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The True Cost of Employee Turnover - Part Two.

19/6/2023

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My last looked at the potential cost of turnover to the organisation. The post resonated with some people, so discussing how we can predict turnover and possibly take preventative measures to manage turnover may be beneficial. It is essential to mention that not all turnover is bad turnover; the focus here is regrettable turnover. Some call regrettable turnover, dysfunctional turnover.   


It goes without saying predicting employee turnover is complex, considering the various factors that impact turnover. Factors include salary structure, work-life balance, job satisfaction, comfort in the working environment, and relationships with supervisors. These factors are variables that can be used to identify employees at risk of leaving the organisation. This is where HR analytics comes into its own. To predict turnover, four main types of HR analytics can help us predict turnover.   


  1. Descriptive Analytics: This type of analytics focuses on what has happened in the past. It uses data aggregation and data mining techniques to provide insight into the past and answer: "What has happened?". Data such as retention rate, turnover rate, average tenure within business units and roles, and internal mobility within the organisation are valuable metrics. This set of metrics focuses on the general data patterns and distributions of turnover in an organisation.
     
     
  2. Diagnostic Analytics: Diagnostic analytics is a form of advanced analytics that examines data or content to answer the question, "Why did it happen?" and is characterised by techniques such as drill-down, data discovery, data mining, and correlations. Data such as reasons for leaving, where they are going to, in terms of the type of employer and location, job level, age, length of tenure in the role at the time of departure, length of tenure in the organisation, travel distance and whether or not they relocated for the role, performance reviews, relationship with management, the condition of the external labour market, the talent market for the positions etc. This set of metrics focuses on the leavers and understanding the individual drivers for their exit.

  3. Predictive Analytics: Predictive analytics uses statistical models and forecasting techniques to understand the future. It uses various techniques from data mining, machine learning, and artificial intelligence to analyse current data and predict the future. Using all the information identified in the descriptive and diagnostic phase, employee behaviour can be predicted. Models such as decision trees or other complex machine learning algorithms are used for classification and regression (Support Vector Machines and Random Forest). You may need the help of your business intelligence team here as intermediate statistics are involved. Predictive analytics helps to identify what factors influence resignations. Based on this data, you may successfully target and decide your retention strategy, which is not based on gut feeling or anecdote.   

  4. Prescriptive Analytics: Prescriptive analytics prescriptive is used to suggest various strategies to reduce employee turnover based on the results of predictive analytics. It goes beyond predicting future outcomes by suggesting actions to benefit from the predictions and showing the decision maker the implications of each decision option. It uses techniques like algorithms, machine learning, and computational modelling procedures. Prescriptive analytics helps to reduce the rate of resignations by identifying and ranking all of the factors that contribute to resignations in real-time. It also helps to retain high-performing or critical employees by comparing resignation rates across positions, locations, tenure, age groups, diversity, and other groups.  Even though valuable insights can be gained through this method, considerations must be given to the unique context and constraints of the organisation.  


A note of caution here, the methods described above don't give us a fail-proof approach for dealing with turnover. Sometimes, one outcome may make an employee stay, and another may leave despite the interventions. 


Regardless, organisations should continue to analyse the various motivations for individuals' choices to depart companies and how employees decide these things. It is essential to gain organisational equilibrium by ensuring that the motivating factors it provides (such as adequate salary, pleasant work environment, and growth possibilities) are equivalent to or higher than the sacrifices (time, effort) demanded of the employee.   
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In conclusion, understanding and managing employee turnover is a complex but necessary task. By leveraging HR analytics and understanding the motivations of employees, organisations can better predict and manage regrettable turnover, leading to a more stable and engaged workforce.  

 

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The True Cost of Employee Turnover

5/6/2023

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I was listening to a podcast episode of Eat, Sleep, Work Repeat. Bruce Daisley was talking to Zeynep Ton about making the case for good jobs. At some point, Zeynep said, organisations don’t know the true cost of turnover. That phrase true cost of turnover stayed with me, and I wondered if I truly understood the true cost of an HR professional beyond calculating the cost of turnover and recruitment. It made me think of the associated cost of growing commitment and engagement, which needs to be factored into the cost of turnover. I thought to dig deeper into the associated costs of turnover.  
 
Employee turnover is an issue organisations face globally, and its impact is often underestimated. The costs associated with employee turnover aren't just financial; they also involve the loss of knowledge and productivity, adverse effects on team morale, and the time and resources required for training new employees. 
 
Financial Costs 
 
The financial burden of employee turnover can be significant. According to a study by the Society for Human Resource Management (SHRM), the average cost of replacing an employee can be as high as twice the employee's annual salary, especially for high-level or highly specialised roles. This cost encompasses recruitment, training, and the loss of productivity during the transition period. 
For instance, consider a tech company that loses a software engineer earning £70,000 annually. Including recruitment costs, training for the new hire, and the productivity gap, the total cost could reach up to £140,000. 
 
Productivity Loss 
 
When an employee leaves, productivity dips. The remaining employees often need to take on extra responsibilities until a replacement is found, which can take months. Even when a new hire is onboarded, they won't be as efficient as the seasoned employee initially, leading to a productivity gap. 
 
Consider the example of a sales manager at a car dealership. If this experienced manager leaves, not only does the dealership lose its established customer relationships and sales acumen, but the rest of the sales team may also have to fill in, leading to reduced sales performance. Suppose that sales manager A (now leaving) makes a monthly sale of £500,000, and sales manager B makes a monthly sale of £500,000. No matter how brilliant sales manager B is, one could hypothetically guess that sales manager B will not all of a sudden start to bring in £1,000,000 monthly. Or, for those of us who love data, you could do a simple calculation if you know the performance baseline: Productivity Gap = Productivity level with the staff member - Average productivity level without the staff member. 
 
Impact on Morale and Employee Engagement 
 
Employee turnover can also significantly impact the morale and engagement of the remaining employees. When they see colleagues leaving, particularly in high numbers, it can create uncertainty and lower job satisfaction. 
 
Suppose an experienced nurse manager in a hospital resigns. This can cause anxiety among the nursing staff, affecting their job performance and patient care quality. It can also lead to a domino effect, causing other nurses to consider seeking employment elsewhere. It is often difficult to measure this cost, but a pulse survey may provide insights into the impact of those left behind. We can learn from the research on those left behind after a restructuring. Issues such as the change in team dynamics, decreased trust in management with high turnover as people fill in the gaps as to why colleagues are leaving, and impact on customers as shown in the nurse manager example.  
 
Training and Development 
 
Training a new employee takes time and resources. It’s not just about teaching them the technical aspects of their role but also about integrating them into the company culture and helping them build relationships. 
 
Taking an example from the hospitality industry, a hotel losing a front desk manager would require the new hire to understand their responsibilities, learn the hotel’s customer service standards, and develop a rapport with regular customers. These costs will vary. The immediate cost that comes to mind is the main cost of the training, employee time in training and other miscellaneous costs, like accommodation, expenses etc.   
 
The Hidden Costs 
 
The indirect costs, such as damage to customer relationships and brand reputation, can be harder to quantify but are equally impactful. Customers build relationships with employees, not companies. If a key contact leaves, it could potentially result in lost business. 
 
In the example of an account manager at an advertising agency, their departure might disrupt the relationship with their clients, affecting client satisfaction and potentially leading to lost business. 
 
In conclusion, the true cost of employee turnover is multi-faceted and often higher than anticipated. Businesses should focus on employee retention strategies and nurturing a positive work environment to reduce turnover rates and associated costs. In my next post, I will look at the antecedents of employee turnover.  ​
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