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How Using Data Analytics Can Unlock the True Strategic Value of Your Payroll

Payroll is arguably the single biggest source of highly valuable, yet underutilised data in any organisation. It can act as a detailed barometer for workforce trends, helping organisations to understand and optimise their employee experiences and ultimately drive better business outcomes.

According to the 2020 Future of Payroll report from the CIPP, 59% of payroll teams believe data-driven and cloud-based technology will help them become more strategic and relevant in decision making.

So why, if data is so important, are so many teams struggling to make good use of payroll analytics?

The common challenges with data

Data is often held in silos across different systems and tools, such as spreadsheets. There’s also typically a lack of integration between payroll data and other HR and business data. Working in silos not only means that data is much more likely to become misaligned or incorrect, leading to errors and potential compliance breaches, but there is no single source of truth from which to draw detailed workforce insights. If information isn’t unified across the business, it becomes difficult to analyse how payroll factors, such as hours of overtime, correlates with key HR factors, such as employee engagement or attrition.

Another key challenge is actually turning unified data into readable information and, ultimately, into actionable insight for the business. No organisation is short on data, but actionable insight from that data is rare. In payroll, this stems from a lack of automation and analytics capabilities; many payroll teams are still building reports manually, which is both time-consuming and less likely to provide the level of business intelligence required to reliably inform decision making. After all, most payroll and HR professionals aren’t data science experts (nor should they need to be), but they are under ever increasing pressure to bring impactful reports to the boardroom.

Thanks to advances in technology, it’s becoming easier to solve these challenges. Leading software providers are now building big data, predictive analytics, and artificial intelligence capabilities into their products, making it easier to collect, standardise, and interpret payroll and HR information across more tightly integrated systems. At the same time, some managed payroll providers are offering data-driven reporting services to add further strategic value and improve visibility for their customers.

Using payroll data analytics

When we talk about releasing the potential of payroll data analytics, what are we referring to? Today, standard reports tend to focus on outputs that give you confidence the payroll is accurate and also satisfy compliance and audit requirements.

More strategic uses include:

Understanding and minimising errors: Using analytics to understand the frequency and nature of errors can lead to improvements in payroll performance and the minimisation of unnecessary costs. Even a small number of recurring errors, such as underpayments and overpayments, can quickly add up to big problems for your organisation, and they can also have an impact on your colleague experience. Analysing error data over time can help you identify trends and pinpoint causes to be addressed. For instance, a specific error that keeps occurring could signal the need for additional training or resource to be invested in that area.

Improving accuracy with real time interventions: Providing information to line managers in real time in a pay cycle can not only help improve the accuracy, but also the overall success of the payroll function. For example, sharing the details of colleagues at risk of under or overpayment, along with the causes, can help managers to act before the payroll is completed, leading to lower organisational costs and a stronger colleague experience.

Workforce planning: Analysing payroll data is useful not only for identifying and addressing present challenges, but also informing future decisions. This is particularly crucial for rapidly growing organisations. If a particular division within your organisation is expected to have significant hiring needs over the next year, you could use payroll data to decide whether it would be more cost efficient to hire permanent or contingent workers. You can analyse not only the difference in average salaries, but also the other costs associated with each option. For instance, the cost of paying benefits, insurance and pension contributions for permanent employees compared to the cost of re-hiring and training contractors.  By delivering this insight, payroll teams can help HR and recruitment leaders to take timely and well-guided actions.

Attracting and retaining talent: One of the reasons why it’s so important to unify payroll and HR data is that organisations frequently see a direct correlation between factors such as salary, rewards, benefits and employee engagement, performance, and attrition. At a more granular level, it’s critical to understand the extent to which a specific combination of factors (such as age, compensation, location, and job function) influences the likelihood of an individual to leave the organisation. With these insights to hand, organisations can tailor and adapt their colleague proposition in order to attract and retain the best talent.

Use data to address your challenges

As leaders from across the organisation look to payroll to be more strategic, especially in terms of process optimisation, financial forecasting, and the colleague experience, it’s difficult to overstate the importance of data to guide organisational decision making. Payroll is one of your organisation’s biggest untapped sources of people data and, as we face an indeterminate period of workforce and economic uncertainty, now may be a better time than ever to use new technology to unlock its true potential.


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Abigail Vaughan

Abigail Vaughan



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09 Mar 2021



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This post is from a series of posts in the group:

Payments strategies 2015-2020-2030

Payments systems visions, strategies, trends, pilots, forecasting, and planning for the short-, medium-, and far-term.

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