A framework for thinking about problems - Part 1
A story about problems
Have you heard the story about the clever engineer?
A toothpaste factory had a problem: Due to the way the production line was set up, sometimes empty boxes were shipped without the tube inside. People with experience in designing production lines will tell you how difficult it is to have everything happen with timings so precise that every single unit coming off of it is perfect 100% of the time. Small variations in the environment (which cannot be controlled in a cost-effective fashion) mean quality assurance checks must be smartly distributed across the production line so that customers all the way down to the supermarket won’t get frustrated and purchase another product instead.
Understanding how important that was, the CEO of the toothpaste factory gathered the top people in the company together. Since their own engineering department was already stretched too thin, they decided to hire an external engineering company to solve their empty boxes problem.
The project followed the usual process: budget and project sponsor allocated, RFP (request for proposal), third-parties selected, and six months (and $8 million) later a fantastic solution was delivered — on time, on budget, high quality and everyone in the project had a great time. The problem was solved by using high-tech precision scales that would sound a bell and flash lights whenever a toothpaste box would weigh less than it should. The line would stop, and someone had to walk over and yank the defective box off the line, then press another button to re-start the line.
A short time later, the CEO decided to have a look at the ROI (return on investment) of the project: amazing results! No empty boxes ever shipped out of the factory after the scales were put in place. There were very few customer complaints, and they were gaining market share. “That was some money well spent!” he said, before looking closely at the other statistics in the report.
The number of defects picked up by the scales was 0 after three weeks of production use. How could that be? It should have been picking up at least a dozen a day, so maybe there was something wrong with the report. He filed a bug against it, and after some investigation, the engineers indicated the statistics were indeed correct. The scales were NOT picking up any defects, because all boxes that got to that point in the conveyor belt were good.
Perplexed, the CEO traveled down to the factory and walked up to the part of the line where the precision scales were installed. A few feet before the scale, a $20 desk fan was blowing any empty boxes off the belt and into a bin. Puzzled, the CEO turned to one of the workers who stated, “Oh, that…One of the guys put it there ’cause he was tired of walking over every time the bell rang!”
The moral of this story is in the final line, where the author asks:
$8 million vs $20 Hmmm! Money well spent?
Is this the right outcome?
I will answer this at the end of the series.
I am going to try to explain in this article how, by having a clear typology of problems, one can successfully and comprehensively diagnose the issues in such a way that the remedy is self-evident. If we can achieve that, I am sure you will agree that it will be a worthwhile tool.
NOTE: This is part 1 in the series. Visit our blog and find the rest of the series which will be published on consecutive days.
Alternatively you can download the whitepaper (PDF) here.