Table 7.1 Turnover Data Across Locations Region

Work satisfaction Supervisor satisfaction Pay satisfaction Benefits satisfaction Competition Index Turnover Rate Total Turnover

Eastern Washington 3.2 4.1 2.0 4.3 7.8 0.33 165

Western Washington 2.9 4.4 3.9 4.5 5.2 0.27 135

Northern Oregon 2.1 3.6 1.5 3.8 6.8 0.41 148

Southern Oregon 3.1 4.8 2.7 4.5 5.4 0.24 77

Northern California 2.8 3.3 4.1 3.1 8.3 0.48 221

Idaho 3.9 4.2 3.0 4.1 4.1 0.29 99

Montana and Wyoming 4.4 3.3 4.1 3.5 3.8 0.36 130

Colorado 3.9 3.5 4.7 3.2 7.9 0.46 212

Utah 2.5 3.7 4.5 3.6 4.6 0.28 106

Nevada 2.3 2.8 2.9 2.4 3.7 0.33 125

New Mexico 3.6 3.2 4.8 2.9 4.2 0.28 101

Arizona 4.1 2.9 2.5 3.1 7.6 0.39 172

Correlations for individual surveys

Donald Perez has also developed a correlation matrix that describes the relationship

between surveys and performance indicators.

Turnover

Work satisfaction Correlation P-value NS

Supervisor satisfaction Correlation P-value -0.19

0.02

Pay Satisfaction Correlation P-value NS

Benefits Satisfaction Correlation P-value -.24

<0.01

N=153

P values < 0.05 are significant

NS indicates NONsignificant P-value

Larger correlation values indicate a strong relationship

Answer for question 1, 2, 3

1. Which geographical regions have the largest turnover? Given Table 7.1, What do you think the problem is?

2. Review the information in the correlation table (Table 7.2). What appear to be the most significant reason(s) for turnover based on this information? What can OutdoorMart do to fix these issues?

3. How could OutdoorMart increase the response rate for the employee satisfaction survey?