"Most of what we call management consists of making it difficult for people to get their work done" - Peter Drucker
Management is the greatest inefficiency in any organisation.
Many of you will be familiar with the work of Gary Hamel , but his explanation of how management ‘spreads’ is always helpful. "Typically a small organisation might start off simply – one manager and 10 employees." "But as it grows it will often keep this ratio and sometimes reduce it. So an organisation with 100,000 employees will have at least 11,111 managers. Because an additional 1,111 managers will be needed to manage the managers." "And that’s before you go near management related functions whose entire function is, well, management." Most of our organisations are focused on growth rather than remaining small and simple. More people inevitably means your coordination and communication problems magnify, the management hierarchy multiplies, and things get more complex. Research shows that every time the size of a city doubles, innovation or productivity increases. However, exactly the opposite happens with organisations. When companies get bigger, innovation or productivity per employee generally goes down. This is why companies which grow quickly get into trouble. A fast-growing company can go from 20 to 400 people without changing anything about how they work. What works in an organisation of 200 people simply doesn’t in an organisation of 2000. Globally, our employees crave more autonomy and less bureaucracy. However, there is currently a gap between wanting autonomy and flexibility, and getting workplace autonomy and flexibility. And the reason it’s difficult is this: it’s impossible to dismantle bureaucracy without redistributing authority. Hierarchical and status-obsessed cultures necessarily militate against relationships based on equality, empowerment and collaboration. Most of our organisations don’t redistribute authority, they accumulate it. So what if we replaced all the managers with robots? As Simon Penny writes for Bromford Lab, at the moment we’re either 100% human led or just starting to explore the possibilities of having machines support decision making. Simon points out that humans are particularly bad at making decisions. Our decisions are largely emotional and often illogical, which can lead to inequity, data bias and bad outcomes. Having a machine help us make decisions more efficiently actually makes a lot of sense. Who says they wouldn’t be better than managers?.The Mystery of Miserable Employees
In an article for the New York Times, Neil Irwin explains how a team at Microsoft used data rather than managers to figure out why a business unit had such poor work life balance. The issue was that their managers were clogging their schedules with overcrowded meetings, reducing available hours for tasks that rewarded more focused concentration. Rather than leaving it to managers to solve the problem the team deployed a Microsoft Office feature called MyAnalytics which allows users to receive nudges when their actions don’t line up with their stated goals. A bot notifies you about how much focused time you had, or how many hours you were on email. Just like wellbeing trackers like Fitbit, rather than doctors, are nudging people to improve the quality of their sleep, we’ll see algorithms, rather than managers, nudging us to be more productive at work. To keep teams productive and happy, managers need to master the basics: don’t overwork or expect others to; hold frequent 1:1s; make cross-functional connections; and of course, keep meetings on time and inclusive. All tasks perfectly suited to a robot.We Are All Managers Now
Like it or not we are headed in a direction of either performing human focused work (social, health workers, coaches) or performing deep non-routine knowledge work. All other tasks will be automated at some time in the near future. It will happen slowly:- Things like Robotic Process Automation will begin to undertake the systematic and behind-the scenes jobs
- AI will complement this software to add thought, judgement and intelligence
- You’ll be told by a bot what the optimally productive length of the workday is for you. You’ll be advised whether it makes sense to focus on deep contact with a few customers or much looser relationships with a wider community
- Monitoring tasks (hours worked, productivity) will be democratised and we’ll be self managing using nudges and prompts – developing the interpretive skills to understand what data is telling us.