Check out this article in Lancashire Business News.
It’s great to have a satisfied customer, even better when they tell other companies how happy they are
I am delighted to have been accepted as a Boost & Co partner.
I set out 18 months ago to help businesses learn and apply process improvement techniques to enable profitability and growth. Like everyone else I have bills to pay, but I wanted a way to help small business owners learn about continuous improvement. The Boost growth mentoring programme enabled me to do just that.
It has been a pleasure and a privilege to help small business owners understand the most effective ways for them to grow their businesses, whilst managing the amount of time they must devote to working in the business. Along the way I have helped business owners to do the following;
- Reduce their working hours whilst increasing capacity through a 30% increase in productivity
- Identify the vital few actions required for their business to grow and thrive
- Implement world class manufacturing techniques normally found in large multinationals into a small engineering company
- Identify the right investment questions to ask when looking at growing through acquisition
In each case the business owner really knew the answers, what they needed from me was structure and a ‘sounding board’ to enable them to sense check their plans.
I believe the key to successful mentoring lies within each mentor. If you are focused on how to directly gain from the mentoring programme and transition the mentee to a paying customer you will not deliver their needs. The key is to focus on delivering value to that mentee as if they were a paying customer. Be generous, give freely of your skills and knowledge with the aim of truly helping. The return may not happen for many years, but I believe that every mentee I help in the right way is another link in forging a reputation for capability and reliability. With each session you get to know each other better and develop a relationship that leads to trust.
When you have established trust, you set the foundation for future recommendations. It is those recommendations that will deliver the return on investment. Mentoring is about ensuring that manufacturing businesses thrive so that there are consulting opportunities in the future. Delivering today’s mentoring at high quality with added value builds tomorrows reputation and income streams.
So with that in mind, I am ‘paying it forward’ delivering high added value mentoring that has a positive impact on quality, cost, and lead time in my customers businesses.
If that sounds like something you need, get in touch, let’s have a conversation.
I was recently asked, as a mentor what do I get from mentoring. The answers are quite basic and rooted in the reason I set up my business.
I set up my own business because I repeatedly saw small and medium businesses struggling with quality issues, high stock levels and long lead times caused by ineffective processes. I wanted to help businesses that are struggling to improve and grow, so I became a consultant specifically to help and support these businesses.
What I gain from mentoring small businesses is
· The satisfaction of helping businesses learn to use world class techniques.
· The opportunity to make a difference for small business owners
· Networking with small businesses demonstrating the value I can add
· Opportunities to actively practice coaching and mentoring skills
· Exposure for my business and my brand
The most important reward by far is the difference I have been allowed to make in peoples lives through removing obstacles to growth, both now and in the future.
Asking for feedback is important for any business, as it helps us to improve what we do and eliminate any negative effects of our activities. What we don’t always recognise is the positive feedback, and the impact we can have on someone’s business when we give great service.
I have started working as a growth mentor in Lancashire, and I have just received my first feedback from that work. It has been interesting and really touches the heart of why I started Tamarind Tree Consulting, it is an opportunity to help people improve their businesses. So getting that first feedback from this sort of mentoring is significant for me. As always, I have set out to do the best job possible for the client. Hearing that the client values the support and has seen practical benefits is brilliant. You can read his testimonial here.
So why this post?
The feedback got me thinking about what is important and why did this work well. It seems to me that focusing on the customer and their needs was key. My role is not to tell them what to do, but to advise and support them through decisions, and activities they are finding difficult. The key factor here is practical application of process improvement, applied with respect for my customer. We haven’t deployed huge amounts of training and tools, there has been no big bang effort. Instead we used the time to focus on the vital few actions, and ensure that we focus on understanding why. This approach leads naturally to collaboration. It has been brilliant to see not only my mentee growing, but also to see this positive impact on his team. You can read his testimonial here
For me, process improvement consultancy is not simply about the hours charged, although more hours is always nice! It is about making a practical, positive difference to the lives of the people I help. Focusing on customers with love may not always result in more hours of work, but it will always help people learn good habits that hopefully stay with them as they, and their businesses grow. People remember those who really help them, and if the opportunity to support them arises, well, I believe you reap what you sow.
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.