The Delta Wire Corporation was founded in 1978 in Clarksdale, Mississippi. The company manufactures high-carbon specialty steel wire for global markets and at present employs about 100 people. For the past few years, sales increased each year. A few years ago, however, things did not look as bright for Delta Wire because it was caught in a potentially disastrous bind. With the dollar declining in value, foreign competition was becoming a growing threat to Delta's market position. In addition to the growing foreign competition, industry quality requirements were becoming tougher each year.

Discussion

1. Delta Wire prides itself on its efforts in the area of employee education. Employee education can pay off in many ways. Discuss some of them. One payoff can be the renewed interest and excitement generated toward the job and the company. Some people theorize that because of a more positive outlook and interest in implementing things learned, the more education received by a worker, the less likely he or she is to miss work days. Suppose the following data represent the number of days of sick leave taken by 20 workers last year along with the number of contact hours of employee education/traiing they each received in the past year. Use the techniques learned in this chapter to analyze the data. Include both regression and correlation techniques. Discuss the strength of the relationship and any models that are developed.

2. Many companies find that the implementation of total quality management eventually results in improved sales. Companies that fail to adopt quality efforts lose market share in many cases or go out of business. One measure of the effect of a company's quality improvement efforts is customer satisfaction. Suppose Delta Wire hired a research firm to measure customer satisfaction each year. The research firm developed a customer satisfaction scale in which totally satisfied customers can award a score as high as 50 and totally unsatisfied customers can award scores as low as 0. The scores are measured across many different industrial customers and averaged for a yearly mean customer score. Do sales increase with increases in customer satisfaction scores? To study this notion, suppose the average customer satisfaction score each year for Delta Wire is paired with the company's total sales of that year for the last 15 years, and a regression analysis is run on the data. Assume the following Minitab and Excel outputs are the result. Suppose you were asked by Delta Wire to analyze the data and summarize the results. What would you find?

3. Delta Wire increased productivity from 70,000 to 90,000 pounds per week during a time when it instituted a basic skills training program. Suppose this program was implemented over an 18-month period and that the following data are the number of total cumulative basic skills hours of training and the per week productivity figures taken once a month over this time. Use techniques from this chapter to analyze the data and make a brief report to Delta about the predictability of productivity from cumulative hours of training.
Cumulative Hours Productivity
of Training (in pounds per week)
0 ................70,000
100 ...............70,350
250 ...............70,500
375 ...............72,600
525 ...............74,000
750 ...............76,500
875 ...............77,000
1,100 ...............77,400
1,300 ...............77,900
1,450 ...............77,200
1,660 ...............78,900
1,900 ...............81,000
2,300 ...............82,500
2,600 ...............84,000
2,850 ...............86,500
3,150 ...............87,000
3,500 ...............88,600
4,000...............90,000

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Hours of Sick Employee Education Days Hours of Sick Employee Education Days 24 16 48 120 4 12 13 14 15 16 28 15 10 65 18 19 20 120 15 48 12 10 12 10 MINITAB OUTPUT Regression Analysis: Sales Versus Satisfaction The regression equation is Sales 1.73 0.162 Cust Sat Predictor Constant CustSat Coef StDev 1.7332 0.4364 3.97 0.002 0.16245 0.01490 10.90 0.000 S 0.4113 R-Sq 90.1% R-Sq (adj ) -89.4% - - Analysis of Variance DF SS Source Regression Residual Error 13 2.199 0.169 Total EXCEL OUTPUT MS 1 20.098 20.098 118.80 0.000 14 22.297 Regression Statistics Multiple R R Square Adjusted R Square Standard Error 0.949 0.901 0.894 0.411 15 ANOVA df sS MS Significance F 0.000 Regression Residual Total 20.098 20.098 18.8 13 0.169 2.199 22.297 Coefficients 1.733 0.162 Standard Error 0.436 0.015 t Stat 3.97 10.90 р.value 0.0016 0.0000 Sick Days