GUEST POST from Steve Todd
Using analytics to improve innovation processes is, well, innovative in and of itself.
I spoke with Tom Davenport last week about using analytics to understand innovation. While my own company (EMC) and other corporations use analytics across many different parts of the business,Tom and I agreed that it is unique to use data scientists to gain insight into innovation processes.
So how exactly is it done?
I have received requests for more detail on the approach that we are using, especially from managers that are unfamiliar with the field of analytics.
In response to these requests I’ve decided to write a series of posts that describe the evolution of my own experience applying analytics to innovation data. These posts will roughly fall into three categories:
1. A description of the data that my team collects internally. Most of my posts have focused exclusively on idea submissions from employees, but the larger repository contains innovation and research data beyond just idea submissions.
2. The training that I underwent to manage my own personal team of Big Data Scientists. This training contains a six-step process that I undertake to gain innovation insight into the data we have collected over the years.
3. My ongoing use of social media to accelerate the collection of innovation and research data world-wide, and the specifics of the approach that I take to motivate teams of “volunteer” data scientists at worldwide locations.
If you are interested in doing some pre-reading along these lines, I recommend taking a look at the posts that I have already written on the topic. I also recommend taking a deeper look at the training that I undertook to increase my own expertise in this area. The diagram below depicts the approach that I use for gaining analytic insight.
Please leave me a note in the comments section if there are specific topics you’d like to see explored along the way.
As Bill Schmarzo put it, be prepared to embark on a most excellent journey.
imagecredit: theosgroup
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