The workforce skills needs of the future are hard to know. Do we need to take a science fiction approach (or data science!) and try and predict the future?

Future skills needs have never been more difficult to discern.

This is because the future of work is becoming a reality faster than we’ve been ready for, despite many prescient warnings, like one from the World Economic Forum in 2018 which predicted 42% of in-demand skills across all industries would change and 54% of all employees would require significant upskilling and reskilling between 2018 and 2022.

It sometimes seems we're all on a just-in-time skills treadmill, watching as technologies and processes change our industries and the skills our employees need to function.

COVID-19 has only accelerated this change and digitisation. McKinsey & Company found companies adopted digital technologies between three and seven years faster during the pandemic, which has in turn put the speed of core business practices into overdrive.

Technology is now cited most by Australian Industry Skills Committee Industry Reference Councils when asked about changing skills needs, thanks to trends like digitisation, automation and robotics, mobility and connectivity and the Internet of Things.

This is having a profound impact on the Australian skills environment.

A 2021 RMIT and Deloitte Access Economics survey found a third of workers felt their job requirements had changed during the pandemic and one in four didn’t have the skills needed to complete their day-to-day job. A massive 87% now required some form of digital skill. A quarter said their data analysis skills were not up to the level required or outdated, while more than half had no knowledge of skills like coding, blockchain, AI and data visualisation. 

Is it possible for learning and development teams to get a better grip on future skills needs?

Plugging into your workforce skills crystal ball

Employers, working together with their L&D and HR teams, will need to raise themselves from the distraction and challenge of finding just-in-time, short-term skills to look at the medium to long-term if they are to thrive and succeed through this period of skills disruption.

As well as throwing the door open to a variety of internal and external sources of advice on industry change and predicted skills needs, they will increasingly have to bake technologies into the skilling equation to deliver the real-time intelligence they need to evolve their workforces.

Better prepared organisations are likely to utilise connected cloud-based SaaS systems to pull data in from multiple sources across the public and private sectors (both locally and internationally) to inform their situational analysis and decision-making processes.

For example, they may need to utilise tech like Pearson's Faethm AI - which utilises billions of data points to help organisations predict the future - or the data in their own systems to extract intelligence about emerging skills gaps to ensure they stay ahead of the skills curve.

This will involve thinking more broadly about where skills exist. While hiring in of talent will be an important tool, technologies are likely to become more sophisticated in analysing the capabilities of external or internal candidates (through the likes of CV analysis) to identify transferable skills that can be built on through upskilling and reskilling.

Learning technologies will also support more efficient learning and skilling programs across organisations and industries. In fact,  this is how the Technology Council of Australia expects to scale and meet a need for a huge 150,000 more technology workers by 2030.

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