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HR and the Fourth Industrial Revolution

We are currently on the brink of a new industrial revolution, which will once again change the way we work forever. While the Fourth Industrial Revolution was a hot topic at this year’s World Economic Forum in Davos, many businesses and their HR departments, which might not follow global economic trends as closely, are unaware of the fundamental shift that their workforce is about to undergo. Big data, artificial intelligence, nanotechnology, 3D printing, genetics and biotechnology will bring significant, seismic, rapidly-evolving and lasting change to the way businesses will operate in the future.

The global labour market will be severely disrupted by emerging technologies and their potential to replace human workers in the next few years. As a result, over 7 million of today’s jobs are predicted to disappear by 2020. Businesses need to make sure they automate the right processes while retraining existing staff to develop the skills they need in the future. In short, businesses need to ensure that today’s workforce is ready for tomorrow’s skills requirements.

Luckily, there is one business function that is better equipped than any other to tackle this challenge. If there were going to be a group of people, a department, an academic field, group of researchers, practitioners and business people who can help with this, it is HR. To understand the current and future impact of key disruptions on employment levels, skill sets and recruitment patterns in different industries and countries, we need the expertise of people who do this for a living.

Within corporations, HR needs to be involved in identifying what roles can be automated or roboticised and what roles should be done by humans. In identifying what skills are required, HR teams can develop staff internally and recruit accurately externally. At the same time, HR departments will need to help their people adjust and stay relevant in the new world of work, especially with the next generation already looming on the horizon. One popular predication estimates that 65% of students entering primary school today will end up working in a job that doesn’t exist yet. To keep up, today’s businesses need to upskill their workforce if they don’t want to lose their relevance.

If this doesn’t happen, we are in danger of facing a dichotomy in the labour force with an increased skills gap, something we are already starting to observe here in the UK where nine in ten businesses currently experience such a skills gap. In future, well-educated workers with relevant soft skills – the art of persuasion, team work, collaboration, salesmanship, emotional intelligence and teaching others – will thrive. Low skilled workers whose jobs involve routine work, repetition or are focused in a narrow technical area will find they are in less demand over time. 

HR people need to define the core skills required by their organisation and then decide where they can find or develop these specific skills sets. This may be through links to education and academia, apprenticeships, on the job learning or by supporting workers in the pursuit of their own personal or professional qualifications. The Fourth Industrial Revolution presents HR professionals with a unique opportunity to become firmly involved in the strategic decision making of a business by helping them adapt to an ever-changing workforce, while at the same time giving current employees valuable soft skills that will always be in demand.

There are changes underway which will help HR departments to do this.  Imagine a world where you could accurately predict the skills the business needs not just today but in say five years’ time, or where you could accurately predict attrition, absenteeism, productivity, career aspirations, requests for more pay, or desire for more of a work-life balance from employees all in advance. Then because you predicted it, you could take corrective or proactive action in good time. That is the type of world we are moving towards as trends in big data, analytics tools, HR and people management combine.

For HR professionals, automation technology will reduce some of the elements of human error and uncertainty inherent in people management. It will improve decision making and risk taking by putting powerful insight in the hands of managers, that when combined with their skills and experience will have a profound difference in the way business works. 

What if you could analyse a candidate’s CV, employment history and characteristics against a job spec, organisational culture and team dynamic, to objectively hire the right skills and personality for the business?

Picture being able to track an employee – to spot potential problems and opportunities before they arise, based on a range of tracking data and past performance, or being able to identify employees that need more help and encouragement in order to become engaged with the business. This allows businesses to be able to manage productivity predictably, in a way only thought possible by using machines. Then organisations could offer a bespoke management style and plan based on advanced knowledge of individual employees’ motivations, desires, goals and characteristics.

All of this could be possible by combining work related data captured from a range of inputs, which is analysed, compared and presented back for the benefit of the employee and employer. Then combined with sales, finance, customer service and operational data, it will become a powerful factor in determining the success or failure of businesses. The businesses that thrive will be those that can harness this power, understanding its inherent value in making the world of work a better place to be.

Advances in big data and analytics tools that lead to all pervasive evidence based decision making, based on rich insight, will lead to a more productive, more enjoyable and more profitable world of work.

For more information on this subject and the steps HR can take to manage and prepare for these changes please call 0800 035 0545 or email HR [email protected]

www.ngahr.co.uk

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