Running a modern enterprise or non-profit is a complex endeavor.
Even a relatively small operation relies on a mix of human and technical systems. And the technology is designed, operated and modified by humans, with their own set of relationships, rules, and behaviors.
We work in these complex systems, often with structures, feedback loops, missions, and environments that are constantly changing.
If dealing with complexity wasn’t hard enough, these systems also include many simple and complicated challenges.
Simple and complicated problems can be solved by understanding the rules that govern the problem, and applying data to arrive at an answer.
But sometimes complicated problems can be difficult to overcome without falling into analysis paralysis. What if you don’t have access to all of the data you need? Or aren’t sure how to break down the problem to even figure out what data you need to solve it?
It can be difficult to figure out where to start. Easy to feel overwhelmed by the pursuit of precision.
With constant pressure to move quickly, an organization may end up focusing on simple challenges, deferring complicated ones, and hoping that the complex systems will evolve themselves eventually and the enterprise will reach its goals.
But there’s a way to make progress without getting bogged down in analysis.
In many cases, estimations are enough for important insights and breakthrough progress.
It’s helpful to have a handful of strategies to try when you find yourself facing a complicated problem. This list was inspired by suggestions in the book “The Art of Insight in Science and Engineering” by Sanjoy Mahajan. While written to help people solve science, engineering, and other quantitative problems, many of the tips are helpful for extracting insights about natural and human-made systems.
To handle complicated problems, Mahajan argues, there are two main strategies. You can (a) organize or (b) discard information to more easily extract insights.
Organizing means creating some structure to help us tackle the problem without becoming overwhelmed. Discarding means knowing what’s ok to overlook to solve the problem or find an answer that’s close enough to help you make a decision.
Here are six ways to tackle complicated problems:
1. Divide and conquer
Break down difficult problems into manageable pieces. Could the larger problem be split into smaller problems to solve? Could you easily estimate the answer or gather some simple data to solve that sub-problem? Or do you need to continue and break that sub-problem down further?
By estimating small problems and combining the results, the answer to your larger challenge might be revealed.
A tree diagram is one way to visually organize the hierarchy of smaller problems and how they relate to the original challenge.
“The tree encapsulates many paragraphs of analysis in a compact form, one that our minds can absorb in a single glance. Organizing complexity helps us build insight.”
– Sanjoy Mahajan
This technique is useful for quantitative estimations, but also for emergent systems where you’re not quite sure how the system will react until you start injecting small changes. Maybe your ultimate goal is to revolutionize a business workflow but breaking it down into components could help reveal insights about new ways to tackle the overall problem.
2. Abstractions
Sometimes breaking down problems into smaller pieces doesn’t help you solve the problem faster. It could instead be beneficial to further organize the information by naming or abstracting out parts of it.
For example, rather than knowing all of the details, you could abstract out larger concepts like file types, organizations, and systems to represent complex ideas and physical systems with simple words.
This simplifies problem solving by treating the inner workings as “black box.” We often don’t need to understand all of the details to extract insights and communicate a message. A higher-level view of the problem can help us spot patterns that might not be obvious otherwise.
One tip for creating your own abstractions is to create an analogy between two systems ex. between mechanical and electrical systems, or between businesses across industries. What about this current problem is similar to past experiences or other fields?
“Our understanding of the world is built on layers of abstractions.”
– Sanjoy Mahajan
3. Symmetry and conservation
What is staying constant, even if the rest of the system is changing or hard to predict? Base your problem solving off of this metric, rather than the many variables, to reach an estimate faster.
For another application, consider if there’s any part of the problem that you could draw a box around and assume that what goes in must come out. Therefore if you’re not sure what the inputs are, you could still estimate the outputs as a proxy.
4. Proportional reasoning
Could you estimate the solution by changing the scale of a problem that you have already solved? For example, scaling a recipe is often a function of how many servings you want to make. Pay attention to how one quantity determines another (ex. The serving size per person will give you information about how many ingredients to buy for a group of six people).
5. Dimensional analysis
Often enterprises track and report metrics. But that information might be meaningless unless it’s compared with other metrics of the same dimensions, such as past performance or the usage of this app compared to another. The ratio between the two could tell you if the situation is better or worse than you should expect, and help you question why that might be so you can make decisions and take action. And our goal with approximations is not just to gather data, but to surface insights that can be used to make decisions quickly.
6. Lumping
Sometimes you need to discard information to make a rough approximation and move forward. Rounding numbers could get you a close enough answer. Rounding to the nearest power of 10 might be necessary. The estimate won’t be accurate but the time you save getting to something close enough will probably be worth it for many back-of-the-envelope calculations. You can do the same by replacing complex shapes with simpler approximations. This allows you to simplify the math to come up with approximations to aid higher-order decisions that don’t require detailed numbers.
Complicated problems are often part of daily life in complex systems, and can be overwhelming. But with these tips to reference, they should be easier to tackle. So you can continue to move forward and make a difference in the enterprises and complex systems that impact us every day.
Which tip will you try out next?
