Here Are the Facts
If you are studying for a Lean Six Sigma Green Belt qualification at the moment, you could easily get the impression that somebody has suddenly rewritten the rule book.
Search online and you will find plenty of discussion about artificial intelligence, process mining, digital transformation, sustainability, automation and advanced analytics. Some of these are genuinely exciting developments, and they are already changing the way organisations analyse and improve their processes.
But there is an important question that tends to get lost amongst all this enthusiasm. Have these developments actually changed what you need to learn for your Lean Six Sigma Green Belt examination?
The short answer is no, certainly not in the dramatic way you might sometimes be led to believe.
The longer answer is much more interesting, because it highlights an important difference between keeping up with developments in your profession and preparing for a professional examination.
First, Let’s Separate the Syllabus From the Profession
Lean Six Sigma has never stood still, and I wouldn’t want it to.
The tools available to improvement professionals have changed enormously during my working life. Computers became commonplace, spreadsheets transformed the way we handled data, specialist statistical software became affordable, cloud computing arrived and now artificial intelligence can analyse information and identify patterns at extraordinary speed.
That’s progress, and I’m all for it.
But none of that means the underlying principles of process improvement have suddenly stopped working. Customers still have requirements, processes still contain waste, variation still affects performance and measurements can still be unreliable. Problems still have causes, and once we’ve improved a process, we still need to make sure those improvements don’t quietly disappear six months later when everybody slips back into the old way of doing things.
That’s why I think we need to be a little careful whenever we hear that something in Lean Six Sigma is new.
A new technology that helps a Green Belt do their job better doesn’t necessarily represent a new Green Belt examination requirement. There’s a very important difference between the profession evolving and the examination syllabus changing.
What Do the Green Belt Certification Bodies Actually Say?
Rather than relying on somebody’s interpretation of what might have changed, the sensible thing is to go back to the organisations responsible for the certification frameworks and see what they actually require.
ASQ bases its Certified Six Sigma Green Belt examination on its published Body of Knowledge. That defines the areas candidates are expected to understand and provides the framework from which examination questions are developed.
The current ASQ material continues to cover the familiar Green Belt territory, including Six Sigma and the organisation, Lean principles and the Define, Measure, Analyse, Improve and Control phases, together with the statistical, analytical and improvement techniques that support them.
The IASSC Green Belt qualification provided through PeopleCert likewise remains centred on the established Lean Six Sigma methodology and DMAIC.
The two organisations don’t publish identical syllabuses, and it would be misleading to suggest that they do. However, when it comes to the question we’re interested in here, their position is reassuringly consistent. There has not been some wholesale replacement of established Green Belt knowledge with a new collection of AI, sustainability and digital topics.
Green Belt remains Green Belt.
In fact, ASQ makes a distinction I particularly like when discussing how a Body of Knowledge develops. Professional certification needs to reflect the state of practice, rather than simply chasing the state of the art. That makes a great deal of sense to me.
A professional qualification should test the knowledge and capabilities expected of a competent practitioner. It shouldn’t suddenly rewrite its examination because a new technology or management idea happens to be attracting attention this year.
So What Does a Green Belt Still Need to Learn?
At the heart of Lean Six Sigma Green Belt is still DMAIC: Define, Measure, Analyse, Improve and Control.
I deliberately describe DMAIC as a journey because one of the biggest mistakes you can make when learning Lean Six Sigma is treating it as a collection of unrelated tools that need to be memorised for an examination. Once you understand the journey, the individual tools start making much more sense.
You begin with a problem or an opportunity. During Define, you make sure you understand what you’re trying to improve, why it matters, who the customer is, what that customer values and where the boundaries of your improvement project lie.
Once you’ve established that, you move into Measure because before changing anything, you need to understand what is actually happening now.
That means understanding the process, collecting meaningful data and making sure the measurements themselves can be trusted. There’s little value in performing sophisticated analysis on unreliable information.
Analyse takes you beyond the symptoms and into the reasons behind them. This is where you start investigating why the process is behaving as it is, examining relationships within the data and identifying the causes that are really driving the problem.
