The importance of payroll in your strategic decision making

Predictive AI is the way to go 

There has been a lot of talk about generative AI in recent months. If you are a payroll manager, however, you know that before chatGPT appeared on the scene in November 2022, payroll departments were already using AI before to optimize and automate certain administrative processes (paperless processing, implementation of chatbots, etc.). 

At Sopra HR, we are currently working on new ways of using predictive AI and our aim is to incorporate payroll data in the company's strategic decision-making process. 

Payroll professionals and AI: a winning combination   

As part of its “simplification” process, the government announced its intention to reduce the size of French payslips - the largest in the world - from around fifty lines to fifteen. They have been promising this for years. 

“Because French payroll regulations are not only sophisticated, but are also constantly changing, the expertise of payroll specialists is essential. Their job requires precision, compliance and automation, points out Adeline Delavoix, HR Transformation Manager at Sopra HR. This is precisely what Artificial Intelligence provides and payroll professionals and AI are indeed a great combination.” 

AI is already used to optimize less important tasks, such as managing time sheets and leave requests. "Many companies have already begun to digitize and classify employee documents, such as sick leave, absence requests, changes in family status, requests for an advance, etc. This could go even further." 

Generative AI: only a part of the overall picture? 

Adeline Delavoix believes that the current popularity of AI, and more specifically the “hype” around generative AI, is limiting. “Yes, we're seeing some great HR use cases emerging, such as virtual reality for training, or chatbots for employee support. But I'm sure we can find even more powerful and innovative ways to use AI for payroll."  

Payroll implements a company’s strategic data and this data may describe an employee’s career path as well as their cost to the company. Such data is the basis for reports used by all the business units and departments. 

“We can go even further, by getting involved in strategic decision-making for Payroll and HR departments,” says Adeline Delavoix. She divides these use cases into two main areas: supporting and motivating employees and managing the wage bill. 

53% of HR professionals are in favor of using AI for HR. 33% are already using or planning to use AI. The top use case (54%) is HR data analysis. Predictive analysis comes in 4th place (42%). 

Source: Sopra HR and L'Usine Digitale survey. Survey conducted at the end of 2023 on a sample of 266 HR professionals in French companies. 

An ally in the talent war  

The e-commerce sector relies heavily on AI algorithms to personalize the relationship with customers and meet each person’s specific needs. With the help of highly personalized suggestions, the ‘customer journey’ is thus optimized. “A company can do the same with its internal customers: its employees,” says Adeline Delavoix. “Employees are individuals that have their own specific career path, career aspirations, expertise, and personal working methods. By comparing these with the career paths of other employees, or with average salaries on the market, AI processes these different criteria and produces an analysis as well as possible alerts.   

In addition to alerts, AI tools provide features specially tailored to each employee, based on their career path, skills profile and areas of interest, so action can be taken before employees become frustrated or risk leaving the company.  

In large companies, opportunities may be missed due to a lack of suitable matching tools. 

Predictions 

“You can use AI tools to analyze payroll-related data (such as salaries, overtime or bonuses) over extended periods and determine patterns that repeat over time,” explains Adeline Delavoix, who also advises comparing this internal company data with third-party data, as mentioned above with the example of average salaries. 

“AI can then go even further by examining influencing factors (seasonal fluctuations, changes in legislation, staff turnover) to produce predictive models and emerging trends for reviewing compensation policies or optimizing costs. By combining this data with company data, we can estimate the expected wage bill in the medium term." 

HR Directors working this way have measurement tools and figures at their disposal and can thus establish their legitimacy and speak “the same language” as their colleagues on the Executive committee, especially the CFO!