Introduction

What Is Workforce Management (WFM)

Workforce Management (WFM) is a critically important function which touches many aspects of a business. In the call center environment, WFM encompasses four key processes:

1. Forecasting the volume of customer contacts, average handle time, resource shrinkage and occupancy
2. Scheduling agents based on forecasts to meet your service level requirements
3. Real Time Performance Management and their impact to Forecasting & Scheduling, such as adherence to schedules
4. Business Intelligence: Reporting, auditing and maintaining data integrity

WFM is connected to all other arms of the operations. Workforce Optimization, or WFO, is the unified approach of integrating the activities associated with WFM with other elements such as Quality Monitoring, Satisfaction Surveys, Training and CAE Scorecarding. WFO blends WFM functionality with logical linkage to quality, training and KPI Scorecards to create a comprehensive approach to maximizing quality and business efficiencies.

This website seeks to establish a facilitate collaboration to support continuous improvement in operating a World Class Forecasting Organization. In such, we set out to establish a set of core goals, and define the approach, process and definitions associated with each of the four processes listed above. All goals are build on a focus of continuous improvement in the areas of business efficiencies and quality of experience

World Class Forecasting Organization

A "World Class Forecasting Model" is designed on the principles which can be examined by 4 dimensions. Each dimension serves as a check-point to ensure that a members participating in the forecasting process are working toward a set of common goals. These goals require continual adjustment to recognize sustained forecasting accuracy, while also striving for continual improvement.

Functional Integration

The Functional Integration dimension is critical to effective management of the forecasting process. The Functional Integration dimension includes 3 themes:

1. Forecasting "C3": Communications, Coordination and Collaboration
   • Communication - Effectiveness between functional business areas (CS, Sales, Techops, Marketing, Finance)
   • Coordination - Extent to which formal processes are in place that provides structure to sharing information between functional units
   • Collaboration – Common goal orientation among functional areas for forecasting excellence

1. Structural Organization: Around The Forecasting Function, Supported By C3
2. Accountability For Contribution To the Forecasting Process

Approach

The Approach dimension addresses what specifically is forecast, and how it is forecast. The Approach dimension includes 7 themes:

1. Orientation: Bottom-Up, Top-Down, Both w/ Reconciliation
2. Historical Demand Approach: Level of detail behind past demand (capturing just calls answered, or integrating IVR, ABA, etc)
3. Product/Customer Differentiation: Extent to differentiate between more/less important products/customers in forecasting process
4. Forecasting Hierarchy: Users at all levels all input and extract at appropriate levels.
5. Technique Sophistication: Degree to taking full advantage of statistical tools, fully integrated with time series and judgmental data
6. Forecasting-Planning Relationship: Business plan and forecast intertwined, rather than one driving the other
7. Level of Training and Documentation of the forecasting process

Systems

The System dimension covers computer hardware and software that support the forecasting process. The Systems dimension includes 5 themes:

1. Integration: Degree to which Forecasting Software is Integrated With Other Corporate Systems
2. Reporting: Level of sophistication behind report-generation systems, ability to generate ad-hoc, or routine reports, both real-time & historical
3. Historical Data Maintained: Existence of advanced data warehouse systems which allow forecast to be updated in real time
4. Performance Measures Handled: Performance measures integrated tightly into systems with easy access and highly visible in reporting
5. Infrastructure Investment: Degree to which investment has been made to infrastructure which allows timely and continuous upgrades and enhancements of forecasting functionality

Performance-measurement

The Performance Measurement dimension is defined as 2 areas:

1. The metrics used to measure our forecasting effectiveness:

• Impact on Profitability
• Customer Service Quality
• Competitive Strategy

2. How our forecast performance information is gathered and utilized:

• Degree to which incorrect forecasts are measured through "forecasting error", versus the inability of other business functions to deliver volume when expected
• Ability to utilize that data to plug into future forecast models (capturing both Judgmental and Planned Events and blending into Time-Series data)

Data Governance & WFM

Workforce Management is an extremely data intensive business function. To successfully build and execute a World Class Forecasting model, our core data definitions contained within the software application must be established with consistent use and adoption by the WFM teams utilizing the application. The WFM application will also require interfacing with a standardized ACD Skill and AUX definition and naming convention, as well as a standardized interface for managing employee data and employee hierarchies.

To maintain data integrity across the WFM model, the adoption and implementation of a Data Governance function is recommended. This function would document, control and implement changes needed to meet business requirements while maintaining consistency in the method and process in which data changes are executed. Through the Data Governance function, the model seeks to maintain the data generated through the WFM application as a single authoritative source relating to all activities associated with the functions of workforce management.

The introduction of a Data Governance function is a fundamental shift in the current decentralized methodology used for managing change in the data architecture. With the ability for small changes in Agent Skills to have a significant impact on multiple systems, including the forecasting and scheduling functions, a Data Governance function is critical to the Forecasting model.