Others are unnerved by the potentially intrusive nature of a data-fuelled society, worried that nothing is private anymore. And, perhaps linked to this, there are those who feel there is, quite simply, too much data available, to the point it becomes unmanageable if not completely meaningless. This certainly applies to the people whose careers are being increasingly shaped by all of this.
So where does HR fit in, and what does this mean for the ever-complex world of employee relations (ER)? Speaking to theHRDirector, our CEO Pete Byrne discusses this very topic…
Before delving into the specifics of data science within the employment landscape, it is firstly crucial to understand the four dimensions – or Vs – of data, for which IBM has been widely credited.
The sheer volume of data that now exists, naturally presents endless opportunities to better understand a given situation. However, on the flipside, it risks feeling overwhelming if there is not a manageable way to handle it. Even in an SME, the wealth of data surrounding every employee, every team’s performance, every customer record, every human interaction, every milestone accomplished – and so on – is colossal.
Data also exists in multiple forms, and this variety often means no two pieces are the same. This multifaceted ‘shape’ of data – from emails and social media posts, through to attendance records, phone call logs, training certificates and personal development plans – compounds potential data analysis difficulties.
Then there is the velocity – or ever-changing pace of updates – to the data, which jeopardises its relevance if the data handler doesn’t have the ability or agility to manage and interpret it in real-time. And lastly the veracity – or quality – of data is imperative because it needs to present a true, accurate and current picture of the scenario at hand.
As the world’s use of data continues to evolve, so too do attitudes towards it. Some modern data thinkers therefore believe that consideration should also be given to the value that can be harnessed from a data set; data variability, which may be influenced by subjective interpretation; and the visualisation or ease with which data can be visibly depicted.
With such a complex picture seemingly forming, it is understandable why many organisations continue to bury their heads in the sand – avoiding the need to conduct deep data analysis at all costs. But we all know that a virtual filing cabinet simply won’t cut it anymore.
The expertise of a data scientist – someone confident in the many data ‘Vs’ outlined above – has never been so crucial. A CIPD article highlighted, for example, that while almost 71% of global HR professionals have access to people data, only 42% acknowledge that they do. There is a gap that needs to be bridged, as quickly as possible.
However, while the world may be becoming increasingly excited about data, the role of a data scientist remains niche. And even vast organisations with impressive talent budgets may struggle to justify the creation of this position.
Organisations should therefore ask themselves whether it is right that a single person – or team –‘owns’ this data approach, or whether a data champion is arguably more valuable than someone who assumes entire responsibility for the BI potential that lies at a company’s fingertips.
For example, if that champion can instil a hunger for data throughout an entire department – or better still the whole business – informed data-driven decision making stands a far greater chance of becoming a mindset, a culture, a cornerstone. It is then not the sole concern of one person, who may not be best positioned to interpret the data, as context is important after all.
Every piece of data should be thought of as a single, standalone ‘nugget’, which must be put into context, so that information can be derived.
Every colleague in an organisation has hundreds of pieces of data associated with their employment status, wellbeing, performance, and development. But only when someone introduces context – such as the make-up of their team, the behaviour and leadership of their manager, their career history, skill-sets and even their personal circumstances – does the data have any real meaning.
Armed with such context, an ER team can start to ask specific questions, such as – Is this person disengaged? Are they a flight risk? Are they being ineffectively managed? Is a worrying trend emerging? What is the problem ‘costing’ the business? This is the knowledge the C-suite is looking for – analysis of the data through a relevant lens, rather than blindly following what data-related assumptions could otherwise imply.
A data scientist could of course take organisations on this journey. However, thought leaders such as Gartner shine a further crucial light on the topic. In thinking about business intelligence – and BI tools more specifically – they explore the notion of “…a self-contained architecture that enables nontechnical users to autonomously execute full-spectrum analytic workflows…and the collaborative sharing of insights.”
And herein lies an important point. ER leaders may not be data scientists, but in an era of innovation and automation, they shouldn’t need to be. They are experts in their own domain – getting the best from people – and it is this intellect that we need to leverage, not their data literacy.
We must therefore consider the role that technology can play in conducting the deep dive analysis that a growing number of ER leaders wish to undertake. Intuitive software now exists across every realm of business – including the people landscape – to process, organise, structure and present data in such a way that information can be uncovered with relative ease. Such tools can effortlessly tackle the ‘Vs’ outlined above, to present ER leaders with insight that – when overlaid with their own knowledge – enables them to derive maximum value from metrics, at pace.
This isn’t a case of ER, or HR, being behind the curve as the headlines would sometimes suggest. On the contrary, it is about the business community on the whole stepping into the realms of what’s possible, when it comes to data deep dives.
This is also not another scenario which sees people’s roles being overtaken by ‘robots’, because human intellect is more important in this field than ever. But this is the chance for the profession to utilise the data at its fingertips, to become a true powerhouse capable of revolutionising the future of work.
Take employment tribunals for instance – something an organisation wishes to avoid at all costs. Claims have risen by 27% in the past year, linked indisputably to the remote working, furlough and redundancy pressures catalysed by Covid-19. But with the economic recovery predicted to be slow and painful, and a hybrid workplace now a permanent fixture for many, the risk of disputes between employer and employee will remain extremely high for some time.
ER teams could therefore utilise data science to interrogate their management of disputes to date, and/or pre-empt the likelihood of a claim escalating to tribunal level in future. Have workforce decisions been made fairly and in compliance with the law for example? Have line managers demonstrated discriminatory behaviours? Is there a training gap?
This more proactive approach to understanding the ‘lie of the land’ internally won’t just help to avoid costly, reactive legal fees and reputational damage. It will also better protect employee morale, team camaraderie, retention, performance and so much more. The business case for such an ‘investment’ in data, should quickly become clear as a result.
The same could be said of so many scenarios across the entire Human Resources piece, from recruitment and workforce planning to the health and wellbeing of colleagues.
In fact, data can now be pulled from so many previously unlikely sources, to give a more enriched picture of the real goings-on inside a workplace.
For example, to an ‘uninformed eye’, analytics from communication tools such as Microsoft Teams could highlight how productive a colleague has been throughout the day – or not. But deeper analysis of their working patterns, could also form the starting point for better understanding whether they are working too many hours, struggling to switch off because working from home has encroached upon their personal time, experiencing technical difficulties due to a lack of training, not getting the support they need from their manager, demonstrating absenteeism or presenteeism because of an underlying health concern, or even being the victims of bullying. Just because the mass adoption of a communications channel is new, doesn’t mean its data should be disregarded.
Without having access to and reporting on the data that really matters, there is too great a risk that misinformed conclusions could otherwise be made, that the individual is merely ‘slacking off’ perhaps.
Of course, this is just one illustration, but the examples are, in truth, numerous. And while the outcomes of such an approach to data could be transformational – in terms of the positive change that could be affected – ER and HR teams are not being asked to trust in bleeding-edge technology that hasn’t already been tried-and-tested.
The fact of the matter is that other business functions – from sales and marketing to finance and operations – are already relying heavily on data science and BI tools to drive that data consumption. But the areas where data could be a real game changer, are as yet, relatively untapped. With a finite set of resources, the ability to supercharge the efficiency and capabilities of the profession therefore need to be leveraged, quickly.
We were delighted to be featured in this month’s issue of theHRDIRECTOR, the independent, thought-led publication for Senior HR Practitioners. We hope you enjoy our article on page 44 by Pete Byrne.
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Pete set up esphr in March 2003, after running an HR resource management business for three years.