For many firms, losing significant revenue and profit to employee theft has been a cost of doing business.
But a new study from Washington University in St. Louis finds that information technology monitoring is strikingly effective in reducing theft and fraud, especially in the restaurant industry.
“Cleaning House: The Impact of Information Technology Monitoring on Employee Theft and Productivity,” by Lamar Pierce, PhD, associate professor of strategy at Olin Business School, finds that mining sales data of employees increased restaurant revenue about 7 percent.
The paper is co-written with Daniel Snow, associate professor at the Marriott School at Brigham Young University, and Andrew McAfee, research scientist at the Sloan School of Management at the Massachusetts Institute of Technology.
Using monitoring software called Restaurant Guard developed by NCR, the researchers measured the effect of theft and fraud before and after installation of the software at 392 restaurants in 39 states.
Pierce and his team found that after installing the monitoring software, revenue per restaurant increased an average of $2,982 per week, about 7 percent. Restaurants also experienced a 22 percent drop in theft.
“The NCR system works with data directly from the point of sale,” Pierce says. “It reduces the need for managers to use cameras and constantly watch their employees. In that sense it’s not more surveillance, it’s better and less intrusive monitoring.”
Employee theft and fraud are big problems in the United States, adding up to more than a $200 billion annual impact on the economy.
“Our results suggest a counterintuitive and hopeful pattern in human behavior,” the researchers write. “Employee theft is a remediable problem at the individual employee level. While individual differences in moral preferences may indeed exist, realigning incentives through organizational design can have a powerful effect in reducing corrupt behaviors in a way that benefits both the firm and its workers.”
Source: Washington University in St. Louis