|By Karen Schwartz
Call Center Forecasting and Scheduling: A Science, Not an Art
It’s amazing how many contact centers are flying by the seat of their pants when it comes to staff assignment and workforce management. Sure, they probably know a little about the seasonal and daily peaks that affect their business and product, but they probably don’t know the more specific variables and details that would allow them to schedule more effectively and more profitably.
In general, the larger the contact center, the more likely they have invested in an automated resource forecasting and scheduling solution, often part of a larger workforce management system. Inversely, the smaller the contact center, the more likely it is that forecasting is done by simple spreadsheets supplemented with inconsistent intuition. There are many problems with spreadsheets and other non-automated approaches, including making sure all relevant data is included, performing predictive modeling and rudimentary analysis, recognizing trends and the difficulty in identifying demand fluctuations based on individual or grouped variables.
Good forecasting and scheduling directly contribute to improved customer satisfaction and call service representative job satisfaction – in addition to better labor cost allocations for the company. However, it’s difficult to schedule efficiency without good forecasting data, tools and IT automation. The accuracy of the forecast directly affects how effectively you staff your contact center, which in turn affects customer service levels.
Manual effort may have worked in a one or two channel world (say, phone and email), but it certainly doesn’t cut it in Contact Center 2.0 — a world where everything from social networking and chat to tweets and avatars may represent new and important channels for customers and call center agents.
Additional communication channels, along with product, territory or customer type specialization by CSRs, result in much more complexity to the forecasting and scheduling equation. For example, call center managers that have visibility to clearly see that chat is usually busy between 6:00 PM and 7:00 PM but Facebook fan page activity doesn’t pick up until after 9:00 PM, can project the staffing for those work loads into the resource scheduling. Therefore, it’s more critical than ever before that contact centers put an effective mechanism in place for capturing and forecasting the volume of each contact method by time period to ensure having the right mix of agents with the right skill sets for each shift.
It’s time, then, to put away those spreadsheets and other rudimentary attempts at forecasting and advance to a more sophisticated call center software automation tool that does what it takes. That includes the ability to forecast for specific events that can directly impact call volume, such as the launch of a new marketing campaign or a product recall. These call center software tools also should be able to handle historical trend analysis and the full panoply of agent skills that are used in various situations, along with the ability to schedule agents with various or multiple skills to different time slots.
Many go further; ISC’s Irene, for example, describes how its optimization engine adaptively learns the characteristics of a particular call center and helps organizations implement advanced forecasting and scheduling capabilities based on their own specific history and criteria. These tools are compelling in advancing call center capabilities.
So how to choose? First, decide whether you want an internally managed workforce management system, like Aspect eWorkforce Management, Genesys Workforce Management, ISC’s Irene, Rex Partners’ Smartrex, and Timera’s workforce management suite. Or maybe you want a system in the cloud—one that is managed and delivered via the Web in a software as a service (SaaS) model and is eminently scalable, but provides the same analysis and functionality. Examples include Monet Software’s WFM OnDemand and Contactual’s OnDemand Contact Center. Some, like ISC’s Irene, offer both choices.
After comparing and contrasting SaaS versus on-premise call center solutions, you can continue the traditional software selection process by creating a weighted requirements document, scoring RFP (Request For Proposal) receipts, objectively evaluating software demonstrations, checking customer references and vetting software vendors. Unlike the software selection process for a customer relationship management software system, which requires collaboration and consensus building among many diverse stakeholders such as sales and marketing divisions, the procurement cycle for call center workforce management solutions which excel at forecasting and scheduling can normally be completed in short order.
Categories: Call Centers
Tags: Scheduling, Forecasting, Workforce Management
Author: Karen Schwartz