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Six Sigma Project Problem #2 - Project Selection

As I mentioned in previous ezines, I've had a chance to look at lots of Six Sigma improvement projects. Even though our Six Sigma action plan has clear guidelines about what to do and how to go about it, few people seem to be able to follow the recipe.

Project Selection

Six Sigma is a powerful tool for eliminating defects and deviation. Here's some of the ways people try to screw this up:

Trying to fix the effects of defects and deviation- The first improvement project I ever worked on was a gift from our VP of information technologies. He asked us to improve customer perceptions of IT. The word "improve" is a clue. Six Sigma is a problem solving process. Customer perceptions improve as a result of reducing defects and devation. We wasted a year working on perceptions when we could have worked on software defects, incomplete requirements, late deliveries and host of problems plaguing IT. Start with problems involving defects and deviation, not the effects.
Trying to fix someone else - When teams pick their own problems, they often are drawn to their own pain. They want to fix their suppliers, their customers or their management. Let me be clear: you can't fix someone else's problem. You can give them the data and ask them to fix it, but you cannot fix it. You can only fix what you do. Fix your process, then help others fix theirs.
Majoring in minor things - Their first time out, teams often try to tackle a problem that isn't too big. The phrase most often heard is: "rearranging the deck chairs on the Titanic." They want to get their feet wet rather than jump in the deep end. Unfortunately, simple problems are sometimes the hardest problems to solve. And the result is so minimal that management wonders why they invested in Six Sigma to begin with.

Here's my recommendation: Start with the worst first! The biggest, baddest problem will have clear Pareto patterns and will be easy to solve. Once you slay a dragon, you'll find everything else to be easy. My first big project saved $20 million dollars in postage. Since then I've never worried about tackling big problems. There's always a Pareto pattern and it's invariably easy to detect and solve.

Deming said you have to pick the right problem. What starts well, ends well.

The solution is simple: 1) start with the worst first, 2) start with real data and 2) let the data analysis lead you to root cause and countermeasures.