When Satya Nadella took over as CEO of Microsoft in 2014 it was seen as a company heading towards irrelevance. Not only had it missed out on mobile and social but its core market was being attacked on multiple fronts by Apple and Google.
Many credit Nadella for pulling off a historical corporate turnaround. Nadella focused on cultural changes to Microsoft which, over five years rewarded the company with a $1 trillion valuation and placing it amongst the wealthiest publicly listed companies in the world.
In an early interview Nadella talked about changing Microsoft from a “know-it-all” to a “learn-it-all” culture. “Take two people, one of them is a learn-it-all and the other one is a know-it-all, the learn-it-all will always trump the know-it-all in the long run, even if they start with less innate capability” he said.
Not all companies pull out of the same nosedive Microsoft experienced. Many successful companies fail to respond to big changes in their environment and never recover.
We often assume that this is because the company ignores the problem or fails to respond. Donald Sull researched why good companies go bad and found that this wasn’t the case. Companies identified the trends and threat and moved rapidly by investing heavily in countering them. They were full of action. Unfortunately, their action was based around more of the same. He described this phenomenon as Active Inertia.
Active inertia is an organization’s tendency to follow established patterns of behavior — even in response to dramatic environmental shifts. Stuck in the modes of thinking and working that brought success in the past, market leaders simply accelerate all their tried-and-true activities. In trying to dig themselves out of a hole, they just deepen it.
In my previous post I talked about the relationship between Method, Product and Performance. I used the example of how Dick Fosbury transformed the High Jump sport with his new method called the Fosbury Flop.
Deming said “Best efforts are not enough, you have to know what to do.”. Active inertia is the corporate equivalent of working harder on the scissor method when all your competitors are mastering the Flop. Essentially working harder at the same method.
This means there are two main concerns for any product or service to answer. The first is to improve performance by focusing on the method and ensuring that it is fit for the product we are trying to produce for our customers.
The second is to focus on knowing how to improve. Customers expect continuous improvement. They expect you to deliver solutions that they didn’t even know they wanted. If you don’t, then when your competitors do, they will switch. And if your competitors don’t but do just as well as you then your customers have little to lose so may still switch.
Essentially our method must be fit for two dimensions:
- Does it meet the customer’s needs today?
- Can it adapt to meet the customer’s needs tomorrow?
The first one assumes a fixed target that we must reach. We know the customer’s demands and we simply improve our method to improve quality, reduce defects, reduce costs and price. Essentially to become increasingly lean.
The second one assumes a moving target. One where our method must include sense checking and the ability to adjust and change. Essentially to become increasingly agile.
The same method
The difference between Nadella’s vision of Microsoft and companies which suffer from Active Inertia is the recognition that both questions must be answered by the same method.
Companies which suffer from Active Inertia believe that they can answer the second question through their current method of working. Donald Sull describes this like countries who fight new wars with the tactics from the last war. They believe their previous victories grant them great insight and advantage. Essentially they are “know best” companies.
Companies which focus on building a single method to answer both are “learn best” companies. They realise that the existing method can only be improved from new learning. Not from previous experience. And that must be built into the method itself.
To understand how well the method achieves this ask yourself: how fast can we go from having an idea to improve to successfully embedding that idea across the company?
Learning at speed
The ability to learn faster than your competitors may be the only sustainable competitive advantage. - De Geus
Having a method which can respond to ideas for improvement is not enough. It must actually learn. Companies which suffer from active inertia work under a fatal assumption. That their ideas will work. This causes them to focus on delivering ever bigger change faster.
A learning organisation doesn’t just focus on changing its method at speed. It focuses on rapidly eliminating the bad ideas from the good. They assume nothing about the validity of each individual idea. All of them are equally likely to be wrong.
Whilst they target ambitious change they do so by always keeping change small. This is because big ideas are full of small ones. And even the small ones need validating to avoid wasting time on committing to them.
Which means a key metric of the method is: how fast can we go from having an idea to validating whether it is worth committing to?
There are dozens of different methodologies which all achieve both of these things. The list includes Agile, Design Thinking, Systems Thinking, Lean Startup’s Build, Measure, Learn, Lean’s Plan Do Check Act, Improvement Kata’s or Observe, Orient, Decide, Act, Hypothesis Driven Development.
All of these methods have learning built in. All of these method rely the systematic observation, measurement, experimentation, formulation, testing, and modification of hypotheses. They are all essentially applications of the scientific method.
In all of these methods experiments are kept as small as possible. A succession of rapid loops gradually increasing in scale. They do not leap from one small experiment to one giant change.
A method which leaps from small to large is not learning. It is simply a “know all” method with the facade of experimentation. It isn’t experimenting to learn but experimenting to confirm existing biases. It learns nothing.
There are three things to conclude from this:
- Improving the method improves the product which improves performance.
- A method which learns faster improves the product faster which improves performance faster.
- They are the same method.