Why data will underpin the transformation of modern leadership

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Most business processes rely on a certain amount of data to operate efficiently, but increasingly it’s the leadership function that is being transformed by a more data-driven approach – and this can only be a good thing. 

Organisations have become hugely data driven around their finances and operations and more recently around their customer processes. Data is real-time and sophisticated, allowing business to segment customers down to the nth degree and engage with them in a tailored way to optimise revenue. 

With the advent of sophisticated HRIS systems, they’ve now started to do the same with their broad employee base, learning more from their people metrics to maximise engagement and drive performance. 

When it comes to leadership, however, too many decisions are still based on ‘gut feeling’ and assumptions, and very few based on smart data or accurate insight.  

If leadership is to transform to keep pace with the evolution of the workplace as a whole, organisations must adopt a more structured, data-driven approach – just as they do with every other aspect of their business. 

Where does data fit?

In most businesses, results are dependent on change, be that cultural, structural, a response to changing market demands, or a result of M&A activity. Whatever the source, two factors are critical in delivering the necessary change.

The first is effective leadership: are leaders capable, equipped and engaged to lead the change required? The second is employee engagement: are employees being engaged to tackle the changes required by those same leaders?

These two elements are critically inter-dependent and this is where data comes in. 

We can only accurately measure, analyse and understand the interaction of these two elements if we have the right data, gathered at the right time, and measured against the right business context.

Changing our flawed approach

Why is this? The reasons become clear if we cite a few generic examples. 

How many promotions are still based, ultimately, on the decision-maker’s belief or faith in a candidate’s ability to step up, as opposed to using systematic data about their performance, behaviours and potential?

How many mission-critical projects do senior executives allocate to colleagues whose main positive feature is that they think similarly to that same executive, as opposed to who has the right mix of experience, capabilities and outlook?

Smarter data strategies can massively reduce how much data you’re gathering while simultaneously making it work harder.

How many hires of senior executives fail because the firm focuses on previous role, sector focus or length of experience, as opposed to using metrics to assess their cultural fit?

I suspect these scenarios are familiar to more than a few of you. If we’re going to alter the way decisions are made, we need to alter what we use to base those decisions on in the first place - and that’s data.

Data takes centre stage

You may question why we should add more data to the huge amounts we already gather. You may also be sceptical about how data can help us make people-based decisions. 

In many cases, we’re talking about using the wealth of data we already have and do nothing with. 

In others, we’re talking about having much less data: employing better, smarter data strategies can massively reduce how much data you’re gathering while simultaneously making it work harder.

Essentially, this is about employing smart data analysis that drives evidence-based decisions, enabling businesses to:

  • Gain an accurate measure of leadership effectiveness – combining data sources with tailored leadership assessment activities means leadership data is much more predictive of hard business outcomes.
     
  • Define a clear path of action – using data analysis techniques that are already proven in other areas of business, organisations can create tailored ‘blueprints’ for each leader that sets out clear measurement milestones. 
     
  • Integrate leadership data with organisational outcomes - connecting leadership data to hard business outcome metrics shows where real leadership ROI lies.  This includes people metrics (retention of top talent), customer data (client spend or customer NPS scores) and financial metrics (such as revenue or profit growth). 

Taking it step by step

This might sound like a utopian vision for some and an uphill struggle for others. 

While such change can’t happen overnight, there are clear, achievable steps that lead to an effective, achievable data-driven leadership model.

Step one: better data planning

Develop clear leadership measurement strategies: what do we want to measure, how will we measure it and what will we do with the data to add value to the business?  

With the rise of data scientists inside HR, this is most likely where that strategy role should be focused.  

We need to get data out of silos. While many HRIS tools can now bring data together onto one platform, they are not truly integrating data. 

This answers questions such as:  how will we measure leadership strengths? How will we track leadership potential and progress against plan?  How will we help leaders with critical feedback at moments of truth in their leadership lifecycle? 

Step two: smarter analytics

Currently, any leadership data that does exist tends to be ‘flat’ and often nothing more than descriptive – think 360 ratings, assessment outputs, nine box grids.   

We need a shift towards smart analytical techniques such as regression analysis, predictive and causal modelling in the leadership realm – essentially, a move from explanatory data to prognostic insights.

Step three: meshing leadership data with other KPIs

Put simply, we need to get data out of silos. While many HRIS tools can now bring data together onto one platform, they are not truly integrating data. 

We should be able to tell a CEO which leadership attributes not only predict employee outcomes (engagement, talent retention) but also customer outcomes (retention, profitability), operational outcomes (productivity) and financial outcomes (revenue growth, improved market share).  

This requires integrated analytics, not just placing data next to each other in a descriptive dashboard.

The proof is in the pudding

This approach is not simply theoretical or a nice-to-have for forward-thinking leadership and HR teams. Our first-hand experienced shows it’s already proving its worth in very different types of businesses.

A fast-growth global financial technology organisation, for example, has used smart leadership analytics for several years.  

Early in its growth curve, the CEO decided that leadership should be subject to the same analytical rigour as its products, marketing, customer feedback and financial modelling. 

We’re likely to see an exponential rise in the adoption of a more structured, analytical approach to leadership and engagement over the next five years. 

A strategy using data analytics integrating leadership talent, customer and operational statistics was put in place to identify which metrics would be predictive of performance, in particular revenue growth. 

The strategy has seen senior leadership approval ratings rise by 25%, employee engagement rise by nearly 40%, and qualitative 360° feedback is rapidly improving.  

Talent retention has improved among high potentials and succession-planning processes at the senior level have evolved. 

What’s more, the firm’s stock price has risen six-fold - well above the market average.

More evidence of success

Meanwhile, a European media corporation decided leadership metrics would be vital in tracking progress towards very high growth targets over a five-year period.  

A leadership framework was put in place, integrating several metrics to predict performance: psychometric assessment data, 360° metrics, employee engagement data, talent retention, customer satisfaction and revenue growth statistics. 

Using a predictive analytics model, the organisation improved collaboration among the top team as they moved from a geographical to a functional structure, and boosted leadership behaviours. 

The working relationship between the CEO and senior leadership team members was also enhanced, a key component in delivering the firm’s overall growth strategy.

Time to transform

There’s much more evidence to share that demonstrates just how integral a data-driven approach to leadership can be to driving positive organisational change and long-term business success. 

What we’re seeing here is just the tip of the iceberg, and we’re likely to see an exponential rise in the adoption of a more structured, analytical approach to leadership and engagement over the next five years. 

As pressure mounts for businesses to work smarter and be ever more agile, how well equipped is your organisation to compete by having the power to make evidence-based, data-driven leadership decisions? 

Interested in this topic? Read Strategic data: unlocking HR's secret weapon.

About Andy Brown

Dr Andy Brown

Andy is the co-founder and CEO of ENGAGE. He has worked for ENGAGE since 2008 and, in 2013, co-led an MBO of the firm.

Andy leads all of ENGAGE’s strategic work with senior executives and heads up the Leadership practice. He works with CEOs, boards and executive teams in FTSE 100 and Fortune 500 firms, as well as with a range of fast-growing entrepreneurial start-ups.

Prior to this, Andy worked in the research and consulting industry for 25 years. He was previously a Partner at Mercer Consulting, a Global Practice Leader at The Empower Group (the strategic consulting division of Manpower), Managing Director of YouGov Consulting and Head of Research at The Gallup Organization.

Andy holds a doctorate in survey analytics from the University of Oxford where he also obtained his undergraduate degree in PPE and an MSc. in sociological research and statistics. He has also been a Visiting Fellow at Harvard University.

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