I was away for the first few days of September so posted some pictures of what I’ve come to call Deergital Transformation, including this one:
For much of the rest of the month I looked at the struggle to deliver projects, particularly ones that we sometimes mislabel as transformational, and how we might think about those in different ways:
- We tend to approach projects as if they are always going to be successful. We go all in, often on giant projects. And yet real world experience in films (2% of films made get to the cinema and only 1/3 of those are profitable)
- Similarly, Venture Capital companies know that they are going to kiss a lot of frogs before they find their prince or princess. They back new companies in rounds – seed, series A, series B etc – putting in more money as the principles are proven and the company moves from concept to demo to beta to live and to scale. Bad bets are starved of funds, or “pivoted” where the team is backed to do something different.
- We, all of us, are quick to suggest numbers – a project will cost £100m, or it will take 48 months, or it will save £1bn – but we are rarely open about the assumptions, and, yes, the pure and simple Wild Assed Guesses. In short, all numbers are made up, treat them with caution unless the rationale is published.
- We all like to set targets, but we don’t always think about the things that have to be done to achieve that goal. By 2040 “we will climb Everest” is fine as an aim, but the extraordinary preparatory work to achieve it needs to be laid out, to avoid the “hockey stick” problem where you get close to the date when you expected to realise the aim, only to find there’s not enough time left. As a regular half and full marathon runner, I know that if I haven’t put the time in before the race, it’s going to hurt and I’m going to let myself down.
- Replacing legacy systems is hard. The typical transformational project when we take what we have had for the last 20+ years and replace it with something new, and add lots more functionality (to catch up with all of the things that we haven’t been able to do for the last couple of decades) is fraught with risk and rarely pays off. The typical agile model of MVP and rapid iteration doesn’t always align with the policy aspiration, or what the users want, because, on day one, they get less than they have today. New models are needed though, really, they’re old models.
October has started on much the same path, though let’s hope that the real storms seen at the end of last month have gone and that the only October storms are of the digital kind.