During my career in analytics, I have had the fortune of working with multibillion dollar organizations looking to set up an analytics capability. While I served them in different capacities–a full time employee, a third party consultant, an independent consultant–and while they all had very different business models, I found that they had one thing in common: The need for change management.
Most organizations approach analytics with a similar mindset. They see it as a tool for survival, and a necessary competitive advantage which any successful company needs to survive.
Of course there are a multitude of challenges associated with implementation, but it is middle management who struggles the most. On one side they face pressure from executive leadership to deliver timely results, and on the other they’re tasked with helping their team adjust to a new, analytics focused, work environment.
While almost any large scale change will pose a challenge for an organization, analytics is specifically difficult because it is not successful until it becomes part of day to day work environment. Until it is adopted at all levels of the enterprise, a company can never untap its full potential or deliver returns on the large investments made in data and IT systems. Therefore, it becomes imperative that as organizations gear up to implement enterprise wide analytics capabilities, they also recognize the need for change management.
In my career I’ve seen firsthand the necessity of change management. One project involved a multi-billion dollar MNC whose focus was on innovation, both in its business practices and its products. The CEO felt that, in order to stay current and competitive, the company needed to adopt analytics into its structure. Over several years, significant investments were made in the areas of data infrastructure and BI tools. The company conducted monthly and quarterly reviews which were overseen by an executive leader with a highly analytical mindset. However, managers throughout the company all echoed the same complaint: They were not given enough information to make right decisions at the right times, despite the fact that there was a team dedicated to data collection and circulation. Company executives were baffled. How could that be possible?
The problem was that the analysts were delivering data without providing insights. They were using fancy BI tools and creating complicated spreadsheets which the rest of the company couldn’t decipher. While the organization had spent millions of dollars getting the tools and the data, no one had defined a common vision or even the term “analytics” across the company. Despite of all of the money and time they had spent, their data was useless so long as it wasn’t being correctly utilized.
On my end, the toughest part has always been convincing front line managers and analysts not to view large scale analytics as a terrifying unknown, but as something that will make their lives easier and add value to their business. The keys to a successful implementation are simple: Communication, patience, and time. It can truly be as simple as listening to managers and understanding where knowledge gaps lie. All it takes is a willingness to have clear dialogues and an understanding that nothing worth having happens overnight.