Is Too...Is Not...Is Too...Is Not...

Recently, I had a classic example for problem-solving right in my neighborhood. A while ago, I noticed a couple of brown spots in our townhouse associations lawns, and a few mower tracks in curves following the curbs and around utility boxes, etc. That seemed to indicate one cause to the effect of a bad looking lawn. A few weeks later, more areas were affected. In fact, one townhouse had so many 'grass burn' tracks it looked like the pit area for the Indy 500.

We immediately thought the lawn service had a problem with the mowing.

As I walked the whole neighborhood in our association's complex, I noticed a few areas that provided different clues. Some lawns were 100% intact. For some neighbors, they had tracks that ended at the 'property line' and the next door neighbor's lawn was immaculate. In one lawn, there was a 'million' burn tracks except for one V area in the middle. Ah-hah, these are excellent clues.

Many decades ago, there was a popular problem-solving technique promoted by Kepner Tregoe. Its methodology asked you to define the problem in specifics so that you knew what you were working on. It also asked you to collect information in order to determine: when the problem occurs and when it doesn't; where it occurs and where it doesn't; what the problem is and what it isn't. And so on.

It's vitally important to note what "is" and what "is not" happening. Those provide strong clues to the causes. The one cause you pick to solve has to be able to explain not only what is happening, but what is not happening too.

We needed to solve the problem of 'burn' tracks in many lawns. It wasn't in all lawns. And it wasn't that the whole lawn was dying. It also started showing up when we had 90 degree weather for weeks in a row and with a lack of rain.

Turns out, we discovered several sprinkler head issues. Now that those are fixed and the weather has moderated back into the 80's, the lawns are recovering quite nicely.

But it wasn't a mower problem at all. A mower problem didn't explain how tracks didn't show up on every lawn, nor stopped at some property lines, or were lacking in the V area. Sprinkler issues did explain these things.

Data, Speak to Me!

Working with one team, a project was progressing into the definition stage. The team was trying to create an objective for the administrative process. They were concerned that they weren't meeting a 14-day deadline very often. The demand for this process was expected to triple as the company grew and they might have to add staff.

The first step of the process seemed to take the longest. Some thought it was averaging a week, leaving only a week for the other three departments to finish the process. They started to outline the steps and talking about the issues and the problems that created the delay.The team started to brainstorm some solutions.  They had some technology answers to the problems. They had some suggestions for suppliers without any ability to influence them.


The Lean experts looked at cycle times and wanted to cut the waste. The Six Sigma experts wanted to look at errors and causes for rework.


No one had taken time to look at the data. The Lean guys were concerned about a cycle time that in worst case would account for one-fourth of a person's time, even at triple the demand. The Six Sigma guys hadn't looked at the histogram, or paid attention to the frequency in processing times.

Once the data was analyzed, people figured out that half of the items were processed in the same day. Only 1 in 4 exceeded a three day processing time. Instead of averaging a week, the first step was averaging a day and a half. 19 of 20 were completed faster than a week. With a bit more data, the team learned that those that took more than 1 day were due to supplier issues, but were easily addressed. Even with problems, the delays were not that big. 

The team did succeed in shrinking the overall range through some creative solutions. But they hadn't started out with quite the mountain to turn into a mole hill. The data showed them that the solutions could be very focused, a relatively inexpensive compared to the ones they brainstormed in the beginning.