The Power of Big Data

The quest for big data has been the panacea of HR leaders for the past decade, but in the ‘twenties’ we’re going to see this ratchet up and both the opportunities and challenges around this evolve.

There are three key ways in which data will provide benefits to HR professionals in the coming decade in a progressive evolution:

  • Big Data – collating data from multiple sources in a data warehouse that can be analysed and triangulated
  • Predictive Data – and an ability to move from analysing data to predictive data.
  • Artificial Intelligence – using data and algorithms, to make decisions and choices in place of human involvement.

At WME one theme came out loud and clear in our ‘Big Conversation’ it was the ask for us to do more with data and analytics.  We are exploring how we can do this and what we can bring to our membership organisations that can give us all real-time insight to them at the touch of a button, not just into each organisations workforce, but how organisations compare to each other and to the Region’s workforce average.

There is real benefit of us being able to see the big picture and then evolve this, to being able to make evidence based decisions and then predictive ones.  What if, as employers, we could all work to drive change against certain metrics, like absence, we could see and quantify our collective efforts.  Then what if we could test out certain hypothesis about our workforce, that would help us to target where interventions and our limited resources have the most benefit.

In 2017 Loughborough University carried out a detailed study on the future impact of technology in the workplace. It found impressive examples within the public sector, where AI was automating routine administrative processes and so freeing up employee time.  This is music to the ears of many organisations, a way to deliver services faster without making cuts to employee numbers.

However, subsequent research by John Boudreau at the University of Southern California argues that the pace of change will accelerate in the use of AI in the workplace.  If something is less expensive, then people use more of it, and in new ways, he uses the example of high-speed computing in the 1980s and 1990s made “math” cheaper. Before then, few thought of movies and music as “math,” but then high-speed computing made “math” so inexpensive that it became cost-effective to translate movies and music into digital “math,” transforming how we purchase, share, and enjoy them.

The authors of the book ‘Prediction Machines’ (Ajay Agarwal and Joshua Gans) argue that AI is similarly making “prediction” cheaper, and that prediction will be used more, and in new ways. Music, movies, art, facial recognition, and many HR decisions can be translated into “prediction”.  Specifically in time consuming areas such as hiring, remuneration, performance and promotions.

I love the possibilities of what data can offer us in the workforce; but these equally come with ethical and legal risks and challenges, which will need a HR response to manage.  We need leaders who understand the ethical challenges and bias which AI can present, it may offer efficiency savings and cutting out the ‘human touch’ to many processes, but at what risk? As the move to AI and robotics grows and the initial simple processes it has been used to automate are being seen as huge successes there is a rush to automate   more complex processes, leading to more tiers of algorithms, more margin for error.  Is enough time been spent in organisations understanding the implications of how AI and data are being used or are we applying our own bias, seeing only the benefits?.

Not enough is yet known about AI in the workplace to really build measures to counter this. Equally big data can lead to big mistakes and we ware already starting to see cases of that emerge around recent GDPR legislation and breaches, that have meant employees have had unprecedented access to data, which, in one click of a button can lead to a costly error in wrongly sharing or using that data. Equally what happens when a human can over-ride an AI decision, or doesn’t?  Depending on the impact, that could lead to a whole new interface between employees and technology and a whole new dimension to potential employee relations cases.

A recent CIPD research report ‘People Machines’ found that workers’ attitudes and behaviours in relation to technology will be influenced by the trust they have in it. One way to build trust is to involve workers whose jobs will be affected by AI and automation early in the design and implementation of technology.

Professions like IT, finance, and research have much to offer in driving technology and data within the workplace, but these thorny questions require more. HR’s foundations in human behaviour, culture, and ethics offer a unique and essential contribution,  and as HR professionals we must make sure its on our radar; it’s not just about how we use AI and data within a workforce sphere of influence, but how as leaders we influence far more widely and not just seek to police the implications of its use.

I wouldn’t go as far to say the robots are coming in 2020, but there is a continuing march into new territory which it is hard not to get excited by.  WME want to be at the front of that march for employers in our Region, but we’ll be asking the challenging questions and ensuring we don’t get carried away to the detriment of ethics and trust in us as employers.

Article By:

Rebecca Davis, BSc MSc FCIPD
Chief Executive, West Midlands Employers

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