Analyze Part 3
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After completing this course, you will be able to:

  • Understand the key principles of Lean Six Sigma
  • Identify improvement opportunities in your organization (projects)
  • Understand and use the Define, Measure, Analyze, Improve, Control (DMAIC) model and key activities
  • Use the basic tools and techniques
  • Understand the role of Yellow Belts in Lean Six Sigma projects
  • Run small improvements in their day-to-day work processes

The modules covered in this learning:

  • Lean Six Sigma Overview
  • Define Phase
  • Measure Phase
  • Analyze Phase
  • Improve Phase
  • Control Phase

The recommended study time for this course is approximately 5 hours.

Please note: this content was produced in the UK and may include the use of British English.

Key exam information

There is no exam at the end of the LSSYB. A Yellow Belt certificate is issued upon completion of the training. 


Welcome. This is part three of the Analyze phase of Lean Six Sigma. In this part, we will be looking at how to analyze the process. In Measure, we talked about drawing a detailed process map. In Analyze, we can go one step further than that and look at the steps within that process map to help some further understanding of what's happening in the process. The word analysis means decomposing. And this we may already have done of the process in the measure phase.

Once we have drawn a process map, we can look at each of the steps and try and define what type of step they are. This definition comes from the work of Taiichi Ohno who created the Toyota production system. When he was looking at the Toyota production system, Taiichi Ohno identified two types of steps: value adding or non-value adding. Since his work, a third type of step has been identified, which here we've called business non-value adding. We will consider that a little bit later.

Taiichi Ohno said a step in a process is value adding if that step changes, transforms, or modifies the inputs into or towards something the customer wants. If that step does not change, transform, or modify the inputs into something the customer wants, then that step is of no value to the customer. Steps which are no value to the customer clearly are known as non-value adding steps. And so we can identify in our process which of the steps are value adding and which are non-value adding.

The third type of step is business non-value adding, or business enabling, or necessary non-value adding. Many organizations have lots of different names for this third step. However, I would say keep the definition simple. For business non-value adding, allocate steps that are done for a regulator or audit. If you extend the definition of business non-value adding, you will find that most of the steps fall into it. And so we will define the steps as value adding, non-value adding, or business non-value adding.

Why do we want to do this? Well, we want to do this because in identifying which steps fall in each category will help us understand where to start to look for improvements. And so we can then, from the process map, identify which of the steps are value adding, which are non-value adding, which are business non-value adding.

Once we've done that, we should look at the steps that are non-value adding because it is here we will find most of the improvements. And the improvements there will probably be easier to take place. Once we've completed what we can do in non-value adding, we can look in value adding, although because by nature these are creating some sort of change or transformation to the inputs, they often are harder to improve and the amount of improvement will be considerably less than non-value adding activity.

Once we've completed the value-adding steps and seeing what we can improve there, we could go on to business non-value adding and see if there's anything that we're doing which we could improve even though we've defined it as being done for the regulator. And so, defining whether you've got value adding, non-value adding, or business non-value adding is simply to help you put things into order of where to look to start improvement, and always start in the non-value adding. We'll look at what makes up non-value adding in the next slide where we consider waste.

Taiichi Ohno identified what he called The Seven Deadly Wastes. In many organizations today, they use the acronym TIM WOOD to help them remember what they are. T stands for transportation. I for inventory. M for motion. W for waiting. O for overproduction. O for overprocessing. And D for defects and rework. Let's have a look at each one of them. Here we'll see some examples and I'll talk briefly about what each waste looks like.

Taiichi Ohno said moving things from one place to another is a waste. You can see this very clearly in a manufacturing operation where raw material is moved to a machine, semifinished product is then moved to another machine, and so on until it gets put into the warehouse. In the nonmanufacturing organizations, this movement is often less easy to see. Often, this movement is electronic. So sending emails is probably today's equivalent of transportation. So if emails are being sent, why are they being sent? Do they need to be sent? Just consider your own situation. How often do you get emails that you don't want, but rather than go back and try and stop them, you just delete them, because that's the easiest thing to do? So moving things around is a waste and we should look for other opportunities, so that we don't have to do that.

Inventory. Taiichi Ohno said storing things is a waste. Storage is a waste because it costs money, it takes up space, things get stored that don't get used. They may become obsolete, and therefore, storage can cost organizations a large amount of money. Now, we're not saying you should never store anything, but you should only store the absolute minimum. In fact, in some financial services, the regulator says that information needs to be stored for a fixed amount of time. However, how much of that information is still being stored when the deadline has actually exceeded? And all of this storage costs huge amounts of money.

