The company wanted to improve their call centre’s management to accommodate for down and busy periods. Staff rostering was done manually and often resulted in having too little or too many staff working. This impacted on customer satisfaction and labour cost.
We built a forecasting tool that produced a report based on past call volumes and staff rostering. The machine learning solution analysed the data and provided recommendations on how many staff should be rostered to accommodate down periods and busy periods.
Managers used the report to roster their staff more effectively.
The company reduced labour cost and improved customer satisfaction by having the right amount of staff to cover fluctuating calls.
- Call centre staff worked in a less stressful environment
- Waiting time over the phone was shortened
- Customers were less frustrated