This is a micro blog this week, because next week we get into measures of variation which is a dry subject and will challenge my creative ability. As we continue our trek into statistics and how to interpret them, there is a very specific area that I want you to pay attention to, variation. The reason variation is so important is that it tells you why something is different and how that matters to the data set as a whole. It also provides you the knowledge of what the data won’t be able to tell you because of the interference the variation causes. This is important because when you interpreting data understanding the limitations is almost more important than understanding what is being told to you.
The first thing to consider is range. Range will tell you the difference between the most obvious observation and the smallest one. This is important because this is where you identify your outliers (variables that are outside the norm, think of road work on a delivery path or a maternity event as an obvious observation). A large range would be the maternity event; it’s so big there is no way to avoid noticing it. A small range would be a traffic event, it may have impact but the impact will not be evenly distributed and it may or may not impact the final result.
There is a measurement range that is good for a sample size of 2, it’s called the inter-quartile range. For a bigger sample stick to standard deviation; Standard deviation tells you the average number of times a variation occurs from the mean.
By all means as usual this is not a step by step approach to understanding variation, but it is enough of a foundation to have a conversation with your belt about the metrics and what they mean to your organization and its strategic goals. If you need help starting this conversation, give us a call and we will be happy to get you started.
This blog is about Six Sigma data analysis. Because statistics are such a big part of the Six Sigma world, it makes sense that we talk about the data that is gathered and what it means. So here we go….
There are different types of data and anytime you measure something you going to need how to interpret it. There are two main types of data: attributive and variable.
Some people call this the most basic form of data, but for business purposes I don’t accept that. Qualitative data is simple in the fact that it is generally data that can be gathered by asking a yes or no question. For example, ‘Did they buy the new product?’ What is limiting about attributive data is that you really can’t analyze the results in a meaningful way, but it can give you a pretty good place to set your focus.
Variable data is also called quantitative and this is the data that you can measure and analyze. In order to decide if data you have is variable ask yourself these questions:
- Can you classify the data and count the results? (Think number of defects for a particular product line)? If you can this is called discrete data and the limitation of discrete data is that it cannot be broken down into smaller measurements to create additional meaning. It’s a one hit wonder.
- Can the data be measured on a time line with meaningful divisions (Think time, production speed, delivery dates etc…) If you can this is called continuous data and it can be divided further to create additional data.
As with all of these blogs, this is to get you started and statistical data clearly has more to it than one paragraph. But information is the first step and one you know what type of data you have, you have a better idea of what you need to know. Give us call and we can help you create where you need to go next.
In this blog we have talked about a lot about the tools used in a change project, but I think that it is time we talk about the information that drives the project-the statistics. The old adage is that the numbers never lie, but when you work with statistics you know that is a relative statement. The numbers can and do lie, usually it comes down to interpretation. So here are some basic things to remember when looking at the statistics your change project will provide.
- Understand that statistics are the foundations of 6Sigma, when you don’t understand a tool remember that everyone participating in a 6Sigma project will understand the statistics.
- The purpose of a statistic is to give you a numerical value for the information collected and analyzed. In other words when you measure something the statistics tell you why the measurement is important.
- The measurements give you a place to start from, whether that is a place to improve or a place to maintain. (Of course in continuous improvement, there is no place to maintain! Always improve!)
- Statistics serve as a common denominator, like everything else they can be taken to the extreme but they create a common language and equalize knowledge. Everyone can know and understand the same thing based on the numbers. Statistics can eliminate personality flaws, individual perception and provide your team with a singular focus.
- The single most important purpose of statistics is the ability to create a new group of problem solvers. Once the group has a common goal they can then began brainstorming for innovative solutions thanks to the data. So numbers=innovation!
As with all things 6Sigma the difficulty level lies within the practitioner. If you want a bunch of charts and reports that can only be interpreted by the consultant, you can find that. If you want to understand how the numbers can help you, give us a call and we will get you started.
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.