Return on modeling effort

Return on modelling effort (ROME) is the benefit resulting from a (supplementary) effort to create and / or improve a model.[1][2]

Purpose

In engineering, modelling always serves a particular goal. For example, the lightning protection of aircraft can be modelled as an electrical circuit, in order to predict whether the protection will still work in 30 years, given the ageing of its electrical components. More and more effort can be put in making this model predict reality perfectly. However, this perfection comes at a price: researchers invest time and money in improving the model. As a Return on investment (ROI), the ROME is a metric for the use of further modelling. It may therefore serve as a 'stopping criterion'.[2]

Typically, researchers will pull towards continuing modelling, while management will pull towards stopping modelling. Being explicit about the cost and benefits of continued modeling may help to make informed decisions that are understood by both sides. Continuous communication between model developers and model users increases the probability of models being actually put to profit.[3]

Domains

ROME is a metric, which can be evaluated wherever modelling is performed with a quantifiable goal. Examples include:

  • Modeling the impact of federal policy on social problems.[3]
  • Modeling a marketing mix to statistically correlate a number of inputs (or independent variables) – such as a marketing campaign – to outcomes (or dependent variables) – such as sales or profits.[4]
  • Modeling the links between enterprise actors to make an informed choice on splitting organizations.[5][6]
  • Modeling the coupling of an electromagnetic interference to a PCB to reduce its susceptibility by improving the routing of traces.[7]

References
  1. Op 't Land, M.; Proper, H. A.; Waage, M.; Cloo, J.; Steghuis, C. (2008). Chapter 4 of Enterprise Architecture - Creating Value by Informed Governance. Springer, Heidelberg, Germany. doi:10.1007/978-3-540-85232-2. ISBN 978-3-540-85231-5.
  2. Proper, Erik (2009). "Models that matter; Return on Modelling Effort". erikproper.blogspot.fr. Retrieved 2016-10-06.
  3. Fromm, Gary (April 28–29, 1977). Gass, Saul I. (ed.). "Review of the non-DoD modeling effort". Utility and Use of Large-scale Mathematical Models: Proceedings of a Workshop. Gaithersburg, Maryland: Department of Commerce, National Bureau of Standards, 1979. 534 of NBS special publication: 15–21.
  4. Thomas, Jerry W. (2006). "Marketing Mix Modeling". Retrieved 2016-10-06.
  5. Op 't Land, Martin (2008). Instrument for fast and effective splitting of organizations. TU Delft. ISBN 978-90-71382-37-6.
  6. Op 't Land, Martin (2008). Applying Architecture and Ontology to the Splitting and Allying of Enterprises. TU Delft. ISBN 978-90-71382-32-1.
  7. Op 't Land, Sjoerd; Mandić, Tvrtko; et al. "Comparison of Field-To-Line Coupling Models: Coupled Transmission Lines Model versus Single-cell Corrected Taylor Model". Proceedings of the 2013 International Symposium on Electromagnetic Compatibility (EMC EUROPE 2013).
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