Context of Case
This case involves the vice president of sales at Selit Corp. and his approach at analyzing sales data. Ron Hagler, had just received a report on the past five years of quarterly sales data for the regions that he is in charge of. After Ron looks at the sales data, he immediately calls a meeting with his regional managers to discuss what he saw. He is correct when he notifies his managers that sales rose and fell during certain quarters and years BUT he failed to understand why these variations occurred.
❖ Ron Hagler has ineffective approach at improving sales ❖ Ron doesn’t understand variation and that every process has it ❖ Risk of losing salespeople
❖ Unmotivated and not empowered salespeople, thus unhappy workers equals unhappy customers
The five whys can help us determine the root cause of the situation
1. Why does Ron need to improve his approach?
A. Because it is ineffective
2. Why is his approach ineffective?
A. Because he only looks at the raw data and doesn’t consider external factors that could affect sales 3. Why does he only look at the numerical data?
A. He doesn’t know the appropriate way to analyze data 4. Why does he not know how to properly analyze data?
A. He is not applying the knowledge of statistical thinking 5. Why does he not use the philosophy of statistical thinking? A. Clearly he does not have any knowledge of statistical thinking and he is not trained in statistical process control and does not understand variation.
Using the five whys technique, I was able to find the possible root cause of the problem. Ron Hagley is not thinking statistically when he looks at the sales data. He simply sees increases and decreases in numbers but he is not thinking them through like he should. Raw data alone does not provide the necessary info you need for quality control and improvement. Data must be organized, analyzed and interpreted. The first thing he should have done was organize the data, by region, by plotting it into some kind of chart so that he could compare the different regions similar to what I did in figures 1 and 2. When I first saw the figures, I noticed that the numbers in some of the regions were significantly higher than some of the others. Clearly, the regions with the larger numbers must be a larger and better region with higher potential for sales. Those three regions were northeast, southwest and northwest. So these regions should be compared against each other since they are all similar in regards to market potential. It is not fair to compare these regions with other regions of a smaller market that may be suffering from losses due to competition or other external factors. So then, the smaller three regions were plotted on a second graph to see how they stack up to other regions of their same nature. Also, Ron should look at sales performance of other companies in similar industries, size and geographical areas to see how they compare relative to its competitors. Based on the charts that I produced, I was actually able to see the true performance for each region based on all five years. Ron praised the managers of the northwest, southwest and northwest regions for increasing their sales but when you look at the charts you can see that the northwest region is actually trending down overall. The northeast region is staying pretty constant and the southwest region is trending up very slightly. So Ron’s analysis of their performance is not too accurate when you look at the data using this tool. Sure, there may have been some increases from the previous year or quarter but overall, they haven’t shown much grow in the last five years. As far as his “problem” regions, his analysis of this data is incorrect as well. He considered the mid-Atlantic, south and north central regions to be “problem” areas...