Back to Search Start Over

The use of multiple models within an organisation

Authors :
Dent, Chris J
Goldstein, Michael
Wright, Andrew
Wynn, Henry P.
Publication Year :
2020

Abstract

Organisations, whether in government, industry or commerce, are required to make decisions in a complex and uncertain environment. The way models are used is intimately connected to the way organisations make decisions and the context in which they make them. Typically, in a complex organisation, multiple related models will often be used in support of a decision. For example, engineering models might be combined with financial models and macro-economic models in order to decide whether to invest in new production capability. Different parts of a complex organisation might operate their own related models which might then be presented to a central decision maker. Yet in practice, there is little awareness of the practical challenges of using models in a robust way to support decision making. There is significant scope to improve decision making though an enhanced understanding of the role and limitations of modelling and through the application of cutting edge methodologies and organisational best practice. This report is in the form of a 'white paper', whose purpose is to identify key issues for consideration whist postulating tentative approaches to these issues that might be worthy of further exploration, focussing on both technical and organisational aspects. It begins with a framework for consideration of how model-based decisions are made in organisations. It then looks more closely at the questions of uncertainty and multiple models. It then postulates some technical statistical and organisational approaches for managing some of these issues. Finally, it considers the way forward, and the possible focus for further work.<br />Comment: 49 pages. White paper arising from Alan Turing Institute project

Subjects

Subjects :
Statistics - Other Statistics

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2008.11813
Document Type :
Working Paper