A forecast in customer support: How to tackle the Herculean task

For better readability, the generic masculine is used in these articles. The designations of persons used in these articles refer to all genders unless otherwise indicated.


A forecast in customer support: How to tackle the Herculean task


Delivering accurate forecasts of the workload in customer support can quickly become a Herculean task. If the actual workload is lower than expected in the forecast, the assigned employees are not being used to capacity. If the forecast is too low, the customer support unit is understaffed. In both cases, this has a negative impact on the key figures by which the success of the customer support is measured. How can an efficient use of staff be made possible and frustrated customers due to long waiting times be avoided? What is the best way to invest the available time and find the balance between data analysis and gut feeling?

What measures do we recommend?

If you want to implement or optimise a forecasting process, the forecast for the coming year on a monthly basis is an optimal starting point. The earlier you start this process, the better. We recommend that you start planning for the following year in the middle of the year. First obtain historical data (ideally for the last 36 months), for example by exporting data of the ACD or ticketing systems used. The basis of the forecast is the estimated workload, which is made up of the contact volume and the average processing time. The data should be analysed per communication channel and contact reason, depending on the question.

With the forecast on a monthly basis, it is primarily a matter of obtaining an overview and recognising fundamental dynamics (e.g. booking/holiday periods for the travel industry or weather conditions for gardening tools). Unexpected factors such as a website outage, a high sickness rate or an error in the billing process, on the other hand, should be considered a one-off incident and excluded from the future forecast process. Also take into account the specifics of the coming year: for example, is there an important event coming up, such as the World Cup, with a planned marketing campaign? With the help of the forecast, the personnel requirements for the coming year can be derived.

In addition to historical data, you should also include knowledge about the future based on organisational framework conditions or strategic objectives, for example, the sales volume planned by the sales unit in your organisation. Calculate the average ratio of sales to contacts. For example, if you know that a sale “causes” an average of 3.2 contacts, you can derive future contact volume based on sales growth rates. Here, too, it is worth thinking a step further: for example, is the complexity of the products sold changing? Are there new processes that will avoid certain enquiries in the future or automate processes?

For a meaningful picture of the future, you should always consider and weigh other influencing factors that affect contact volume and processing times, in addition to historical data and the planned sales volume. It is advisable to create a comprehensive checklist with internal influencing factors such as current marketing campaigns, the time of the invoice dispatch, the introduction of a new product or a new self-service tool for the customer and external influencing factors such as new regulations, the economic situation or simply the weather. We recommend taking an active role and encouraging exchange with other departments to identify possible influencing factors early on and assess their impact on the volume of work.

See the forecast as part of a holistic planning and control cycle, which is continuously refined based on the current analysis data and new framework conditions and also delivers new results in the short term. Continue the annual forecast as a continuous forecast. The monthly comparison of the expected with the actual volume provides new insights, which in turn are relevant for the next forecast.

What are the benefits of a continuous and data-based forecast?

The forecast process pursues three target dimensions: Cost efficiency, staff satisfaction and customer satisfaction. In staffing planning, the main goal is to find a balance between understaffing and overstaffing. A number-based and transparent forecast also supports you in demanding the resources you need. Prepare your team for potential influencing factors and new reasons for contact so that customers perceive the contact as purposeful. Make sure that the effort and benefit of the data analysis are always in proportion and trust your experience and intuition so that you do not lose sight of the goal.

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Gender reference

For better readability, the generic masculine is used in these articles. The designations of persons used in these articles refer to all genders unless otherwise indicated.