Updated: Aug 10
Having worked within the data industry for over 20 years it is fantastic to see how data has become such a strong asset in order to drive transformational business change.
However, the term data has become a catch-all for a number of different tasks depending on what your role is within the business. This can be anything from creating a new platform, new product development, operational efficiencies to drive growth through personalisation at scale or business intelligence.
All of these initiatives require different approaches, tools and technologies – but how do all of these data driven initiatives ladder up to driving business change and who owns the overall data strategy to manage investment, efficiencies in development and governance.
Often without the investment in a Chief Data Officer this can fall between different responsibilities within a business structure. It can lead to disparate strategies and investments being made to solve a specific problem or becomes a never-ending IT implementation.
Recently as part of new business meeting we came across this situation. There was an ambition to be data driven, but there were very different definitions of what that meant across the senior management team on what that actually meant and where to focus effort.
It felt very much like the fable of the blind men and the elephant, where as each man touched the elephant they would describe different objects, from a fan for the ear to a rope on the tail. Each equally correct based on their limited exposure - but not able to appreciate other areas of the elephant or business in this case.
However, after a very healthy debate it came down to understanding what the priority of the business was and the need to create an organisation data agenda as to what was going to make the biggest impact. Only then could we start focussing on what the data initiatives, tools and technology were in order to fulfil these.
Data strategy isn’t just about the clever algorithms and the most sophisticated tech – it’s determining what the business problem it can solve is and then understanding how to support this using data and tech.