient to Numbers

Educators use the term "innumeracy" when they discuss the fact that American schoolchildren achieve lower scores on math exams than their counterparts in Asia.  Whether the phenomenon is real or just a catchphrase for some larger social trend, the fact remains that by the time Americans reach adulthood and enter the business world, they are absolutely in thrall to arguments tarted up with quantified data.  Terms such as "quantomania" and "numerenvy" might describe the situation.  Pharma suffers from it as much as any other manufacturing or service sector.

Otherwise knowledgeable business people with well conceived positions on particular issues will fold like a card hand without a meld when they are confronted by opposing arguments that feature quantified facts and figures.  Whether the issue concerns developing a particular compound, entering a therapeutic market or buying another company, the numbers people swing the big sticks.

It makes no difference that every few years, companies in one industry after another will fall into embarrassing or even ruinous disasters from lemming-like adherence to quantitatively based initiatives.

Twenty-five years ago, Tom Oliver, then a business writer for the Atlanta Journal and Constitution, told the story of how Coca Cola made itself a laughing stock in the marketing world when it changed the taste of its franchise Coke in favor of a sweeter version.  Common sense suggested to many of Coca Cola's experienced marketers the wisdom of launching the sweeter Coke as a "flanker" alongside the legacy version.  But no-o-o-o, quantitative studies made the point that the sweeter Coke would cannibalize the older version and leave market leadership in Pepsi's hands.  So Coca Cola withdrew the older tasting version and outraged millions of loyalists around the world.  Sheepishly, the company brought back the legacy version under the name Classic Coke.

More recently, investment bankers contracted a bad case of quantomania and hired mathematicians, physicists and other prestidigitation artists to develop mathematical models for directing securities trades.  The result was the financial meltdown of 2008.  One of those whiz kids, Emanuel Derman, tells about the folly in his recent book, Models Behaving Badly.  A physicist by training, Derman maintains that mathematical modeling is a fine means of understanding and predicting actions in quantum electrodynamics.  Financial instruments, on the other hand, involve the behavior of people, something that changes willy-nilly.  As a result, models created for generating windfall profits usually fail.  Mathematical representations in physics, according to Derman, posit genuine theories of reality, but "financial models are only mediocre metaphors."

The failures of quantitatively driven initiatives occur so regularly, with such disastrous results, that the important question is why this style of discourse holds the sway that it does.  Herewith are some speculations.

1. Quantitative assessments create the erroneous impression of being non-partisan.

Large organizations are inherently political and routine actions typically gore someone's ox while favoring the careers and job security of others.  In environments where everything is political and actions are automatically perceived to derive from invidious interests, quantitative data provide the illusion of objective assessments that impartially reflect reality.

Despite that perception, the true nature of quantitative data permits and, in fact, requires as much subjective input as any non-numerical sort of assessment.  Consider, for example, the widely divergent results projected for the same political races by the various pre-election polls.

The difference with the subjectivity inherent in quantitative studies rests on the fact that the places and methods of exercising such bias tend to be more abstruse.  As a result, someone who presents quantitative data to support a position often goes unchallenged because people not familiar with the methods are unable to identify the hocus pocus.

2. Assessments and recommendations based on quantitative data often seem macho. 

Despite the fact that math whizzes are as nerdy as analysts and researchers that use different methods, in business meetings a command of quantitative data often projects a masculine command of the situation.

Perhaps that is due to the fact that math and statistics nerds who have mastered their discipline's arcane language occasionally lack the verbal agility and psychological acumen of people clearly associated with partisan positions.  In those parts of Anglo-American society favoring the strong-silent type, such a cryptic lack of verbal embellishment is considered quietly assertive.  A John Wayne or a Clint Eastwood mumbling some terse remarks about p values and confidence intervals at a brand team meeting could probably win approval for any cockeyed marketing program.

3.  The operational measure of business entities is quantitative.

Businesses are created to generate profit and a return on capital.  The blather about serving the public need or the general welfare is diversionary.  Milton Friedman and his coven of 18th century followers claim businesses should pursue no other objectives.  In any case, profitability is assessed by quantitative measures and profit trumps all other considerations.

A popular textbook on introductory financial accounting carries the subtitle, "The Basis of Business Decisions."  The concept is fairly asinine because it is equivalent to claiming that the basis for playing and managing baseball is the knowledge of scorekeeping.  Nevertheless, the dollar, yen and Deutschmark are, by definition, entities that exist in number.  Perhaps as a result, any communication using the same symbols that describe filthy lucre, by implication suggests similarity to a pile of dough.

Perhaps there are other reasons for the potency of quantitative data based on psychology, gullibility or defects in the common culture.  The interesting point for pharma is that the industry has always contained within itself the capacity to rise above the quantomania.

The drug industry employs chemists, other bench scientists and clinical researchers to develop new therapies.  Their work is highly mathematical and statistical, but the products themselves are created for selection and use by practicing physicians whose work consists of highly subjective judgments.  In their current book, Your Medical Mind, physicians Jerome Groopman and Pamela Hartzband write, "The best doctors practice 'judgment-based medicine,' meaning they consider the best available evidence and then assess how it applies to the individual patient."  Ask a room of ten physicians to apply their judgment to the same, routine case and three, five, perhaps ten different answers will emerge.

Judgment will always rein in the selection and use of pharma's products, yet the business people who manage creation of the drugs "identify with their natives," i.e., the scientists, in hoping that formulas and numbers can replace their own considerations.  If that approach prevails, then personal computers could cost-effectively replace many six- and seven-figure a year managers.

Think about that over the holidays.

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