Accurately forecasting customer contact volumes is a critical activity for effective customer care operations. This enables your business to select adequate and to control your operating costs. Getting this wrong has the following consequences:
Over capacity: Agents are unoccupied, leading to unnecessary business expense and a risk of lower agent job satisfaction
Under capacity: Insufficient number of agents to meet customer demand, leading to unanswered calls and increased resolution times
2 Launching your operations
Before launching a new customer care operation, it is important to conduct capacity planning to forecast your required headcount. You should also forecast how this headcount will change overtime. This can be particularly challenging in new markets, where you do not have access to historical data on customer contact volumes.
Factors to consider while forecasting agent headcount include:
- Support volume projections
- Number of languages supported
- Number of channels supported (e.g. voice, email, chat)
- Hours of operation
- Customer support SLAs (e.g. time to first response)
- Agent productivity
The budgeting process for customer care operations relies on the availability of long term forecasts for customer contact volumes. These forecasts will be used to determine the number of agents required to meet your desired operational metrics.
The conversion from contact volume to headcount and further to budget, should take the following factors into consideration:
Average handle time – how long it takes to solve each type of customer contact
Productive hours – how many hours the agent is actively resolving customer issues
Price per hour – as determined by agent wages or contracts with vendors
It is worth including a buffer in your budget to cover additional planned and unplanned operational expenses. Remember to include specific amounts for any additional projects, pilots or experiments your team will conduct during the year, and any incentives you may have incorporated in contracts with your vendors (e.g. awards, events, conferences or competitions).
4 Budget forecasting and performance monitoring
Building a forecast model and using it to quantify staffing and budget requirements is a complex process. Where possible, you should identify a data analysis specialist within your organization to complete this analysis.
There are many different options available for forecasting resource requirements. The Erlang C formula has proven to be particularly popular within the customer care industry. This provides a tried and tested approach to calculate your resource requirements within a set time interval, accounting for a range of assumptions.
When building a forecast model, it is important to be aware of the compromises that must be made between the granularity of your forecast (e.g. by day, language or product) and its accuracy. As with any estimation technique, results are likely to hold on average, but not in extreme cases.
Once you have a forecast in place and your budget has been allocated, you should conduct frequent reviews to measure how you are performing against expectations. It is important to understand the source of any variances and take appropriate action (e.g. modify your operations to stay within budget or request additional budget).
5 Systems and tools
Many CRM systems include integrated forecasting capabilities. This should be taken into consideration when planning your workflow management system. This functionality simplifies analysis of customer contact volumes, allowing the identification of seasonal trends or the impact of changes to your products/services.
While these systems can produce forecasts based on historic trends, it is a good practice to be aware of upcoming changes within your business and to make the necessary adjustments to your customer care forecasts. As an example, a new product launch or major marketing campaign will increase customer activity and have a corresponding impact on your customer care volumes. It is important to establish effective lines of communication across your organization to ensure sufficient agents are available to respond to these changes and meet customer demand.