Transform your business with a compelling call center, serving as a bridge between customers and your company. Every business needs to know the accurate call volume and efficient customer interaction, which is only possible through an effective call center. For the accurate requirement of resources in the organization, the future supply and demand of resources improve the organization’s performance. In the modern world, businesses must prioritize customer satisfaction above all else.
Call center forecasting aims to uphold quality service and efficient handling of customer queries by analyzing past data. This process enhances effective decision-making and aids in planning for future needs.
Analyzing historical data and allocating current data can help configure accurate future call volume predictions. Managing overstaffing or understaffing, decision-making, and workforce management will aid in handling customer inquiries effectively, allocating resources efficiently, and strategically managing future demands.
Let’s have a look at what call center forecasting is,
What is Call Center Forecasting?
Call center forecasting is the method used to predict and plan future call volumes based on historical data coming into the call center via voice calls, emails, SMS, or other customer interaction through various channels over a given period. Effective call centers enhance customer satisfaction and operational efficiency and optimize resources such as staffing and technology to provide adequate customer service.
The call center is vital as a gatekeeper in handling customer queries and resolving issues.
It enables the analysis of historical data such as customer call records, engagement, and interactions across various communication channels. This analysis maintains future demand, enhancing overall performance by aligning services and products with forecasted data. Contact center forecasting mainly aims to plan for future resources through historical data analysis.
What is Call Center Forecasting Used For?
Contact center forecasting enables organizations to achieve customer demand, allocate resources efficiently, and enhance overall operating efficiency.
Well-planned and accurate staffing maintains high customer satisfaction and reduces unnecessary costs, providing timely assistance so customers can efficiently meet their requirements. In modern business, call center forecasting methods provide well-planned and accurate staffing, enhance customer satisfaction, reduce unnecessary costs, and provide timely assistance.
Accurate forecasting can enhance the organization’s performance by creating agent schedules or improving KPIs like average response or wait times.
Here are some essential uses:
Contact center forecasting identifies the staffing needs and enables the control of overstaffing or understaffing, resource allocation, and accurate supply and demand resources in the organization, which helps determine the optimal staffing and required resources.
Accurate forecasting aligns staffing levels, operational resources, and budget planning with predicted customer demand, enabling organizations to operate cost-effectively.
Performance monitoring is a critical aspect of call center forecasting, which involves tracking and analyzing the agent’s performance, required resources, and overall operational performance to improve business effectively and make sure the customer experience is up to the mark as well as overall call center success
Planning and decision-making
Call center forecasting evaluates future demand patterns and prepares for changes in customer behavior and market dynamics. Call center forecasting predicts the future call volume, which improves and identifies future planning and decision-making.
Call center forecasting creates a platform for the organization to function effectively. It aids in operating efficiently, reducing costs, planning resources effectively, providing quality customer service, and making informed strategic decisions.
Benefits of Call Center Forecasting
Optimizing staffing levels, resource allocation, and overall operational efficiency improves customer satisfaction and exceptions, so accurate forecasting allows the organization to upgrade its performance and handling correctly.
Here are some benefits of contact center forecasting,
- Enhanced staffing levels:
Call center forecasting enhanced staffing levels by evaluating the accurate skilled workforce in the assigned task to handle the task effectively. So, accurate forecasting allows the right agent to do the right task.
- Resource planning: Call center forecasting provides accurate results to handle calls effectively and plan for appropriate infrastructure, technology, and other resources needed to function with the call volume coming shortly.
- Customer satisfaction: Contact center forecasting involves analyzing data from past customer interactions. This forecasting process is crucial for addressing issues of overstaffing and understaffing, ultimately preventing agent burnout. This proactive approach minimizes customer wait times, leading to happier customers and enhanced customer satisfaction.
- Cost efficiency: Contact forecasting provides accurate data that helps minimize costs and anticipate future resource supply and demand. This proactive approach prevents unnecessary staffing, ultimately leading to a reduction in labor costs.
- Improve service quality: Contact center forecasting enables quality service to customers by reaching their needs and managing agents with their strengths. Happy customers are the organization’s assets, which helps to run the call center smoothly, so the company should manage the right agent in the right place, which improves the quality of services.
- Proper workforce management (WFM): call center forecasting helps maintain the workforce with the right plans and information, enhancing the organization’s performance and elevating it to the top level. Appropriate management of the organization’s workforce improves the management quality, achievable through effective forecasting.
- Ability to adopt changes: The dynamic nature of the call center allows it to adopt changes, which is a valuable asset to the call center for long-term success. Moreover, the adaptable nature of call centers allows them to scale operations up or down quickly according to demand.
