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How to think scientifically, solve problems and get past the ‘bouncer of Continuous Improvement’

Excellent manufacturers are excellent problem solvers who are continuously striving to learn. In this blog, Manufacturing Advisor Nick Brandwood examines the common characteristics of effective learning organisations and how SME manufacturers can apply ‘scientific thinking’ to build the foundations for Continuous Development.

In the words of the writer and poet Archibald MacLeish: “There is only one thing more painful than learning from experience and that is not learning from experience”. And what an experience we’re living through. It really says something of the challenges of COVID-19 at the moment that even EU Exit, our other major concern on the horizon, is rarely mentioned.

It would be nice to think that something good can come from all this uncertainty – that this experience, in exposing the vulnerabilities within an organisation, has helped to pinpoint and prioritise opportunities to improve, and ideally the plans to see them through. Another word for this is ‘learning’. Going forward, the companies that learn effectively will be the companies that survive and thrive.

Excellent organisations

When I think about excellent manufacturing organisations, I think of companies like Toyota. Toyota considers itself a ‘learning organisation’ focused on the development of excellent problem solvers.

Here’s a question. Is an excellent organisation:

  1. One that has eliminated all problems and performs consistently to this level every day; or
  2. One that constantly challenges itself to identify and solve new problems, and values effective problem solving above all else?

Toyota defines an excellent company as one that’s constantly striving to learn. A company that identifies new problems and solves them; that continuously improves.  Statement a) isn’t completely wrong as it infers a foundation of standard work, which is crucial, but Continuous Improvement is a constant journey from best current method to (new) best current method. And before you embark upon that journey, there are some rules you need to follow. A ‘door policy’, if you like.

Continuous Improvement ‘door policy’ – Foundation activities

If you want to get into the Continuous Improvement club and wear the luminous hand stamp that says ‘excellent problem solver’, there are a few things the bouncer is looking out for at the door:

  • You must have an identified and agreed best current method – one way of doing an activity that everyone commits to. The bouncer is looking for evidence of a stable foundation on which Continuous Improvement can be built:
    • Good workplace organisation: The 5S method provides clear rules and visual controls over what constitutes the ‘standard condition’. Anomalous conditions and remedial activity to revert to standard should be made obvious
    • Standard Operational Procedures (SOPs): Best practice should be captured in a standard document; pictorial, quantifiable and error proofed where possible. People should be trained to the standard, and the training validated and verified regularly
    • Training Matrices: Confirmation that good workplace organisation and working to SOPs is valued. A clear indicator of who can do what without introducing another source of variability into the process.
  • It’s not critical at this stage that your method is unequivocally the best, but for now take comfort that:
    • The best current method is a hypothesis (theory) to be tested through experiment
    • There’s no such thing as a failed experiment. Your theory is either proven or it’s disproven. Either way, your knowledge increases
    • The key is doing something and testing it. So do something!
  • Once you have a best current method and the impetus to do something, the next challenge is to implement scientific thinking. What do you expect to happen? This is a powerful question because it requires that changes are quantifiable. To paraphrase Albert Einstein, if you have an hour to solve a problem, you should spend 55 minutes understanding it and 5 minutes thinking about solutions. But if you can’t express your process in numbers, you can’t really understand it, and if you don’t understand it how do you determine what’s critical? If you don’t know what’s critical, how do you improve it?

Thinking Scientifically

The cycle of Continuous Improvement when expressed scientifically is as follows:

  • There is a current condition (best current method) which can be measured as a number
  • There is a theory of how this can be improved
  • An improvement experiment is derived and the question asked: “What do we expect to happen?”
  • The answer to this question can be measured as a number.
  • The experiment is undertaken
  • The measured results are analysed
  • Conclusions are drawn. Either the theory was proven, and the process was improved, or the theory was disproven, and the change had no effect.

Remember: there’s no such thing as a failed experiment; either way you’ve learned something that you didn’t know before. The key is to capture the experiments that result in process improvements in standard work. If you’re already confident with 5S, visual management, SOPs, error proofing, training matrices, then this should be straightforward. If you’re not, ask us for help.

By the same token, if what you’ve learned from your experiment is that your theory was wrong, then learn from this too. Capture it and communicate it so nobody wastes time by having the same bright idea in two years’ time.

The scientific method I have detailed here is synonymous with the Plan, Do, Check, Act (PDCA) cycle:

  • Plan: Quantify your current condition and identify the target condition, next experimental step and what you expect to happen
  • Do: Undertake experiment
  • Check: Analyse results, review what happened against what you expected and form conclusions
  • Act: Either update best current method based on findings or use knowledge to inform current understanding and form new hypothesis.

In discussing the PDCA cycle I would recommend you read the book Toyota Kata by Mike Rother, which is an effective method for coaching yourself and others through this scientific learning cycle as practiced by Toyota.

The key question

As I mentioned previously, “what do you expect to happen?” is a powerful question in Continuous Improvement activities. Not only does it force you to quantify and measure your process as a matter of routine, it also pushes you to develop meaningful actions and think about how far along that journey the action will take you:

  • It tests your current understanding of the process and your ability to express it in numbers
  • It demands you prioritise actions based on criticality
  • It ensures actions are aligned to the target condition
  • It’s clear when actions are complete
  • It’s demonstrable when actions have been effective.

Asking “what do you think will happen?” also brings purpose, momentum and clarity to daily review meetings by encouraging people to speak in numbers. Try it the next time an issue is discussed and an action proposed – what is the current condition in numbers? What is the ultimate target condition in numbers and from this specific action what do you expect to happen in numbers? Then, did it happen and can the action be closed?

I have a theory that this question will improve the effectiveness of your daily meetings and your ability to problem solve. The next step is for you to conduct an experiment to test my theory – either it’s proven and you learn something, or it’s not and you still learn something. There’s no downside; just knowledge. So give it a go, put the right foundations in place to satisfy the bouncer and welcome yourself into the Continuous Improvement Club. You deserve a drink after all this hard work!

We’re re-designing our services to help you recover

As we emerge into this brave new world post-EU and COVID-19, we’re busy looking at new ways to aid business recovery and help you plan for the future. If you need help with any of the issues raised above, contact us and one of our specialist advisors will be in touch.

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