Management Case Study #2

Turkell Stud Mill Case

Abstract

The Turkell Mill Stud Mill is experiencing an average loss of around $100,000 due to failing to adjust for short blocks during their log acceptance. This case will suggest that the number of samples is increased, which may prevent further financial loss and also time loss due to having to performing a 100% or “spread” inspection of all of the incoming logs.

Turkell Stud Mill Case

The logging process believes to have a short length of around 4.23 percent. The total number of logs purchased during the year is around 250000 to 300000 logs which amount to a loss of approximately $100,000 based on failing to adjust for the short block. This means that an approx. of 11000 to 13000 logs is actually short in length. Out of this only 10 percent of short length logs are identified. Therefore 90 percent of short length logs are not covered. One major reason for this is only 4 out of 50 logs in a shipment are examined to determine the length of entire lot and adjustments are based on the success or failure of these 4 logs.

A simple and easy way to overcome this issue is to increase the check size of the logs for judging the shipment. The sample size should be increased to 8 to 10 logs per shipment. This may lead to an issue of increasing inspection time. However, the increase in sampling could actually decrease the number of “spreads” or truck unloading in the inspection area. On doing so, the mill will be able to form a better understanding of the variance in the shipment and pay according to the better adjusted figures. However, this may not be a sufficient resort to eradicate the losses faced on account of short length logs, this will meanwhile act as a resort to decrease the losses significantly and further act to increase the percentage of detection of short logs.

If the increase in sampling size prevents further loss to the company, the decrease in inspection time from “spreading” may please the truckers and prevent them from going to other mills. Small bonuses could also be used as an incentive for truckloads that have the least amount of rejects.

References

Sower, V. E. (2011). Essentials of quality: With cases and experiential exercises. Hoboken, NJ: John Wiley & Sons.