Could a data-analytics-led assessment of your leadership style and approach make you a better leader?

AI-assisted health management has helped to create a new class of data, one that was hitherto invisible. For years, AI (in a nascent form) has been able to look for patterns, particularly in health where indicators of future ills can be seen by computers long before humans have any idea. Early diagnoses can cut future later interventions and improve the chances of people living longer. 

And now, AI is used routinely in the workplace. GPs can focus on listening while AI monitors and summarises consultations. The meta data from these interactions could give health leaders an indication of the general health of local populations as well as emerging trends. In other words, AI is now becoming part of how we do what we do.

And so to leaders. AI can now monitor, record and transcribe meetings. It can summarise the key points and set out the expected actions, almost in real-time. Might it also be used to extract valuable leadership lessons, helping leaders to improve?  

Programmes can now show who spoke and for how long. It can pull out how many of these contributions resulted in action. It can show who encouraged contributions, built on points made and moved discussions forward. Careful reading of transcripts will show who talked over whom, who brought new ideas to the table and who merely built on or even acquired others' ideas.

For most leaders, where meetings are the daily meat and drink of their work, this insight could prove invaluable. Over time, transcripts could help extract lessons about the kinds of approaches that encouraged participation. Data could yield lessons on attentiveness, participation, contributions, usefulness and even value added. All too often, in our traditional, analogue-based thinking, these data remain invisible. And yet, in a plan-perform-review world, they matter.

It can take the idea of improving leadership skills on quite a new journey. Other than annual 360-degree assessments, leaders are rarely able to assess their leadership value-added. Partly, it's a failure to articulate what excellent leadership looks like, making comparison difficult. Talk tends to be about leaders who get things done but less on how. What's more, assessments may be blinded by apparent success – nobody wants to talk down a star. But unless we are clear about what good looks like, it can be hard to improve on anything.

Data offers a way in. In process-heavy areas, it is possible to compare productivity across departments. Literally, how much stuff gets done and with what quality. Analytics could be used to tell us how often leaders met with staff, what the level of post-meeting productivity was, as well as bringing into the picture sickness levels and other negative impacts.

In the analogue world, dissecting leadership is not easy. Poor leaders may not be confronted about their inability to inspire, motivate or enthuse their staff. We may talk ruefully about poor manner or abrasive personalities but that's to sidestep a central problem: if you don't know how well you're doing, it's hard to do it better.

If leadership is about driving up productivity by enabling staff to shine, then data analytics can show whether this is happening or not. Data could highlight emerging patterns in similar departments – enabling the comparison of productivity rates, number and quality of meetings, and other indicators of engagement (including sick leave, one indicator of not being engaged). And because data is forever, a leader's whole career could be looked at for salient patterns of behaviour.

And in a plan-perform-review world, where an honest dispassionate appraisal of a leader's work can be made, those falling below expectations can use this insight to change their behaviour. Leaders who routinely talk over people would be able to see how often and with what impact they do this. Leaders who actively encourage contributions from all corners might see their positive impact and the outcomes it creates.

Data can take away the awkward conversations that prevent poor leaders from improving. Leaders' Dunning Kruger syndrome gets in the way of useful insight. Staff can simply learn to accommodate poor leaders hoping that they'll just move on. Analytical data can help change this.