Artificial intelligence based on machine learning can help compensation managers in many ways – to provide support for decision making grounded in analytics, to allocate HR budgets efficiently, and to improve the employee experience. Through these actions, businesses can in turn eliminate bias and enhance pay decisions. An investment in AI can show significant savings when done correctly. As an example, in recent years, IBM realized $107 million in savings because of AI.
In the current environment of increasing data points and improved technologies to do something with this data, an AI tool is prepared to handle large sets of data and make sense of it using algorithms and data science faster than any human. Forecasted data can be presented based on historical data for managers and employees when they need it. Inherently, if data can be decoded and transformed into informed business decisions, it will lead to smarter compensation planning.
Companies can increase pay transparency by connecting specific behaviors to higher compensation. They can also have access to robust forecasted accruals to aid in budget planning. When a sales manager can pinpoint the performance factors for each of their salespeople, they are now able to provide a tailored experience to provide additional training their sales reps need or rewards and recognition they deserve. When an employee gets a personalized employee experience and feels like their pay is strongly linked to their performance, biases are also reduced.
Bias in Compensation
In a competitive workplace, the impact of unconscious bias – especially when related to pay, can be costly to an organization. Based on a recent survey, 34% of workers believe that their pay is determined by what their manager feels they deserve to make and not based on their performance, skill set, and experience. In addition, even with diversity and gender programs, women still make 80% of what men earn (American Association of University Women).
When managers are making pay decisions based on how they feel or what they have done in the past, it can lead to error and unfairness. This often happens when a company does not have a firm grasp of its sales data or performance metrics. AI tools like Symon.AI can help reveal your business’s unconscious biases and enable leaders to start making concrete connections between pay and performance.
Furthermore, employees are far more likely to leave their job if they perceive bias. Based on a Center for Talent Innovation, employees are three times more likely to say they are planning to leave their current jobs if they perceive bias. Turnover is costly for companies, as more is spent on replacing workers, training, and development. On top of this, it could impact the effectiveness of your existing workforce. Existing employees who view bias around them are likely to become disengaged and hurt the company’s bottom line. The level of disengagement is rising for U.S. companies, resulting in $450-550 billion in losses each year.
To combat the bias, companies can invest in technologies such as AI to provide transparency, performance summaries, and better salesforce reporting for leaders which can result in enhanced pay decisions. Symon.AI can take existing historical sales, quota, and payout data to find patterns and outliers. Perhaps, there are seasonal trends in your business, resource capacity issues, and top performers that aren’t being recognized? AI can bring these issues to the surface with ease. And the best part – AI gets smarter as time goes on.
Symon.AI Dashboards
Many companies are now analyzing their gender distribution and equality metrics. Symon.AI can quickly and easily generate dashboards that give management teams insights into this. For example, gender distribution by quartile can help business leaders gauge whether they need to re-evaluate whether women are being paid fairly and adjust accordingly.
Also, the management and HR will also want to determine which roles specifically are generating the pay gaps so they can further investigate the reason for that.
A tool like Symon.AI can also summarize current and forecasted seller performance so sales managers can track and reward positive behaviour. In this example, Symon can quickly summarize the distribution of performance for your salesforce:
At a more granular level, Symon can show you the top performers:
Or your worst performers:
Having this data readily available will indicate which sellers a manager should put more effort into training and guidance.
In addition, along with analyzing existing performance and workforce data, Symon.AI can predict future behaviour. It can forecast seller performance based on historical data and seamlessly integrate into existing presenter reports or data discovery dashboards in Varicent.
Conclusion
As companies emphasize enforcing fairness in the workplace, using technologies like AI can make a big difference to increase pay satisfaction and decrease employee turnovers.
Would you like to know more about the impact of AI on sales? Click here.
