Measuring Geographic Innovation at EMC Labs China

Measuring Geographic Innovation at EMC Labs ChinaI have been writing about my new experience managing a research team in China. The well-trodden rules of engagement for “glocalization” don’t apply in a reverse innovation environment. I’ve been feeling my way around my new role, looking for an approach to use as my baseline. Here’s what I’ve come up with so far:

Get to know each member of the research team and launch new initiatives that (a) map onto their skillsets and career goals, and (b) deliver value back to the corporation.

I visited China and began to meet (and understand) the team. In particular, I met several people with great strength in analytics and data mining, and I spoke to them about a hypothesis that, if proven, would provide great value to EMC. This hypothesis asserts that the analysis of global research and innovation activities (in the form of emails, documents, presentations,etc) would yield insight into the specific growth of EMC knowledge in different areas of the world.

They were engaged. Two of them (Tao and Baoyao) set off on parallel paths to prove the hypothesis. Tao focused on Topic Modeling, Baoyao focused on a Natural Language Processing variant. Research teams are meant to be autonomous. With the help of several university interns, the EMC Labs China team dove into the work, and I returned to the U.S.

Several weeks later, they shared preliminary results. The chart below shows topic comparisons between the research activities of two different countries (China and Russia). As part of Tao’s research he generated the following chart:

GK
This chart profiles two countries (China = 0, Russia = 1), bucketizes the topics into ten categories, and then analyzes the distribution of documents into those categories. In certain areas it is clear that Russia has more focus than China, and vice versa. I won’t dive into all of the details here, but there are some areas where Russia has demonstrably more focus (e.g. compression algorithms) while China clearly has more involvement in others (e.g. Hadoop improvements).

Baoyao, as part of his NLP investigations, created the word cloud below which yields further insights into innovation and research activities within Russia:

RCOE

I was very pleased with the both the accuracy of the results and the insight I gained from their efforts. I hope to spend more time in future posts elaborating on some of the difficulties, successes, and lessons learned for this particular use case. The point of this post, however, is about the overall approach to managing global innovation.

The team essentially validated my hypothesis. They were able to use their considerable skills in solving a significant problem. The stakeholder in this effort (me) gained great insight. It is valuable. Their efforts resulted in visibility inside and (as of this blog post!) outside of EMC.

The model of mapping valuable business problems to global skillsets and career goals worked in this case. Future posts will explore other insights that I am gaining during this process.

image credit: ecvv.com

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Steve ToddSteve Todd is Director at EMC Innovation Network, and a high-tech inventor and book author “Innovate With Global Influence“. An EMC Intrapreneur with over 180 patent applications and billions in product revenue, he writes about innovation on his personal blog, the Information Playground. Twitter: @SteveTodd

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