M is motion. Whereas transformation is the movement of things, motion is the movement of people. So where do people have to move around in order to do their job? How often do you have to get up from your desk and walk to a printer to get a printout and walk back again, or how much movement is involved in going to meetings? Are they on the same sides? Are they on different sides, in different cities, in different countries? Huge amounts of movement. Can we achieve what we need to do without all that movement?

The W is for waiting. In a nonmanufacturing organization, waiting or delays often prove to be quite a large part of a process. What causes these delays? We may be waiting for some information. We may be waiting for someone to do something. Particularly things like approval. And so, wherever we find delays, we should be asking, why are these delays occurring, and what can we do to stop them? In one example, a yellow belt was looking at a process and discovered that 47 people had to approve the process before it could move on. This incurred huge amounts of delays and waiting for the people working in the process. In her work, she reduced this to five. This speeded up the process no end.

The first O is overproduction. Making more than is absolutely necessary. In the manufacturing world, Taiichi Ohno would've said that overproduction is the worst of all the wastes, because it leads to everything else. In nonmanufacturing, it's difficult to see overproduction sometimes, because we don't make products. So where do we overproduce? I would suggest that one area of overproduction is the amount of reports we make and the size of the reports. And often these are produced just in case rather than because there is a clear need. And linked to the production of reports, I'd suggest we collect lots of data which often doesn't get used.

The second O is overprocessing. This is doing more than is absolutely necessary. This might be adding too much functionality to a product. Again, this is difficult to see sometimes in a nonmanufacturing organization. But I would suggest an example of overprocessing in nonmanufacturing is excessive checking. We love checking things. Not only do we love someone checking it, we will even check what someone else has already checked. Excessive checking is a waste and we should look for other opportunities so that we don't have to check, which really means take action on the process to make sure that it does not go wrong. If it doesn't go wrong, we don't need to check.

The D of TIM WOOD is defects. Defects cause difficulties for customers, cause rework for the organization and in themselves create huge costs. Wherever there is a defect we should be trying to understand the root cause and therefore in the future prevent that the root cause from creating that defect. Since Taiichi Ohno's Seven Deadly Wastes, other wastes have been identified. Two more are shown here.

Unclear communication. How much chaos and confusion and waste does unclear communication create? And the second one we have here is one that many people talk about as the eighth waste, and that is are we using the skills and the knowledge of the people who work for us, because if we're not, it's a waste. In some organizations, it's been known that management have taken an attitude of, well, you're only paid to do the job. You're not paid to think. This is a waste. People doing the job have lots of ideas about what goes wrong, what frustrates them, and therefore should be utilized to say how can we improve them. Wherever we find waste, we should be challenging it and looking for opportunities to either reduce it or eliminate it.

In reality, we often replace a large waste with a lesser waste. You will never get rid of all waste. But many processes have a lot of waste and therefore we have lots of opportunities to improve them. Once we've drawn our process map, identified what's value adding, what's non-value adding, and what's business non-value adding, we can then look at those steps and come to some conclusions about can we improve them? This will ultimately improve the process.

The value stream map, which you saw in the Measure phase, can be used to identify some of these wastes. The timeline at the bottom clearly shows delays on the raised part of the timeline. So in this situation, we could be asking why is one of the delays 10 days? What can we do to reduce that? Reducing that would reduce the overall time in the process. If you're familiar with drawing a detailed process map and do not want to draw a value stream map, you can show delays by using the symbol D between tasks to represent the delays.

If you do this on a detailed process map, you will discover that there are many delays in the process. But this just opens up opportunities to question them and improve them. The idea of value analysis and reducing waste can be applied to any process. Here is an example of someone visiting A&E with a suspected broken arm. They get to reception and sign in, they're asked to wait, they then have an initial assessment. They're asked to wait. They then see the doctor who sends them for an x-ray. They wait. They have the x-ray. They go back to see the doctor, but wait. They see the doctor. They give them their decision, and then maybe they're asked to book another appointment.

You'll notice in this process there are lots of wastes. And so we could look at this and in it, we've got some timings. So which of these steps are of value to the customer? There may be some debate about this, but one could argue that the x-ray is a value-adding step. It now allows the decision to be made. Have you got a broken arm or not? The x-ray takes eight minutes. Of the total time, 162 minutes, this is less than 5%. So in this process, less than 5% of the time in the process is a value to the customer. There are lots of opportunities to improve this process.

In summary of Analyze, Analyze is about looking at your process and identifying which of the steps are value adding, which are non-value adding, which are business non-value adding, focusing on the non-value adding and looking for opportunities to reduce the waste. From the data door, we might have collected data and presented it in some sort of graph. We would then be using the graph to help us identify the root cause. Once we've identified our root causes, we must verify that they truly are, otherwise, we would be spending time working on something that's not going to improve the process. This is the end of the Analyze phase.

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