According to Hemanth Puttaswamy, chief technology officer at HR-tech company Saba, the traditional approach to employee compensation is “socialistic and reactive,” and it basically amounts to people using Excel spreadsheets to distribute money across different jobs and different locations. Some call this the “peanut butter approach” — spreading compensation money evenly across the company the way one spreads peanut butter over a slice of bread.
“Companies [are] trying to force the socialistic structure in a capitalist company,” Puttaswamy says. “They say, ‘If you have a performance rating of 3 or 4 in job X, then you get a hike of 3 percent. That’s it.”
The problem with such system is that it does not account for individual achievement, nor does it operate on any real insight into the employee population. Sure, employers can simply award fixed raises according to performance ratings, but what about all the other variables? What about accounting for the fact that one employee who scores a 4 may have higher potential and bring more value to the company than another employee who scores the same? What about accounting for “hot commodity”employees who have in-demand skills and are therefore more likely to leave the company? What about the microeconomic trends in the industry and the macroeconomic trends overall?
Emily He, Saba’s chief marketing officer, agrees that compensation needs to be more proactive and individualized. She could do without the peanut butter: “I really believe in super-specialization. When I look at my team across the board, everyone is doing something very different. In that scenario, it’s really hard to design compensation with the peanut butter approach, because everyone contributes in a different way. I want to have a personalized approach to rewarding employees and compensating them.”
“We wanted to do [compensation] differently,” Puttaswamy says. “We wanted to provide … individualized salary recommendations.”
That’s why Saba has created Compensation@Work, a new addition to the Saba talent management suite that aims to be “a predictive solution for simplifying and personalizing the increasingly complex employee salary and incentive pay process.”
Big Data, Machine Learning, and the Capitalistic Approach to Compensation
“What we have is a capitalistic structure,” Puttaswamy says. What he means is that Compensation@Work uses big data and machine learning to help compensation planners individually tailor compensation packages to each employee, based on a number of factors.
“[When compensation planners] are planning their budget, [Compensation@Work] comes up with a recommendation on who are the most important people in the company and how much more you should be paying to retain those people versus the opportunity costs lost if you lose those people,” Puttaswamy explains. “What does replacement cost, and what does retention cost?”
Compensation@Work creates such recommendations by analyzing company signals and micro- and macroeconomic trends. Puttaswamy explains the system as a group of overlapping circles. These circles are:
- Value: That is, what value does the employee bring to them company? “Many things go into high value,” Puttaswamy says. “For example: influence in the internal social network, the peer-to-peer impressions that you receive, the performance-rating score, how well you are doing within the company, and … the social contributions that you have made, including the questions you are asking and the answers you are giving.”
- Risk: This calculates the probability of losing an employee by looking at organizational trends and trends in the industry and the economy overall. “We segment employees based on the organization, the location, the job, the number of years of service, the promotions they have received, their education, and many other areas like that within the company,” Puttaswamy says. “Then we look at the trends — the microdata and the macrodata, the economics data.
- Pay: This is where Compensation@Work looks at industry benchmarks and peer benchmarks within the company to establish what an employee should be paid. “Even if you are paid two percent over the average, it doesn’t mean that is the right pay for the individual,” Puttaswamy says.
“The intersection between these three circles is what the compensation is all about,” Puttaswamy says. “We look at all these signals and say, ‘Okay, what is the right pay for the person? What pay will retain them, and should we retain them?’”
Saba believes that, aside from personalizing the compensation process, Compensation@Work may also help companies take a more proactive approach to talent management — something that He says is incredibly important, given current trends in HR.
“Now, when HR people talk about talent management, they often talk about managing processes more efficiently or addressing employee concerns,” He says. “If someone expresses a desire to leave, you kind of jump right away and try to retain them.
She continues: “We don’t believe in that type of talent management. We think a more effective way to manage talent is to proactively look at your entire company and identify your superstars and proactively go to them with a compensation package and a career plan that makes sense to them, so that you have a better chance of retaining them.”
“In the old budget management system, there was no insight to the complete population,” adds Puttaswamy. “Now, you can go have a conversation with the CEO and say, ‘Okay, these are the 20 people out of 2000 employees whom the system has flagged as most important. I need to go offer them more. ‘And you know the reasons why the system was recommending them.”