• 13 Nov 2006
  • Research & Ideas

Science Business: What Happened to Biotech?

 
 
After thirty years the numbers are in on the biotech business—and it's not what we expected. The industry in aggregate has lost money. R&D performance has not radically improved. The problem? In a new book, Professor Gary Pisano points to systemic flaws as well as unhealthy tensions between science and business. Key concepts include:
  • The biotech industry has underperformed expectations, caught in the conflicting objectives and requirements between science and business.
  • The industry needs to realign business models, organizational structures, and financing arrangements so they will place greater emphasis on long-term learning over short-term monetization of intellectual property.
  • A lesson to managers: Break away from a strategy of doing many narrow deals and focus on fewer but deeper relationships.
 
 
by Sean Silverthorne

Thirty years ago it appeared as if biotech would not only revolutionize healthcare, but also radically improve the very process of R&D itself. This hasn't happened. Though some firms such as Amgen have created dramatic breakthroughs, the overall industry track record is poor—in aggregate, the sector has lost money during this period, new research shows.

What went wrong? Professor Gary Pisano provides answers in the new book Science Business: The Promise, the Reality, and the Future of Biotech, in which he argues that the very structure of the industry, what he terms its "anatomy," has created poor conditions for a science-based business to flower. "The sector has indiscriminately borrowed business models, organizational strategies, and approaches from other high-technology industries under the (false) premise that if it worked there it will work here," Pisano writes.

More fundamentally, biotech suffered from a basic mismatch between the objectives and requirements of science and those of business. Specifically, Pisano argues, the business side of the industry was continually challenged by three characteristics of science: profound and persistent uncertainty, the complex and heterogeneous nature of the scientific knowledge base, and the rapid pace of scientific progress. "The health of the sector depends on how well it can cope with all three of these challenges," writes Pisano.

In this interview Pisano discusses his research, the future of the industry, and what lessons managers might learn from an industry in structural disharmony.

Sean Silverthorne: Biotech has not lived up to its expectations, either in providing outstanding returns for investors or improving R&D productivity. Broadly, what has gone wrong?

Gary Pisano: In the very broadest terms, everyone expected biotech to "work" just like all other high-technology industries, and thus we deployed a lot of the same thinking, models, financial arrangements, and strategies that worked elsewhere, but just didn't fit here.

Q: The biotechnology anatomy, as you describe it, has worked well for certain things in the industry, but not so well for others. What are some of the attributes of the anatomy and how has it contributed to performance shortfall?

A: Let's take one: the market for know-how.

I argue in the book that "monetization of intellectual property" has been a powerful shaping force in biotech. The idea behind monetization of IP is that you don't need to actually develop a product; you can just develop a piece of IP, and then capture financial returns through licensing or other market arrangement. This has worked wonderfully in semiconductors and software, but monetization of IP only works there because of some very specific conditions. You need to have a very modular knowledge base; that is, you need to be able to break up a "big puzzle" into its relatively independent pieces so that a particular piece can be valued independently; and you have to have well defined intellectual property rights. It is hard to sell stuff where the rights are not well defined. There are all sorts of hazards.

These conditions are pretty well met in industries like semiconductors and software; but they do not characterize at all the state of the science in biotech. So, as a result, we have been pursuing an anatomy that focuses on breaking up the pieces of the puzzle into independent pieces (having lots of small specialized firms) when what matters is the way we integrate the pieces.

Q: A theme of the book underscores the tensions between science and business inherent in a science-based business. In general, what are these tensions, and how have they hindered the evolution of the biotech industry?

A: Science and business work differently. They have different cultures, values, and norms. For instance, science holds methods sacred; business cherishes results. Science should be about openness; business is about secrecy. Science demands validity; business requires utility. So, the tensions are deep.

What has happened is that we have tried to mash these two worlds together in biotech and may not be doing either very well. Science could be suffering and business certainly is suffering. If you try to take something that is science, and then jam it into normal business institutions, it just doesn't work that well for either science or business.

Q: Clearly the biotech business has not offered great returns to investors for its thirty years of performance, yet fresh capital continues to flow in. Why the discrepancy?

A: Great, great question. It's a puzzle.

Investors have been very patient. Maybe they are lured by the possibility of owning stock in the next Amgen. On average, returns have been poor, but returns of particular winners have been enormous. Perhaps investors have been over-optimistic. But, it's easy to see how they can be this way. With years of R&D spent in the past, it's pretty easy (and logical) to believe that the future is bright, and therefore today is the right time to invest.

Q: Are there lessons in your book for managers in industries outside biotech?

A: While there is no one right answer for all companies, a few basic things might be helpful.

One is rethinking alliances and the strategic purpose. As I argue in the book, too many organizations (both big and small) think of these in very "transactional" or "deal-making" terms. They do not think about the potential value of the relationship. So, they structure fairly narrow contracts, with lots of ways to bail out. They then mitigate the risks by doings lots of deals. This is the game everyone plays. But, that doesn't get you anywhere in terms of integration or long-term capability building.

I would really like to see some companies start to experiment with a different approach to alliances: one that focuses on fewer, but deeper relationships. I think this is the only viable strategy for really small firms. They have to find partners that truly believe in long-term, committed relationships, not those who are looking to diversify their risks.

On average, returns have been poor, but returns of particular winners have been enormous.

A second big area has to do with structuring of internal R&D. I argue that integration matters a lot. But that means you have to organize your R&D in a truly integrated fashion. Too many companies still have many silos between the key disciplinary areas.

Q: What does the future look like for biotech? Who will be the winners and losers, and do you foresee a radical restructuring of the environment, as you suggest is necessary?

A: It is starting to happen. I can't say who will win and who will lose. Firms that have some existing scale are better positioned to do the kind of integration I talk about, but no one can predict winners in this space.

Q: What are you working on now?

A: I am very interested in how markets for intellectual property work and don't work. This has been something I have looked at throughout my career, but I continue to be puzzled by it.

We see IP trading in many contexts outside of high tech (e.g., music, entertainment, et cetera). There is talk about the U.S. becoming an IP economy; well, if that's the case, then we need to understand how markets for IP really work.

The other offshoot from the book is continued investigation of the general problem of science-based businesses (outside of biotech and pharma). What kind of skills do we need to teach managers of such businesses? Where you have massive uncertainty, you can't rely on a lot of the traditional tools of analysis to support decision making. But, once we get outside those traditional tools, what do we have? Is there something beyond intuition? I think there is, but I need to spend a lot more time getting my hands around that.