Driving the data agenda: Leadership in the algorithm era

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I engaged in a very interesting debate through LinkedIn recently, relating to a job advertisement for a director of analytics. I loved the discussion because it was centred on the capabilities required to take on a leadership role in data-based analytics. It caught my attention because it reflected one of the personal questions I challenge myself on – namely, how analytical do you need to be to lead in analytics?

I have spoken to colleagues and industry friends on this topic, because it is easy to feel like an imposter in analytic circles. The ability to go deep into Python, write algorithms or code, and even do the basic stuff such as advanced Excel manipulation are all out of my reach without giving more time to learning and deeper understanding. I am not afraid of learning new skills, but I don’t think it is necessarily what an analytic leader needs to drive the data agenda forward and deliver results through analytics.

The primary ability for a leader of any analytic function in a business is to show the value from the work that is being created and how it fits with business success. We don’t need all the detail to drive great teams. What we do need is the ability to see how data fits into strategic goals and how we can build a strategy for analytics that complements the business objectives.

One of the essential tasks of an analytic leader is storytelling inside our business. We have to fight for the budget for our data and the teams that will drive impact in the organisation. It is at this senior level that we need the ‘data story’ to be heard, by showing a return on investment – but we also need to keep it simple.

Our voice is heard loudest when senior executives who really get the value of data are at the centre of the decision-making process. Ensuring a return on investment is crucial to win hearts and minds, but we can help by creating a connectivity to our work. Making the outcomes feel real is crucial to analytic leadership. Tell your stakeholders how they, as individuals, would benefit from your team’s work and output. If we need to explain the details of complex work, we lose the audience – just think about how often we are asked to speak in layman’s terms. Highlight the value of the data, but do not get lost in the detail of the latest artificial intelligence solution or new neural learning when pressing our case.

Our role is to look broadly at our industry, to take a step back and see the range of innovation that is coming. In doing so, we ensure that we are not falling behind. One of our strengths as a business function is the ability to show how we are keeping our organisation across the most exciting technological developments. There is so much to say in our field, with developments coming through continuously.

We do need to benchmark ourselves regularly through our formal and informal networks on what is going on elsewhere. I, like others, try to ensure that we have a flow of analytics that might be deemed business as usual, but is delivered alongside newer capabilities that we want to test. This is where we can create energy inside our business but make sure it is about results and not a ‘nice to have’.

There is a key watch-out that the leadership community cannot escape as we try to create a compelling story for analytics. We do need the experts around us. We need to invest in expertise and to give those teams the opportunity to grow as individuals. Where we see great work we should shine a light on the teams internally and externally, and give them the credit for advancing the business. Connecting our teams to the new stuff is part of the engagement process to let them learn, grow and to address any concern over change. Demonstrating to our teams the bigger picture of the business is vital to make the link from their work to the company mission, and how we contribute to success.

If we work on and develop these parts of our leadership roles, we will continue to grow the visible impact of the industry, driving the investment that makes us essential – and all without needing to be functional experts in absolutely everything.

This article was first published in the January 2021 issue of Impact.