Where Do the Ideas Come From?
06/07/2011 12:00:00 AM EDT
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When it comes to purchasing and implementing laboratory systems’ software, return on investment is inevitably one of the key drivers. The up-front requirements to justify the expenditure are usually aligned to process improvement and productivity often driven by a functional need to work with dispersed teams, across different sites, regions and time zones. But there’s usually a secondary, softer requirement aligned to return on investment, but more difficult to quantify, that alludes to an improvement in knowledge management within the organisation by making laboratory information explicit, accessible and reusable.
Now, knowledge management (KM) is a scary topic, open to abuse and exploitation by unscrupulous vendors and consultants. Personally, I’ve never felt that comfortable with the term, although the principles make good sense. Furthermore, it seems that an ‘industry’ has grown around the topic that identifies KM as a potential revenue stream.
I’ve spent some time working in KM teams and with KM initiatives in my corporate career, and the conclusions that I came to were:
- KM solutions do not come in a shrink wrap box.
- You cannot implement KM, it is an outcome.
- KM is about people; technology can facilitate good KM, but that’s all.
Basically, the technology is a big part of the problem, but a small part of the solution. It’s the human element that makes KM work. We can deploy systems that facilitate the management of data and information, but knowledge is a human quality and we need the right kind of culture, behaviours, skills and expertise to take best advantage of the technology. After all, any of us could find plenty of information that explains how to play a piano, and we can find the scores of famous piano concertos, but that doesn’t mean to say we can all become concert pianists. OK, playing the piano is a physical skill – so what about the mental skills?
Technology seems to be driving us towards a belief that everything can be reduced to a logical and systematic process. And in the right circumstances this is fine. But serendipity has always had a significant role in science; so many of the major scientific breakthroughs and advances originate from ‘what if’ moments, chance observations and things that went wrong. We often learn more from failure than success! You can’t help but wonder where we would be if Lean and Six Sigma had come along a couple of centuries earlier. That’s not to say that Lean and Six Sigma don’t have a place in science, but we need to keep some reasonable space for right brain thinking alongside the systematic and structured approaches that strive to attain increased efficiency and productivity.
So can innovation become an industrial process? It’s not unreasonable to assume that we may have picked off most of the low-hanging fruit, or had it fall on our head, as far as scientific breakthroughs are concerned. Further innovation will be dependent on the exploitation of greater extremes of knowledge and understanding. And that’s where knowledge management comes in - striving to make sense of all of the data and information in which we seem to be drowning. We need the technology to assemble and look after the data, but making sense of it is down to us, and we need brains to do that. In the main, so-called knowledge management ‘solutions’ are no more than data or information management ‘solutions’. It’s only when you add the human component that KM can flourish. But even then, it still needs the right environment, hence the concept of a ‘laboratory ecosystem’.
As much as management may want to see such an ecosystem, it cannot be bought; it cannot be implemented; it cannot be deployed. It is something that, given the right environment, can be nurtured and cultivated. It is dependent on an open and collaborative culture and supportive leadership; not secrecy, discipline and rigid management. Participants need to opt in; not be forced in.
The worry is that the digital revolution may be driving a lot of our thinking to be ‘digital’, with the risk that random, analogue mindsets and gut feelings may be seen as irrelevant and inconsistent with modern concepts of science. So this is where the ecosystem comes in. How do you bring together the formality, efficiency and discipline of good science with the spontaneous, quirky and challenging ideas of innovative scientists? There’s no magic formula; it’s a leadership challenge that encompasses a range of skills that enables technology, culture and knowledge processes to underpin the ecosystem. It’s something that can take years to cultivate, and minutes to destroy.
Our ever-increasing dependence on technology for communication runs the risk of reducing the amount of time we spend in face-to face dialogue. Email, PowerPoint and Word documents do not serve as an efficient cradle for innovative thought processes and ideas. Raymond E.Dessy (1) made the point that ‘Management should spend more time in horizontal communication than in vertical communion.’ When it comes to the rest of us, it’s a good lesson, but the communion needs to be horizontal as well. Creating good opportunities for face-to-face communication and communion still has the power to spark ideas and therefore has a fundamental role to play in the laboratory ecosystem.
1. The Analytical Laboratory as Factory, Raymond E.Dessy, Analytical Chemistry 1993, 65, 802A-809A.
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