The busy working life of a modern global payroll team involves a myriad of challenges. They include complying with the regulations of the countries in which the business operates and handling huge amounts of data on a daily basis. There are few within the payroll sector who would turn down a helping hand with these daunting tasks. Thanks to the immense progress in HR and payroll technology, that helping hand is now available.  

Technological advancements in artificial intelligence (AI) have not only improved the handling of big data by payroll and human resources teams but also enabled the use of predictive analytics, unlocking many potential benefits for both the team themselves as well as the business as a whole. Indeed, a 2018 Oracle report found that HR teams were more engaged in analytics than any other function in a typical business, including finance. 

Reduced workload 

On a very simple level, predictive analytics reduces the onerous burden of payroll processes and in-depth data analytics tasks from the human resources team. Released from the time-consuming upkeep of the payroll system, HR professionals will be able to focus on more complex operations and human-only tasks such as strategizing and communicating. Not only will this save the business money in administrative staff, but the business will run more smoothly with the extra time dedicated to planning and forward-strategy. 

Error management 

With the increased visibility that predictive analytics offers, identifying, locating and rectifying errors become quicker and more efficient. 

Payroll is often the biggest single overhead for international corporations, usually accounting for between 50 and 70 percent of company expenditure. Accuracy is therefore essential to achieving a strong company bottom line. Not only will a predictive analytics system be able to identify errors more quickly by comparing data input to previous iterations, but it will be able to track errors over time. Spotting a spike in errors in a particular location or at a particular time of year will allow organizations to make plans to eliminate the factors that could be leading to such mistakes, such as staff absence or holiday. 

Analysis and prediction

Advancements in AI and machine learning have enabled the analysis of data trends that would have previously been impossible or extremely time-consuming for humans. The payroll system is one of the most data-rich areas of many businesses, it makes good business sense to leverage that information to the company’s advantage. As long as data is up to date and accurate, predictive analytics can offer valuable insights on employee turnover and absence amongst many other variables. 

Credit Suisse used analytics to predict which staff members were likely to quit their jobs and even why. This enabled the HR team to work on improving the employee experience as well as plan to fill future vacancies. This saves the company $7,000,000 every year. 

Experian’s ‘flight risk’ predictor analyzed over 200 aspects of employee experience including team size, commute length and supervisor performance to assess which staff members might be likely to quit. Their data revealed that staff in teams larger than 10 to 12 people were more likely to leave, and the company took action to resolve this weakness. As a result, attrition dropped by between 2 and 3 percent over the subsequent 18 months. 

Adopting technology with reporting and analytics software will assist global payroll teams in strategic planning for the future. Access to information such as employer costs per country can provide valuable insights for the business for expansion plans. Tasks such as recruitment and talent acquisition are easier with the use of analytics tools, as the technology can review annual reports to predict the future needs of the business. Such advanced future planning of budgets and cash flow will optimize business performance whilst minimizing costs, giving a boost to the company bottom line. 

Use of people analytics guarantees that human capital management (HCM) is operating at an optimum level both for the business and the employee. The system identifies any skill gaps or training deficits and HR teams can resolve them in a timely fashion.

The Mexican government used workforce analytics to ensure the smooth running of their oil and gas industries by identifying skills gaps in their staff and eliminating them. 

Employee benefits 

The use of predictive analytics can improve employee engagement, from new hires to existing talent management. Employee data can influence future hires, ensuring they are a good match in terms of skills and background as well as culturally, thus ensuring that the people the company brings onboard are primed for success in their role. 

Payroll analytics can also advise on salary, holiday allowance, and training requirements, offering candidates and employees additional benefits that they cannot refuse whilst ensuring they represent good value for the business. Footwear retailer Clarks conducted a company-wide survey to understand which of the benefits on offer their employees valued the most. They were then able to adjust employee packages to improve staff satisfaction by 15 percent saving the company money. 

Employee satisfaction is documented, measured and responded to thanks to big data and analytics.

“Employee experience programs used to take months to develop and to collect useful information,” reports Webb Stevens, GM at Qualtrics.  

Payroll software can handle millions of responses in real-time and offer fast and effective analysis of trending results. 

Best Buy was able to add $100,000 to their annual income by conducting quarterly employee satisfaction surveys which lead to an improved score of 0.01 percent but was enough to add a significant sum to their bottom line.

The power of payroll 

Global payroll teams, empowered by in-depth insights and analysis will not only improve the running of the Finance, Payroll and HR department but bring their improved understanding of how to reduce costs and improve employee productivity to the wider business. 

Cisco used demographic data when deciding on locations for business expansion. By reviewing variables such as usage rates of office space, costs and talent availability they could make smarter tactical moves for the company’s future. 

Faced with the challenges of the future, whether it’s the IT skills gap or Brexit, these insights into payroll data sets will prove invaluable to the success of global businesses. Payroll leaders will find themselves called upon to stand amongst business leaders to offer their opinion on business decisions.  Taking payroll far beyond the fundamental role of paying people on time, predictive data analytics is the key to unlocking the real power of Finance, payroll and HR departments and the maximum performance capacity of the business as a whole. 

To find out how you can unlock your payroll data for key strategic decision making, contact us today!

 

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