Competing With Data & Analytics
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Here at MIT Sloan Management Review we’ve been conducting data analytics research with our partner, SAS, through two channels: a survey on how companies are using analytics and interviews with global business leaders. In the process, we’ve made some intriguing discoveries. One big one: A significant information transfer gap is compromising many organizations.
While companies are gathering all manner and volume of data — structured and unstructured, terabytes and petabytes — when it comes to getting insights from that data to the frontlines, where insights really matter, many organizations are losing their way.
What that means is that an important opportunity — the ability to act on insight to influence things like innovation and competitive advantage — is being missed.
Here’s how one CEO we spoke with outlined the promise of effective information transfer to the frontline:
“The biggest problem corporations face, whether it’s customer service, whether it’s sales, whether it’s an airline rep, is that they’re asked to make critical decisions for the corporation, but the information they’re provided is very, very hard to consume and use,” said Opera Solutions founder and CEO Arnab Gupta. “Increasingly what we are finding is when you use the power of predictive analytics and the sciences, you can bring information to the front line — average, normal human beings — in a way in which they can apply their creativity by simplifying and moving away from the world of information to the world of directive actions and insights.”
But the reality is: a majority of companies don’t find a way to disseminate insights to the frontline.
According to our survey data, 65% of respondents say their organizations are effective at capturing data, but just 46% of respondents say they are effective at disseminating information and insights. [You can read more about our initial research findings in “Innovating With Analytics,” in the Fall 2012 issue of MIT SMR. The full report will be available mid-November.] Compounding the issue, only four percent of organizations use all the data they collect. Nearly 30 percent use “not much” of the data they collect.
One CEO of a multinational outsourcing and technology development firm we spoke with estimates that while his organization captures about 80 percent of its workflow data, it utilizes just 20 percent.
“We believe that a lot of this information which is being captured is not being used, in the sense that we are not really, from a human resource management point of view, addressing challenges to people based on their social preferences or the way they use [corporate intranet] social media. This is a complete black hole as far as we are concerned,” says Ganesh Natarajan, vice chairman and CEO of Zensar Technologies. “Nearly 40 percent [of our data] is being analyzed. . . probably less than 20 percent is being used. We have a long way to go before we can regularly transfer insights into productive applications.”
This information transfer gap exists at Zensar not because the data is unavailable or because the organization can’t slice and dice it, but “because somebody hasn’t thought of, ‘yes, we need this information and we could use it in this way,’” says Natarajan. “I think that is the interesting area here, because the ability to integrate more and more into the learning process of the organization is really what analytics will, to my mind, eventually deliver.”
We think several cultural factors may explain why companies are experiencing this information transfer gap. Difficulties in sharing data and insights across silos play a role, as do a lack of confidence in the quality of data across silos, which can sabotage delivery of insights to those who can use them best. Plus, few companies have a chain of communication that can effectively transfer insights from the place they are created to frontline staff who can get the most value from them.
Having insights flow to the front-line is more about having a data-aligned culture than overcoming some sort of technology barrier — it requires an organizational mindset that can nurture data’s metamorphosis from insight to value.