Three Trends for Business in 2022

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05.01.22
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While the years seem to merge, the wheels of change are spinning faster than ever. Here are three things your business needs to think about as we hit 2022 running.

By: Chris Hafner

Get Hybrid Right… Real Hybrid

Coming out of 2021 was a blur. It went really, really fast and we adapted to different technologies and different ways of working. But the companies that are going to differentiate themselves in 2022 are the ones that really get hybrid right.

Hybrid isn’t just half the team on Zoom and half the team in the office. There are tools and technologies out there to really think about the human aspect of hybrid experiences. There are new categories of tools to support all types of interaction – face to face, remote, hybrid, asynchronous, synchronous.  There are new digital facilitation capabilities, like the ‘Howspace’ out of Helsinki, Finland, that allow for a wide range of dialogic interaction in a fun, flexible environment. 

Or a brilliant little startup from the female CEO and co-founder Taylor Nieman, who became disenchanted with the way Zoom, MS Teams, and other platforms handled social interactions.  She and her team took a human behavioural science approach to reimagine digital social interactions. It’s an absolutely brilliant, human centred solution. 

Slack, Miro, Teams, Zoom are all well and good – but firms reimagining the future of work with hybrid as the norm are likely to outpace others.

Flexible Talent Models

There’s a lot of noise today about the ‘great resignation’. And prior to that, we’ve had discussions around the ‘war for talent’. We need to take a step back and take a look at what that really means.

I don’t like the term ‘war for talent’. Talent is people, human beings.  Talent isn’t a prize or commodity to be won on a battlefield. Talent shouldn’t be ‘taken prisoner’ by a victor.

Talent is something we need to develop, nurture and inspire. So I think that organisations in 2022 really need to rethink their fundamental construct of talent. There is a shift in talent trends. It isn’t just about work-life balance, the trend is towards work-life ‘states’.  Balance is doing both at the same time – the traditional 9-5 work week ‘balance’.  Work-life ‘states’ is about people who will move in and out of states of work and non-work – they may work for 8 months, then want to volunteer or travel for 2 months. 

Many in the workforce have multiple talents – and prefer to utilise those talents at different times – programming for a few months, then picking up a gig to do creative design. We need to rethink our workforce in an age where the work can be taken to the people. 

So rather than retaining talent for just our organisation, we need to be thinking about how we can tap into flexible talent as and when we need it. Firms that embrace a more flexible, transient workforce will likely move at a greater pace than those still battling it out for captive talent.

3D illustration of many pawns over black background plus a golden one. Concept of talent sourcing and spotted candidate

Explaining Your AI

We’ve got to weave technology in here somewhere as artificial intelligence is starting to mature a bit. And some of the challenges we’ve had, especially with machine learning, is the ‘learning’ piece, not the ‘machine’ piece.

Everyone says that data is the new oil. Well, as of today, oil is really not very valuable, right around $70 for a barrel of WTI crude at the time of this writing. And I don’t know about you, but I’ve never used crude oil in my life, and I doubt anyone else reading this has either.

What we have used is the byproduct of oil once it’s been refined, organised, structured into its valuable components to release value through the refining process. That’s where we get value out of oil, and it’s the same with data.

Over the last few years, we’ve had this data rush.  We’ve had a mass amount of data, but we really couldn’t make sense of it. Not much of it was information. So a lot of synthetic data had been created.  That synthetic data carries the DNA of its’ origins, so may well be biased.  Algorithms trained on biased data produce biased results.  This is where alternative data comes in. 2022 will see alternative data move beyond hedge funds into the mainstream. 

And I think in 2022, we’re going to see some more legal cases around explainable AI. Tell me how your AI or algorithm came to that conclusion? Why did you serve that advert to me? Why did you exclude me from this opportunity?

Organisations who focus on explainable AI and leverage alternative data sets will protect themselves, their employees, their partners and their customers, as well as advance their AI ambitions.  These organisations will be the ones best suited to overcome the legal and ethical challenges around artificial intelligence.

Hafner circle
Written by
Chris Hafner