Most Models Are Wrong

Most Models Are Wrong

“The most that can be expected from any model is that it can supply a useful approximation to reality: All models are wrong; some models are useful”.

~ George E. P. Box

George E. P. Box

George Edward Pelham Box FRS (18 October 1919 – 28 March 2013) was a British statistician, who worked in the areas of quality control, time-series analysis, design of experiments, and Bayesian inference. He has been called “one of the great statistical minds of the 20th century”. He repeated his aphorism concerning the wrongness of models in many of his papers.

The first appearance (1976) reads:

“Since all models are wrong the scientist cannot obtain a “correct” one by excessive elaboration. On the contrary following William of Occam he should seek an economical description of natural phenomena. Just as the ability to devise simple but evocative models is the signature of the great scientist so overelaboration and overparameterization is often the mark of mediocrity.”

 ~ George E. P. Box

He wrote later (1978):

Now it would be very remarkable if any system existing in the real world could be exactly represented by any simple model. However, cunningly chosen parsimonious models often do provide remarkably useful approximations. For example, the law PV = RT relating pressure P, volume V and temperature T of an “ideal” gas via a constant R is not exactly true for any real gas, but it frequently provides a useful approximation and furthermore its structure is informative since it springs from a physical view of the behavior of gas molecules.

For such a model there is no need to ask the question “Is the model true?”. If “truth” is to be the “whole truth” the answer must be “No”. The only question of interest is “Is the model illuminating and useful?”.

~ George E. P. Box

What’s A Model?

The Marshall model belongs to the group of models collectively referred-to as Scientific Models.

“A scientific model seeks to represent empirical objects, phenomena, and physical processes in a logical and objective way. All models are in simulacra, that is, simplified reflections of reality that, despite being approximations, can be extremely useful. Building and disputing models is fundamental to the scientific enterprise. Complete and true representation may be impossible, but scientific debate often concerns which is the better model for a given task.

Attempts to formalize the principles of the empirical sciences use an interpretation to model reality, in the same way logicians axiomatize the principles of logic. The aim of these attempts is to construct a formal system that will not produce theoretical consequences that are contrary to what is found in reality. Predictions or other statements drawn from such a formal system mirror or map the real world only insofar as these scientific models are true.

For the scientist, a model is also a way in which the human thought processes can be amplified.”

“Models are typically used when it is either impossible or impractical to create experimental conditions in which we can directly measure outcomes. Direct measurement of outcomes under controlled conditions (see Scientific Method) will always be more reliable than modelled estimates of outcomes.”

The Marshall Model

I’ve written a number of blogs posts (plus a White Paper) on the Marshall Model, and its relationship with Rightshifting, so I’ll not repeat that material here.

How is the Marshall Model Useful?

  • Explains the fundamental source of productivity – or lack of it – in organisations generally.
  • Predicts the likely path of attempts to “go Agile or “be Agile”, embark on Digital Transformations, adopt Lean or Theory of Constraints, etc..
  • Situates a range of approaches to business productivity along a spectrum (the Rightshifting spectrum), in order of effectiveness.
  • Defines the challenge facing organisations that wish to significantly improve their productivity and effectiveness.
  • Illustrates the role of the collective psyche (within social systems).
  • Offers a way forward to higher productivity, joy, engagement and seeing folks’ needs better met.
  • Provides interventionists with insights in how to intervene in organisations seeking to improve, similar to the way the Dreyfus Model provides interventionists with insights in how to intervene in situations where individuals seek to improve their skills. (How to best adapt and adopt styles of intervention to suit where the organisation is at, in its journey towards maximum effectiveness).
  • Offers a seed for building a shared mental model of the factors governing an organisation’s relative effectiveness, as well as a means to understand the mental models typically in play within organisations.

Some time ago I wrote a post on how folks might use the Marshall Model.

Aside: Please let me know if you would value an elaboration of any of the above points.


“Truth … is much too complicated to allow anything but approximations.”

~ John von Neumann

The Marshall Model is not Truth. It is truthy, in that it has some utility as described above. It is a hypothesis, one I’d be delighted for folks to debate, dispute and discuss. Do you have, for example, your own go-to model for explaining organisational productivity? Where does the Marshall Model sit, for you, on the spectrum of “highly useful” through to “not very useful at all”? Would you be willing to share your viewpoint or hypothesis on organisational effectiveness and productivity?

– Bob

Further Reading

All Models are Wrong ~ Wikipedia Entry
Scientific Modelling ~ Wikipedia Entry
George E.P. Box ~ Wikipedia Entry
Mental Models ~ Wikipedia Entry
Models Are The Building Blocks of Science

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