Database Reference
In-Depth Information
related to innovation and researchers spanning multiple areas within the company
and outside of it. GINA also enabled EMC to cultivate additional intellectual
property that led to additional research topics and provided opportunities to forge
relationships with universities for joint academic research in the fields of Data
Science and Big Data. In addition, the project was accomplished with a limited
budget, leveraging a volunteer force of highly skilled and distinguished engineers
and data scientists.
One of the key findings from the project is that there was a disproportionately
high density of innovators in Cork, Ireland. Each year, EMC hosts an innovation
contest, open to employees to submit innovation ideas that would drive new value
for the company. When looking at the data in 2011, 15% of the finalists and 15%
of the winners were from Ireland. These are unusually high numbers, given the
relative size of the Cork COE compared to other larger centers in other parts of
the world. After further research, it was learned that the COE in Cork, Ireland had
received focused training in innovation from an external consultant, which was
proving effective. The Cork COE came up with more innovation ideas, and better
ones, than it had in the past, and it was making larger contributions to innovation
at EMC. It would have been difficult, if not impossible, to identify this cluster
of innovators through traditional methods or even anecdotal, word-of-mouth
feedback. Applying social network analysis enabled the team to find a pocket of
people within EMC who were making disproportionately strong contributions.
These findings were shared internally through presentations and conferences and
promoted through social media and blogs.
2.8.6 Phase 6: Operationalize
Running analytics against a sandbox filled with notes, minutes, and presentations
from innovation activities yielded great insights into EMC's innovation culture.
Key findings from the project include these:
• The CTO office and GINA need more data in the future, including a
marketing initiative to convince people to inform the global community on
their innovation/research activities.
• Some of the data is sensitive, and the team needs to consider security and
privacy related to the data, such as who can run the models and see the
results.
