In metrics the most honest finding will be that your metrics will have degrees of variation. Understanding where and how those metrics occur, is the key to using your data in a forward thinking strategy. Let’s start with something simple, like toy production. We are going to track some standard variation sources.
Within Unit Encoding
This variation source occurs when you are measuring output from a single production cycle. Some places that variation is likely to occur are the width of parts, color shading, length of toy etc. Now you can choose to analyze different production cycles on the same day or alternating days, but you will always be comparing samples from the same cycle. A new production sample means a new data point.
Between Unit Encoding
These names are dead giveaways, but I digress! This implies that you are looking at samples from two different production cycles. This is different in that you would want to identify two different samples from different production cycles. The variations you are looking for will give you some clue as to whether the variations are operation influenced or process influenced.
This is the trickiest variation source. This specifically calls for you to compare your variation averages from all of your data points in a single day. So you can theoretically have both within unit variation data and between unit variations data, depending on how specific you need to get.
The key to getting the most out of your data is to understand what it’s telling you. Understanding where the variations are coming from is the first step to getting the most out of your data.
As we go over Six Sigma statistics, we have to talk about normal distribution. Before we get to that though we have to talk about why distribution is important to the way you interpret your data. In interpreting your data there is something you should know before you tackle how the information observed, confidence intervals. Confidence intervals is more complicated than this blog, but basically what you need to know is the greater the confidence level the less likely the variation is to occur and the more you can guarantee the accuracy of data analysis. In confidence levels there are 3 common ones that we use in data analysis, 99%, 95% and 90%. The standard of measurement is 95%, the higher the better but as a baseline 95% is a solid analytic benchmark.
Okay so back to normal distribution. Here’s what you need to know.
What is it?
You find normal distribution when you take all of your data and create a visual representation of the information. You will illustrate when recurring variations show up in your process. It is actually more helpful when you have a distribution that isn’t normal because then you can say ‘Aha it was the 3 hour traffic jam that affected the process’. When you hear people talk about the curve, this is what they are referring to.
When do you use it?
This is a tool that is best when used as a continuous probability model with measurements that you don’t have to create. Think about the weight of a cargo shipment or the number of a specific product you receive.
Raw scores and Z scores
Each normal distribution will have a raw score which is made up of two parameters: the mean and the standard deviation. The Z score measures how far you varied from a particular point on your data line. In real terms it means, if you want to see how many errors occurred on the 5th then standard deviation shows you that.
Why is it important?
The area under the curve shows the proportion of the curve and which tells you how important this data is to your business. Is the curve is small then you now that the distribution occurs within a relatively small set of circumstances which is easier to control within process. A wider distribution shows you that your process can be interrupted by a variety of factors and may need you to keep a close eye on it.
In this blog we have talked a lot about the different tools we can use in our improvement projects, but it’s my professional opinion that knowing why something works is as good as if not better than knowing that it works. In this blog post we need to discuss how you categorize defects. When you have enough data to cast a critical look over your process, you will find yourself face with the inevitable question of ‘how to I classify the variety of errors’? Well have no fear; here are the 3 most common classifications:
A controllable error or defect is something specific that you can pinpoint and directly affect with improvement. For example think of the lowering of the thermostat to improve the operating expenses or pressing the collate button on the copier to reduce the prep time for paperwork.
These are errors that occur during the steps of a process, like a safety checklist or a quality control checklist. The easiest way to decide if an error belongs in this category is to ask yourself ‘ is this a routine step to completing a task? If the answer is yes, then it’s procedural.
This is the trickiest category of all because it is basically a runoff category. This category is for things that cannot be fit into a specific setting or procedure. The category is for miscellaneous and arbitrary errors, think things like the amount of noise children make in school. If it is too big to measure and too hard to assess, it is most likely a noise classification.
The trickiest thing about 6Sigma is knowing which tool to use, to that end knowing where to classify potential areas of improvement is even more necessary. This is a great place to start and once you are ready to start categorizing your errors, we can help. Give us a call and we can you started.
