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If you read one article in 2020, make it this one…
This is the best article I’ve read this year on the People side of scale-ups (and I’ve read quite a few). So as you wind down on 2020, why not make a bit of time to imbue the wisdom of Khalid Halim…
A couple of things really stood out for me. First, I love “the law of start-up physics: humans grow linearly, companies grow exponentially“. In other words, if you’re a scale-up, your company is going to grow quicker than your people can. Once you accept this premise, you have to face into the most challenging aspect of rapid growth: that there are transitions in your journey when the team that got you there won’t be the team to get you through the next wave of growth. To put it more bluntly, leading a scale-up means you have to disappoint people who’ve worked their guts out and who’ve been critical to your success, either by moving them out or by bringing in new people above them. And as Khalid points out, this is a lot easier if you’ve agreed this is how things will end from day one.
The second, is Khalid’s point about how a Founder can escape the trap of personal linear growth if they own the narrative. Stories scale. If you can continually communicate a vision that stretches and inspires people; if you can keep people grounded in your company’s purpose and character; and if you can define the problems and opportunities you need people to focus on – you can be a Founder who attracts the talent you need to navigate rapid growth.
And if you want some help thinking through and articulating that narrative, you know who to call…
The power of recommendation engines
If Khalid’s article was my favourite of 2020, this one from the MIT Sloan Review was easily my favourite of the week. It’s a great discussion about the potential of recommendation engines to improve the employee experience and to nudge performance, and it really brought home to me the potential of the peopleOS perspective.
Let’s take learning as an example. In the traditional HR mindset, L&D starts with the assumption that ‘teacher knows best’. The L&D team decides what people need to learn. They then create or source the content, design a course and release it to the business. This process usually takes months, and when you’ve invested that amount of time and effort into something, the last thing you want is to capture the data that might prove it was a waste of time. So the content typically gets released without a robust feedback loop and the L&D team moves onto the next thing on the to do list.
Now, when you start from the perspective of a peopleOS, you’re not looking to create learning content for your people, you’re looking to create a system that can teach itself. In this context, recommendation engines become incredibly powerful ways of nudging learning and behaviour change. Rather that ‘teacher knows best’, there’s the scope to harness your people’s natural curiosity and to use a recommendation engine to help them lay a trail others can follow.
And here’s the thing I don’t think people have got their head round yet – the data and insights opportunities in an employment relationship are different to consumer relationships. You might have a smaller n, but in a healthy, trusting culture, I think people are prepared to share much more with their employer than they are a retailer they buy from.
When you think about a recommendation engine being driven not just by reviews, but by information on the context and the behaviour (whether that’s from wearables, interactions on communications channels, performance, feedback and effectiveness data), the potential is mind-blowing. You can start to get to a place where your peopleOS is predicting not only the most effective content, but also the most effective contexts in which it’s deployed. 🤯
For fellow tsundoku sufferers
I’ve been going a bit stir crazy over the past few weeks: waking up, sitting down in my home office, working all day, then going to bed and repeating the process. Mrs G spotted I was looking a bit ‘sub-optimal’ and on Tuesday she suggested we take the morning off to head to one of my favourite bookshops ‘Mr B’s Book Emporium of Reading Delights’ in my hometown of Bath.
I suffer from a condition the Japanese call tsundoku – a compulsion to buy more books than you could possibly read in a lifetime. On Tuesday, I gave full vent to this affliction and felt much better for doing so.
If you’re in the mood to treat yourself (and you’ve already got the playbook…), here’s the Behavioural Scientist’s best books of 2020…
I think we’re all probably done with 2020 now. Personally I need to take a bit of time off and I’m looking forward to starting 2021 with a clean slate. Frankly I can’t be bothered to do a newsletter again this year, so don’t expect the next one until January.
Before I sign off for the year though, I wanted to share this great brandbook from Quiet Room. I can’t decide whether the venn diagrams, competitor analysis or curve of credulity was my favourite bit…
Merry Christmas and a Happy New Year to you all…
Founder and self-satisfied buyer of books at The Pioneers