Corpus ID: 221340706

The use of multiple models within an organisation

@article{Dent2020TheUO,
  title={The use of multiple models within an organisation},
  author={Chris Dent and M. Goldstein and Andrew Wright and H. Wynn},
  journal={arXiv: Other Statistics},
  year={2020}
}
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… Expand

References

SHOWING 1-10 OF 25 REFERENCES
Computational modelling for decision-making: where, why, what, who and how
TLDR
There is a need to reinforce modelling as a discipline so that misconstruction is less likely; to increase understanding of modelling in all domains, so that the misuse of models is reduced; and to bring commissioners closer to modelling,So that the results are more useful. Expand
Computational Modelling of Public Policy: Reflections on Practice
TLDR
Policy modelling will continue to grow in importance as a component of public policy making processes, but if its potential is to be fully realised, there will need to be a melding of the cultures of computational modelling and policy making. Expand
EXPLOITING UNCERTAINTY—INVESTMENT OPPORTUNITIES AS REAL OPTIONS: A NEW WAY OF THINKING IN ENGINEERING ECONOMICS
Abstract A new trend in corporate planning is to exploit uncertainty by taking investment opportunities as real options. This options approach is to complement the conventional net present valueExpand
Transparent to whom? No algorithmic accountability without a critical audience
ABSTRACT Big data and data science transform organizational decision-making. We increasingly defer decisions to algorithms because machines have earned a reputation of outperforming us. As algorithmsExpand
Design for Variation
ABSTRACT Statistical engineering is the study of how to best utilize and integrate statistical methods with other engineering disciplines and information technology to solve high-level, complex,Expand
Review of The Aqua Book: Guidance on Producing Quality Analysis for Government
Review of:HM Treasury () The Aqua Book: Guidance on Producing Quality Analysis for Government. HM Treasury: United Kingdom
Optimal Model Management for Multifidelity Monte Carlo Estimation
TLDR
This work presents an optimal model management strategy that exploits multifidelity surrogate models to accelerate the estimation of statistics of outputs of computationally expensive high-fidelity models and shows that a unique analytic solution of the model management optimization problem exists under mild conditions on the models. Expand
Computational modelling for decision making: why, what, how, who
  • See also Walport, M. et al
  • 2018
The use of scenario analysis in disclosure of climate-related risks and opportunities
  • 2018
Transparent to whom
  • 2018
...
1
2
3
...