One of the key things learnt from 6Sigma is the ability to accurately measure and analyze the information your organization collects. This can be as technical or as general as your organization needs, the key is to understand the level of specificity your organization needs and analyze from there. A Black belt will be able to give you in depth analysis, but a good one will give you exactly what your organization needs. We’ll start the discussion with Multi- Vari Analysis.
What is Multi-Vari Analysis?
Simply put this puts a face to the data. Once you have collected all of your information Multi-Vari studies take the data and illustrate the patterns of variation within the data. It helps you identify group or correlations between subgroups and over time. When you can identify the groups, you can make assumption or draw conclusions based on the data. For example if your data shows the your staff made more errors on product X you can draw the conclusion that your improvement efforts need to be focused on that particular product.
What is it used to assess?
Multi-Vari studies are useful in many ways but the most standard uses are
- to illustrate data in graphics.
- to show how work is influence by defined variables.
- to show the impact of specific material, departments or methods.
- the effects of external factors such as noise, delivery delays etc.
When you need to show stakeholders, influencers or project staff what you have found multi- vari studies are a great way to produce a visual. Since most people learn by doing, a visual representation allows them to see what they have done and to show leadership the gains or losses accordingly.
In keeping with my last post on Six Sigma tools and how to use them, I thought this week we would discuss control charts. In Six Sigma, control charts are a staple, but like every tool it as its limitations.
What is a control chart?
Control Charts (sometimes called Shewhart charts) are used to determine whether a process is in control, if there aren’t any uncommon variations shown then the process is under control. Now to be clear a process will always have some type of variation, these variations are common variations. What control charts create are a visual illustration of uncommon variations. These variations are important because they can pinpoint where the problems are in your process.
What are the advantages?
The advantage of this tool is the ability to display all the variations that occur during a process; it eliminates guess work in risk identification and is very useful in process improvement. Now on the other hand, the control chart shows all variations, some variations are erratic and cover a large scope. If you find your variations resemble this, the control chart is probably not the best tool.
When do you use a control chart?
A control chart is best utilized when you have a specific process to measure and you know the parameters and constraints of that process. If you have a vague idea and aren’t really sure how the process works, then control charts are not your ideal tool. If you know how a process begins, but have no idea how it plays out then you are more suited for a better method.
What does a control chart look like?
Now this is a synopsis for control charts and is by no means an in-depth explanation. What I hope this post does is create a basic understanding and a starting place for the use of control charts and how to interpret the data you will receive. There are many other factors to consider when using a control chart and you will need to be familiar with statistical limits and errors. For a more detailed explanation, please consult a belt.