Business models: Understanding the numbers

 

It’s actually quite simple: at the end of a business model there should be as large a positive figure as possible. But getting there can be quite exciting.

Understanding a business as a cybernetic system

The term cybernetics – also known as “the art of steering” – comes from the Greek “κυβερνήτης (kybernetes) for steersman”. How do you control a system in which each variable influences the others?

Business model: when everything is connected to everything else

‘When we think about business models, we focus on the yield model of a company or a brand. For good reason: the aim of every company is to generate profit. All products and processes always contribute to this goal. Sometimes more. Sometimes less.

Nothing is linear

Unfortunately, the world does not work according to the “if-then principle”: if I take this action, then I will get that result. Business models are self-referential, non-linear systems: practically any variable can be both a cause and an effect. For example:

Production costs have an impact on the margin. The latter is therefore a consequential variable. However, in order to realise the margin on the market, a premium positioning may be required. This makes the margin the initial parameter. The positioning in turn determins (and is determined) by the target group. The target group influences the quantity. Here the circle closes: the quantity influences the production costs.

good-market.ing - Business model - everything is connected to everything else
Exemplary presentation of some possible relationships between variables in a business model

You can’t just work in one place

This simple example alone has four consequences:

  1. It is unrealistic to believe that you can work on one factor in isolation.
  2. A business model must always keep an eye on the bigger picture.
  3. It should be possible to quantify the correlations.
  4. You have to decide individually which variables to include in the respective analysis so as not to increase the complexity unnecessarily.

 

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