The proceedings of the 2014 Workshop on Human Centered Big Data Research was recently posted.  At this meeting, I was selected to make a presentation on the organizational structure and application of supply market intelligence.  (My presentation was also captured in a video that you can watch if so inclined!)

My presentation presented results of a recent study on key actions that organizations are taking to improve access to supply market intelligence.  The research shows that many organizations are using haphazard approaches to drive insights into supply markets, but that there is an increasing recognition of the value of market intelligence in many industries, particularly in manufacturing.

It was also clear that the field of Big Data is expanding rapidly, and that intelligence agencies are including many different approaches to collecting data from multiple sources to drive insights.  For instance, a study by Samantha Szymzcak, Dan Elk, and William Elk  identifying human attention as the limiting resource for employing Big Data for operational use. The framework leverages prior research in attention management, sensory perception, and joint cognitive systems to lay out a Human Centered Big Data Research agenda.

Another fascinating topic was that of human “sense-making”, which means that there is not always a need for perfect data.  Alex Endert and Bill Pike discussed how many phenomena we wish to understand do not always have a  defined start and end, data about these phenomena arrive in stream over time. The challenge is to characterize the phenomena from this stream, allowing models or hypotheses that explain the phenomena to evolve over time as data arrive. Their ultimate finding – perfect data is not needed to drive the right intuition and deductive decisons in many cases!  This is good news, as many of the datasets found  in supply chains are indeed imperfect…

There are many other great presentations and abstracts that occurred at this conference that anyone interested in Big Data and intelligence should browse!