R&D People Matter

earth-on-microscopeIn the long-gone days of my Catalyst column on the original ChemWeb.com, I wrote about how R&D was becoming a distributed endeavour. It was going the way of large-scale data problems that are best solved using a distributed computing environment, or Grid. Now, roughly a decade later, it seems the management of globally dispersed R&D teams is coming of age.

According to Hans Thamhain of Bentley University in Massachusetts, USA, it is common practice for companies to look for partners that can perform research and development better, cheaper, and faster. Managing such a geographically dispersed team is still a complicated process, especially in high-technology industries.

He points out that collaborative technology, such as “groupware” and other tools have made multinational joint efforts more feasible. However, as ever, true success rests on the team leaders effective must understand more than just the various work processes and the collaborative technology.

From medical research to computer systems, companies try to leverage their R&D budgets and accelerate their schedules by forming alliances, consortia and partnerships with other firms, universities and government agencies. These collaborations range from simple cooperative agreements to ‘open innovation’, a concept of scouting for new product and service ideas, anywhere in the world.

Thamhain has studied 27 high-tech companies operating across 14 countries and found that for distributed R&D to work, those team leaders must understand fully their own organisation and be able to deal with the complex social, cultural, and economic issues as well as the technical factors a multinational enterprise faces.

With today’s almost infinite connectivity possibilities across the globe, companies can access the best talent and most favourable cost and timing conditions anywhere, regardless of the location of their company headquarters. “Organising and managing such globally dispersed R&D teams towards desired results is an art and a science, and a great challenge,” says Thamhain. And, while machines are very good at carrying out processes, even in the age of silicon and electrons, people still remain the best at doing art and science.

Research Blogging IconHans J. Thamhain (2009). Managing globally dispersed R&D teams International Journal of Information Technology and Management, 8 (1) DOI: 10.1504/IJITM.2009.022273

5 thoughts on “R&D People Matter”

  1. Interesting post, David. With respect to Thamhain’s research (and that of others), I’m frequently puzzled at a missing element of the collaborative technology toolkit, namely, a tool to help find and assess experts.

    Whether internally or in other institutions, it would seem obvious that a knowledge intensive organization would try its best to enable its employees to connect with the right people, beyond just providing a company directory. Yet there are few tools to facilitate the optimal identification of human resources for a given task when it comes to knowledge intensive domains. How useful is a corporate directory if you can’t figure out whom is the right person?

    While a smallish number of organizations have fielded such “expertise locators”, they remain rare and rarely heard of outside knowledge management circles. In my work in many very knowledge intensive organizations, I have yet to come across a system that does a good job of answering the question “who is the most knowledgeable person regarding X”. Approximations exist, most noticeably in the form of LinkedIn, but such systems don’t really focus on what the person KNOWS; rather, they tend to follow a traditional cv paradigm, making it difficult to truly assess what the person knows (let’s call it expertise) and compare it with the expertise of others so that a ranking can be generated.

    This is why we built http://ResearchScorecard.com, an expertise finder that covers biomedical scientists at Stanford University and UCSF. By data-mining the products generated by scientists, we are able to greatly facilitate the finding of individuals with just the right kind of expertise, AND estimate their level of expertise, so that one can make an informed decision as to whom one might want to consult first. Granted, it is easiest to do such with publicly funded scientists, but in principle a similar approach is possible even within the confines of a private company.

  2. I know about Innocentive, but are there any more narrowly focused networks you can join? Innocentive has so many projects that are way outside my area of expertise that I find time spent on it unproductive.

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