For any of us that have been building social and collaboration solutions over the last few years, it’s sometimes felt like we are pushing water uphill. We all intuitively know that, to use the slogan of the Democratic Convention, “we are stronger together”. We know that helping to bring people together, to help them share knowledge, insight, or opinion, to help them work together as a team instead of individuals, brings value to the business.
However, we’ve been challenged to measure this value in a quantifiable way. One of the big challenges IMHO is that social and collaboration systems have not been adequately integrated into the actual act of doing business, which has made it difficult for us to reliably quantify changes in engagement with changes in business outcome. Thankfully this is now starting to change and one of the areas that is starting to “get onto the collaboration bandwagon” is my own area; that of analytics and data science.
Tim Vincent (our IBM Analytics Group CTO) and Bill O’Connell (IBM Distinguished Engineer) have just recently released a blog post (Insight Ops: The road to a collaborative self-service model) that starts to paint a picture of a new world of analytics where the act of doing data science is no longer a solitary act, but rather one which is transparent, collaborative, agile, and iterative; a system that allows all participants to actively engage in the process; not just the data scientist or analyst, but the business user, the executive, the information architect, the developer, and the subject matter expert. And there is no reason to imagine that this couldn’t also include the consumer or citizen in the future.
This blending of social and collaboration with analytics and data science, is particularly exciting for me because I believe it will at last get the analytics community really engaged and enthusiastic about the potential insights that they can derive from the collaboration and social data generated within the data science experience. It’s human nature for us to care about the things that effect us, and once analytics systems become social and collaborative, I guarantee that every data scientist will start thinking about ways that they can maximize the value of this data for themselves and their projects.
We are already seeing this happen inside IBM as described in the Insight Ops blog post, which talks about “capturing and capitalizing on knowledge”, tapping into the collective intelligence of the analytics community, and using analytics to help us find that “needle in a haystack”.
I’m really excited to be part of this new movement inside IBM and anticipate lots of exciting innovations that will completely transform how data science happens. Bringing together what was previously two separate communities within IBM, the bigdata folks and the social guys, is already generating new ideas and perspectives that I believe will make data science more inclusive, collaborative, agile, transparent, and ultimately more successful. We are most definitely “stronger together” :-)
And for those of you who may be attending IBM World of Watson 2016 I hope to be there sharing some of the exciting work we are doing with my talk on “Collaborative Analytics: The next frontier for social and collaboration systems”.