Scalable learning vs Scalable efficiency

by David Poole | 3 mins read

Automation is shaping virtually every institution on the planet, from small and medium sized enterprises right through to government organizations. But its success or failure will in large part be driven by the mindsets adopted by business leaders.

Take Twitter as an example. Since Elon Musk bought the social media company for $44 billion last year, the mercurial entrepreneur has, it seems, largely taken a traditional approach to automation, viewing it as an opportunity to take costs out of the business and to make the company much more competitive.

As a result, Twitter now has around 2,000 employees globally, down from approximately 7,500 in October. Inevitably this has reduced overheads significantly, but it’s also had a massive impact on the quality of the service as well as how the brand is perceived by advertisers (many brands initially walked away from Twitter though some have returned in recent months).

That’s not to mention its impact on its online community of users and former employees!

 

Scalable efficiency

In one recent case, a disabled Twitter employee tweeted Musk directly to find out whether he still had a job because HR was unable to tell him. It turned out that he had been fired but his job was later reinstated. And in a recent BBC Panorama programme, Elon Musk’s Twitter Storm, research suggests that the company no longer has the staff in place to protect people from trolling, coordinated disinformation and child sexual exploitation.

Driven by fear, it’s an approach to automation that John Hagel - the founder and co-Chairman of the Center for the Edge at Deloitte - calls the ‘Scalable Efficiency’ model. "Often, people focus on one slice of automation," Hagel said. "When we take that view of the future of work, we end up with modest results. The imperative is to take a holistic view."

One downside of the scalable efficiency model is (as we have seen with Twitter) loss of trust as workers – even leaders – wonder just how long their jobs are going to last. And while some companies talk about reskilling people whose jobs have been eliminated through automation, others simply turn to the gig economy hiring people on an as-needed, project basis to make fixed labor costs variable.

Far better for navigating the latest wave of automation, Hagel argues, is to adopt an automation mindset driven by curiosity and exploration, rather than one purely based around cost cutting. He calls this more positive approach to the new technology ‘scalable learning.’

 

Scalable learning

Speaking at the recent CEE Business Services Summit and Awards in Warsaw, Poland, I talked about the differences between the two distinct approaches to automation. And about how while there is nothing wrong with building a career around the scalable efficiency model, the institutions with the greatest chance of succeeding in the future will be those driven by scalable learning.

Using the scalable learning approach, leaders can focus on how their organisation can learn faster at scale (though leaders do need to be pragmatic in pursuing this new paradigm in order to reduce pushback). Rather than watching e-learning videos or training programs on how to do an individual job more efficiently, scalable learning involves creating the infrastructure and incentives that will make everyone think about how to create new value for the business.

According to proponents of the scalable learning model, by making value creation the focus of everyone – from workers on the factory floor to the front line sales teams and maintenance staff – organisations will become much better at identifying problems that stand in the way of success and be more likely to think about new ways of working. “Our view is that, if you ask powerful questions, exciting questions, it excites the passion in [employees] who could make a difference,” Hagel said.

 

Unlocking human potential

At the heart of any digital transformation has to be the people within your organization. There are wonderful things that humans can do that AI can’t currently do and will never be able to do in quite the same way. That’s why we are seeing the phenomenon of ‘human fallback’ because automation can today only handle simple processes and queries and eventually the end customer needs to speak to a human.

However, don’t expect overnight success with the scalable learning model. “If you believe transformation is a rational process, about collecting the right data and presenting it to the right people, you have already lost,” Hagel said. “Transformation is fundamentally a political process, not a rational process.”

It is too early to say whether Elon Musk will be successful in his ambition plans to turn Twitter into a commercial success, but he will certainly need to get ‘champions of change’ on board if he hopes to push through his bold plans. That requires an approach to automation that isn’t driven simply by fear and cutting costs, but by the potential for change and future growth.

That’s how we think at Cognition and it’s how we built our business. Contact us HERE to see how we can help scale your business.