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Natalie Cramp



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Beyond the buzzwords – why fact must come first in HR decision making

Natalie Cramp explores why HR leaders should ignore the latest lingo and sharpen focus on data to bridge the growing employee-employer disconnect.

The Great Resignation. Quiet Quitting. Quiet Hiring. Productivity Paranoia. TWaTs (the name given to those who work on Tuesdays, Wednesdays, and Thursdays). And more recently the Great Retention. It would seem that every other month there is a newly coined HR term to describe the latest workplace trend.

Of course, this is nothing new. For years, the corporate scene has been overwrought with cliches, buzzwords and industry jargon, usually designed to simplify and sensationalise, and all too often without any real degree of real, hard concrete evidence.

But it’s important that these sweeping generalisations are treated with a very strong ‘pinch of salt’.

The reality is, after all, that no two businesses’ HR requirements and issues are ever the same. They can vary dramatically depending on the sector, size of business, location and everything in between. Therefore tarring the majority with the same brush can prove wholly inaccurate.

At the same time, we are living in an age which calls for the increasing hyper-personalisation of HR services.

The new breed of employee

Out of the post-pandemic has emerged a new breed of employee – one that wants remote working, higher pay, more flexibility around their home lives and better career progression and development aligned to their own personal aspirations and goals.

This continues to see a marked shift towards ‘best fit’ roles as HR directors come under pressure to create and fit jobs and opportunities around their best people in order to retain them.

Of course, this is no easy feat, particularly in the context of a challenging economy, political instability and ongoing talent wars, all of which continue to disrupt and bring uncertainty.

you can understand whether you are likely to disproportionately lose employees from minority groups and whether further culture interventions are needed.

Solution to new employee demands

However, there is a solution. I believe that today’s latest advances in data and AI offer a unique opportunity to transform how organisations attract, retain and engage with their employees.

In fact, according to recent research conducted amongst UK workers, almost three quarters (72%) believe that applying data to HR decisions could be better than the practices currently used by their employers. This number rises to 80% for BAME employees and 82% for disabled employees.

The study also reveals that 61% of employees are comfortable with data being used to monitor them – so long as they can see it – believing it to enable fairer decision-making.

To understand more, let’s consider the application of data-led HR in a number of key organisational touch points.

Employee data application

Take for example, when it comes to a promotion or personal development. While it’s not to say that an algorithm can ever offer a complete substitute for experience and intuition, data’s capability goes far beyond measuring simple KPIs or productivity stats.

It can take into account a huge range of sources from the structure such as performance reviews to the unstructured – such as behaviour on a video call meeting. In this way, it can make it easier to stay on top of performance targets and reward staff on proven progress.

It can also go a long way in helping managers identify and address worrying trends such as regular overworking or underworking in order to address any issues before they escalate.

Data-led workforce engagement

Another top priority for HR leaders is effectively engaging their workforce. A 2021 Gallup study indicates that the UK has some of the lowest employee engagement levels across the globe at just 11%.

Again, data-led HR offers a real solution that begins at recruitment and continues throughout the employee life cycle. It enables employees to collect data insight from employees (in a similar way you would from a marketing perspective for consumers) and analyse key trends to identify. Types of communications and benefits are then identified that are most effective in order to adapt their strategies accordingly.

Most likely, it will also see the end of the tiresome, annual employee engagement survey in favour of a more continual approach. For example, implementing quick-fire surveys that employees need to complete immediately.

There still is no replacing the human touch.

The result?

In this way, HR teams can be more in tune with employees’ needs and employees will feel better understood and more appropriately rewarded – helping to increase employee satisfaction and, in turn, retention.

It can also help you predict when an employee is likely to leave, so that effective interventions are taken at the point you can still make a difference. And you can understand whether you are likely to disproportionately lose employees from minority groups and whether further culture interventions are needed.

But that’s not to say that it’s time to take the human out of HR. While the application of data science can provide the actionable intelligence needed to help busy HR teams understand employees and any issues they are facing better – there still is no replacing the human touch.

This is something Amazon knows only too well having seen how an unchecked recruitment algorithm designed to eliminate the gender gap actually ended up perpetuating – something which could have easily been avoided with human oversight.

Moving forward

HR and data teams should work hand in hand, with both parties collaborating in the collection of data, how algorithms are designed, how they are refined, and, critically, how the outputs are interpreted to make decisions.

Clearly, as we look to the HR task ahead it is by no means an easy one – and more certainly not one that can be defined by the latest trendy, often not wholly accurate jargon. Rather, if busy HR teams are able to respond faster, better and with greater agility to the evolving workplace, it’s time to enter the age of data-led HR.

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