The complex search process of invention
I’ve lost count of the number of times I have seen business cases for search and for collaboration that cite ‘enhancing innovation’ as a reason for investment. When you dig deeper you realise that this is just a sound bite that has no basis in reality. A significant amount of effort has been expended over the years on measuring innovation rates, for example based on patents and published research papers, but inside the enterprise things are a lot more complex. Innovation and invention take time, and there is no better example of this than the stories behind the award of the 2016 Nobel Prize for Chemistry to Sauvage, Stoddart and Feringa. The award is the culmination of research dating back to the early 1980s an then a process of success and disappointment but above all a commitment to a goal. Another stimulus was the recent acquisition by Nokia of Bell Labs, the epitome of an invention powerhouse. Bell Labs was where Claude Shannon founded the digital age in 1948 with his paper on the Mathematical Theory of Communication.
Perhaps because I have worked alongside Ben Feringa on a Royal Society of Chemistry committee this year’s award has caught my attention more than most. I recalled seeing a research paper some time ago about the the processes behind invention and it took me a while to track it down to the journal Research Policy. It makes interesting reading. I should say at the outset that ‘search’ is being used in the widest of contexts, not the use of a search application. The authors summarise their paper very well.
“Using an extensive archival content analysis of notable inventors we find that the search and discovery process of invention is inherently complex, non-linear, and disjointed. Successful inventors are skilled at managing these complex systems, receptive to feedback, and able to revisit and change course. Our search model includes a stimulus, net casting for information, categorizing that information, linking unrelated ideas, and discovery. Our findings articulate the search process as a complex progression through a series of simple stages. As such, the study contributes to our understanding of complexity and the complex systems view of the invention process.”
There are parallels here with the way in which business decisions are made. It is not just a process of undertaking a search and then making a decision. There are multiple steps with a significant amount of feedback at each step. Only though understanding the processes of decision making, of which invention is arguably a special case, can we begin to develop search applications that support this process. As an example, being able to maintain a search query history so that a search can be re-run with a small change in query structure on the basis of further consideration of the challenge. One of the implications is that seemed relevant at the time of a search may turn out to be irrelevant only a day or two later. This rather makes a mess of assessing ‘relevance‘ as the basis for search performance.
The Research Policy paper is not open access, and I’m not suggesting that purchasing it is going to transform your search application in the next 24 hours. It does provide an excuse for me to highlight the need to understand user requirements at a very granular, process-specific, level, and not with simplistic surveys about ‘What information do you need to find’ or providing an ability to personalize that is too often an excuse not to look carefully into user requirements.