The future of skills: using tech to put people first
Reskilling or upskilling for an entirely new role is often seen as a big leap, but data-driven tools could begin to make it less of a jump than previously imagined.
Artificial intelligence (AI) is regularly cast as the villain of the workplace. The truth is more nuanced. Yes, smart tech solutions like AI are on the rise. Yet, on the flip side, today’s digital workplace is also driving opportunities for new skills and career options.
A quick ‘what if’... consider smart tech: what if AI was also seen as a positive facilitator of new career opportunities?
“Reskilling and upskilling are often seen as a time-consuming and costly exercise by businesses, so we were interested to find out if data and AI could help in some way and, if so, what future redeployment journeys might look like,” says Patrick Hull, Unilever Vice President, Future of Work.
Job skills pilot project
To assist with the research process, we brought on consultancy firm Accenture and Canadian start-up SkyHive, an expert in workplace analytics.
Two propositions framed our approach. First, that jobs might be better viewed as a combination of multiple skills, rather than singular roles. Second, that data could potentially augment human perceptions about the skills required for specific roles.
The second idea came from SkyHive. When the AI specialist used its data-driven technology to analyse job-specific skills, it identified an average of 34 skills per person in a role. However, employees often downplay the number of skills they have, typically putting the figure at 11.
There’s another intrinsic benefit of a more data-driven approach to reskilling and redeployment: the elimination of preconceptions, reports Nicholas Whittall, Accenture’s Managing Director of Talent & Organisation/Human Potential.
As he notes: “AI eliminates human bias that recruiters or managers often hold in terms of who’s truly capable of doing which job.”
By way of a baseline, the HR teams at Unilever and Walmart selected ten different roles from across their respective businesses.
Each team then drew up a list of the main skills they associated with each role and the potential training pathways for reskilling people for different roles.
Accenture and SkyHive then reviewed the lists and subjected them to a variety of data analytics tools. Their objectives: to see what skills might be missing, to spot where skills overlapped, and to determine the most efficient way to upskill our existing talent.
By breaking roles down into their component parts and analysing them in granular detail, the skills gaps between different functions emerged as far less wide than initially thought.
Take two jobs that, on the face of it, may have little in common: an inventory replenishment manager and an eCommerce manager. The data shows that there’s actually a 63% crossover in skillsets.
“What the pilot has taught us is that AI and data analytics give us solid grounds for having an optimistic view about the future of work and the opportunities for reskilling,” Patrick observes.
Becoming future fit
Our hope is that other companies from the consumer goods sector will add their own case studies to the research (the key learnings of which are below).
In the long run, our ambition is that the findings will move from the hypothetical to the practical, informing how HR professionals address the pressing skills challenges faced by businesses.
“Focusing on expanding opportunities for growth for our own people is front and centre of our Future-Fit strategy. We know that if they grow, then our business also grows,” Patrick notes.
“Giving our people the training to fill internal skills gaps is good for them and for our business. If data and AI can help us do that better, as this initial pilot indicates it can, then great, let’s use it.”
As the research pilot goes forward, Patrick is confident that the role of tech will increasingly be seen as a friend, not a foe, of today’s fast-moving world of work and skills.
Key Learnings: Future Skills Pilot Report
- Skilling is just smart business: preparing existing employees for new roles is often the quickest and most cost-effective solution to filling skills gaps.
- HR must empower individual talent mobility: emerging data and AI-driven technology can support HR’s efforts to equip people to build and shape their careers.
- AI is essential for eliminating bias: machine-learning offers an objective, equitable means of creating new or potentially overlooked job pathways.
- A culture change is required: upskilling needs to be seen as a competitive advantage or as a business imperative.
- Cross-industry collaboration is an accelerator: preparing people for the future of work has to be a collective effort; no individual company can do it alone.