There are a lot of good reasons why data and facts form the true foundation of Lean Six Sigma. Want to know who your customers are and what they want? You need to collect data. Want to improve processes? You’ll need to collect data on variation, defects, and process flow. Want to avoid the kind of needless arguments and squabbling that destroy teamwork? Have a rule that people must support their opinions with facts.
You also need data and facts because they’ll save you a lot of trouble and prevent a lot of wasted dollars and time…
When the utilities in one state were de-regulated, one company suffered a great deal of “churn,” losing customers about as fast as it gained new ones. They were forced to spend a lot more money on marketing now that they had to compete for customers.
The customer service staff had noticed several cases where new customers came on board then changed their minds right away, ultimately switching to a different company. Very quickly, these examples grew into a widely held assumption that new customer turnover was the reason behind the churn. The new customers were, the reasoning went, targets of marketing efforts by rival power suppliers.
The service staff therefore began focusing on how to keep these new customers from switching. They developed a new Welcome Pack explaining their services and benefits, which they began sending to thousands of new customers every week. At a cost of $8 a piece, this packet represented a significant investment.
At one point, however, a Lean Six Sigma team at this utility company collected data on churn. They found that new customers only accounted for about 4% of the total. The other 96% were long-term customers who were switching utility companies. In other words, the company was spending thousands of dollars each week on something that would solve only 4% of the problem! So they re-directed their marketing efforts to try to keep the customers they’d had for some time.
This company’s experience is common. Their initial decision about what to do was wrong because they made it without data. Having data can make a huge difference in the decisions we make every day on the job, and is particularly important in improvement projects. Unfortunately, learning the data habit is harder than it has to be because of a number of roadblocks:
Once your company has made the commitment to collect data, the obvious question is “what kind of data?” Making that call is something you’ll learn about if you go through training or participate on a team. To jump start your own thinking, we’ve given examples of actual data collected by teams in Chapters 7 and 8. In general, it all falls into two categories: result measures and process measures:
In a baseball game, for example, the final score is a “result” measure. Stats like hits, errors, strikes, and walks are all “process” measures. They tell you what went on during the game to produce the final score.
You need both results and process measures to be effective in Lean Six Sigma. You absolutely have to keep track of the final result. But the only way you can improve a result is to change the process, and you’ll need process measures to tell you what has to change and how.
What should you actually measure? Here are four typical types of data that teams find useful:
Won’t Gathering Data Slow Us Down?
At the end of its project, one team working on a purchasing problem realized that it had spent 75% of its project struggling to get good, reliable data. When some people hear a number like that, their first reaction is “we can’t afford to spend that kind of time just gathering data!”
That kind of reaction is short sighted. It was BECAUSE of the time they invested in getting good data that the team in question could solve a problem that had been around for years. Getting the right data also allowed the rest of the project to go quickly. Whenever the team faced a decision such as “what solution should we try?” they could look at the data. So discussing the data replaced the kind of endless arguing that happens in teams who don’t use data!
Skipping the data collection step is NOT an option in organizations that are really serious about Lean Six Sigma.
Roger Hirt, a Six Sigma specialist who works with the City of Fort Wayne, Indiana, was sitting in on a city panel meeting once where a city employee was reporting on an ongoing project. During the meeting, an influential member of the panel piped up to offer a solution. The employee thought about the suggestion and said, “I guess that would be possible.” But then Roger stepped in. “Just a minute. We have to look at what the data tells us about the problem before we’d know whether that solution would do any good.”
It’s impossible to go back through history, or even look at organizations today, and see how many bad decisions were made because people didn’t gather data. The number would be astronomical. Today, organizations that are using their resources most effectively insist on using data as often as they can.
But it’s a hard habit to learn because we’re so used to not collecting data. We have to re-train ourselves to pause before making a decision and think about whether there is existing data we could look at, or if we need to collect new data. Learning to ask one simple question—“What does the data tell us?”—will make a huge difference in your improvement efforts.
Foundations of Lean Six Sigma
Implementing Lean Six Sigma