engineering

Return on modeling effort

Return on modeling effort is a engineering topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Return on modeling effort rather than just read about it. In short: Return on modelling effort (ROME) is the benefit resulting from a (supplementary) effort to create and / or improve a model. Purpose In engineering, modelling always serves a particular goal.

Key takeaways

Return on modeling effort belongs to engineering; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Return on modeling effort to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Return on modeling effort from memory before moving on to harder problems.

Reference excerpt

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

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'. 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.

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. 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. Modeling the links between enterprise actors to make an informed choice on splitting organizations. Modeling the coupling of an electromagnetic interference to a PCB to reduce its susceptibility by improving the routing of traces.

Research The initiative "Models at Work" studies the creation, management and use of domain models in scientific and industrial practice, aiming at a diversity of goals, varying from (as truthful as possible) representation of the conceptual structure of the domain that is modelled, via animation, simulation, execution and gamification, until automated (logic-based) reasoning.

References

Worked examples

Example 1 — a first encounter with Return on modeling effort

Start with the simplest possible case. Write down what Return on modeling effort claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In engineering, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Return on modeling effort before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Return on modeling effort ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Return on modeling effort

In research: Return on modeling effort appears in engineering research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Return on modeling effort in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Return on modeling effort is common in secondary-school and first-year university syllabi. It links to neighbouring topics Acronyms, Engineering ratios, Financial models, so understanding it makes those chapters shorter.
In everyday life: Look for Return on modeling effort outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Return on modeling effort in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Return on modeling effort means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Return on modeling effort out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Return on modeling effort in simple terms?

Return on modelling effort (ROME) is the benefit resulting from a (supplementary) effort to create and / or improve a model. Purpose In engineering, modelling always serves a particular goal.

Why does Return on modeling effort matter?

Because it connects several engineering ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Return on modeling effort?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Return on modeling effort.