Advanced Forecasting


Planning for both the short and long-term future in health and social care is vital. Allocating too many resources to a service can lead to waste and overspend, while under provision can lead to long waiting times and even the potential for loss of live. Future estimates of demand for a service are also useful in the designing of procurement contracts and logistical plans.
The advanced forecasting module builds upon the concepts and core ideas introduced in our introductory forecasting course whilst providing attendees with specialist knowledge of more rigorous forecasting techniques.
In particular, the module will cover how to use ARIMA models, the box-jenkins approach and various ensemble forecasting approaches to aid the health or social care planner produce forecasts in dynamically changing healthcare situations. Although it is not strictly necessary to have attended the introductory forecasting course, it is highly recommended that you have done so as this will enable you to get the best from the material covered.

Aims/Learning objectives:

  • Understand the steps involved in the forecasting process
  • Appreciate the role of forecasting methods in strategic planning
  • Understand and know which approaches are best suited to different types of forecasting problems.
  • Demonstrate the ability use the ARIMA modelling framework to create time series forecasts
  • To be able to apply the newly learnt approaches using R
  • Gain practical experience of the R programming language

Who should attend?

The course is ideally suited to those that want to increase their understanding of forecasting methods and best practices, in particular when applied to problems arising in local health or government services. The course will therefore most interest those looking to deepen their knowledge of advanced forecasting techniques and their limitations.

Course delivery

The course is delivered in a face-to-face format using lectures and course materials to introduce and explain the various theoretical concepts. Later in the day, an afternoon session held in the computer labs will provide attendees with a chance to practice what they have learnt on industrial problems.


Overall in order to take part in this module, potential participants will need mathematical skills to include simple algebraic manipulation (GCSE grade B or better) and some understanding of basic statistical techniques.
Participants are encouraged to take this course in combination with the introductory course, otherwise a numerical background in finance, accounting, budgeting or purchasing is recommended to be able to get the most from the material.
Basic IT skills are required, e.g. use of excel spreadsheet.

Software Support

The software required for this course includes Microsoft Excel 2007/2010 and R


Prof. Thierry Chaussalet or Philip
Tel: +44 (0)20 3506 4575

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Excel Sim
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