For Darwin Hanson, it was an awfully close call. The independent analytics consultant was helping a client—a big-name aerospace company—crunch salary data when suddenly he noticed that the numbers just weren’t adding up.

“What the data showed was that a person who was just hired as an engineer was eligible for a larger salary than a person who had been fully competent in the position for two to three years. Up until that point, nobody had caught the error,” recalls Hanson. The mistake—although detected just in the nick of time—still cost the company nearly $20,000 in lost productivity and consultation fees.

Welcome to the fast-paced world of compensation analytics. These days, countless compensation survey vendors, from Mercer to Aon Hewitt, are under unprecedented pressure to produce reams of data for analytics purposes. Companies then purchase these data packages to determine factors such as the top pay level for a seasoned engineer, bonus payouts for new sales reps or compensation packages for senior-level managers.

The problem, however, is that a single miscalculation or error in data can cost a company hundreds of thousands of dollars.