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Resource Allocation Forecasting & Optimization

C = {z = x + iy x, y ∈ IR} 2x + 2y + z + 4t = 0 z = −1 + i nα = θ + 2πk −x + 2y + z + t = −1 a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) nα = θ + 2πk

Resource Allocation Forecasting & Optimization

Workforce Scheduler

Managing staff allocation to specific tasks can be complex. Determining factors include: different levels of staff experience, different numbers of jobs that can be filled, the complexity of the tasks to be performed (often involving complicated predefined sequences), volatile and uncertain demand, and finally, specific contractual and operational constraints.

C = {z = x + iy x, y ∈ IR} 2x + 2y + z + 4t = 0 z = −1 + i nα = θ + 2πk −x + 2y + z + t = −1 a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) nα = θ + 2πk

Our Workforce Scheduler solution, thanks to a configurable algorithm, offers the possibility to analyze different scenarios in order to find the one that best resolves the trade-off between cost and service level for scheduling staff hours.
Starting from the data, our solution allows for the estimation of the volume of activities to be satisfied in a given period, as well as to plan the shifts of resources needed to ensure a quality service, while respecting all the allocation constraints.

Improved work life balance

Thanks to a better design of working hours according to the needs of each employee

Lower costs

A more balanced and accurate schedule avoids the cost of hiring unnecessary extra staff

Increased productivity

More efficient time scheduling allows for better work with a clear impact on the quality of the final products and services

Examples

Sectors

Application examples of Workforce Scheduler

Industrial

Defining the allocation of factory workers to maximize productivity

Healthcare

Establishing healthcare workers schedule that minimizes total costs

Services

Determining warehouse staff timetable that reduces time to ship goods

Would you like to know more about this applied solution?

Watch the tutorial

Deepening

Operating logic

Our solution includes a first configuration phase of the scenario, where the lists of personnel and requirements (skills and competencies, team composition, contractual and regulatory requirements, availability, costs, etc.) are provided.
Subsequently, a simulation of the service requirements is carried out based on the customer's request, approximating how many employees will be needed at any given time.

Method