Questions and Answers About Analytics as a Source of Business Innovation
Some of the questions from our March 15, 2017, webinar went unanswered, so we’re addressing them in upcoming blogs.
Topics
Competing With Data & Analytics
On March 15, 2017, MIT Sloan Management Review held a free, live webinar to share the findings and insights from our latest Data and Analytics Initiative research report, “Analytics as a Source of Business Innovation.” The report summarizes our findings about the increased ability to innovate with analytics and how it is producing a surge of benefits across industries.
If you missed the webinar, the recorded version is available for free, on-demand viewing. Thanks to everyone who participated in the webinar — we had a great turnout.
During the webinar, many participants asked questions. Unfortunately, we had time to answer only a few during the webinar itself. But we didn’t want to leave so many unanswered. So, instead, we’ll answer some of the questions in this and an upcoming post. We’re sorry that we still won’t be able to get to them all, but we hope we’ve covered the ones asked by the most people. We’ve paraphrased some of the questions to provide context, combined similar questions, and anonymized them.
How does one embed data analytics in business processes that predominately rely on qualitative data, such as sales leads?
In our 2016 report, “Beyond the Hype: The Hard Work Behind Analytics Success,” we discussed the blending of analytics and intuition. That report quoted Jim Sprigg of InterContinental Hotels Group, who said, “Intuition versus data is a false dichotomy.” The core of the idea is that approaches that rely on either quantitative or qualitative data alone will likely fall short of approaches that combine both. So to figure out how to embed, it may be helpful to first think about two “why” questions:
- First, why do they rely on qualitative approaches? The business processes you mention may predominantly rely on qualitative data; is the word “predominantly” used because people have tried incorporating analytics but haven’t found them useful? Or is it because that’s historically how the processes have been done. The path toward using more analytics (or perhaps not) can be quite different depending on circumstances.
- Second, why embed analytics? I think (of course) that there are many good reasons that one would embed more analytics. But what does the organization hope to obtain? Management involves allocation of resources.