January 13, 2003 | Knowledge management commands a great deal of attention these days. But is it justified? The tendency by some potential customers is to dismiss it as a disingenuous attempt by vendors, especially those in IT, to boost flagging sales. While this suspicion carries a kernel of truth, compelling evidence shows that knowledge management can return impressive results to pharmaceutical and biotech R&D organizations.
What Exactly Is It?
Formally defined, knowledge management (KM) is the assembly of information structured in a way to take action upon it relative to your organization's goals. Practically speaking, it entails processes, techniques, and technologies that aim to leverage the knowledge generated in a given organization.
Knowledge is typically created in the context of a specific task or project, but its value is often much broader. Fundamentally, KM makes the collective knowledge of an organization available to the right people at the right time to minimize rediscovery of known facts, resulting in better- informed or faster decisions.
Establishing KM is a custom process and requires an analysis and an implementation phase. The analysis involves examining existing business processes, organizational structures, and available technologies to determine how applying the concepts of KM might improve results, considering the practical realities of an organization.
Why It Matters Now
The pharmaceutical industry is under enormous pressure to push more new drugs through R&D. It last solved concerns about revenue growth with faster peak sales and other marketing achievements. Now, improvements to R&D productivity are viewed as the path to achieving growth targets. In this arena, knowledge management is particularly relevant given recent changes in the way R&D is organized and conducted.
R&D has become "industrialized." Highly specialized and compartmentalized units consume, produce, and pass knowledge to other widely dispersed units in the organization. This information interdependence makes systematic and timely exchange of information essential. These information handoffs often require each specialized group to interpret or transform the information in order for it to be useful.
Finally, as the understanding of the scientific domains underpinning pharmaceutical R&D has advanced, intellectual capital has become more critical. Preventing the loss of valuable knowledge when researchers leave, enhancing knowledge assets in mergers, and supporting an increasing number of R&D decision points are among the ways KM can help leverage valuable intellectual capital.
That IT is increasingly central to creating value through KM initiatives is hardly surprising. But a sound understanding of the contents of the IT tool kit is required before undertaking KM initiatives. Without knowing, broadly speaking, about technologies that are potentially applicable, it is difficult to assess the scope of available opportunities for improvement.
Identifying and evaluating potentially relevant products and technologies under the KM umbrella should be specific to each organization. A useful approach to sift through these products and technologies is to map them to four essential processes (see "Key Steps Along the Way"). For example, collaboration products are particularly relevant to step 3, while structured data repositories and data storage are most applicable to step 2. Many tools and products are relevant to multiple steps.
Structured repositories are becoming increasingly important to pharmaceutical research and development. Step 2 involves the creation of a repository to centralize the storage of knowledge. A list of companies' researchers and their areas of expertise would be an example of an unstructured repository. Such repositories, where knowledge is input as text or documents and a classification scheme and an indexing engine facilitates searching and retrieval, are widespread in this industry.
But thanks to emerging technologies and their growing value, structured repositories are increasingly common. They enable knowledge to be centered on a model for the underlying scientific discovery paradigm. For example, a repository structured on the basis of how small molecules affect biological activity enables classification of information based on relationships intrinsic to the underlying chemical and biological processes. This facilitates assessing an organization's state of knowledge regarding particular research questions; disseminating or accessing the information in the repository; and creating new knowledge from it through mining, analysis, and incorporation of addi-tional information.
Despite its promise, KM initiatives may be retarded by continued hype and myths. Understanding the capabilities of relevant technologies makes it clear that one solution won't fit all. Only when you have a heavy investment in particular KM technologies should you consider constraining your analysis. The reuse may be justified.
Another myth is that knowledge management can provide a global fix. Successful initiatives target specific areas of decision making. KM systems that perform as intended are mapped to the idiosyncrasies of individual business processes and work habits. Moreover, the full benefits of KM are rarely immediately realized. Information must be gathered and stored, mistakes uncovered, and process and organization changes rolled out. Even then, you're not done. Scientific and IT processes and technologies continually evolve, as do business strategies, organizational structures, and the external environment. Knowledge management systems must have the flexibility to evolve to keep pace.
KM is not new to this industry, but it has not been embraced nearly enough. For knowledge to be useful, it needs to be available to be acted upon. Increasingly, it isn't. Implementing the KM processes, techniques, and technologies that enable substantial gains is an iterative process. The sooner you begin, the sooner you can iterate until you get it right.
How do you know when you've gotten it right? When you wonder how you ever managed your drug discovery process without it.
Richard Dweck is the founder and CEO of 3rd Millennium, a bioinformatics consultancy in Cambridge, Mass. He can be reached at firstname.lastname@example.org.