**Steven Forth** is a Managing Partner at Ibbaka. See his Skill Profile on Ibbaka Talent.

Guest Post by Fabian Szulanski

Part of Ibbaka’s mission is to support a community of people committed to understanding value in all its forms and the role that value plays in building organizations. Our own approach integrates design thinking and value-based pricing with systems thinking. We think of pricing as a system, one that interacts with other business systems. You can see an example of this in Your pricing model needs a value model.

Fabian Szulanski brings a deep knowledge of systems thinking and design to his work. In this short essay he blends value networks with systems dynamics to get a better understanding of how pricing takes part in a dynamic system. We think you will find his ideas useful as you work on building organizations focussed on driving value to the customer (V2C) and basing your pricing strategy on that value.

From Value Networks to Systems Thinking: System Dynamics Modeling and Pricing by Fabian Szulanski

Value networks and systems dynamics have traditionally been used separately. Experts in value networks come up with one diagram of how businesses work while experts in system dynamics build their causal loops and stock and flow diagrams. By using these two approaches together one can get two different perspectives on how value flows through systems.

The figure below is a simple, rough example, of a value network. Basically, a value network is composed of different roles (not actors) in a system, exchanging tangible and intangible resource flows. If all goes well, value emerges.

Note that what flows are resources, which are not variables per se. For example, an invoice isn't a variable. Pressure isn't a variable either. These need to be more granularly specified in order to become variables.

The analogy is that each resource is like a large cable, with many little cables inside it, which represent the attributes or values of the resource. For example, the resource named Product, if it was a car, could have assigned attributes like physical dimensions, quantitative quality (such as errors/million of units), quantitative features (such as quantity of airbags, or horsepower measured in HP); or values, which always depend on human perception, such as safety, reliability, sportiness and comfort.

At this level, we are talking variables, not resources. We are talking about quantitative/qualitative, or tangible/intangible variables, which we can specify.

How to proceed now? There are two possibilities.

We could identify the problematic resource flows in the value network, and doing a conceptual exercise, modify the value network's structure in order to solve the problem, by adding or removing some of these resource flows. This is not too professional, because it's mostly an exercise of imagination and educated guesses.

A different approach would be to do some magic and go from the value network diagram to a causal loop diagram, which will correspond to a stock and flow diagram. That we can specify, validate and simulate, in order to try different interventions. This is more robust than staying at the level of the value network.

Let's reveal the magic trick. Once the problematic resource flows are identified, we select their most problematic attributes or values. In a relatively simple network, we could select 3 or 4 variables.

We choose a certain time horizon and ask the question: How have those attributes or values behaved over time? We draw a set of behavior over time diagrams.

And... voilá! What we inadvertently drew is what in System Dynamics is called a reference mode, which is the set of variables whose behavior constitutes the problem slice we would like to consider.

As there is a correspondence between a causal loop diagram and a stock and flow diagram, we can either and move on from there. We may stop without specification, if we prefer qualitative modeling for insight generation. When we need a more quantitative approach, we can go through the whole process, defining each feedback loop, leading to a simulation model for prospective problem solution testing.

How might readers model the pricing system's value network and analyze different pricing policies with the relevant and correspondent system dynamics model?

And then you go on navigating in Systems Thinking and System Dynamics waters.

I hope you enjoyed this little story.