This stage sees the development of a model which aims to project demand and supply across the futures described by the scenarios.
There are three stages:
- Data and assumptions: This is where we input our data. There are four kinds of input we use:
- Baseline data: this includes facts we know such as current training and workforce numbers.
- Assumptions: predictable trends and assumptions where key data is not available or of poor quality.
- Parameters we can control: related to the policy choices which will secure adequate supply to meet demand.
- Intrinsically uncertain parameters: these may vary by scenario generated in the Delphi process.
- Policy levers: Policy levers are the parameters that decision makers can control to ensure that workforce supply meets future requirements, for example yearly student intake, length of training, numbers entering employment after training. A critical part of workforce modelling is defining what policy levers can be varied, and in what combination, and testing them against scenarios to see the effects on supply and demand.
- Demand and supply model: We use an award-winning system dynamics modelling methodology to calculate workforce demand and supply.
A core element of the framework is the use of system dynamics (SD) modelling to calculate workforce demand and supply. The models constructed by the CfWI vary greatly in size and complexity. The medical model developed for the medical and dental student intakes project (MDSI) contains 15 separate influence diagrams, has 997 distinct variables and is initialised with 903,525 items of data. Other models, for example dentistry, pharmacy, psychiatry and acute medicine, are of similar complexity. This places them firmly in the category of industrial-scale models, and thus there is a clear need to use a formalised, software engineering approach.
Since the development of the first SD workforce model, we have gained considerable practical experience. Decision Analysis Services Ltd (DAS) has worked with the CfWI to formalise and document our approach. They provide technical consultancy to support the analysis of strategic challenges facing government and industry decision-makers using systems modelling and simulation methods.The benefits of this include models that are better designed, easier to use, more focussed, and more efficient. Applying a rigorous formal approach also results in increased stakeholder confidence in model outputs.
The approach is composed of four steps: model scoping, model construction, model documentation and model testing. Each step is described in detail and is supported by best practice guidance. The CfWI’s approach collates best practices from the many excellent references addressing SD model development and is informed by practitioner experience at the CfWI. Our approach provides the following:
- There is a clear description of how the SD modelling fits within the wider robust workforce modelling framework.
- Detailed guidance on SD modelling best practices is provided, along with examples drawn from our tested workforce models and checklists covering model scoping and testing.
- Workforce SD models are typically data-intensive, so particular attention is given to the critical activities of data gathering, loading, and testing.