Contact Centre Forecasting and Scheduling

Contact Center Forecasting and Scheduling ranks as one of the most misunderstood disciplines in the Contact Center industry. I have observed operations in utter chaos and the worst-case scenario; grind to a halt from underutilization of the staff and attrition rates. This article will attempt to clarify proper approaches and the importance of precise forecasting and scheduling.

Although operational costs vary from one Contact Center to another, staffing costs inevitably always accounts for the most significant expenditure in a Contact Center budget. Some Malaysian Contact Centers experience up to 70% of their budget allocated to staffing costs. Therefore, staffing is one resource that requires maximum utilization to realize a positive ROI.

Clearly if the contact centre manager can maximize the use of the people in the contact centre, the impact on the budget will be considerable.

The key to unlocking the mystery of forecasting and scheduling lies in precise call forecasting. It is crucial because it will enable you to determine precisely how many staffs you will need in the contact centre at any given point in time.

 Overstaffing your contact centre will translate into high costs resulting in underutilization of headcount. You will find staff sitting around surfing the net or reading magazines while waiting for the next customer contact to arrive in their respective call-masters. However, understaffing could be more detrimental to the overall health of your contact centre.

The outcomes could be long waiting times for customers with the repercussions of taking a drastic hit on your Customer Experience Index (CEI). Furthermore, loss of revenue if you are in a sales-driven operation. Most damaging of all, dissatisfied and overworked staff contribute to a high attrition rate.

Forecasts can be looked at in three durations; short-term (up to three months), medium-term (from three months to a year) and long-term (up to two years). If you run an established contact centre, you will need to forecast yearly for budget allocation. It is wise to generate periodic short-term forecasts throughout the year as the environment changes.

 Kevin Hook, in his book The Human Face of Call Centers, describes two elements to consider when generating periodic forecasts of call volume for your contact centre:

The total number of calls will arrive over a specific period (three months, a year etc.)

How on a monthly, weekly, daily and hourly basis you can identify trends in the pattern of contacts arriving

Your basis for periodic call volume forecasting is historical data. Assuming your contact centre has been in operation for some duration of time, any decent ACD will be able to provide you with the appropriate historical call volume data that you request.

Assuming we are looking at element two as explained above, an analysis of your historical call volume over the last year or two will yield findings of your calls arriving in patterns depending on the environment or situation. These patterns you will go on to discover repeats themselves;

• the hours between 9:00 a.m. and 11:00 a.m. receives a high call volume,
• Monday is a busy day
• December is a quiet month
• Festive seasons could see your contact centre assaulted with high or low call volumes.

 A high level of perceptiveness and acuteness to specific factors must be in place when analyzing the call volume data. Examples are:

• the knowledge of marketing running campaigns usually impacts call arrival
• the last week of the month where your organization mails billings out,

These trends can be identified and factored into your forecast as a percentage deviation from the average call volume for the month, week, day or hour. So, for example:

• Total annual calls forecasted: 84,000
• Average calls per month (84,000/12): 7,000
• Factor for December (-20%)
• Calls expected in December (7,000 – 20%) 5,600

Unless you can accurately forecast the total volume, all this isn't very meaningful.

There are several statistical techniques for forecasting which fall into two categories:

• Time-series forecasting
  Projects past patterns and trends into the future using rolling averages, and they work on the basis that established patterns will be repeated and are reasonably accurate for short term forecasting (most forecasting software packages for ACDs use some time-series analysis)
• Explanatory forecasting
  Techniques such as regression analysis seek to reveal the links between sets of variables to produce a forecast, e.g. establish the link between past changes in pricing structure and call volumes to predict the impact of future changes.

In a customer service environment, the number of contacts made correlates to the total number of customers. The more customers you have, the more calls you are likely to receive. Therefore it is possible to forecast contact volumes by establishing the historical relationship between the size of the customer base and the number of contacts received.

Updated in Dec 06, 2024.

In 2021, many contact centers were primarily relying on traditional forecasting methods and manual scheduling, which led to inefficiencies and an inability to adapt to sudden market changes. However, in 2024, there has been a significant shift towards AI-driven tools and data analytics, enabling contact centers to make more accurate predictions and optimize their workforce dynamically. Additionally, there's an increased focus on contact center training and customer experience training to enhance staff skills and improve service quality. These advancements not only improve call volume forecasting accuracy but also enhance overall operational efficiency, allowing centers to respond swiftly to fluctuations in customer demand while maintaining high service levels.

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