COMPLIANCE
Making payroll data go further
Sandra Was ACIPP, payroll process junior manager – global process owner, Capgemini, provides some real-life examples of where payroll data can be used to make cost savings and improvements for wider organisations
T here’s a never-ending supply of information all around us. Data is present in pretty much all facets of our life, from our phones and computers to the many sensors and gadgets we use daily. We produce it while using the internet, making purchases, interacting with people. It’s gathered from everywhere: social media platforms, traffic sensors, healthcare equipment and weather stations. This data offers critical insights to help us in comprehending the world around us and allows us to make decisions based on facts and information. How can we describe data? It’s a group of information or values which is collected, processed and stored for the purpose of analysis or use. It can take various forms, such as text, images, numbers, audio or video. Advances in technology have made it easier to manage and use the vast amounts of information we encounter. With the help of machine learning algorithms and artificial intelligence, we can quickly and accurately sort, analyse and interpret large datasets. As it is in our everyday lives, data is also ubiquitous and highly valued in the business world, including payroll. In the world of payroll data Analytics data in payroll refers to the information collected and analysed in relation to aspects of the payroll process. This data can provide insights into:
l payroll costs l employee turnover l absences l areas of error. Analysing payroll data can help
one where we spend most of our time, as we need to collect essential data. What kind of information can be gathered in payroll? And when analysed, what does it tell us? I would like to provide a few examples (see table adjacent). These are just a few examples which help to consider the type of payroll data we can gather, and what it can tell us. The effective use of payroll data or, in fact, any business data requires proper management, storage and analysis. It involves employing various technologies and analytical tools to convert raw data into insights, which in turn influence decision making. Examples of payroll analytics tools and metrics include payroll software, key performance indicators, dashboards and data visualisation. Payroll analytics can provide valuable insights to help optimise and streamline payroll processes, scale back costs and improve overall efficiency. At the end, it brings benefits to the entire organisation. What are those specific benefits? Payroll analytics can help with: l compliant payroll processes: to ensure compliance, for example, with HM Revenue and Customs. And by regularly monitoring payroll data, organisations can identify any non-compliance issues and take appropriate action l better budgeting and forecasting: giving organisations insights into their labour costs, which can be used to make accurate
organisations to identify patterns, trends and issues, which can subsequently inform business decisions and improve efficiency, accuracy and compliance in payroll administration. The entire process of ‘payroll analytics’ can be drawn up in a very simple five step plan: (1) collecting the relevant information, collating the data we would like to analyse (2) gathering the data by using appropriate tools to examine and identify trends (3) identifying the areas for savings, whether those are time savings, cost efficiencies or other, during this phase we uncover inefficiencies in our payroll processes (or more holistically, in our organisations) and we spot areas where savings can be made, improvements can be implemented and any ‘gold plating’ can be removed 4) optimising the processes. Here is a milestone – we need to act on the results of our previous findings and optimise our processes (5) continuously monitoring payroll analytics to track progress towards savings goals, while identifying areas for further improvement. As with any project, the first phase is the
STEP 2 ANALYSING
STEP 3 IDENTIFYING
STEP 4 OPTIMISING
STEP 1 COLLECTING
STEP 5 MONITORING
| Professional in Payroll, Pensions and Reward | November 2023 | Issue 95 38
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