Optimize Facility Management & Maintenance Scheduling for Optimal Results

Improve margins by 10-15% with an optimal workforce structure

Custom-fit decision support software solution that guides planners in making the best planning and scheduling decisions on strategic, tactical, or operational time horizons.

Improving the efficiency of facility management scheduling and equipment maintenance optimization activities through intelligent planning and scheduling optimization of tasks and employees.

Complete this form to learn more about how we can help you fully optimize your workforce scheduling procedures.
Trusted by companies around the world.
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tactical planning and preventive maintenance activities

Dynamic maintenance planning

Intelligently plan service activities over the next year so that service frequency targets are met. Improve efficiency by grouping or bundling services based on proximity and skillset requirements. Use advanced machine learning combined with historical data to predict future reactive service demand. Smooth workload over time to minimize the need for contractors or overtime.

Strategic and tactical workforce planning and optimization

Intelligently decide which teams or employee types should do what work, when and where. Satisfy demand at the least cost while respecting a variety of constraints and preferences, such as distributing the work smoothly over the planning period.
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● Operational task assignment and scheduling of employees

Operational task assignment and scheduling of employees

Create optimal daily plans, schedules and routes based on the tactical plan combined with the latest activity history and sensor data. Re-plan in response to last-minute events, like high-priority repair tickets or employee absences. Efficiently interleave planned and reactive work, for example by opportunistically pulling forward upcoming planned work when it’s more cost-effective.

Demand Prediction using Machine Learning (ML)

Create demand forecasts based on ML models built off of historical performance data and any other correlated signals, such as weather, sales data, etc.
● Demand Prediction using machine learning (ML)