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Call Centre Forecasting & Workforce Scheduling​

Call Centre Forecasting & Workforce Scheduling​

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Call Centre Forecasting & Workforce Scheduling​

Call Centre Forecasting & Workforce Scheduling​

Take the guesswork out of rostering call centre staff. By using machine learning and predictive analytics, you can effectively manage your workforce and improve customer service.

Technology Stack

Predictive Analytics

Machine Learning

Problem

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.

Solution

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.

Results

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