Friday, August 10, 2018

My New Book Part 11


In my last post, we continued our discussion on what I believe are the 4 best tools for problem solving.  I discussed the Pareto Chart and presented a simple example of how to construct one.  In today’s post we will look at the third tool, the Causal Chain.  Much of what I have discussed in this series, is taken from my newest book, A Guide for Problem Solving, Prevention and Making Effective Decisions - Roadmaps for Today and Tomorrow.

The Causal Chain

The final tool we will be discussing in this series of posts is the causal chain. When problems occur, we know that a chain of events has taken place to alter the performance of the process. We aren’t always certain as to what happened, so we need some kind of tool or technique that will help us develop a theory as to what did happen. One of the most effective tools available for accomplishing this is the causal chain. Causal chains are step-wise evolutions of problem causes. Each step in the causal chain represents an object in either a normal or abnormal state. The object is placed on the line to the far right of the chain, with the state it is in listed directly beneath it.

So, in the figure above, the object in distress is the press and its state is that it has stopped. Although we might use a cause-and-effect diagram to list the variety of reasons why the press stopped, it does not explain the causal mechanism that actually caused it.

In the figure above we see that a press has stopped and we ask the question why. The press stopped because the motor stopped. Why did the motor stop? Because the current has stopped flowing. We continue asking why until we reach the end of our chain, and find that the press stopped, because the motor stopped, because the current stopped, because the pressure switch opened, because the air pressure was too low, because the air compressor failed, because the oil level was too low, because of a gasket that failed. We have now developed a potential theory as to why the press stopped, and along the way we have identified objects or items (e.g., current, oil level) that we can test to prove or disprove our theory. Each step is the cause of the next step and the effect of the preceding step. That is, the information on the step to the left is always the cause of the information on the step to the right.

What if we have more than one potential cause? How do we handle that situation? The answer is simple. We just create additional, individual chains like the one in the figure above and place them along the y-axis as in the figure below. This is an actual example from a team that was working on a core machine that was malfunctioning. Here the team brainstormed and came up with four different chains. Each individual chain is, in reality, a brief theory to prove or disprove, as to how the core machine was malfunctioning.

Ultimately, the team either eliminated the chain as a potential cause through testing or developed action items for each of the potential root causes. At the end of the day, the team performed all of the actions in the gray shaded boxes, and the problem was not only solved, but it was improved from its previous state.

Remember, the primary purpose of a causal chain is to develop a stepwise chain of events that explains why a particular performance shortfall exists. Once this is complete, hypotheses or theories can be formulated as to why a problem exists. Causal chains are, in my opinion, one of the simplest and effective, yet most underutilized tools available for a team to use.

In my next post, we’ll start a new blog post series on a different topic.  As always, if you have any questions for me, just send me an email and I’ll answer it.
Bob Sproull