Build a movement, not an enclave
Photo credit: Alex Saks via Unsplash
The current wave of AI products have been around long enough for enterprises to launch ‘AI transformation’ initiatives, to wonder why those initiatives aren’t yielding the results they hoped for, and to reach for new ways of working to try to jolt them into life.
For people who have worked in technology for more than a few years, this cycle is familiar: a new technology becomes generally available (cloud, mobile, web, Big Data and so on); bold claims are made for the impact of that technology (cut costs, improve customer engagement, make better decisions and so on); initial projects fail to make that impact; big transformation programmes also fail to make that impact; enterprises make organisational changes to try to get the benefits they were promised.
If you have seen this cycle many times, you have probably developed several survival tactics: try to get behind the hype and learn the fundamentals of the new technology; learn what it can do and what it can’t do; calm unrealistic expectations; salvage value from failures; and, ultimately, work with your peers to develop sustainable professional practice.
Such tactics may be perceived as cynical during the first rush of enthusiasm and heightened expectations, and as naive when everything is going wrong. But I think that they are merely practical responses to an industry where constant change engenders repeated irrational action.
One of those irrational actions is so familiar that it might as well be built into the transformation plan. Milestones in that plan would include:
A transformation initiative is launched with hope and fanfare.
The initiative becomes bogged down.
When asked why things are moving so slowly, leaders say that they don’t have enough people, they don’t have the right people, and that they are held back by process and bureaucracy.
The organisation creates a brand new team, with extra resources (usually recruited from outside the company) and permission to skip all the processes and break all the rules.
Unfortunately, those aren’t the only milestones that need to be added to the plan. If we are to reflect the full story, we should also include:
The team has some initial success, releasing solutions which have low dependencies on other systems and platforms (a new app, a chatbot, a dashboard).
Praise all round.
As the team attempts to deliver more profound change they discover that integration is difficult, and that, even if they are exempt from processes and approvals, the teams that they are working with aren’t.
Delivery slows down and the new team and the existing teams blame each other (‘Cowboys!’ ‘Dinosaurs!’).
The new team calcifies into an enclave with its own culture, traditions and ways of working, as well as its own approval mechanisms and bureaucracy.
Given the repeated occurrence of this pattern, perhaps enterprises attempting AI transformation (or whatever form of transformation comes next) should try something different. We can still start with a new team: after all, teams are our primary units of transformation. However, that team should have some explicit ground rules. First, it should seek genuinely new tools and new ways of working, so that it can discover things we don’t know. Simply scrapping approvals and letting people pick their own tools are not new, and don’t help us make interesting discoveries. Second, the team should be deliberately engaging and outgoing, learning the lessons that other teams have learnt, and being open about what works and what doesn’t. They should operate as part of the community, not stand apart from the community, And third, they should have a deliberately high turnover, allowing people to join the team, and encouraging existing members to join other teams. Rather than being a team of strangers which tells others that they know better, they should be a team of friends who share problems and share solutions.
Enterprises that put the work in to build such teams may be able to change the milestones on the transformation plan so that they read something like this:
A transformation initiative is launched with hope and fanfare.
The initiative becomes bogged down.
When asked why things are moving so slowly, leaders say that they don’t have enough people, they don’t have the right people, and that they are held back by process and bureaucracy.
The organisation creates a new team, drawing people from across the organisation, with the goal of figuring out ways to use the technology effectively.
The team has some initial success, working with other teams to make small changes across multiple systems.
Muted praise.
The team and the teams it works with steadily accelerate the pace of change as they gain confidence and competence.
New ways of working and tools ripple across the organisation as people move in and out of the team.
The change becomes a movement which delivers and exceeds the goals that the enterprise was seeking.
This is, of course, hard to do. But I believe it is more likely to succeed than simply repeating a pattern of past mistakes and hoping for a different outcome.
