Jeans Inc. case Study
Summary of case
Jeans Inc. is a large textile factory employing 600 people located in the Midwest. The factory is one of many that reports to a larger corporation. Most of the workers are low to semi-skilled, union members, and very diverse (18% Hispanic, 9% Asian, 3% African American, and 70% White). Over 80% of Jeans Inc.’s employees are female (Hatcher, Brooks, 109).
Jeans Inc.’s primary problem is a high employee turnover rate. Employee turnovers are costing Jeans Inc. thousands of dollars a year. The plant manager estimates that the turnover rate has cost the plant $100,000 a year due to overtime pay and its inability to meet production and training expectations (Hatcher, Brooks, 110).
Jeans Inc. asked the local university for help. The university created a team to address the turnover problem. The team consisted of a faculty member with performance consulting experience and five doctoral students with varying knowledge about performance analysis (Hatcher, Brooks, 110).
Initial Problem Statement
Jeans Inc. has a high turnover rate of around 90% annually (Hatcher, Brooks, 109). Turnover cost the plant thousands of dollars a year. Of great concern was the high operator turnover which is estimated to cost the company $100,000 a year (Hatcher, Brooks, 110). Many of the operator trainees failed to complete their training probation. Therefore, there were few operators available to replace those who left (Hatcher, Brooks, 110). Thus, In order to address the turnover rate several issues needed to be addressed. Areas such as low area unemployment, communication problems (rumors of plant closing), and inadequate job training orientation had to be dealt with to properly find a solution to Jeans Inc.’s employee turnover problem.
Performance Analysis
To conduct the performance analysis the team conducted their analysis in three phases, a preanalysis, analysis, and post analysis/intervention (Hatcher, Brooks, 111). Qualitative and Quantitative methods were utilized to analyze the turnover problem. Qualitative methods used were interviews, document collection, observations, and a case study. Quantitative methods used were surveys to collect employee attitudes and reactions. The performance analysis was primarily conducted using qualitative methods. Interviews, observations, and extant data reviews were used over quantitative analysis because 1) the nature of the work environment and the problem required a deeper level of understanding, 2) the literature review that did not fully address the problem, and 3) qualitative analysis was a strength of the analysis team (Hatcher, Brooks, 113).
Cause Analysis
The performance team identified numerous factors contributing to the high employee turnover rate at the factory. The biggest influences identified by the team were (Hatcher, Brooks, 124-127):
Intervention Selection and Development
To address the problems mentioned the team created a multiple intervention approach since there was not a single approach to address the problem, they were all inter-related. The team created the following interventions (Hatcher, Brooks, 124-129):
Once the interventions were implemented the company’s turnover rate fell to around 60% and at one point fell to 35% (Hatcher, Brooks, 129). However, the plant still closed so the team felt there were unresolved problems and concerns regarding their interventions. Namely, they felt that the employees were concerned about the team’s outcomes. Trainers were especially fearful of possible outcomes and viewed their need for additional training as management questioning their abilities. Second, it was wrong to disband the team after the preanalysis phase. Finally, external events most likely had a mitigating effect on the performance analysis (Hatcher, Brooks, 130).
Despite this, the team was pleased with some of their findings. They were satisfied that they all agreed to a multi-faceted approach to solve the problem. Lastly, they believed that their use of qualitative data was correct to find the gaps in performance, especially in the factories climate of distrust. Due to their use of qualitative methods they were able to build trusting relationships with employees (Hatcher, Brooks, 131).
Critique
The performance analysis team from the university did some things correctly in their effort to reduce employee turnover at the factory. They especially nailed their approach of using qualitative methods to solve the performance problem. Qualitative methods allowed them to collect rich data and build trust with employees at the plant. Additionally, no one approach was going to solve the problem so the team correctly utilized multiple interventions in an attempt to reduce turnover.
However, the team should have done some things differently. To start, they probably should have not let the whole study last for 30 months. This cost the factory more money and perhaps if their interventions were implemented earlier, could have helped save the factory from closing. Also, there was too much time and effort spent on training when more cost effective methods could have been used, such as implementing higher rewards and incentives to employees. Finally, the team should have really addressed the rumors of the plant closing. This would have made a difference with moral, focus, and incentive of employees to stay. It should not be understated how potent this factor was to the success of the study (Hatcher, Brooks, 133).
