-Albert Einstein
The most complicated problems in life are systems problems.
An example system problem is what to look for in a life partner. It’s not one thing; It’s not two things. You need to identify a combination of character traits that align with you. A basic list could be:
self aware and takes action
fun and dynamic
high IQ
articulate
attractive
loyal
honest
compassionate
not strongly affected by nor seduced by status
reliable
If you atomize each trait, e.g., “find someone who is only compassionate”, then it’s easy. What makes it hard is finding a partner who possesses all the traits. Say you have 20 required traits, and on average, 60% of people possess each trait. Then less than one out of twenty-five thousand people fit your criteria.
Hopefully, it’s not that hard as positive character traits tend to correlate with each other. And there are likely different weights for what you find most important in a partner. For me, being self aware and able to take action on things they’re aware of is most important. The ability to grow is core.
I know guys who say if a woman has been to Art Basel more than once, they’ll never seriously date them. There are always exceptions. Arbitrary one off rules go out the window when understanding system problems.
The only way to solve systems problems is with systems thinking.
Designing Systems
The design of the system has cascading effects.
For its size and complexity of workflows, Amazon is the most competently run org in the world. Amazon takes many of the best aspects of the army and implements them in the private sector. SOPs (standing operating procedures) are required. Specific, Measurable, Actionable, Realistic, and Timely (SMART) goals are implemented and measured throughout. Amazon pushes a writing culture where employees and management have to vigorously defend their decisions whether it be project/product oriented, firing an employee, or promoting an employee.
Horizontal frameworks need to be applied to simplify systems to manageable size problems. Innovative structures need to be devised and implemented to teach example frameworks for how to solve systems problems. Take a problem I deal with daily—
In enterprise SaaS, almost all basic problems are solved. Best practices are known. A plethora of single point solution SaaS companies exist. There are known processes to build, market, and sell these products. What’s hard and what’s most valuable are solutions to entire vertical and horizontal workflows. These are the SaaS systems problems, or what Parker Conrad calls compound startups.
Compound startups require in-depth understanding of a super complex system. One part of the system affects every other aspect. How a system is architected from the ground up affects the data model, which will affect reporting and other use cases. Solutions you choose early on have downstream effects. If you aren’t deliberate with your choices, the foundation upon which everything is built may need to be refactored later on. It’s often impossible for legacy players to refactor their foundation, leading to opportunity for startups to enter the space.
Systems Everywhere
Biotech problems are systems problems. Almost every part of the human body has an effect on other parts. There are doctors who won’t operate on your knee if you have gingivitis. We still can’t predict with 100% accuracy how simple single cell membranes will react in controlled environments. If you want to go deeper, look at the high level of how our immune system works.
How top generals run their armies from a logistics, tactical, and strategic perspective is also a systems problem. Government policies are system problems as they lead to second and third plus order consequences that are usually unforeseen by policymakers. Sometimes it’s as simple as when Hawaii put a price cap on oil, then they had an oil shortage because it became no longer profitable to ship oil to Hawaii.
I was at a conference where a well known entrepreneur/investor asked a world famous investor what frameworks and cognitive biases one should be aware of when investing. The famous investor said we should be aware of questions asking about cognitive biases. It was a great troll. Just do good deals.
It’s true we shouldn’t spend too much time being meta as there are diminishing returns. But in reality, frameworks are necessary to do good deals. Frameworks overtime become unconscious, but they still exist. Frameworks are foundational to how we perceive the world and guide the actions we take.
Our Systems
How to design an effective system requires an understanding of primitives and how incentives work.
What makes people effective at work? Bias for action, being correct, delivering results, learning, being curious, thinking big, owning their decisions, etc. It’s not one metric. We need a holistic view.
We need to be deeply curious to figure out how to solve a systems problem. The vast majority of the time, it’s best to keep our eye on the ball. But zoom out every now and then and see the forest for the trees. What are your most important system problems?