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Effective Reduction in Employees’ Turnover: A Transactional Lean Six Sigma Case Study - Variance Reduction International (VRI)
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Effective Reduction in Employees’ Turnover: A Transactional Lean Six Sigma Case Study

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Transactional Lean Six Sigma

Effective Reduction in Employee Turnover: A Transactional Lean Six Sigma Case Study

Lean Six Sigma (LSS) is a method used to identify and eliminate waste, or non-value-added activities, in an organization. It helps organizations streamline processes, cut costs, improve quality, and develop better products. This paper presents a case study of a company’s experience in implementing LSS in the Human Resource (HR) function within a Transactional Services setting.

According to the Institute for Business Value, the average cost of replacing an employee is $49,000 per person. That’s the equivalent of an annual salary of $1,400, which is a big amount of money. The average cost of an employee turnover in Transactional Services, including retail, travel and entertainment, is $4,700 per employee, per year. This means that every time a person is hired for one of these Transactional Services, it costs the company $4.

The goal of this paper is to provide an overview of the Lean Six Sigma methodology and to analyze a successful case study of implementing the methodology within a Transactional Services company. This paper presents an approach to reducing turnover and enhancing the overall performance of employees.

This case study is about a corporation that struggled with a high level of voluntary turnover among employees across its network.

Lean Six Sigma in HR

Alessandro Laureani & Jiju Antony (See International Journal of Productivity and Performance Management. (2010) Vol. 59, No. 7, pp. 688-700. Emerald Group Publishing Limited) stated that Transactional Lean Six Sigma has been less popular because of the uncertainty that the processes in the industry do not lend themselves to the exact set of statistical tools of Six Sigma.

Even more doubtful is the application of LSS into HR practices, where the focus is on managing the human capital of the organization, an area where it can be really challenging to extract data using strict metrics. However, with the evolving definition of HR practices, companies have been applying LSS in HR management. 

In the same publication, they defined 7 points as the Human Capital Value Stream Map (VSM) based on merging terminology of Lean and HR. The Human Capital VSM is the flow of human capital required for an organization to deliver its products or service to customers, with the objectives briefly described below:

  • Attract. To establish a proper employer’s brand that attracts the right calibre of individual.
  • Select. To select the best possible candidate for the job.
  • Orient. To ensure new employees are properly trained and integrated in the organization.
  • Reward. To ensure compensation packages are appropriate and in line with the market.
  • Develop. To individuate talent and ensure career progression.
  • Manage. To supervise and administer the day-to-day job.
  • Separation. To track reasons for voluntary leavers and to maintain a constructive relationship. 

It is possible to apply the LSS tools to each step of the human capital VSM in order to eliminate waste in the HR processes. For each step in the human capital VSM, it is necessary to establish proper quantitative metrics that allow objective assessment and control of the process step: this makes use of the more quantitative statistical tools from the Six Sigma toolbox.


This case study presented by Alessandro Laureani & Jiju Antony (See International Journal of Productivity and Performance Management. (2010) Vol. 59, No. 7, pp. 688-700. Emerald Group Publishing Limited), aims to demonstrate the power of LSS in the HR area of a business and remove the myth that LSS is only applicable to manufacturing operations.


The company was experiencing a high level of voluntary turnover among employees across its shops’ network, with a peak of 40% in some geographic areas and an average of 35%, and a cost of tens of million dollars every year. The study aims to reduce turnover to an overall average of 25% across the organization.

The project team, led by a Black Belt, went through each of the VSMs phases mentioned previously, to identify its own relevant stakeholders and critical to quality characteristic. Extensive research was also conducted to collect the VOC: former employees for the past two years were surveyed regarding the reasons why they left the organization.

A questionnaire was designed to understand the reasons why they left the company, ranking from one (weak reason) to five (very strong reason) various possible reasons. A Project Charter was completed and agreed among relevant stakeholders; process maps for each step in the HR VSM were also prepared. 

