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By Michael Greeley

 March 10, 2003 | Help me out here. Did everyone in the bioinformatics field try to violate one of the most fundamental tenets of economic theory — the law of supply and demand? Were we not dutifully taught that demand begets supply, and that with plentiful supply, the per-unit price of that supply will drop? If so, why is it then that so many business models today are predicated on explosive supply (of data) creating increasingly higher per-unit prices of that supply?

In the face of projected extraordinary demand for data (we can debate whether perception equated true end-user demand) and the seemingly limitless supply of venture capital, the bio-IT field over the past few years developed exciting new tools to generate, aggregate, visualize, and analyze the overwhelming volume of data being unleashed. Unfortunately, the many undifferentiated bioinformatics vendors have had to divide up what for some time has been a small, nascent market.

The novelty of what these tools could create arguably led to an exaggerated valuation of that per unit of data. The promise of these new tools caused investors to extrapolate to untold riches because those data, in and of themselves, were going to be extraordinarily proprietary and valuable. While the potential was overwhelming and exciting, the irony is that the explosion of these data led to their commoditization. The problem may be that too many data were created, or, more precisely, the wrong types of data.

Crossing Over 
As an investor in this sector, I believe that we are living through a painful recalibration of everyone's expectations. As seductive as the promise was, the disappointment being felt today is equally disturbing. Entrepreneurs are "redefining" their business models, searching for new value-added services, trying to extend their current product portfolios into new applications. But what does that mean?

The many bioinformatics vendors have had to divide up a small, nascent market.

The bio-IT sector is a "crossover" sector. On one hand, it attracts traditional IT investors who understand the needs of data-intensive enterprises and can counsel early-stage IT companies on how to sell into those accounts. On the other hand, the domain knowledge required in bio-IT is so specialized that traditional life science investors are most qualified to understand the needs of the actual users of these products. Unfortunately, not all venture firms are able to synthesize these potentially conflicting sets of insights.

So as entrepreneurs talk about "evolving" their business models, keep in mind that the IT investor who thought he or she was funding an informatics software company that is developing a robust set of tools may not care to see that company then utilize those tools on a proprietary basis to develop new drug compounds. Vendors of oil discovery software tools don't typically aspire to become integrated oil companies. What they do is develop new tools that facilitate the discovery of elusive oil fields. Is there a lesson here?

At Your Service 
In the face of data commoditization, the other evolution often mentioned is the migration from a product to a service model. In the old days (i.e., the mid-1990s), many venture investors were excited about the software service model. Unfortunately, the landscape is littered with many companies in many verticals where that model proved to be flawed. Two principle reasons are often cited: The level of product customization per customer was so great as to make deployments uneconomical, and customers were loath to see their data reside elsewhere. Both issues may continue to be factors as one contemplates the bio-IT service model. That said, keep in mind that a number of emerging growth companies, with demonstrated initial customer traction, are providing services to allow customers to monetize large repositories of data with little incremental costs.

At the outset of new technology deployment in the enterprise, there are valuable roles to be played as a systems integrator. In the bioinformatics industry, these companies are hired to develop, deploy, and audit knowledge management (KM) systems. While these business models are dependent upon professional service economics, which venture investors tend to be leery of, above-average rates can be exploited because of the required domain expertise. Additionally, systems integrators at this stage of market development become a powerful channel for the independent solutions providers and consequently may continue to generate interesting margins. The goal of simply getting a working KM system is often realized with cost concerns being secondary.

The other evolution in today's bio-IT marketplace involves point-solution providers, those companies that provide only one element of a bioinformatics system. Many of them are expanding their product offerings to incorporate additional software modules. While rather ambitious, the goal of creating KM infrastructure systems for drug discovery is a credible one. Of course, as vendors seek to sell more comprehensive, and more expensive, solutions, other issues emerge around selling across multiple functions and multiple lines of business.

So have we tried to violate fundamental rules? Clearly, some companies were financed with little regard for supply and demand. The data explosion might have unwittingly re-priced downward those same data.

It's not just about supplying data. To maintain a blended per-unit price that is compelling, it's imperative to create products and services that can be bundled.

New supply may beget new demand.

Michael A. Greeley is managing general partner of the East Coast investment portfolio of IDG Ventures, a global network of venture capital funds with approximately $600 million under management. He can be reached at mgreeley@ 

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