To survive — and perhaps thrive — in this unpredictable future, pharmaceutical companies need to make some bets about the way the future of the industry will unfold, and design their diversification strategies to position them for success in one or more of the scenarios they envision. We think these need to be strategic bets, which mesh with the companies’ key capabilities systems — the things each company does with distinction that provide its competitive advantage. We recommend that companies begin that journey with a five-step process for identifying the best opportunities.
Just how uncertain a time has Big Pharma entered? Consider a balloon in different weather conditions. Release the balloon into a light sea breeze, and it may bounce a little from side to side, but it will inevitably and predictably fly in the direction of the wind. Repeat this experiment and the results will be almost identical to those of the first try. This is an example of a deterministic process, meaning you can predict the balloon’s behavior and ultimate location with a high degree of accuracy by knowing its aerodynamics and the speed and direction of the wind.
Now try to predict what will happen with a balloon in an unstable weather condition like a tornado, with the wind gusting in different directions. Even if you let two balloons go at the same time, they will end up in totally different places. You can’t predict the outcome of this experiment any more than you could predict that Dorothy and Toto would end up in a brilliantly colorful place called Oz. A balloon in a tornado is an example of a stochastic process — the outcome is inherently unpredictable.
Most industries go through periods of both deterministic and stochastic development. For instance, the computer industry in the 1960s and 1970s had all the characteristics of a deterministic process. IBM, Burroughs, Cray, and others pursued similar strategies, selling giant data processing machines known as mainframes. The personal computer changed the dynamics of the industry, triggering a turbulent stochastic period. It became impossible to predict where the computer industry was going, and in the early 1980s the incumbent players’ strategies diverged significantly. Some bet that the old mainframe paradigm would prevail; others expanded to new product and service areas. The outcome was stark: Many companies didn’t survive (case in point: Cray), and others (such as IBM) survived only by making significant changes to their business models and product portfolios.
After years of steady and predictable growth, the pharmaceutical industry is entering a stochastic period of its own. That pharmaceutical companies have divergent views of how the future will evolve is evident in what they’ve done in the area of mergers and acquisitions. On an aggregate basis, M&A activity involving the 10 largest pharmaceutical companies looks pretty chaotic — no clear pattern is visible in their behavior from 2004 through 2010. (See Exhibits 2 and 3.) Capital transactions in animal health, consumer health, devices, generic drugs, and branded pharmaceuticals all accounted for tens of billions of dollars in acquisitions, divestitures, or both. The one exception is biologics, a type of medicine that everyone seems to agree will be important in the future.
When you look at M&A activity on an individual company basis, however, the pharma companies’ behavior looks considerably less chaotic. Most of them have used deals to narrow their focus to two or three areas besides core pharmaceuticals and biologics. (See Exhibit 4.) The other focuses they’ve selected are the result of an assessment by each company of where it might succeed, and the amount of diversification it can support.