Extreme Ownership in Data Analytics
Extreme ownership in data analytics has made its way into day to day business thinking when Jocko Willink and Leif Babin published the book with the same name in 2015. Ex Navy SEAL officers Willink and Babin advocate ownership across all areas of personal and professional life. Pointing fingers is not productive and one needs to take responsibility for everything in his or her personal sphere of influence.
Based on valuable lessons from the Iraq war, it is crucial to admit and own mistakes, and develop a plan for improvement. In business this applies to each and everyone as well. Business leaders adopting extreme ownership are not driven by their egos or personal agendas. All that matters is bringing the mission to a successful end. There are no bad teams, only bad leaders. Willink and Leif successfully started a business consulting career based on extreme ownership ().
Blaming others is unacceptable
Jumping from Navy SEALS to a business context, we can also apply extreme ownership to a data analytics context. In data analytics business users often point fingers to the people that produced a report, dashboard or some form of data model. It’s an easy get-out-of-jail card if you don’t fully understand the numbers. Often it is this lack of ownership that dictates end-users’ behavior. End users often think they can’t take ownership of the numbers simply because they didn’t produce the report in the first place. Nor did they build the data repository and its routines that form the basis of these reports. They think this absolves them from any responsibility.
Know your game, know your numbers
This needs to be turned around. The reports represent your part of the business and you need to take full ownership of that. Know your game, know your numbers. Self-help analytics is the perfect vehicle for you to do just that. Recreate the numbers and see if they make sense. Ask the questions and fully understand the logic that is applied. It’s only your business we’re talking about here!
In our organisation I’m responsible for our Data, Planning and Analytics projects. How well these projects perform dictates how well my business unit is performing against set delivery targets. We have a fantastic supporting department that provides relevant dashboards and reports, but sometimes the numbers don’t make sense, have confusing (or no) definitions and are difficult to interpret. By sinking my teeth in the underlying data warehouse and cube layer myself, rather than just relying on the reports provided, I’m able to reconstruct the key metrics. This allows me to have a meaningful dialogue with the relevant parties, thereby gaining a richer understanding of the levers that drive these metrics.
Don’t get me wrong, the objective here is not to create an overwhelming amount of shadow IT or analysis-paralysis that will do more harm than good. This exercise should always remain focused on facilitating a constructive discussion between relevant parties for the greater good of your mission at hand: achieving your business goals.
Extreme ownership principles in data analytics also dictate that you as a business user should try to be involved as much as possible in the early stages of new development projects (providing input into report specifications and business logic formulation), as well as throughout the project in testing and review activities.
Ultimately, good old self-help analytics, guided by extreme ownership principles, will drive much needed data literacy within the business community. And this in turn will translate into business results, especially in today’s challenging business landscape.
Read more from Erwin around data, analytics and planning: