Business Analytics Talk by Iqbal KaurFebruary 25, 2015
During my Analytics-focused career, I have had the fortune of working with multi billion dollar organizations looking to set up capabilities in Analytics. While I served them in different capacities (as full time employee, a third party consultant, an independent consultant) and while they all had very different business models, I found that they all had one thing in common – the need for Change Management alongside something as paradigm changing as Analytics.
Analytics is viewed by most organizations in similar ways. Top management recognizes this as the competitive advantage, as a tool to survive the ever-changing economic realities and as something that has become part of any forward-thinking company that expects to hold its own in next 5-10 years. The analysts who have been doing MIS or Financial Analysis all their careers are much closer to reality when it comes to data availability, IT systems and process changes needed to implement analytics on a large scale. Understandably, they are more than hesitant when they hear CXO stalking about Analytics as the need of the hour. Middle management is the one worst hit – On the one hand, they are under pressure from executive leadership to deliver results and on the other hand, they have a team that is worried about how this renewed focus on Analytics in the workplace will shape their professional future.
While this scenario is true for most large-scale changes, the challenge with Analytics is that it is not successful unless it becomes ingrained in the day-to-day culture of the organization. Unless it’s adopted at all levels of the enterprise, one can never unlock its full potential and deliver returns on the large investments made in data and IT systems. Hence, it becomes even more imperative that as organizations gear up to set up an enterprise-wide Analytics capability, they need to recognize the change management needs that would accompany it.
Just to put the need for change management in perspective, I would like to share an example from my experience. A multi-billion dollar MNC that uses innovation in its products as the competitive edge decided that it needs to adopt Analytics in order to stay relevant as newer younger companies were coming up with an equally innovative product range. Over the last few years, significant investments were done in the areas of data infrastructure and Business Intelligence (BI) tools. There were monthly and quarterly reviews presided over by an executive leader with a highly analytical mindset. However, process owners across this business function chain kept saying that they didn’t have enough information to make right decisions at the right time. All this when there was a dedicated team analyzing raw data and churning out reports to all levels of this business function at a regular frequency. So where exactly was the issue?