As well as having a strong view on this myself, I was delighted to see a friend of mine weigh in with a well-articulated argument as to why they can. That friend is a man who used to be my right
Andy is a very capable statistician, leader and marketer. He is someone who have come to admire and respect over the years we have worked together. Andy Sutton currently leads data & personalisation for Woolworths in Australia. As someone with a foot firmly in both technical & business camps, he is a true hybrid leader worth listening to.
Over to Andy to explain why this can work…
Why non-Data Science leaders can be effective
I felt compelled to write my first ever article following a conversation I was part of on LinkedIn last week. To cut a long story short, I commented on a post which was berating data science leaders who don’t have a data science background. I didn’t agree with the perspective that only data scientists can lead a data science team, but faced a number of return comments suggesting I was wrong.
I’ve been fortunate to work for some amazing leaders in my roughly 20 years in data and analytics (Paul being one of them). On the surface these leaders haven’t had a huge amount in common. I’ve worked for marketers, sales directors, commercial managers, IT leaders and strategists – so it’s fairly obvious that a technical background in data and analysis isn’t a prerequisite for me to be led by someone so what does it take?
This isn’t exhaustive but the beginnings of a list to which anyone reading this can add. Would be interesting to know whether we all have the same views – or if different aspects appeal to different people
What leadership characteristics make the difference?
The ability to link the work of an individual to the work of the business. If you can make everyone in the business feel like they’re critical to the success of it then you’re on to a winning formula.
Too often I’ve seen teams with low morale because their role is seen as a necessary evil or BAU rather than talked up as contributing to the strategy. Is it any wonder people don’t feel motivated or inspired in their role if their leader doesn’t see their role as important.
Leaders who trust their team members employ them and then get out of their way to let them do their roles. Easier to say than do though! If you micro-manage then teams & individuals will lose the ability to think for themselves.
As an example I once had a micro-manager. I gave up trying to do my best work because I knew that however good a piece of work was she would find a way to ‘add value‘ to the output. So I started delivering at about 75% and left her to do the remaining 25%. Far better would have been to trust me to deliver the output and get the result she wanted.
The ability to know what you don’t know and ask your team to fill the gaps for you. Servant leadership is the new buzz word as we all move in to an agile world – but the best leaders have always known this.
I once had a leader who told me the first 6 months of leading a team he had no idea how to help them as they were far more technical than he was. He realised after 6 months that wasn’t his role.
His role was to sell what they did to the wider business, get positive feedback for them, generate more work and help them deliver it. He wasn’t there to jump in and help them – and he didn’t know how to anyway.
What have I missed? What has been your experience?
Even as I write this I’m sure there are far more bullets that others will think of – but I wonder if technical ability will be in any ones list? I’m sure when I started out in analytics I would have put a technical manager as one of the bullet points – but times have changed.
Part of this relates to the fact that the analytics world is moving so quickly. In the age of big data, machine learning, deep learning, AI and the like few people have the technical skillset across all of these disciplines. Even fewer would also have the experience, relationships and vision to lead great teams.
This is a very wide generalisation, but some of the most technically competent analysts I’ve worked with have no desire to lead teams. They would much rather be building and deploying their own models or algorithms.
I’m sure there are data scientists and analysts who make great data science leaders – but I’m equally sure there are data science experts who make useless data science leaders. Being a guru of data science is not a pre-requisite in my mind.
What do others think?