Over the past 12-18 months I’ve been working a lot with various process change. Transition to this, transition to that, and all the associated process change required as you learn and adapt along the way. If I had to call out the biggest challenge, or even blocker to success, it would be people’s unwillingness to fail.
*Fail: to fall short of success or achievement in something expected, attempted, desired, or approved:
The experiment failed because of poor planning.
*Dictionary.com (I underlined the word experiment)
From my experience people’s understanding and definition of the word fail is too negative. It can often prompt quitting… “I failed and that, so I’m going to quit”.
I’ve been thinking about how to change that, or perhaps even a new word to use…
They just don’t work. 😉
The reason I underlined the word experiment in the example taken from Dictionary.com is that it aligns so nicely with where my thinking is currently at – treating process change as an experiment, or a series of experiments to be more precise. Attempting to soften the blow of the words fail and failure.
Taking from science, what happens when an experiment fails? Sure, we could simply quit thinking that our hypothesis is false. However, the science community teaches us to push on, revisit our variables and control them more tightly if required, take information gathered from the failure and revise the hypothesis, then experiment again. Rinse and repeat.
Remember, a failed experiment can yield just as much valuable information as a successful one, if not more!
Identify Potential Process Problem/Desired Change – At this point you’re thinking about the why, the goal of the change. Transitioning to a new way of working? Identified a timeliness problem via value stream mapping? This is the starting point where you identify a potential process problem, decide a change is required to drive efficiency, or perhaps you’re told to change by a higher power. Whatever the reason, you need/want to change.
Build Process Change Hypothesis – You’re now thinking about the how. Big bang? Small increments? What can you attempt in order to see success with the change and meet the desired goal.
Plan Experiment/Control Variables – The size of the plan and the amount of effort put into it will of course depend on the experiment and the amount of variables you’re potentially dealing with. When experimenting you need to be able to control and understand the variables, and with process change this can be extremely difficult due to the often large scale of human involvement. You may even need to allow for the mood of people involved, and who knows what that could be from one minute to the next. This is where understanding more than control is important. If you can at least understand the variable (as you cannot control a person’s mood for example) you can allow for it during the experiment and when drawing your conclusions.
Run Experiment – Execute your plan and run your experiment! Take notes, collect data/information, monitor your variables and continue to understand them if you cannot control them.
Draw Conclusions – This is the important part (well, it’s all important but this is where you can influence people’s view on failure). Did what you implement meet your goal? No. That’s fine, we’re simply experimenting remember. Take what you’ve learned from the experiment and circle back to the top!
This all seems very easy and logical in theory. As with most things, in practice it’s far more difficult. Some cautions:
- Don’t bite off more than you can chew. The size of the experiment can make a huge difference in the success of this change process and people’s willingness to fail. If you build and experiment that will take months to run then people’s acceptance and understanding of a failure will be much harder to come by. Not only that, with a larger process change experiment comes more variables. You need to limit the variables as much as possible, especially those you cannot control.
- Use the language of experiment often. The ‘general’ understanding of the word experiment (and the process of experimenting) brings a softer meaning to the words fail and failure. People understand that experiments fail, and that it doesn’t mean we should immediately give up.
- In line with the first caution above, think about the level of risk associated with your experiment. If your experiment does fail, what will the impact of that failure be? Can you recover quickly? If you assess the impact of the failure being too great then it could be a sign you need to breakdown the experiment into smaller ones, or remove potential high risk variables. You can’t sell a process of experimenting if your experiments keep killing the business!
The key with all of this is getting people to understand and accept that a certain level of failure is OK, as long as you’re learning from it.