Senior HR executives are in a bind right now. The world is throwing data at them, and asking for answers back. Their role may have been traditionally defined by a certain set of data activities – turnover reports, payroll management etc. – but they are now expected more and more to increase business value as well.

It is not in the collection and managing of data that an L&D executive now adds value, it is in analysing the data and using it as a solution to a business problem. This shift in job emphasis to adding value, while not shedding any of the requirements that are always expected to be filled by an L&D executive, is a significant challenge, but does represent an opportunity for talent managers to increase business value through the insights they can uniquely ascribe in their role as an L&D executive.

Prof. Dana Minbaeva, speaking at the final Talent Forum in 2017, believes HR mangers and learning and development executives shouldn’t be overwhelmed by this new landscape. Data analytics shouldn’t require a PhD in statistics or a massive team – what it really needs is a definable and actionable goal.

Human Capital Analytics
Dana uses analytical techniques to draw a clear link between human capital analytics and improved business performance, as well as suggesting concrete solutions in the process from an often-complex set of data. Performance of any company today arises from a complex set of organizational and human dynamics – understanding and making sense of this complexity is only the first step.

The next step in HR will come from not just understanding the complexity, but producing definable business actions based on that understanding. Analysing and predicting the effect of today’s complexity on tomorrow’s performance is necessary for building differentiated competitive advantage and demonstrating the value of HR analytics.

So, how does someone in the talent development field analyse and predict a complex future?

Predicting the Future
Often, this would be done through a change management project or analytics research project i.e. mining company data to produce a dataset that can be analysed by management. The key for the L&D executive is to mine this data with the philosophy that it will supply an answer to a tangible business question.

These business questions could come from the annual report, the latest business meeting or as an original idea – the point is that it is mining and analysing data with a purpose.

To give context, it is perhaps useful to look at a successful analytics research project. At a multi-national facilities company they set about finding a correlation between employee engagement, customer experience and profitability.

Through their annual survey, they received 500,000 responses (total questions) from their employee survey and 20,000 responses from customers that represented 7,500 global contracts. It would have been very easy for the HR team to simply put the figures gathered in a report and send it out, leaving the analysis open to the readers’ interpretation. Instead, they asked the business question ‘Does an engaged employee lead to a more profitable company?’ and then set about manipulating the data they had collected to answer it.

Firstly, the HR team matched employees with global contracts and plotted the satisfaction scores. They then compared these satisfaction scores with the profitability of each project. The results were clear – there was a strong correlation between employee engagement and the profitability of the contracts they worked on..
Now, management could see a clear, visual and direct link between a happy employee and a profitable company. The HR team had proved that an engaged employee delivers increased profitability and the engagement strategies they employ are justified and, indeed, could be increased.

There’s no such thing as perfect data
Often the first step is the hardest, as the data available to an L&D executive can be overwhelming in size, or simply impossible to gauge how accurate it is.

The promise in the future is of perfect data; that machines will input correct values and output correct results. In truth, perfect data may never be achievable. People make mistakes, and data will always include those mistakes (indeed, the mistake may spread like a rotten apple in the barrel).

Do not wait for the perfect data to come along before starting a project. Take what you have and get stuck in. There will also be a great deal more credibility to your work if you use original data rather than second-hand research.

Human capital analytics is not about big or better data, is about better analytics. It is about asking the right questions, and driving towards the right answers. By investing in human capital analytics, the management sends a definite signal – performance matters.

Reshaping the HR Role
Ultimately, this is about reshaping the HR role. In the future, a L&D executive will not be a supplier and manager of data, they will be an interpreter of data and a solution provider. The value of strategic HR is not in gathering big data, producing extensive dashboards, or making gigantic spreadsheets – those things will easily be handled by administrators or IT systems in the next few years. In the analytic revolution, the battle for strategic HR lies in:

> Changing the mindset, attitudes, and habits associated with the use of evidence for decision making;

> Asking the right questions, which are those questions that link strategies, people, and performance; and

> Accepting key responsibilities for implementing change, and for managing the changes in culture, process, behaviours, and capabilities that result from analytic initiatives.

If all the traditional talent development functions are becoming increasingly automated, where will the future value lie? It will be up to the modern L&D executive to become a vital cog in the business apparatus – a voice that speaks from the highest level rather than to it.

This article is based on a talk given by Dana Minbaeva at the IMI Talent Forum for members. Dana Minbaeva is the Professor of Strategic and Global Human Resource Management at the Department for Strategic Management and Globalization, and the Head of the Ph.D. School in Economics and Management, Copenhagen Business School.

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