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Trends and Early Indicators March 24, 2014

Posted by Tim Rodgers in Management & leadership, Process engineering, Quality.
Tags: , , , , , , ,

Everybody understands that it’s better to be proactive and avoid problems rather than be reactive and respond after the problem has surfaced. In quality we try to shift from fixing defects to defect prevention. In strategic planning and project management we identify risks, assess their impact, and develop mitigation plans. If we could know in advance that something bad is about to happen, we could surely avoid it.

And of course that’s the problem: it’s hard to accurately predict the future. We may have identified a serious risk, but we underestimated its likelihood. We knew there was a good chance it would happen, but we couldn’t predict when it would happen. We put a plan in place to reduce the risk, but we had no way of knowing if the plan worked until it was too late.

Control charts are a great tool for monitoring a process. Once you’ve established process stability and eliminated special causes, the process will operate within a range of variability defined by common causes. Rules based on probability and statistical significance help determine when the process is starting to drift from stability, which gives the process owners time to investigate and eliminate the cause.

That’s great for measurable processes that are repeated frequently, but there are lot of business processes that are neither. We can’t identify, much less eliminate, the causes of variability. You can wait until the process is complete, measure its effectiveness, and make improvements before the next iteration, but that’s still reactive, and it can be expensive when we miss the target. We need tools to predict the outcome before the process is complete so we can perform course corrections as necessary.

We need leading indicators to determine if we’re on-track or heading off the cliff. In project management you can look at schedule, task completion, earned value, and budget trends. Risk planning can include triggers that provide early warning (i.e., if this happens, then we know we’re OK / we’re in trouble). Products and software can be designed to enable early testing of high-risk subsystems and interfaces, and manufacturing process parameters that impact critical performance requirements (determined from FMEA or PFMEA) can be monitored. We will always rely on judgment and experience to minimize risk, but if we don’t implement warning systems we might as well use a crystal ball.



1. Gede Prama - March 25, 2014

I am happy to read it. Have a beautiful day 🙂

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