This week we will continue our discussion on process mapping, I promise it will not go on forever, but it does have a lot of intricacies. Many people think that process mapping is just putting some shapes on a diagram, but it means much more than that. There are 3 levels of process mapping that are commonly accepted among the 6Sigma crowd.
Level 1 –The Macro Process Map
This is typically how management views the processes of the organization; it’s a big picture, future strategy kind of view. It also creates the ability for management to see how to position the organization or resources in a way that complements the product/service being created. This is a high-level map which generally includes:
- Activities that relate to one major process step
- How the process fits into the big picture
- Little specific detail
- Visualizes only major process steps
- Can be used with only a general understanding of the purpose of the process and its steps.
Level 2-Process Map
This is the worker bee process map, where the people who have specific knowledge of the process come in. This is the map that is used to identify all the major steps a worker takes to complete a process. Within Level 2, there are 4 types of process maps:
- Linear Flow- A straight line from beginning to end.
- Swim Lane-shows you who is responsible for what task.
- SIPOC-a little more complicated. It takes five areas: your suppliers, your inputs, your process, your outputs and your customers.
- Value Stream-a specific map that helps to visualize and understand the metrics for the performance of major steps.
Level 3-Process Flow Diagram
Level 3 is not a must because this is a micro process map. It is where you zero in on a specific area and focus on the steps in the process that are causing whatever challenge you are having. When beginning this level you need to ask the following questions:
- Which steps contributed to the problem?
- Where would the problem most likely have occurred?
- Are there elements to the product/service that lend itself to the problem?
These questions help you find the focus that you decided in your problem statement. For this to work you will have to break each step in the process down, most easily using SIPOC. Remember a Level 3 map should include:
- All process flows
- Any set points
- Any standard or automated procedures
- Inputs and outputs (specify if the are controllable or non-controllable)
- Defects per unit
- Yield and rolled throughput yield
- Value and non value added activities
It’s a lot of information, but mapping a process is a fundamental step in your improvement project. It is absolutely critical that you get it right. For more help or more information, give us a call and we will be happy to get you started.
6Sigma Tools: Process Mapping-Standard Symbols
As I said last week, process mapping is one of my favorite 6Sigma tools and the best thing about it is that anyone can do it. Now as with all things 6Sigma it can be as complicated or as easy as you want it to be. It may seem like process maps have a secret language, but this week’s blog helps you decipher the code.
What is it?
Rectangle illustrates an activity within the process. When activities are described in a rectangle they generally begin with a verb.
When you see a diamond, a decision has to be made. These decisions are generally yes/no or go/stop.
An arrow shows you which way the process is flowing and where it is connected.
A parallelogram shows that this step in the process is a data point.
An ellipse shows the start and ending of a process but some people like ovals or circles. I like circles myself, it really doesn’t matter but if you want to get technical ellipses are the Alpha and omegas of process maps.
Some people swear by MS Project or Visio, but the truth is that MS Excel or MS Word is just as effective for producing process map. The meat of this tool is that you illustrate the steps. I’ve provided an example of one of the process maps I designed for a client, when you first start mapping a process it’s better to focus on something simpler. This process is just an example of what a finished process map looks like.
What should it include?
At a bare minimum it should show how and where the process starts, who/what influences it (inputs) and the end goal/product. A more desirable map shows cycle times, value and non-value added tasks and activities, decision points, problems with immediate fix capabilities and process control needs. But that is not a hard and fast rule; your client will dictate what the map needs to show. As you can see from my process, my client wanted a “no-fluff” chart, a map that only illustrated the tasks that actually took place.
Why use it?
Aside from the clarity that comes with visualization, process mapping is good for:
- Visualizing improvement points
- Understanding root cause possibilities
- Complementing analytical tools with the data it provides
- Identifying what you will need to make improvements.
What doesn’t it do?
Every tool has its limitations and the process map does not give you a silver bullet. It cannot determine the level of variation, but it can determine if there is variation. It cannot stabilize your process but it can illustrate the best place to start looking for improvements. When you are ready to start giving your processes a deeper look, let SPC help get you started.