Forecasting in WFM

Tue May 21, 2024

The basis of any staffing plan is to workload forecast. Without a good forecast of the work to be expected, the most sophisticated effort to calculate staff numbers and create schedule plans is wasted effort. Good accurate forecast is the most important step of the process.

WFM analyzes call volume and average handling time (AHT) in order to predict future trends. This data enables WFM to build accurate forecasts for the anticipated workload, and to calculate the staffing required to meet that workload

The purpose of the forecast is to predict workload so that we can get the right number of staff in place to handle it. And there are many different situations in the call center environment that require a forecast to be done. The most common scenario for which we forecast is simply normal, day-to-day operations. But you may also require a forecast for special situations such as planning for new call type(s), opening a new center, a merger or acquisition, or a change in operating hours. Or you may be implementing a new technology that will affect your call volume or pattern and need to determine what the resulting change means to staff workload. Whatever the reason, its important to understand the basic principles behind workload forecasting and how to apply them to accurately plan call center resources.

Setting Service Objectives or Parameters for Forecasting

With WFM forecasting, you can set specific service objectives. You can also adjust these objectives and then rebuild the forecast, which provides a detailed “what-if” analysis of the potential impact of staffing or service-objective changes. WFM forecasting uses parameters to see the difference such as:

• Call volume
• Average handle time (AHT)
• Average speed of answer (ASA)
• Desired percentage of calls handled within a target time (service level)
• Occupancy
• Maximum percentage of abandoned calls

Steps involved in Forecasting

Step 1: Gathering the Data

Step 2: Predicting Monthly Calls

Step 3: Creating Daily and Half-Hourly Forecasts

Step 4: Adjusting for Other Business Influences

Step 1: Gathering the Data

The first step in the forecasting process is gathering historical data. past history is the best indicator of the future in most call centers, so gathering this history is the first task. The most obvious source of this information will be historical reports from the ACD — specifically the number of calls offered and handle time information by half hour.

Another critical step of the data gathering process is to eyeball your information to make sure there are no data aberrations. You will want to look for any abnormally low or high call numbers as well as missing information. When you identify something out of the ordinary, you should first determine the reason for high or low call volume, and then decide if it needs to be adjusted or not.

if it is a one-time incident, or an event that might occur again but you can not predict when (like a storm), you want to normalize the numbers up or down to reflect realistic volumes. On the other hand, if it is a repeatable, predictable event, these numbers need to stay in the data so that the forecast reflects the event in the future. (Hint: It is important to note in the data why each aberration occurred so you will remember it for future planning purposes!)

Step 2: Predicting Monthly Calls

The next step in the process takes us from raw data to a prediction of what is coming for a future month. There are several approaches to get us to this future forecast:

Point Estimate. This is the simplest approach and assumes that any point in the future will match the corresponding point in the past. (i.e., the first Monday in April next year will be the same as the first Monday in April of this year). This approach has obvious shortcomings in that it does not account for any upward or downward trends in calling patterns.

Averaging Approaches. There are a variety of methods that incorporate simple mathematical averaging, ranging from a simple average of several past numbers, to a moving average where older data is dropped out when new numbers are available. The most accurate averaging approach involves weighted averaging, where more recent events are given more weight or significance than older events. So if the call volumes on the first Monday of April for the past three years have been 2400, 2500, and 2600 calls: the simple average would be 2500 calls, the moving average might be 2550 calls (dropping out the oldest data). In a weighted average approach we might assign an 80% weight to the most recent number, with only a 10% weight assigned to each of the prior years giving us a prediction of 2570. But while the weighted average approach is probably the closest to what an actual forecast would be, it still misses the upward trend in the data that simply can not be identified and incorporated by averaging together old numbers.

Time Series. The recommended approach for call center forecasting involves a process called time series analysis. This approach takes historical information and allows the isolation of the effects of trend (the rate of change) as well as seasonal or monthly differences. It is the approach used in most call centers and serves as the basis for most of the automated workforce management forecasting models. The basic assumption is that call volume is influenced by a variety of factors over time and that each of the factors can be isolated and used to predict the future.

The first step in a time series approach is to isolate the effect of trend. Trend is basically just the rate of change in the calls. While that trend can be upward or downward, in most call centers, trend simply means the growth rate. It is important to determine this rate as an annual trend rate as well as a month-to-month change.

Once the trend rate has been determined, the next factor to isolate is the effect of seasonality or month-to-month variances. This process is fairly tricky, since you cant really determine monthly or seasonal factors just by looking at the most recent twelve months of data.

Step 3: Creating Daily and Half-Hourly Forecasts

Once monthly forecasts are in place, the next step involves breaking down the monthly forecast into a daily prediction, then further down into an hourly or half-hourly numbers.

To predict daily workload, you must first calculate day-of-week factors. Most call centers have a busier day on Monday than other days of week and it is important to know what percentage of the weeks workload this day and others represent.

The good news is that it is not necessary to go back and analyze two years worth of information to determine these factors. Typically evaluating the last few weeks worth of daily call volume data is sufficient to identify daily patterns. Just select several clear weeks of data (those without holidays or other major events that might skew the proportions) and see what the total Monday volume is compared to the weekly total. Then repeat for the other days of week. These percentages reflect your day-of-week patterns.

Once the daily forecast is in place, its time to repeat the process for time-of-day patterns. It would be nice and easy to schedule staff if the calls came in evenly throughout the day, but since that’s not reality, its critical to know when the peaks, valleys, and average times are. Again, gather several clear weeks of data and evaluate the Mondays to look at how each half-hour of the day compares to the daily total to create your Monday half-hourly patterns. Then repeat for the other days of the week.

Step 4: Adjusting for Other Business Influences

The final step in the forecasting process is an important one. There are many factors that influence the call centers workload and the smart workforce planner will have a process in place that considers all the these factors in the forecasting process.

Think about all the different areas of your organization that influence the calls you receive. The most obvious one is the marketing department who has tremendous impact of your work based on the sales and marketing promotions they do. Hopefully you have a formal communications process in place to hear about marketing plans well ahead of the actual event so they can be built into the forecasting assumptions.

Make sure you consider all the other pertinent areas as well. Will the billing departments new invoice format cause a flood of calls? How about sales forecasts from the Sales teams that can help you plan staff 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 is critical that you communicate regularly with all these influencers of call center workload as you prepare and fine-tune the forecast.

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