I am exploring the intersection of knowledge management and data science to leverage emerging content analytics, natural language processing, and machine learning capabilities that can unlock value in unstructured information.
RECENT EVENTS & PRESENTATIONS
KM Workshop 知識管理 for Taiwan PDA and FDA, Taipei, Taiwan – 3/2018
Knowledge Leaders Council, Thousand Oaks, CA – 2/2018
The Conference Board Knowledge & Collaboration Council, Boston, MA – 10/2017
Knowledge Leaders Council, Washington DC – 9/2017
4th Life Science Knowledge Management Summit, Boston, MA – 8/2017
A question at work reminded me of some research I had done recently about the new organizational knowledge clause in the latest revision of ISO 9001. It had nothing to do with fish mind you, it’s just not that easy to find a related visual.
Now, ISO 9001:2015 has a new clause, 7.1.6, on organizational knowledge and its management. This clause has no equivalent in ISO 9001:2008. In fact, it seems to be the only clause that is completely new. The other clauses seem to have some equivalent in the earlier version, in letter or in spirit.
The author goes on to differentiate between a strategy and technology-only approach to KM; I quote the strategy definition here:
Look at one definition of knowledge management: KM is an enabler to achieve an organization’s objectives better and faster through an integrated set of initiatives, systems and behavioral interventions, aimed at promoting smooth flow and sharing of knowledge relevant to the organization, and the elimination of reinvention. KM seeks to facilitate the flow of knowledge from where it resides, to where it is required (that is, where it can be applied or used), to achieve the organization’s objectives.
The article continues with an outline of a strategic approach that is worth a closer look. Now I’ll have something to read over sushi tomorrow.
While I think we naturally conclude the explosion of information in the medical research world is a good thing, there are of course challenges. The problem is compounded when you consider the information both inside and outside an organization.
It’s always exciting to see advances involving things like big data and semantic web applied to medical research. Supplementing or enhancing the human researcher, not replacing them, simply described as “computer-assisted serendipity” in this interesting article describing work at Oak Ridge National Laboratory focused on literature-based discovery, is worth a look.
A side effect of this information explosion, however, is the fragmentation of knowledge. With thousands of new articles being published by medical journals every day, developments that could inform and add context to medicine’s global body of knowledge often go unnoticed.
Uncovering these overlooked gaps is the primary objective of literature-based discovery, a practice that seeks to connect existing knowledge. The advent of online databases and advanced search techniques has aided this pursuit, but existing methods still lean heavily on researchers’ intuition and chance discovery. Better tools could help uncover previously unrecognized relationships, such as the link between a gene and a disease, a drug and a side effect, or an individual’s environment and risk of developing cancer.
One of the more memorable items from his talk was about how to organize a children’s party (within the context of complexity). Anyone who’s been a parent and/or worked in a large corporation will find it amusing and insightful. I was happy to see it captured in this video below:
The technology that organizations wanted to employ was Microsoft’s SharePoint. There were several generations of KM technology—remember Lotus Notes, for example?—but over time the dominant system became SharePoint. It’s not a bad technology by any means, but Microsoft didn’t market it very effectively and didn’t market KM at all.
and something quite prevalent in my world (you may have heard of this “big data” thing):
KM never incorporated knowledge derived from data and analytics. I tried to get my knowledge management friends to incorporate analytical insights into their worlds, but most had an antipathy to that topic. It seems that in this world you either like text or you like numbers, and few people like both. I shifted into focusing on analytics and Big Data, but few of the KM crowd joined me.
In my view, one thing is certain: there is tremendous value locked in the heads of employees, hiding in content of all types, and waiting to be found in large data sets.
Enterprise tools of all kinds, from content management to search to analytics, are continuing to evolve. The increasing demands of global competition are driving a more collaborative workforce.
Regardless of wether we continue to label efforts to unlock that value as knowledge management, they will remain important.
Employees that were rated as more innovative didn’t have bigger networks; rather, they had more bridging ties—ties that connected them to other employees who were themselves not connected.
If we are circulating too much with people we have known forever or people who themselves are all spending time in the same meetings and interactions, then we are not getting the performance impact we can from social-media tools. Bigger is not better. The magic lies in the new ideas and perspectives that can come from connections into different networks.