Australian businesses are looking to leverage AI-powered workforce solutions to save money in losses from employee absenteeism.
With 13 per cent of rostered retail hours wasted and 7 per cent of hours scheduled not worked, employee absenteeism is a big hit to retailer’s bottom lines.
But AI-powered technology is helping retailer’s lower rates of absenteeism while improving productivity and staff morale.
With absenteeism costing retailers $600 million in lost revenue in the Christmas period alone, Steven Volz, Head of Retail, Kronos APAC, an AI workforce management solution, told Retailbiz that finding new ways of improving staff attendance offers retailers huge opportunity to boost profit margins.
Managers need accurate absence data to enable strategic workforce planning, but often have insufficient access to it, he says, with 56% of retailers naming building work schedules that align with the demands of customers, the business and employees as one of the most difficult, complex, or times consuming issues.
“A lot of what you can do through AI is utilise tools to improve or reduce that absenteeism. So you start with first and foremost an accurate forecast, and ask ‘what is the demand I need to service customers inclusive of absenteeism trends?,’” he says.
Mr Volz says absenteeism not only causes lost sales opportunities, but is also a cause of lost expenditure as a result of the additional costs of hiring contract staff.
But modern workforce management solutions can simplify the forecasting and labor scheduling process by utilising algorithms to develop accurate demand forecasts and improve visibility and subsequent employee engagement rates, he says.
“By providing more accurate allocation of staff in forecasts you are ensuring that you are taking into consideration their preferences and that will get you more engaged employees,” he says.
Utilising AI to manage your workforce can also help to improve compliance by predicting potential breaches of rules around break periods or overtime.
“What AI does is give preemptive insight to predict potential breaches of compliance such as minimum rest between shifts, overtime and fatigue risks,” he told Retailbiz.