Our client is a world leading research university, comprising multiple faculties and schools, and offering a range of course work and research degrees.
The client required a 40-year strategic planning model that enabled senior stakeholders to conduct high level strategic forecasting. The project included an integrated suite of modular detailed planning models allowing for ownership of the forecast at faculty and department level whilst remaining consistent with the overall strategic plan.
The key requirements of the model included:
- Driver Based Approach – The analysis and construction of detailed driver trees of the university’s operations in order to visualise how key variables interact.
- Data and Modular Design – The development of structurally consistent models and calculations enables efficient consolidation of faculty and department financials, and the ability to switch on/off faculty and department models and strategic initiatives.
- Scenario Handler – The ability to run scenarios, apply shocks, and to capture and compare various configurations of these shocks and scenarios through automated sequencing provides a very powerful tool for what-if analysis.
- Outputs and Dashboards – A suite of dynamic output sheets for management presentations at both the faculty/department level and group level. The outputs presented key metrics and financial outputs, as well as the ability to deconstruct key calculations to enable quick analysis and interpretation of the model outputs.
Forecast worked closely with the client’s central planning team to agree and map detailed value driver trees which guided the scope and structure of the strategic planning models. Forecast developed the models using Excel and replicated the model calculations using KNIME analytics software providing far greater data processing and integration capacity.
The development of a centralised strategic planning model that integrates with a series of modular detailed planning tools provided a unique suite of tools for the client. The ability to run ‘shock’ scenarios through the model proved invaluable for the planning team to understand the impact on student revenue during the COVID19 period.