The 2021 Texas power crisis was the result of many things—being unprepared for an extreme snowstorm, inadequately winterized power equipment, power grids isolated to the state, and so on. However, it’s fair to say this crisis was largely a miscalculation of risks. It was a failure to predict and mitigate a series of compounding factors, which led to a break under pressure. We can call it a failure in Systems Thinking.
After the fact, it’s easy to say that Texas should have winterized their wind turbines, but that’s only one detail—the crisis was the sum of much more. All power took a hit, including coal and nuclear. Worse, gas production froze along with pipelines.
As heating demands rose sharply, the lack of natural gas was problematic as many of Texas’s power plants rely on gas to generate their electricity, thus the power grids going offline was inevitable. The halt of gas production was perhaps the biggest culprit in the power crisis, but the broader system—particularly electrical infrastructure across much of the state—had little recourse without it. It was an inability to mitigate undesirable emergent behaviors and cross-dependencies that resulted in catastrophic failure.
Again, a failure in Systems Thinking.
Systems Thinking says nothing lives in isolation. Everything affects everything. It’s like the butterfly effect of chaos theory, which isn’t to say butterflies set off chain reactions that blow volcanos or cause tsunamis, but that the Earth is a complex and interlinked system, where even something as small as a butterfly is moving with everything else.
The idea of managing complexity in systems is nothing new—System Thinking has been around for decades. The challenge now is that many organizations still aren’t giving Systems Thinking its proper due, sometimes with a great cost. This is true even of PLM and its users, but vendors are catching up.
The concept of the butterfly effect was first used to describe the impossibility of predicting the weather far into the future, because weather systems are too complex for us to track every proverbial butterfly. Similarly, it is impossible for any one person to fully understand today’s design complexity, which is increasing at an ever-accelerating pace. No one can or should predict every little variant or mistake on their own. So rather than chasing butterflies, we can govern our design complexity with effectively applied Systems Thinking.
We do this with a modern PLM platform capable of tracking all life cycles of the system, from conception and design to operation and maintenance.
Because of rising complexities in today and tomorrow’s products, with more functionality and more variance of functionality, often the design of a product has become the design of a system with many different implementations. PLM platforms came from the mechanical world that focused on just the product. Now they’re evolving to meet a world of systems—a world where you have to have to manage everything about a system as a system of systems first, without knowing the details of the design of products.
We apply Systems Thinking to how we look at what PLM is managing. Because everything affects everything, it is critical the platform be able to connect the product at all stages to a system model, such as with a Digital Thread. Tools have to be able to show their data models to PLM data models. Whatever system PLM is going to manage in the future, it has to do so in the context of a data model of that system, where every change goes through said model. The system model is the connective tissue sitting inside PLM and everything in PLM connects through it. That is the crux of Systems Thinking.
PLM used to manage just design data. Now we’re managing design intent, which drives design data. We can’t predict the outcome of every storm, so we should instead prepare to mitigate their effects.
Steven Jobs once said, “You can't connect the dots looking forward; you can only connect them looking backwards.” Predicting the future—and future failures like in Texas—requires full traceability from the beginning—in short, with a Digital Thread and the platform to support it. This is the strength of a PLM Platform, as they not only manage design data, but also the system across the entire lifecycle from the start to any indefinite point in the future.
Failure may not always be completely preventable, but with the right thinking and platform, it should always be manageable.
Mark Reisig is the Vice President of Product Marketing at Aras.