Scenario analysis around pandemics, conflicts, and climate risks (as well as any other plausible systemic cascading risks I’ve left out) would also greatly assist resiliency efforts, enabling us to understand realistic cascading effects and target interventions to hedge against cascading risks that may happen at a reasonable probability.
That depends. For example, global food supply depends on a system of stocks and flows that emphasizes flows and concentrated sources. This is a problem with our global system of manufacturing and trade and the tendency of corporations to optimize throughput while lowering costs. The whole system is not designed to handle something like:
a multi-breadbasket failure
declines in productivity plus increases in population
A mapped and monitored system for the entire food supply chain (from fertilizers to seed sources to ship berths), production and delivery system will show problems at sources, pathways, chokepoints, and sinks. It won’t solve the likely problems though.
In the case of a multi-breadbasket failure, sources decline, temporarily or permanently, depending on the causes. Flows collapse, and we turn to stocks. A monitoring system is worthless unless:
the failure is gradual.
a solution is available.
We need the type of system you’re talking about, but we also need resiliency built into the system now. We need:
more local food production in countries that import
better farming practices in countries that export and a reduction in their productivity
less waste at all stages
We need to spread out food sources and reduce overall productivity proactively, pulling back from producing in areas that we will lose to climate change. We also need larger stocks and a change in how we produce foods.
The type of modeling work you’re describing, if intended to produce resiliency, would quickly reveal:
that we already face uncertainty about availability of some inputs
that we already want sources of inputs closer to where they are used, to avoid flow problems
that we need to utilize whatever products more efficiently
in order to increase resiliency of product supply to whatever region or small population. I say “whatever” because I am not too sure where they will be in 20-30 years.
There are other constraints on supply shortages of various products to do with politics and greed, governments and money (for example, with food: terminator seeds, agricultural run-off, govt subsidy incentives, big food lobbying)
We understand the supply-chain essentials that interfere with resiliency:
concentrated global sources/insufficient local production
We need the type of system you’re talking about, but we also need resiliency built into the system now.
My low-confidence rationale for including a section on modeling, scenario analysis, & its helpfulness to building resiliency is twofold:
1. Targeting & informing on-the-ground efforts: Overlaying accurate climate agriculture projections on top of food trading systems can help us determine which trade flows will be most relied on in the future and target interventions where they would be most effective and neglected—e.g. select between various agriculture interventions in different regions, lobbying for select policies or local food stocks, and tailoring food resilience research/engineering efforts towards countries and situations that will be projected to need it most.
Even for large-scale reforms, I feel like trade models can help inform the right balance of redundancy vs efficiency in a given situation.
2. Influencing risk-sensitive actors: Having accurate trade flow models can also help determine & project dangerous economic second-order consequences, creating more accurate risk analyses and thus further incentivizing governments and risk-sensitive organizations toward a coordinated systemic reform/response.
That depends. For example, global food supply depends on a system of stocks and flows that emphasizes flows and concentrated sources. This is a problem with our global system of manufacturing and trade and the tendency of corporations to optimize throughput while lowering costs. The whole system is not designed to handle something like:
a multi-breadbasket failure
declines in productivity plus increases in population
A mapped and monitored system for the entire food supply chain (from fertilizers to seed sources to ship berths), production and delivery system will show problems at sources, pathways, chokepoints, and sinks. It won’t solve the likely problems though.
In the case of a multi-breadbasket failure, sources decline, temporarily or permanently, depending on the causes. Flows collapse, and we turn to stocks. A monitoring system is worthless unless:
the failure is gradual.
a solution is available.
We need the type of system you’re talking about, but we also need resiliency built into the system now. We need:
more local food production in countries that import
better farming practices in countries that export and a reduction in their productivity
less waste at all stages
We need to spread out food sources and reduce overall productivity proactively, pulling back from producing in areas that we will lose to climate change. We also need larger stocks and a change in how we produce foods.
The type of modeling work you’re describing, if intended to produce resiliency, would quickly reveal:
that we already face uncertainty about availability of some inputs
that we already want sources of inputs closer to where they are used, to avoid flow problems
that we need to utilize whatever products more efficiently
in order to increase resiliency of product supply to whatever region or small population. I say “whatever” because I am not too sure where they will be in 20-30 years.
There are other constraints on supply shortages of various products to do with politics and greed, governments and money (for example, with food: terminator seeds, agricultural run-off, govt subsidy incentives, big food lobbying)
We understand the supply-chain essentials that interfere with resiliency:
concentrated global sources/insufficient local production
vulnerable transport
waste at source or sink
overemphasis on flows rather than stocks
Where do we go from here?
I agree with the following statement:
My low-confidence rationale for including a section on modeling, scenario analysis, & its helpfulness to building resiliency is twofold:
1. Targeting & informing on-the-ground efforts: Overlaying accurate climate agriculture projections on top of food trading systems can help us determine which trade flows will be most relied on in the future and target interventions where they would be most effective and neglected—e.g. select between various agriculture interventions in different regions, lobbying for select policies or local food stocks, and tailoring food resilience research/engineering efforts towards countries and situations that will be projected to need it most.
Even for large-scale reforms, I feel like trade models can help inform the right balance of redundancy vs efficiency in a given situation.
2. Influencing risk-sensitive actors: Having accurate trade flow models can also help determine & project dangerous economic second-order consequences, creating more accurate risk analyses and thus further incentivizing governments and risk-sensitive organizations toward a coordinated systemic reform/response.
Open to have this opinion change.
Yes, so gather information about what’s happening and tell those who could be effected by changes later on.
I proposed a reform to enhance food system resiliency for smaller regions and populations. What do you think of it?