Only then does it make sense to move into Improve. Once you understand the causes, you can develop and evaluate potential solutions rather than simply throwing ideas at the problem and hoping that one of them works.
Finally, Control makes sure the improvement lasts. There isn’t much point spending months improving a process if six months later everybody has quietly returned to doing things exactly as they did before.
That logic hasn’t become obsolete. If anything, modern technology is giving us increasingly powerful ways of applying it.
Where Do AI and Process Mining Fit?
This is where the subject becomes much more interesting than simply asking whether something appears in an examination syllabus.
Artificial intelligence can certainly help an improvement professional. It can explore large amounts of information, identify patterns, help generate possible causes, summarise customer feedback and perhaps reveal relationships that would take a human analyst considerably longer to discover.
Process mining can be equally useful because it can help us see what is actually happening inside a process rather than relying entirely on what people think is happening.
Anyone who has spent time mapping a real business process will probably recognise that problem. Ask several people to describe the same process and you’ll often discover that each of them has a slightly different version of how it works. The documented procedure may give you yet another version, while the actual transactions reveal something different again.
Process mining can therefore give the improvement professional another valuable source of evidence.
But notice what’s happening here. We aren’t replacing Lean Six Sigma with AI or process mining. We’re giving the Lean Six Sigma practitioner additional ways of investigating the problem.
The Green Belt still needs to understand the customer, the process, the data, variation, root causes, improvement and control. Modern technology can help us do some of those things faster or better, but it doesn’t remove the need to understand what we’re doing in the first place.
New Tools Don’t Make Established Knowledge Obsolete
I’ve watched this happen in project management as well.
Whenever an important new technology appears, there is a temptation to assume that everything that came before it has suddenly become old-fashioned. Usually it hasn’t. The new technology changes the way we perform part of the job, but the underlying thinking remains just as important as it was before.
A calculator didn’t make mathematics obsolete, and Microsoft Project didn’t make project planning obsolete. In exactly the same way, artificial intelligence doesn’t make critical thinking or process-improvement knowledge obsolete.
In fact, there’s an argument that better tools make good professional judgement even more important.
Give a capable Green Belt access to AI, process mining and modern analytics and you may enable that person to work faster, analyse more information and discover insights that would previously have been difficult to find.
ve the same technology to somebody who doesn’t understand the process, the data or the principles behind Lean Six Sigma and you may simply enable them to reach the wrong conclusion more efficiently.
The foundations still matter.
What Should You Actually Study for Your Green Belt Examination?
If you’re preparing for a Green Belt examination, my advice is much simpler than some of the material you may encounter online.
Start with the official Body of Knowledge or syllabus for the qualification you’re actually taking and use that as your compass.
Then work through it with the aim of understanding the material rather than simply remembering enough terminology to recognise the correct answer in a multiple-choice examination.
If you’re learning SIPOC, for example, don’t stop when you can remember what the letters stand for. Understand why you might use it and what it helps you see.
When you’re learning process capability, understand what the numbers are actually telling you about the process.
When you reach hypothesis testing, understand the question you’re trying to answer rather than seeing it simply as a collection of statistical formulas.
And when you’re studying something such as FMEA, think about why identifying a potential failure before it reaches the customer is so valuable.
Once you begin thinking this way, Lean Six Sigma becomes much easier to understand because the tools stop looking like separate examination subjects and start becoming parts of the same improvement story.
The Danger of Studying Too Much
This may sound like a strange thing for somebody who sells training courses to say, but more study material isn’t necessarily better study material.
I’ve seen students start with a perfectly sensible learning plan and gradually bury themselves beneath books, websites, YouTube videos, downloadable guides and notes collected from half a dozen different sources.
Usually, it happens because they’re worried that somewhere out there is another fact they haven’t learned yet.
The result is that instead of becoming more confident, they become less confident because they can no longer see the boundaries of what they’re actually supposed to know.
That’s one of the reasons the official Body of Knowledge matters so much. It gives your examination preparation a boundary.
