COMPUTD and Callosseum Present Advanced Workforce Scheduling at CCW 2026 Berlin 

 

February 23th to 26th 2026

At CCW 2026 in Berlin, one of Europe’s leading events for contact center technology and workforce management, COMPUTD and Callosseum jointly presented APOLLO Scheduler, an advanced workforce scheduling solution designed for the operational complexity of modern BPO and contact center environments. 

The event brought together industry leaders, contact center operators, and technology providers to explore the future of customer operations, workforce optimization, and AI-driven systems. 

For COMPUTD, the event provided an opportunity to demonstrate how advanced optimization engineering can address structural challenges in workforce scheduling. 

Addressing Structural Limitations in Workforce Management 

 

Many contact centers rely on traditional workforce management (WFM) systems to generate schedules. In practice, however, these schedules often require extensive manual correction before they become operational. 

Planners frequently adjust schedules using overrides, spreadsheets, and additional calculations. As a result, many organizations effectively operate with two scheduling layers: the schedule generated by the system and the adjustments made by planners.   

This situation is not caused by planning discipline but by the design of traditional scheduling engines. Most WFM systems apply constraints sequentially, optimizing service levels first and adding contracts, preferences, and fairness rules later. Each step weakens the previous one, creating conflicts that planners must resolve manually.   

Engineering APOLLO Scheduler 

 

To address these structural limitations, COMPUTD and Callosseum engineered APOLLO Scheduler, a dedicated workforce scheduling engine for complex contact center and BPO environments. 

The system converts operational inputs into a single integrated optimization model, including: 

  • demand forecasts 
  • service level requirements 
  • agent skills and availability 
  • labor contracts and rules 
  • employee preferences 

Using this model, APOLLO Scheduler automatically generates complete agent-level schedules that balance service levels, operational efficiency, and workforce fairness.   

The scheduling engine is built on integrated integer linear programming, enabling all operational constraints to be optimized simultaneously rather than sequentially.   

Built for Operational Reality

 

APOLLO Scheduler was designed specifically for complex operational environments such as multi-client BPO portfolios and multi-skill contact centers. 

Unlike traditional schedulers, the system optimizes schedules under real-world operational constraints including labor rules, skills coverage, agent availability, and employee preferences.   

The platform can operate as a standalone scheduling application or alongside existing workforce management systems, allowing organizations to extend their scheduling capabilities without replacing their current WFM infrastructure.   

CCW Berlin as a Platform for Industry Dialogue 

 

During CCW 2026, discussions with contact center leaders focused on the growing complexity of workforce scheduling. 

Increasing operational scale, fluctuating demand, and evolving workforce expectations are pushing traditional workforce management systems beyond their design limits. This is creating demand for advanced optimization models that can manage operational constraints simultaneously. 

The collaboration between COMPUTD and Callosseum combines AI product engineering expertise with operational BPO experience, enabling the development of scheduling systems designed for modern contact center environments. 

About APOLLO Scheduler 

 

APOLLO Scheduler is an advanced workforce scheduling engine developed by Callosseum and COMPUTD. The platform converts forecasts, service levels, contracts, skills, and employee preferences into a unified optimization model that generates operational schedules for contact centers and BPO operations.   

Learn more at 

www.apolloscheduler.ai

Team members on this event

Samantha Merlivat

Business Development

Pieter Schaap

Managing Partner

Marcel Schün

Partner

Marcell Ignéczi

Managing Partner

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