Systems dynamics approach to risk management

New Zealand is no stranger to this type of event with the 2017 rupture of the Marsden Point to Wiri pipeline leading to numerous flight disruptions at the time. More recently, COVID-19 has posed challenges relating to supply chain blockages in shipping and ports, exacerbated by the blockage of the Suez Canal earlier this year, highlighting potential gaps in the way we identify, measure and subsequently manage risk.

Systemic risk is the possibility that an event at the company level could trigger severe instability or collapse an entire industry.

Within this context, risk is often managed at an individual node level (i.e. not at an industry or sector-wide level) making it difficult to understand how disruptive events in one area may impact another.

As a result, risk treatments may not accurately consider the effect beyond the organisation itself, making it difficult to address the root-cause, quantify overall impacts and test intervention actions, leading to an unsatisfactory long-term outcome.

This is particularly true in our transport systems and supply chains. The recent incident at the Suez Canal is a case in point. How were the impacts of this event rapidly understood, what were the best response paths and how were decisions made? Having the ability to quickly understand a scenario and the impact of mitigation measures can be invaluable in such situations where there is a significant impact to our global economy.

Robust response scenarios for different types of disruption can be instrumental in addressing the knock-on effects to the entire economy or supply chain. Dynamic simulation and system dynamics enable a data-based understanding of how infrastructure performs as well as the impact of changes in the external environment.

Increasingly dynamic models, sometimes referred to as techno-economic models and digital twins are used to understand, optimise and plan development of our critical infrastructure.

Such models use different linear and non-linear logic such as agent based, discrete event simulation, and systems dynamics to accurately simulate how infrastructure ‘eco-systems’ perform given different assumptions, business rules, and external inputs.

These models can simulate the impact of disruptive events and test multiple response scenario options. Importantly these models can understand and quantify systemic risks across supply chains and enable us to test where, when and how we intervene to enable the least impactful net-risk outcome.

In the case of the Suez Canal, historical vessel movement data could be used to develop a simulation model which considers global shipping flows. This type of model could then be used to see how vessels would build up in the event of such an incident and understand the effects of different scenarios, in order to facilitate decision-making and minimise the effect on global supply chains. For example, simulating the impact of an immediate decision to re-route all vessels around Africa.

An added benefit here is the ability to assess the overall economic cost of delayed production inputs, exports, trade and fuel supply depletion which ultimately impact GDP. Importantly these models can understand and quantify systemic risks across supply chains and enable us to test where, when and how we intervene to enable the lowest net-risk outcome.

Such an approach extends beyond quantifying physical movement or service delivery risk, it can also rapidly quantify economic as well as environmental, social and governance (ESG) impacts. A system approach can mean that response options can be optimised to seek the lowest possible negative economic and ESG impact. Likewise, this approach can be used to enhance the productivity, economic and ESG output of most systems by optimising how nodes interact together in a systemic way.

The ongoing strength in the New Zealand export market, combined with rising consumer demand and growing port constraints highlight the increased need for a greater understanding of transportation system risk and mitigation options. Dynamic models will enable us to understand impacts and assess responses in real time. Complementing this with industry forums to understand their likely responses to critical events and the downstream effects, may then provide us with an invaluable method of developing system wide response plans whether it be for supply, critical infrastructure or both.