their thoughts on the issues involved. By the time they’ve created the interrelationship diagram, the team will have a detailed understanding of what they need to do, the drivers of success and the many and varied interrelationships involved, and they will feel they own the output from the exercise.
© John Morgan and Martin Brenig-Jones
Figure 2-3: Creating an affinity diagram.
© John Morgan and Martin Brenig-Jones
Figure 2-4: A sample interrelationship diagram.
It’s highly likely that affinity and interrelationship diagrams will be used at the beginning of a design project, where the DMADV method would be used rather than DMAIC.
Figure 2-3 shows the steps in the creation of an affinity diagram. The process works best if you use sticky notes and silently brainstorm ideas on an agreed issue statement; for example, ‘what issues are involved in introducing Lean Six Sigma into our organisation?’
Follow these rules:
✔ Use one idea per sticky note.
✔ Write statements rather than questions.
✔ Write clearly.
✔ Don’t write in upper case (reading lower-case words is easier).
✔ Avoid one-word statements (your colleagues won’t know what you mean).
✔ Include a noun and verb in each statement.
✔ Don’t write an essay.
After everyone has finished writing their sticky notes, maintain the silence and place them on the wall, as shown in the first part of Figure 2-3. Move the notes into appropriate themes or clusters (see the middle figure), you’ll probably need to break the silence here. Finally, give each theme or cluster a title describing its content (see the final figure). Ensure that each title provides enough description; doing so is helpful for when you move into the interrelationship diagram, shown in Figure 2-4.
An interrelationship diagram identifies the key causal factors or drivers for your programme or project, by enabling you to understand the relationships between the themes or clusters. In looking at the different pairs of clusters you’re trying to see if a cause and effect type of relationship exists, so does ‘this’ have to be done before ‘that’, or does ‘this’ drive ‘that’.
In Figure 2-4, the headers for the themes or clusters from the affinity diagram have been put into a clock face on a flip chart and you now work your way round looking at the relationship between each pair. As you do so, you need to consider whether a relationship exists or not, and, where it does, determine which has a greater effect on the other – for example, ‘must this happen before this does?’
If a relationship does exist between two clusters, connect them with a line. Importantly, either there is a relationship or there isn’t, so don’t use dotted lines – you might start with a pencil, though! Agreeing some ground rules is sensible to ensure the relationships are tangible.
After you’ve determined the ‘causal’ cluster, draw an arrow into the ‘effect’ cluster. Some discussion is likely to take place about which way the arrow faces, but it has to go one way or the other – two-headed arrows are not allowed! In Figure 2-4, you can see that A drives B, but that B is the driver of C. The numbers represent arrows out over arrows in.
The finished diagram can be presented as shown in Figure 2-5, and you can clearly see the key driver is A, whereas E is probably the outcome of the project. You need to particularly focus on A to ensure your project or programme is successful.
© John Morgan and Martin Brenig-Jones
Figure 2-5: Identifying the key drivers.
After you’ve defined the problem, at least based on your current understanding, you need to clarify how, and how well, the work gets done. To understand the current situation of your process, knowing what it looks like and how it’s performing is important. You need to know what’s meant to happen, and why. Understanding how your process links to your customer and his CTQs is also helpful. What does the bigger picture of the process look like?
Knowing the current performance of your process is essential – this knowledge becomes your baseline – but knowing what’s happened in the past is also useful. Measure what’s important to the customer, and remember also to measure what the customer sees. Gathering this information can help focus your improvement efforts and prevent you going off in the wrong direction. Using control charts (see Chapter 7) can help you make better sense of the data, as they provide a visual picture that demonstrates performance and shows you the variation within the process. Importantly, control charts help you know when to take action and when not to by enabling you to identify the key signals so often hidden when data is presented as a page of numbers.
Lean Six Sigma projects can take longer than you might like because the right data isn’t in place in the day-to-day operation. So often organisations have data coming out of their ears – but not the right data. You need to develop the right measures and start collecting the data you do need – which takes time.
In the Measure phase, you discovered what’s really happening in your process. Now you need to identify why it’s happening, and determine the root cause. You need to manage by fact, though, so you must verify and validate your ideas about possible suspects. Jumping to conclusions is all too easy.
Carrying out the Analyse phase properly helps you in determining the solution when you get to the Improve phase. Clearly, the extent of analysis required varies depending on the
