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Article 2 min read

Be ready for anything: support forecasting and scheduling

By Andrew Gori

Last updated September 21, 2021

One of the easiest ways to distinguish a good support organization from a great one is this: good ones are capable of meeting the everyday challenges as they occur, but great customer service organizations use support forecasting to predict future scenarios and prepare for them.

The most common scenario to forecast simple normal, day-to-day operations and historical trending based on any number of factors, such as seasonality or new product rollouts. But you may also require a forecast for special situations such as planning for new customer issues, expanding support to service new regions, a merger or acquisition, or incorporating new hours of operation. Or you may be in the process of implementing a new technology or support channel that will affect your call volume or response times, and need to determine what the resulting change means to staff distribution or workload. Whatever the reason, it’s important to understand the basic principles behind forecasting and how to apply them to accurately plan accordingly.

How to scale your

Forecasting and scheduling basics

Whatever you’re trying to forecast, there are some basic kinds of data that can help you predict how to best plan and adapt:

Historic data

Look at the previous two years of tickets, including average handle time by half hour: Be on the lookout for extremes, such as holidays or busy seasons.

Average monthly ticket volume

A date in the future will often match a date in the past.


Your customers use different channels for different issues. So be sure to slice data by voice, chat, email, etc., to get an accurate view of each.

Agent activity

Factor in time spent or lost in the contact center for training, in one-on-one meetings, lunch, breaks, vacations, sick time, etc.


Metrics like knowledge base page views and self-service ratio over time will give you a sense of which issues your customers are using self-service options to solve, and whether or not the self-service options you provide are resulting in fewer tickets.

In all cases, adjust for other business influences. Will the billing department’s new invoice format cause a flood of calls? Will sales forecasts help you plan staffing needs based on the new customer account base a year from now? Is the fulfillment area changing the way they package and ship products that may cause an increase (or decrease!) in your call volume? It’s critical that you communicate regularly with all these influencers of your support team’s workload as you prepare and fine-tune the forecast.

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