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Powering Compensation and Benefits Metrics in Organizations with AI

As organizations look for new ways to hire and retain talent, some have begun to leverage artificial intelligence (AI) to more precisely compensate employees. The concept of offering salary adjustments and benefits to reflect the value of an employee's skills rather than the level of a specific job in being increasingly adopted, particularly when those skills are highly in demand and critical to success.

Artificial intelligence’s approach to Compensation Management helps management take the guesswork out of decision making. It has the ability to empower leaders to recognize contributions and address any unintended pay gaps that may present.

Taking the lead, several organizations like IBM have designed AI-powered decision support tools that assist with compensation planning by helping managers avoid underweighted or overweighted data points. Such applications review dozens of data points to make recommendations while integrating external information like industry norms, legal requirements, etc. with internal data on factors such as cost to replace. IBM has been using AI in its compensation systems for several years now and has shifted performance management to focus on ongoing feedback rather than a single periodic performance rating, while also tying salary increases more closely to employee skills.

AI-based compensation support has led to saving of 1000s of human-hours while providing decision advice based on many more variables than were previously accounted for. Furthermore, by focusing on skills in determining compensation, the use of AI minimizes the chances that bias exists in the compensation process. By taking advantage of AI to make compensation fair—based on a variety of rules including education, experience, certifications and more—businesses move closer to closing pay gaps.

Even chatbots are making their way into compensation management in the form of self-service chatbots which can address employees' requests on compensation topics. This is very effective in providing compensation-related answers in real-time, improving HR responsiveness and reducing support costs.

The use of AI-driven compensation technology can also mitigate the risk of employee turnover, which costs businesses as much as 33% of a worker’s annual salary to replace them. 

There are now AI-Services that simulate and analyze different compensation models and incentives scenarios, to identify patterns and further optimize those models to increase performance and save costs. For compensation and rewards, this can result in optimized incentive plans with better outcomes at lower costs. For sales, this can result in optimized territory and quota plans to maximize sales performance.

Timely compensation and rewards, a key outcome of AI introduction, have been found to have a direct impact on employee engagement as well. A study by Globoforce found that employees who receive regular small rewards, in the form of money, points, or thanks, are a staggering 8 times more engaged than those who receive compensation and bonus increases once a year.

Employers can leverage AI not only for current compensation needs but also to ascertain future skills requirements and how much it will cost to acquire and retain those skills in the workforce. To price skills correctly, employers can use AI to harvest datasets from both internal and external sources, separate skills that roles require now and are likely to require in the future and determine pay for those skills based on geography.

  • Posted Date: 18-MAR-2020