Then, the team defined the key metrics of the project and processed the data, to determine the size of the opportunity and calculate the defects of the process. Some of the metrics identified were:

  • cost per hire;
  • time to fill a position;
  • training/orientation expenses per hire;
  • use of performance management program; and
  • use of exit interviews.


Data used were from the population of employees who voluntarily left the organization in the past two years that showed a disproportion of those with less than six months’ service.

With the vast majority of leavers (61.3%) in the first 6-12 months of employment, it appeared that the recruitment and orientation steps were instrumental in determining whether the employee was going to stay a long time with the company. Lack of training and orientation was mentioned as one of the most important factors in the questionnaire answers from ex-employees, together with career progression.

In terms of defect, the team decided to consider a defect of the HR process as any employee who voluntarily left the organization: for this, the defects per million opportunities (DPMO) calculation was outlined.


The project team reviewed the data collected in the questionnaire and sliced them across different dimensions, using a Paynter Chart (see Chart below), to highlight the most common reasons why employees left the organization. 

Based on the data, the 4 most common reasons for leaving were:

  1. lack of career growth opportunities (i.e., no opportunity of career advancement in current role);
  2. work schedule expectations (i.e., problems with the work shifts pattern required);
  3. work duties (i.e., problems with the duties requested to be carried out); and
  4. compensation (i.e., unsatisfied with the salary level).

Even though compensation was an important reason for leaving at the beginning of the employment, its importance dwindled, but subsequently increased significantly again at the first year anniversary of employment (following the performance review cycle). After sometime, employees were more concerned with the lack (or perceived lack) of career opportunities than anything else.


The project team considered that lowering the turnover rate was necessary to increase job satisfaction, acting on the factors that were highlighted as the most important from the data analysis. As the vast majority of employee turnover took place in the first 6-12 months of service, it was decided to focus improvement actions on the recruitment and orientation process of the human capital VSM, as those were the steps directly affecting new recruits. 

Ideas for improvement were generated in quality improvement workshops (“Kaizen”) conducted across different regions, with representatives from the local HR department, and led by the Black Belt in charge of the project. The team opted for the following improvement actions to be tested:

  • The recruitment process was reviewed, with less reliance on recruitment agencies and more of direct recruitment and a so-called “Refer-A-Friend” program – this is a scheme where existing employees are rewarded for referring a person to the company. 
  • An extensive review of the training and orientation for new hires was also conducted, covering the time from the new hire accepting the offer to the end of the induction period. A standard, global orientation day was designed, to ensure that each new employee was made aware of the mission, vision and values of the organization.

The above improvements were first piloted in two regions (one US state and one European country) and, after a positive result, they were deployed across the whole corporation.


All these actions were implemented and turnover levels monitored in the following months; a monthly employee turnover report was produced for each business unit, highlighting the percentage of voluntary turnover for each business unit over the previous month.

The overall, corporation wide, employee turnover rate decreased from an average of 35 to 25%. A C-Chart Control Chart was developed to monitor the employee turnover level over the last 24 months. 

As part of the Control Phase, the project team also developed a tool-kit detailing the new process. The new process was handed over to the process owners, who would be accountable going forward: the HR lead in each business unit. Each HR professional will be responsible for the ongoing deployment of the new process in his or her area of responsibility.

To ensure its continuous visibility, the key relevant metrics were included in the HR dashboard wherein senior management can have access to review company’s performances.


With the following main results:

  • a reduction in turnover from 35 to 25%; and
  • cost savings of $1.3 million on an annual basis.

It is concluded that Lean Six Sigma can be used to improve administrative processes, such as HR processes: implementing the Lean Six Sigma DMAIC breakthrough methodology in HR follows the same path as implementing it in any other part of the organization. However, there are some specific key learning points and challenges to the HR area, such as:

  1. difficulty in developing an appropriate Measurement System Analysis and metrics;
  2. data collection can be extremely challenging, as the project team is dealing with very sensitive issues; and
  3. difficulty in performing any pilot or design of experiment: any of these is going to impact the behavior of the staff, and might cause an issue in accurately measuring its results.

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