Increasing motivation and productivity with simple A/B Testing Experiments

Motivating employees is a challenge that business founders may encounter at any stage of the business lifecycle and at any business size. In a new study conducted by George Georgiadis and Michael Powell from the Kellogg School of Management, both associate professors of strategy, develop a model that shows how organizations can use A/B testing to find more effective ways of structuring performance incentives. The researchers built a mathematical model to analyze interactions between an employer and its employees.

“If you’re willing to do an A/B test, you don’t have to know that much. You just observe how [employees] react.”

— Michael Powell

A/B testing is essentially an experiment where two or more variants of a page are shown to users at random, and statistical analysis is used to determine which variation performs better for a given conversion goal. In this example, A can be paying employees a higher salary, whereas B could be a slightly lower salary yet with commission potential.

The approach has a number of benefits that make it practical for organizations to use. For one, unlike a lot of previous economic research into incentives, it doesn’t require that the employer understand in advance anything about their employees’ preferences, such as how much they dislike working at a faster pace. It also doesn’t require them to fully understand how much effort goes into being more productive in a given work environment.

The essence is to propose a change – which can be around not only remuneration packages, but also strategy, operations, working hours, work location, frequency of meetings – and observe the results. With a conscious effort to start paying attention to these in such experiments, looking for correlations, this approach can prove to be an innovative way for growing businesses to scale smarter.