In this paper, we equip you with...

The business benefits of machine learning in call centre forecasting and planning

Common challenges that contact centre forecasting managers are facing

Tips on how to get started without having to create a dedicated team of data scientists

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A comparison matrix of some of the most popular forecasting tools on the market used for demand planning. 

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A guide to evolving call centre forecast accuracy to improve service levels and optimise resources.

Contact centres are the fundamental link between customers and businesses. Forecasting how many agents should be available in the contact centre at any given point is a critical process, and it's time consuming. 

Microsoft Excel is the most commonly used software for forecasting - but it was never designed to produce hefty forecasts. There are several challenges associated with using Excel as a forecasting tool such as single person dependencies, not using all available data and lack of automation.

In this paper, we demonstrate the power of machine learning to save time whilst improving accuracy and ultimately elevate your customers' experience.


Lack of innovation

A lot of organisations have been using Excel for forecasting since their inception, and they're struggling to innovate. 

Not using all available data

Due to Excel's limitations, forecasting managers can often disregard data that may be very useful to their forecasts. 

Single-person dependencies

Another challenge with Excel is that often individual planners will have their own preferred tools or spreadsheets for forecasting. The lack of a shared modelling workflow leads to single-person dependencies and operational silos, preventing effective collaboration and stressful scenarios if that person is away from the business. 

Lack of automation

Many teams simple spend too much time on cleaning data, pre-processing it and preparing it for the forecasting Excel spreadsheet. This manual work is not only error prone, but also prevents planners from experimenting with new algorithms and ideas to improve accuracy or forecast faster.

A easy to follow guide to evolving call centre forecast accuracy to improve service levels and optimise resources.

Business benefits of machine learning in call centre

Tips on how to get started

Common challenges faced by call centre managers

A comparison matrix of Forecasting tools

What to expect in this guide




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