I’ve been writing several blog posts recently that describe EMC’s use of analytics to accelerate the innovation that is coming from global university research partners world-wide. The geographic locations of many (but not all) of our university research partners are depicted on this map.
In addition, in my last post I described how EMC tries to keep track of “what” research activities our global partners are working on through the use of Stanford’s Topic Modeling Toolbox:
In this post I’d like to shed a little more light on how to take these research themes and map them to specific geographic regions. In order to do this, it helps to describe the inner workings of EMC’s innovation analytics framework in general.
The framework is founded upon activities that are closely tied to innovation, including:
- University Research
- Customers/Partner engagements
- Knowledge Transfer/Brown Bag sessions
- Employee ideas
- Intellectual property
Visually these activities can be depicted as follows:
The analytic framework is essentially a data gathering process that can record these activities via a variety of methods, including (a) manually, (b) via email, (c) via crawling of a file system, or (d) as part of Outlook calendar invites. No matter what the source of ingest, all of the innovation activities (including university research), are funneled into an analytic sandbox, which stores both structured and unstructured content (the graphic below describes this approach, and was previously described in a series of posts on the data analytic lifecycle).
The beauty of this approach is that the geographic location of the structured and unstructured data is preserved during the ingest phase, and thus available for analytic queries. For example, the diagram below highlights an answer to the question: “What types of research has EMC funded recently in Russia”?
The resulting map and word cloud depicts that compression research is occurring in Saint Petersburg, Russia. This is due in large part to the strong mathematical skills of the EMC employees and universities in that region.
I recently contributed an article that described my own personal empirical data about innovation at our global R&D locations. The approach described above is an alternative, data-driven approach to classifying a company’s global innovation activities.
Who are the EMC employees conducting the research? Can the analytic framework drill down to the employee level and discover which EMC mathematicians are involved with this compression collaboration, and/or which Russian employees participate in university research in general?
The answer is yes, and more detail will be described in an upcoming post.
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Steve Todd is an EMC Fellow, the Director of EMC’s Innovation Network, and a high-tech inventor and book author Innovate With Global Influence. An EMC Intrapreneur with over 200 patent applications and billions in product revenue, he writes about innovation on his personal blog, the Information Playground. Twitter: @SteveTodd