Smarter staff scheduling for Pelt's after-school child care program

Approach: data-driven capacity planning for out-of-school childcare

Analysis of occupancy rates and childcare capacity

To address this challenge, the project began with a thorough analysis of current operations. All relevant data was collected and analysed, including staff schedules, shift structures, childcare locations, clock-in and clock-out records, and historical child attendance data.

This data was used to map childcare demand in detail. Changes in the number of children present throughout the day were linked to the staffing levels required at each location and during each time slot. This provided an objective picture of actual capacity requirements and identified the periods when additional childcare staff were needed.

Mapping staff preferences and shift feasibility

Alongside the quantitative analysis, the project team also explored less visible factors that have a significant impact on staff planning. These included existing working practices, preferences and constraints, such as:

• Preferences for continuous shifts rather than split shifts
• The desire to work more or fewer hours
• The ability to combine childcare work with a second job
• Mobility constraints
• A preference for fixed locations to ensure continuity of care for children

These insights highlighted that childcare staff planning is not simply a mathematical problem, but is also strongly influenced by the practical feasibility of shifts and employee satisfaction.

Developing flexible shift types for childcare

Based on these insights, several alternative shift models were developed to better reflect actual childcare demand. Whereas the organisation had previously relied mainly on fixed shift types, the project created opportunities for more flexible staffing models.

For example, one childcare worker can open a location, with additional colleagues joining as the number of children present increases. This allows staffing levels to be aligned more closely with actual demand without compromising the quality of care.

Optimisation model for efficient childcare staffing

The main challenge lay in the large number of possible combinations of staff members, locations and shift types. To make this complexity manageable, a mathematical optimisation model was developed.

The model automatically calculates the most suitable staffing allocation to meet childcare demand, taking into account:

• Legal requirements and staff-to-child ratios

• Staff preferences and shift feasibility

• Operational requirements at each location

• Cost efficiency and occupancy rates

This helps prevent understaffing while keeping overstaffing to a minimum.

Simulation model for future childcare policy scenarios

In addition to optimisation, a simulation model was developed to assess different future scenarios. This enables the organisation to evaluate the impact of policy decisions and external changes in advance.

Scenarios include:

• Changes in childcare regulations and staffing standards

• An increase in the number of children attending out-of-school childcare

• The opening of additional childcare locations

• Children with additional support needs

• New shift structures or staffing configurations

Web application for scenario analysis and staff planning

The results of these analyses were integrated into a user-friendly web application. This enables the organisation to independently simulate and compare scenarios and make well-informed, data-driven decisions.

Results: future-proof and efficient childcare staff planning

• Greater insight into capacity, occupancy and staffing needs. The project provides a solid foundation for sustainable staff planning in out-of-school childcare. For the first time, the organisation has a transparent overview of the relationship between childcare demand, staffing levels and operational efficiency.

• A better balance between work schedules and employee needs. The new approach makes it possible to align schedules more closely with operational realities and staff preferences. This improves shift feasibility and supports a better balance between workload and flexibility.

• Evidence-based policy decisions through scenario simulation. The scenarios developed allow policy options to be modelled and assessed in concrete terms. Their impact on workload, childcare capacity, staff retention and cost efficiency becomes visible before decisions are made.

• A future-proof approach to out-of-school childcare. By combining optimisation, simulation and data analysis, the policy team now has a powerful tool to proactively address future challenges. This lays the foundation for a future-proof out-of-school childcare system in Pelt, better equipped to deal with staff shortages and changing regulations.