Enhancing WFM Tools: Bridging the Gap in Forecasting and Capacity Planning

Over the years, I've come to appreciate the constant innovation and new features that workforce management (WFM) vendors have introduced. However, one area that hasn't quite hit the mark for frequent usage by WFM teams is the forecasting and capacity planning tools. Here’s why these features might not be as successful as others within the software.

Firstly, forecasting is predominantly based on time series methodologies. While multiple time series forecasting models are a solid choice for businesses with stable trends and predictable seasonality, they fall short in two major areas. Companies with unpredictable trends or uncertain market sizes find these models less beneficial. Additionally, most WFM teams are keen on identifying key drivers influencing transactional volumes, but the tools lack features that aid in discovering these drivers and incorporating correlated values into forecasts. This limitation makes the forecasting tools less practical for a forecaster, leading to their underutilization.

Moreover, the capacity planning tools do not offer a feature that allows WFM teams to create and maintain a database tracking employee movement. A primary function of capacity planning is to constantly understand the exact number of available employees for each contact center’s line of business and communication channels. Without support from the tool, capacity planners are forced to rely on manual inputs or develop in-house databases to track employee movements such as hiring, attrition, promotions, and transfers. 

Additionally, most tools do a poor job of translating capacity into financial projections for compensation planning. The lack of customization and flexibility in the tools fails to accommodate the complexities of compensation planning, such as differentiating between accruals and cash flow, overtime rules, leave policies, holiday pay, geographic compensation variances, and projected benefits usage.

Lastly, the accuracy of output metrics such as service level, average speed of answer, and abandonment rate is inconsistent. While the tools may perform adequately for simple operations where associates work within a single line of business and communication channel, they struggle to deliver accurate forecasts when complexity increases, such as when associates are spread across multiple lines of business and communication channels.

While WFM tools are undeniably beneficial for workforce management teams, they would significantly gain from enhancing their forecasting and capacity planning features. Incorporating more robust data engineering and analytics, improving customization for compensation planning, and expanding functionality to track and analyze employee movement would make these tools not only more comprehensive but also more indispensable to WFM teams.