Human Resources
Who should be assigned to which task, when, and where, in order to optimize efficiency while balancing workload and complying with business constraints? Between strict regulations, employee expectations, and fluctuating employer needs, workforce planning quickly becomes a complex puzzle. Atoptima’s decision-driven AI tools enable the design of robust, fair, and efficient schedules, while significantly reducing manual planning time.
-30%
Operational costs
Robust
Planning
÷5
Planning time
Challenges and Issues
- Complexity of multiple constraints: compatibility between skills, certifications, individual preferences, contractual obligations, and employer needs
- Workload volatility: variations due to seasonality, unforeseen events (absences, emergencies), and business uncertainties
- Equity and regulatory compliance: adherence to collective agreements, maximum working hours, and mandatory rest periods
- Organizational balance: ensuring fair workload distribution to foster employee satisfaction and retention
Use Cases Covered
- Automated schedule design: generation of timetables that comply with regulatory constraints, required skills, and individual preferences
- Robust workforce planning: dynamic adjustment to absences, emergencies, or activity peaks through flexible optimization models
- Team sizing: simulation and calculation of the optimal number of staff required based on forecasted workload and growth scenarios
- Multi-site and multi-team management: smart allocation of resources across sites, departments, or projects to maximize operational efficiency
- Customer service centers: optimal assignment of agents to time slots and channels (phone, chat, email)
- Healthcare and personal assistance: planning of nurses, home care workers, and shifts, ensuring service continuity and legal compliance
- Industry and retail: adjustment of schedules according to seasonality and peak seasons
Benefits
- Increased operational efficiency: reduced time and costs associated with manual planning
- Balanced workload: equitable distribution across teams, reducing the risk of overload or underutilization
- Optimized resource allocation: better matching of available skills with actual needs
- Regulatory compliance: adherence to labor laws, collective agreements, and internal policies
- Optimal team sizing: adaptation to workload variations and anticipation of future needs
- Systemic decision support: leveraging HR and operational data to guide strategic choices
- Robust solutions to disruptions: continuity of service despite unforeseen events (absences, emergencies, workload peaks)
