## The core elements: Risk, Capacity, Negligence

The Risk-Capacity Model is a simple simulation of the survival of a system. The system might represent an organisation, market, nation, or Life on Earth. The three main parts the Risk-Capacity model are:

**Risk** — the chance that the system has of terminating in any time period**Negligence** — the process through which increases risk**Capacity** — the process that reduces risk

The core message of the model is: if the growth of risks exceeds our ability to reduce risks, then the expected lifespan of the system is short.

## Example systems

Let's start by examining only the effect of risk on system longevity. In a system that has a risk of 0.1 (ten percent) per year, there is a 90% chance of surviving to the second year, a 81% chance (90% × 90%) to survive until the third year, and so on:

By the tenth year, there is less than a 40% chance that the system will have survived.

In this next model, the risk level starts at 10% as it did in the previous model, but now there is 1% capacity:

By the tenth year, all risk has been eliminated and the chance that the system survives has stabilised at about 60%.

In this next model, risk starts at 0, capacity is 10%, and there are periodic spikes of 30% negligence:

This system has a 40% chance of surviving ten years.

### Details on using the Risk-Capacity Model for system simulations

All three variables — risk, capacity, and negligence — range from 0.0 to 1.0 each period. Capacity and negligence could either be constants or the result of a process (e.g. to simulate negligence that introduces in batches, such as the third example system above, or capacity that waxes and wanes over time).

Each period,

**risk** is reduced by

*capacity* and increased by

*negligence*. In examples 2 and 3 above, this was a simple addition: 10% risk - 1% capacity = 9% as in year 2 of the second example. You could also use multiplication, in which case year 2 of the second example would have only been reduced to 9.9% risk.

The value of

**system longevity** is equal to 100% minus the cumulative risk so far. Thus, each period, the new longevity is calculated by subtracting the risk level from the previous longevity:

*longevity2 = longevity1 × (100% - risk)*#### Simulating choices

When using the Risk-Capacity Model to present choices, the variable of

*risk* cannot be directly altered. Instead, actors in the model can only be presented with choices regarding either of the two input processes,

*negligence* or

*capacity*. For example, you might simulate:

- what happens if capacity is increased?
- what happens if negligence is decreased, or made less volatile?

#### Other examples of model variations

You could also elaborate the

*capacity* component of the model to have more sub-aspects, for example to simulate the need for risk assessment. Such a modification have two additional variables:

- Transparency, from 0.0 to 1.0, indicating the degree to which risks are understood, and can therefore be dealt with or reduced
- Work, from 0.0 to 1.0, simulating the amount of resources applied to risk reduction

Then each time period,

- Capacity = Work × Transparency

In order to simulate an effect whereby new risks are not understood, simulate this every period:

- Transparency = Transparency - RiskGrowth

Adding this to the Risk-Capacity model now lets you simulate two ways in which we might improve our capacity to reduce risk: either through risk assessment or capacity-building.