Author: Tim Akerman
Lean out for low hanging fruit?
What is lean?
So many times when people start implementing lean they focus on so called ‘ low hanging fruit’ but is that all there is to it?
The approach of some practitioners would suggest it is, however there is so much more than just taking ‘low hanging fruit’. Also let us not forget that low hanging fruit is often overripe and may not be the best quality!
So where does this focus on ‘low hanging fruit’ come from?
My perception is the reason for such immediate focus on ‘low hanging fruit’ comes from two things. Firstly, there is an unrealistic expectation of the rate of improvement from process improvement activities. Many senior executives seem to have a very short horizon for improvement, and if money is to be spent on process improvement there must be a return within six months, sometimes within three months. This forces a focus on short term improvements, the so called ‘low hanging fruit’. There is nothing wrong with making these improvements, they are free cash, necessary and failing to address them can be damaging to profitability and performance, but this approach should not be confused with a structured lean implementation.
‘Low hanging fruit’ approaches will deliver short term improvement in both process and financial performance, however this will be unsustainable and will not drive the business to be a time based competitor. It is implicit in the description that these rewards are easy to access and obvious things to do, so what is the difference in lean manufacturing? We are making improvements, reducing costs, its all the same thing isn’t it? Actually, no it isn’t. Making obvious improvements should just be done and requires little or no effort and little skill to achieve. Lean manufacturing should focus the business on time based competition, that is making things faster, more reliably and ultimately this will reduce costs. Notice that lowering costs is one result of lean manufacturing. The real focus in lean manufacturing is superior customer satisfaction through time based competition.
Why is time based competition so important?
Time based competitors have distinct advantages over other competitors since for every quartering of total completion time, they experience a doubling of productivity and reduce costs by 20% At the same time they enjoy three times the growth rate of competitors and double the profit margin. This is achieved through a relentless focus on what is of value to the customer
For a process operator access these benefits, they have to implement a sustained and structured lean manufacturing initiative which addresses the following key features of lean;
- Value
What does the customer value? Without knowing this, how can you ensure that value is added and delivered to the customer? The lean journey is always from the customer perspective, since focusing on this the customer values is the best way to ensure business activities generate a profitable return - Value Stream
Mapping how and when value is added to the product enables the business to focus all efforts on doing things the customer values. Mapping the value stream is about more than just the physical activities, it encompasses all of the information flows, all work in progress, everything required to create and deliver the product and / or service the customer needs - Flow
What is the most efficient way to join two points? A straight line, in the same way it is important that materials flow in one direction through the process. The flow should always be from raw materials to delivery of finished product, with minimal work in progress. - Pull
In an ideal manufacturing environment, materials are pulled through the process by demand from the ‘customer’ rather than having materials pushed into the next process regardless of whether to not they are needed. - Perfection
A continuous improvement approach should be adopted, always looking to create additional value in the process,. this should be done either through incremental changes or through a major step change.
Most ‘low hanging fruit’ is of value from the perspective of the supplier’s costs, not from the perspective of customer value, so whilst it is valuable and important to address these losses, it does not replace a lean manufacturing implementation.
Start with understanding value from the perspective of the customer, map the process as it is (current state VSM), then map the process how you would like it to be (future state VSM). Construct a plan to modify the process from current state to future state, taking into account the financial and personnel resources needed to when declaring a timescale. This is then used as a blueprint for the lean transformation.
Lean is a structured, rigorous, disciplined process requiring dedication, focus and hard work to deliver profound and sustainable improvement in the time based competitiveness of the process, leading to improvements in
- Process cycle time
- Waste
- Lead times
- Customer satisfaction
- Turnover
- Margin.
Three Simple Questions…
A behaviour I suspect many lean six sigma mentors have seen with new belts is paralysis by analysis. Newly qualified, with access to powerful statistical analysis software and on their own for the first time, their first reaction is to conduct every statistical test they can think of, working on the principle that they are looking at the data from every perspective. What they are actually doing is in part showing off their new found skills and in part showing off their unconscious incompetence. That is not to say they are incapable, only that they lack experience.
When mentoring new belts I always start them out with three simple questions.
The reason for these questions is to make sure that they learn what I believe is one of the most important skills in lean six sigma; focus. I have noticed over many years that when belts who are new to statistical analysis gain access to a powerful statistical analysis package.
So back to the questions. The first question is this;
1. Can you write a simple statement of what you want to know?
It may seem obvious, but often people forget the first discipline of six sigma – DEFINE.
Starting analysis without actually stating what you want to know leads to confusion. It is all too easy to conduct a series of statistical tests then when the results are available find you can’t remember what you originally set out to discover. Let’s be honest, most of us have done it and had to start again, that’s how we learned not to do it.
It is for this reason that I tell anyone starting to do statistical analysis, do nothing until you can write a simple statement of what you are trying to discover. If you don’t know what difference or correlation you are trying to discover, how can you possibly choose a suitable test? We all suffer from a cognitive bias that makes it easy to believe we know what is required. However, if we can’t write it down simply, and in plain language, do we really know what we are trying to discover?
Having written down our question in plain language we need a way to answer our question. This leads to the second question;
2. How will this test answer the question posed above?
There must be a direct link between the analysis undertaken and the purpose of the test. For example if we want to know if changing a pigment gives the same colour for a particular application, we should consider how the testing has been done. If the tests are done side by side in a laboratory on the same piece of substrate and the results are normally distributed without outliers, a paired t-test would be appropriate. However if the testing occurs in different factories on different batches of substrate and the results are not normally distributed with outliers, Moods median test should be used.
The context of the data has to be considered when deciding which test to use. Again, the test selection and the logic for selecting the test should be written down in plain language. If you cannot do that, you have not adequately considered your test selection and should revisit your thought process.
So now we have a clear picture of what we want to know and what test should be done to answer that question. What else is required?
3. Write down the rules for interpreting the test.
It is vital that the rules for interpreting results are written down before the analysis is done. If an alpha level of 0.05 is selected and the p-value from the test result is 0.93, the test fails.
Remember the cognitive bias from the problem definition? It appears here again; if we write the p value after conducting the test, we may decide that an alpha level of 0.1 is adequate. The interpretation of the test is different, because our decision making has been influenced by the results, the test acceptance hers hold is no longer objective. For example, if failure resulted in an expensive process change in a business with limited finance, going back to the pigment example, if the new pigment is lower cost it would be easier to accept a larger difference to push the change through. That may not satisfy the customers’ needs and may result in higher complaints and potentially higher costs in the long term. the combination of a desire to save money and an apparently small difference in performance will have seduced the operator into unconsciously compromising their standards.
How should the decision criteria be documented? That is the whole point and purpose of null and alternate hypothesis, but that is for another time.
Following these three simple rules will ensure clarity of purpose, that there is a rational link between the desired information and technique applied and that the pass / fail criteria are set objectively. Following these simple rules for data analysis will save a lot of time and help the practitioners to become confident and productive in a shorter time.