As the economy improves and unemployment rates decline, it becomes more difficult for electrical contractors to recruit and retain qualified employees. The number of skilled employees available to manage and install projects limits your capacity and potential revenue, but turnover is accepted as an inevitable cost of doing business. Understanding the true costs of replacing employees is a necessary foundation for effectively attracting the most qualified people in a competitive hiring market.
The cost of turnover
Costs related to replacing an employee are for separation, recruitment and productivity. Both voluntary and involuntary separations trigger expenses for exit interviews, severance pay, extension of benefits and possibly unemployment claims or legal defense costs. Recruiting a replacement requires time to write job descriptions, search for candidates, screen and interview prospects. Then, the new employee must be processed, trained and integrated into your team.
Productivity costs are often difficult to measure. Other employees may be paid overtime to fill the gap, affecting their own morale and productivity. The learning curve for the new hire raises the cost of related projects and increases costs related to errors and rework. Opportunity costs result when other employees are mentoring and training the new person instead of concentrating on their own work. Any new person, regardless of competence or intent, also causes a ripple effect in the culture of the team during the first weeks of assimilation.
Experienced employees who leave also cause a ripple effect, when they take with them a portion of the institutional wisdom unique to every organization. Like a jigsaw puzzle with a missing piece, the expertise, judgment and efficiency an individual has developed will affect the quality of the final picture. That effect may be incidental at best or central to the flow of your work, depending on where in the puzzle the piece was located.
Sometimes called the “book of knowledge,” this is seldom captured strategically through a formal transfer process before the experienced employees leave. Without the human context, the information in your computer data banks cannot be applied effectively to problem-solving or future planning.
Predicting and managing
Historically, employers gleaned information on the causes of employee turnover through surveys and exit interviews, and some turnover was accepted as a cost of doing business. A recent model developed by the ADP Research Institute contains a possible tool for predicting which employees are most likely to leave voluntarily, potentially offering a more proactive strategy for managing turnover.
ADP RI studied payroll data for 2015 and 2016 from 41,000 companies with at least 25 employees each. From this pool of 12.5 million employees, benchmarks were developed for several industries. Across all industries, the average monthly turnover rate was 5 percent, with a seasonal pattern showing the highest rate in September and the lowest in March. The construction industry monthly average was 6.2 percent; however, 63 percent of the companies achieved a lower rate.
Between 60–70 percent of the measured turnover was voluntary, and the model identified 40 attributes contributing to voluntary turnover as having varying degrees of impact. Lead factors in voluntary turnover are pay and promotion, followed by overtime, commute time, experience and tenure. The relative weight of each attribute varies across companies and industries, and attributes work in combination with each other.
What does this mean?
A subset of 7 million employees from 1,900 of companies with 1,000 or more employees was used to develop a model predicting voluntary turnover. This model can identify employees at risk of leaving at a rate five to six times higher than guesses based on historical company records. It offers the potential to predict unplanned departures in time to prevent them, although the attributes need to be identified for each company before implementing the prediction component.
The lead factors also seem to conflict with many of the opinions and conclusions from other sources about employee motivation, loyalty and intent to stay. Some of these factors vary between generations, because their attitudes toward work and how jobs are structured can vary.
Whether or not you use a predictive analysis model, a deeper understanding of what employees expect from their jobs will help reduce turnover rate and its associated costs. Creating a book of knowledge and preventing a “brain drain” as your most experienced employees retire also is advisable. My next column will address the issue of how to mitigate the effects of losing your baby boomers.