Call center forecasting primarily aims to optimize productivity and assign the actual number of agents to handle the contact volume. Some appropriate methods for optimizing call center forecasting depend on factors such as call center size, data availability, historical data quality, budget, and desired level of accuracy.
How Do You Calculate Forecast Accuracy in a Call Center?
Call centers employ various methods to create accurate forecasts for specific reasons. For instance, short-term forecasting requires different methods compared to long-term forecasting.
To calculate forecasted accuracy in a call center,
Step 1: Subtract the actual number of calls by the forecasted calls offered within a given period
Step 2: Divide the difference by the number of actual calls
Step 3: Then multiply the answer by 100 to get your percentage
Suppose you have a business named XYZ. During a specific period, you received 500 calls, while you had forecasted 400 calls for that period. Let’s put those numbers into a formula like this:
((500 actual calls – 400 forecasted calls= 100)/ 500 actual calls = 0.2)*100= 20%
So, there was a 20% difference between what was forecasted and what actually happened.
Three commonly used methods for call center forecasting are:
Triple exponential smoothing
Triple exponential smoothing, also known as the Holt-winter technique, has been widely applied to forecasting tools within the workforce management system since the 1960s. Components of triple exponential smoothing are Level, Trend, and Seasonality. This forecasting technique is more accurate for evaluating short-term trends and seasonality than other methods.
Multiple temporal aggregations
MTA (Multi-temporal Aggregation) is a method to combine hourly, daily, and weekly data with long-term trends to calculate forecasting/scheduling looking further ahead.
Auto-regressive integrated moving average (ARIMA):
ARIMA includes three components: auto regression, integrated, and moving average, where these components can compare data with past patterns and current observations and smooth out data over several past periods.
Best practices for Call Center Forecasting and Scheduling
Call center forecasting and scheduling involve practices of handling the workforce effectively. One of the most common patterns is historical data analysis, which involves analyzing past call patterns, seasonal trends, and historical call volumes to forecast future demands.
To get optimal results and achieve effective workforce forecasting and scheduling in call centers, organizations should adopt the right approach to land on getting optimal results.
Here are best practices for contact center forecasting and scheduling,
- Schedule the right staff:
Call centers should assign experienced agents during busy call hours to get the most accurate result according to their strengths, which supports getting happy customers.
- Time-series forecasting:
Time-series forecasting techniques support projecting future call volume according to past data, which relies on mathematical models.
- Workload distribution:
Categorizing call types into different groups can enhance the call center efficiency. Workload distribution is crucial, which promotes a healthy work environment.
- Implement workforce management software:
The contact center should implement effective workforce management software to improve operational efficiency and customer satisfaction.
- Historical data analysis:
Analyzing past data is one of the most common methods that involve past call patterns, seasonal trends, and call volumes to forecast future demands.
- Plan a schedule for your needs (short/long term): Monitor the current workload and plan a schedule according to the short-term and long-term needs. Proper planning and accurate resource allocation can improve the quality of services and maintain a healthy customer base.
- Machine learning algorithms
With advanced AI and machine learning technology, call centers can improve scalability and adopt predictive models to forecast call volume. AI-based call center forecasting software helps to predict more accurately than traditional forecasting software.
There could be frequent changes in staffing plans, so the organization should be ready to be competitive in the market and meet clients’ demands.
Call center and scheduling ensure efficient operations, flexibility, and resource management, delivering exceptional customer experience. Customer service solutions offer the best platform to maintain customer service operations effectively.
Call center is an act that involves planning and predicting future call volumes and customer interactions based on historical data analysis.
Optimizing the organization’s call center forecasting and scheduling leads to greater customer focus and responsiveness. Call center forecasting is essential for maintaining the quality of services, enhancing customer experiences, and addressing issues such as agent burnout and customer wait times.
Thus, call center Forecasting is the ongoing process of resolving potential threads in the organization. This enhances the accurate identification of resource needs in the organization.
How do you create a call forecast?
To create a call forecast, you should track historical data and utilize it to identify trends and patterns. Finally, use the result to create a forecast for upcoming customer interaction. Regularly review the data to make sure whether the forecast meets the accuracy and is up to date.
How do you forecast service levels in a call center?
A call center’s service level forecast involves predicting the percentage of calls that will be answered within a set period of time, such as 60% of calls answered within 1 minute.
What are the different types of forecasting in a call center?
Various types of forecasting are employed to predict the call volume and demand in a call center. Here are different types of forecasting commonly used in call centers:
- Call volume forecasting
- Workforce forecasting
- Average Handling Time(AHT) forecasting
- Service level forecasting
- Historical data analysis
- Trend analysis
- Seasonal forecasting
What is SLA in a call center?
A server-level agreement(SLA) is a set of instructions that outline the customer service standards that support agents must fulfill during customer interactions.