Within a year, productivity increased by about 44 %.
“This is a huge increase,” he says George GeorgiadisAssociate Professor of Strategy at the Kellogg School of Management and an expert on performance -based motives.
The reason for this hit productivity was thin. About half of the increase came from existing workers who made more efforts. The other half was due to a displacement of the type of Safelite workers. “The less productive employees left and the new hires they replaced were significantly more specialized and productive,” Georgiadis explains.
Safelite’s success story quickly became an example of finance textbooks, which depicts how performance on performance could boost productivity both by motivating today’s workers and attracting better talents.
Inspired by this example, many companies believed that increasing incentives – such as bonuses, supplies or stock options – will naturally attract the best talents and lead productivity even higher. Indeed, many companies focusing on growth, including technological giants such as Google and Netflix, have adopted more and more generous motion structures, hoping to attract and maintain top talents and maintain profits.
However, despite its widespread popularity, this approach has a crucial blind spot. He assumes that intense motives always lead to a better choice for workers-that it will attract more high-quality workers and productive workers. But research by Georgiadis and his colleague Henrique Castro-Pires From the University of Miami he disputes this case.
Their findings indicate that the deepest motives do not automatically guarantee better recruitment and, in some cases, they can be reversed.
The hidden disadvantages of abrupt motivation
To this end, Castro-Pires and Georgiadis developed a mathematical model to explore how prospective employees respond to changes in motivation remuneration structures.
Their model considers the following scenario.
An employer, such as the manager in an organization, publishes a job that offers performance -based pay.
Potential candidates – who vary at the skill level – attribute whether they will be implemented on the basis of how imperative the remuneration structure is compared to other employment opportunities. Each candidate is being promoted that high -qualification candidates are more likely to go through low -special -special candidates. The employer then chooses to hire among the candidates passing the test and every employed employee decides how difficult to work.
Common wisdom suggests that the increase in incentives will naturally attract high -quality applicants. However, the researchers found that the highest incentives tend to attract both high -special and low -specific candidates.
In fact, depending on the labor market, the deeper motivation can disproportionately attract low -specially employees. High -quality employees often have more and better employment opportunities than low -specific employees, making them relatively rare in the applicants’ pool. As a result, the increase in incentives can accidentally increase the percentage of low -special -special candidates, eventually damaging the quality of the employer’s workforce.
“Scalable motives are not a panacea for the choice of workers,” says Georgiadis. “In some cases, it can really hurt the choice. Companies therefore have to actively think about how to structure incentives to improve the applicant’s pool.”
An example in sales
Take, for example, employees in a standard department store. Since their remuneration is based on commission, sales partners in the store may be encouraged to sell more if their manager hit their supply rate from, say, 5 percent to 7 percent.
At first glance, the highest commission rate looks like a shoo-in to attract better talents. After all, specialized sellers can create more sales, so they will benefit more than higher committees.
But the reality is thinner.
When the committee’s interest rate goes up, the work becomes more attractive not only for high -quality partners but also for low specialization. Thus, although high -qualification candidates can benefit more than the superior commission, there may be a larger number of low -skilled candidates attracted to the highest profit potential of the job. And if the team of potential low-skilled candidates expand faster than that of high-special-special candidates-which can easily occur depending on the labor market for sales partners-then the growth committees could actually lead to the recruitment of the lower-specific partners, harm it.
Because of this, “you must systematically consider how motives could unintentionally attract lower -specific applicants, rather than assuming that the strongest motives automatically improve the quality of the workforce,” says Georgiadis.
Practical steps for employers
While the researchers’ model does not provide a solution of a size, it offers practical guidance for companies wishing to optimize their incentives.
Georgiadis suggests that employers should design incentives that specifically attract high -special employees than they do to low -skilled employees.
“If you are simply increasing the pay, everyone benefits and more people apply from both swimming pools,” says Georgiadis. “But if you restructure incentives so that high -qualification employees are better, while low -skilled employees are not, then you improve the choice by attracting more than the first.”
Of course, achieving this balance is easier than it is. Employers rarely have complete information on the alternatives of the applicants’ work, their precise abilities or their preferences.
To deal with this, Castro-Pires and Georgiadis suggest a simple methods that companies can at least use if the changes they make in their motives improve their choice of workforce.
Employers should monitor two simple measurements before and after adjusting to their structure: the total number of applicants and the number of applicants rejected during the examination. If the total number of applicants is increased more than the number of applicants who fail the sorting test (in percentage terms), this indicates an improved option-that is, high-special candidates pass the sorting process.
In addition, the researchers developed a two -part test that can help employers identify the optimum motivation structure.
First, the employer must make a slight adjustment to their structure to pay incentives prior to hiring employees and observe how it affects the total number of applicants, as well as the number of applicants who fail the projection test. This experiment allows one to conclude all motivations that improve the choice of employees.
Then, after hiring employees, the employer must make a second adjustment to the incentives and monitor how employees’ productivity responds to this change. The combination of data from these two experiments only provides enough information for employers to identify the optimum incentive system for their condition.
“In principle, there are infinite scenarios that need to be examined,” says Georgiadis. “But a key result shows that, under some cases, the data from these two simple tests is enough to guide employers to the best motivation structure.”
