Data Can Do for Change Management What It Did for Marketing
One area so far relatively untouched by data is change management. That’s not because there isn’t a problem to solve. A survey of these different studies by Manchester Business School concluded that failure rates were consistently in the range of 60% to 90%. It’s time for that to change. The combination of predictive analytics, large data sets, and the processing power of today’s computers is starting to transform change management. Just as the discipline of marketing has transformed from soft to hard science in the past 20 years, so too will the practice of change. But before that can happen, we have to understand why data has failed to catch on in change management to date.
Business in the 21st century is being redefined by a data-driven revolution. Take the MIT Media Lab’s experiment to see whether it could estimate retail sales performance on “Black Friday,” the day following the US Thanksgiving holiday. Instead of waiting for data from the stores themselves, they used location data from mobile phones to infer how many people were in the parking lots of major retailers. Combining this with data on average spend per shopper enabled them to estimate a retailer’s sales, even before the company had recorded it themselves.
This is just one example. Judgments that used to depend on human intuition alone are now supported by insights gleaned from complex analyses and predictive modeling. Retailers combine data on demographics and weather to predict sales and develop merchandising plans. Banks and lenders have predictive analytics engines that tell the lender the probability that a customer will pay them back. Housing market price changes can be more accurately predicted from analysis of Google searches than by a team of expert real estate forecasters. Investment is rushing into big data analytics as firms seek to find ways to first understand and then take advantage of the possibilities on offer. There has been a rapid uptake in health care, consumer marketing, crime reduction, agriculture, scientific research, and many other areas.
One area so far relatively untouched is change management. That’s not because there isn’t a problem to solve. The failure of major transformation projects to deliver the expected benefits is a well-documented phenomenon: many change programs simply do not achieve their business goals.
It’s time for that to change. The combination of predictive analytics, large data sets, and the processing power of today’s computers is starting to transform change management. Just as the discipline of marketing has transformed from soft to hard science in the past 20 years, so too will the practice of change.
