Database Reference
In-Depth Information
2.8 Case Study: Global Innovation Network and Analysis
(GINA)
EMC's Global Innovation Network and Analytics (GINA) team is a group of senior
technologists located in centers of excellence (COEs) around the world. This team's
charter is to engage employees across global COEs to drive innovation, research,
and university partnerships. In 2012, a newly hired director wanted to improve
these activities and provide a mechanism to track and analyze the related
information. In addition, this team wanted to create more robust mechanisms
for capturing the results of its informal conversations with other thought leaders
within EMC, in academia, or in other organizations, which could later be mined for
insights.
The GINA team thought its approach would provide a means to share ideas globally
and increase knowledge sharing among GINA members who may be separated
geographically. It planned to create a data repository containing both structured
and unstructured data to accomplish three main goals.
• Store formal and informal data.
• Track research from global technologists.
• Mine the data for patterns and insights to improve the team's operations
and strategy.
The GINA case study provides an example of how a team applied the Data Analytics
Lifecycle to analyze innovation data at EMC. Innovation is typically a difficult
concept to measure, and this team wanted to look for ways to use advanced
analytical methods to identify key innovators within the company.
2.8.1 Phase 1: Discovery
In the GINA project's discovery phase, the team began identifying data sources.
Although GINA was a group of technologists skilled in many different aspects of
engineering, it had some data and ideas about what it wanted to explore but lacked
a formal team that could perform these analytics. After consulting with various
experts including Tom Davenport, a noted expert in analytics at Babson College, and
Peter Gloor, an expert in collective intelligence and creator of CoIN (Collaborative
Innovation Networks) at MIT, the team decided to crowdsource the work by seeking
volunteers within EMC.
Here is a list of how the various roles on the working team were fulfilled.