Master what you’re expected to understand first. Once you’ve done that, there is absolutely nothing wrong with expanding your professional knowledge as far as your curiosity takes you.
But don’t confuse those two objectives.
Should We Ignore New Lean Six Sigma Developments?
Absolutely not. In fact, I think that would be just as big a mistake as assuming that every new development must immediately become part of the Green Belt examination.
This is where we need to distinguish between examination preparation and continuing professional development.
I want somebody who has completed Green Belt training to be curious about artificial intelligence and interested in what process mining can do. I want them thinking about sustainability, automation and modern analytics because the organisations in which they will apply Lean Six Sigma are changing.
This is something I’m looking at for my own Lean Six Sigma Masterclass.
The Masterclass already teaches the established Green Belt knowledge and takes students through the complete DMAIC journey. However, I can see considerable value in adding supplementary videos covering some of these newer developments in the future.
The reason for adding them wouldn’t be that the existing Green Belt material has suddenly become out of date. It would be because we can build additional modern capabilities on top of those established foundations.
That’s an important distinction.
First, learn how to become a competent Green Belt. Then let’s look at some of the newer tools and technologies that could make you an even more capable improvement professional.
How I Teach Lean Six Sigma at Projex Academy
My own Lean Six Sigma Masterclass at Projex Academy follows the improvement journey rather than treating Lean Six Sigma as a dictionary of tools, formulas and definitions.
We begin with the foundations and then work through Define, Measure, Analyse, Improve and Control. Along the way, you’ll encounter the statistical techniques, Lean tools, process-improvement methods and problem-solving approaches a Green Belt needs to understand.
But just as importantly, I want you to understand when and why you would use them.
After all, your boss isn’t going to walk into your office on Monday morning and announce that you’ve got a Pareto Chart problem!
They’re much more likely to tell you that complaints have increased, costs are rising, customers are waiting too long or a process is producing too many defects.
They give you the problem. Your job is to work out what is really happening, which questions need answering and which Lean Six Sigma techniques will help you answer them.
For me, that’s the point at which Lean Six Sigma stops being an examination subject and becomes a genuinely useful professional skill.
If that’s the way you prefer to learn, you can find the Lean Six Sigma Masterclass at Projex Academy on Projex.com.
And What Happens When DMAIC Isn’t Enough?
There is one other interesting question that naturally follows from all of this.
DMAIC is enormously powerful when you have an existing process that needs improving, but occasionally you discover that the existing process isn’t simply performing badly. The fundamental design itself may be wrong.
Alternatively, you may be creating a completely new product, service or process, in which case there isn’t an existing process to improve in the first place.
At that point, repeatedly trying to improve what you’ve already got may not be the smartest approach. Instead of asking how we can make the existing process perform better, we need to ask how we should design the product, service or process properly from the beginning.
That’s where Design for Six Sigma, or DFSS, enters the picture.
It uses DMADV as the methodology
The distinction between improving something that already exists and designing something correctly from the outset is important enough to deserve an article of its own.
And that’s exactly where we’re going next.
Your Test Back in the Workplace
So, if you’re studying for Lean Six Sigma Green Belt and you’ve started wondering whether all the discussion about AI, process mining, sustainability and digital transformation means your learning has suddenly become out of date, here’s what I’d suggest you do back in your workplace …
Go back to the official Body of Knowledge or syllabus for the certification you’re actually taking and use that as your compass. Work through the DMAIC journey until you understand not only the individual tools but how they fit together to help you solve a real business problem.
Once those foundations are secure, become curious about everything that’s happening around them. Explore AI and process mining. Look at how sustainability is influencing business improvement. Understand how automation and modern analytics might help you work more effectively.
But keep the distinction clear.
The Lean Six Sigma profession will continue to evolve, just as every worthwhile profession does. That doesn’t mean the Green Belt examination syllabus is rewritten every time a new technology arrives.
Learn the foundations properly, understand how to apply them and then keep adding useful new tools to your professional toolbox.
That way, you’re not simply preparing yourself to pass the examination.
You’re preparing yourself to use Lean Six Sigma when somebody gives you a real problem on Monday morning.
