Competition for top talent
Top employees set a high bar for organizations to meet when considering where they will put their skills to work. Employers will have to differentiate themselves to attract these top workers and it won’t be enough to compete on the traditional salary and benefits package. In addition to this, the current rate of baby boomers eligible to retire is at 10,000 every day for the next 19 years. Even organizations that can attract top talent need to find the means to keep them, as younger demographics between the ages of 25-34-years-old have an average tenure at their place of work for 2.8 years (U.S. Bureau of Labor Statstics, 2018). All this has challenged employers to compete harder to ensure they can acquire and maintain top talent for their organization with not only strong compensation and benefits, but also flexible pace, hours and location. Imperative to the success of these adjustments is a payroll system that can handle flexible pay options.
AI and automation in payroll
Going forward, machine learning will allow us to start looking at every earning and tax deduction for an employee in a payroll run and using their historical pay to identify anomalies. This changes the way humans interact with a payroll cycle by placing less of the transactional burden on a payroll analyst and more emphasis on payroll analysts’ understanding of the end-to-end payroll process to solve the issues machine learning uncovers. This shift from a partitioned system of running a payroll cycle allows payroll departments to become a strategic partner to the business with their knowledge of an organization’s payroll cycle from start to finish and the ability to communicate this knowledge to company leadership.
AI’s ability to make inferences off historical payroll data will lead to providing better guidance around important employee compensation actions, such as benefit elections. AI’s analytical capabilities will also allow the quality reviews that happen during a payroll run to occur in the pre-payroll stages. With the ability to detect mistakes to time-submission based on historical employee time data for example, payroll AI can alert the employee of the mistake and allow them to resolve it in real time and before the inaccurate data is carried over into the payroll cycle.
The future of the payroll analyst
Those organizations that embrace these transformations around payroll open payroll analyst job duties to a variety of problem solving opportunities. Organizational leadership is always looking for their analysts to provide insights around payroll data, so as payroll colleagues free up their time by moving away from transactional and toward analytical functions they can focus more on process improvement and insights. These payroll colleagues also hold the important role of being the payroll AI and automation experts, as the machines running the transactional processes of payroll are only as good as the people who maintain their learning and integrity.
For more insights around the transformation of payroll you can watch the full video of Wilson's conversation with Workday below.