Jeans Inc. is a large textile factory employing 600 people located in the Midwest. The factory is one of many that reports to a larger corporation. Most of the workers are low to semi-skilled, union members, and very diverse (18% Hispanic, 9% Asian, 3% African American, and 70% White). Over 80% of Jeans Inc.’s employees are female (Hatcher, Brooks, 109).
Jeans Inc.’s primary problem is a high employee turnover rate. Employee turnovers are costing Jeans Inc. thousands of dollars a year. The plant manager estimates that the turnover rate has cost the plant $100,000 a year due to overtime pay and its inability to meet production and training expectations (Hatcher, Brooks, 110).
Jeans Inc. asked the local university for help. The university created a team to address the turnover problem. The team consisted of a faculty member with performance consulting experience and five doctoral students with varying knowledge about performance analysis (Hatcher, Brooks, 110).
Initial Problem Statement
Jeans Inc. has a high turnover rate of around 90% annually (Hatcher, Brooks, 109). Turnover cost the plant thousands of dollars a year. Of great concern was the high operator turnover which is estimated to cost the company $100,000 a year (Hatcher, Brooks, 110). Many of the operator trainees failed to complete their training probation. Therefore, there were few operators available to replace those who left (Hatcher, Brooks, 110). Thus, In order to address the turnover rate several issues needed to be addressed. Areas such as low area unemployment, communication problems (rumors of plant closing), and inadequate job training orientation had to be dealt with to properly find a solution to Jeans Inc.’s employee turnover problem.
Performance Analysis
To conduct the performance analysis the team conducted their analysis in three phases, a preanalysis, analysis, and post analysis/intervention (Hatcher, Brooks, 111). Qualitative and Quantitative methods were utilized to analyze the turnover problem. Qualitative methods used were interviews, document collection, observations, and a case study. Quantitative methods used were surveys to collect employee attitudes and reactions. The performance analysis was primarily conducted using qualitative methods. Interviews, observations, and extant data reviews were used over quantitative analysis because 1) the nature of the work environment and the problem required a deeper level of understanding, 2) the literature review that did not fully address the problem, and 3) qualitative analysis was a strength of the analysis team (Hatcher, Brooks, 113).
Cause Analysis
The performance team identified numerous factors contributing to the high employee turnover rate at the factory. The biggest influences identified by the team were (Hatcher, Brooks, 124-127):
- Management and supervisory issues
- Poor operator and trainer training
- Poor orientation training
- Poor communication from management to workforce
Intervention Selection and Development
To address the problems mentioned the team created a multiple intervention approach since there was not a single approach to address the problem, they were all inter-related. The team created the following interventions (Hatcher, Brooks, 124-129):
- Job responsibilities were revised to reflect actual tasks being performed
- Reduction in amount of communication oriented paperwork
- Revision in use of the plant electronic public address system
- Developed trainer job descriptions
- Developed and implemented an RJP process to be used during orientation training
Once the interventions were implemented the company’s turnover rate fell to around 60% and at one point fell to 35% (Hatcher, Brooks, 129). However, the plant still closed so the team felt there were unresolved problems and concerns regarding their interventions. Namely, they felt that the employees were concerned about the team’s outcomes. Trainers were especially fearful of possible outcomes and viewed their need for additional training as management questioning their abilities. Second, it was wrong to disband the team after the preanalysis phase. Finally, external events most likely had a mitigating effect on the performance analysis (Hatcher, Brooks, 130).
Despite this, the team was pleased with some of their findings. They were satisfied that they all agreed to a multi-faceted approach to solve the problem. Lastly, they believed that their use of qualitative data was correct to find the gaps in performance, especially in the factories climate of distrust. Due to their use of qualitative methods they were able to build trusting relationships with employees (Hatcher, Brooks, 131).
Critique
The performance analysis team from the university did some things correctly in their effort to reduce employee turnover at the factory. They especially nailed their approach of using qualitative methods to solve the performance problem. Qualitative methods allowed them to collect rich data and build trust with employees at the plant. Additionally, no one approach was going to solve the problem so the team correctly utilized multiple interventions in an attempt to reduce turnover.
However, the team should have done some things differently. To start, they probably should have not let the whole study last for 30 months. This cost the factory more money and perhaps if their interventions were implemented earlier, could have helped save the factory from closing. Also, there was too much time and effort spent on training when more cost effective methods could have been used, such as implementing higher rewards and incentives to employees. Finally, the team should have really addressed the rumors of the plant closing. This would have made a difference with moral, focus, and incentive of employees to stay. It should not be understated how potent this factor was to the success of the study (Hatcher, Brooks, 133).