Snippets about: Problem Solving
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Simple, Complicated And Complex Problems Require Different Approaches
Gawande explains a helpful framework developed by professors Brenda Zimmerman and Sholom Glouberman that defines three types of problems:
- Simple problems like baking a cake from a box mix. These can be solved by following a straightforward, standard recipe. Success is almost guaranteed if you precisely follow the instructions. No special expertise is required and results are easily replicated.
- Complicated problems like sending a rocket to the moon. These consist of many simple problems that must be coordinated correctly. They require teams of experts in different domains and precise timing. Unanticipated difficulties commonly arise. But with enough planning, a complicated problem can usually be solved reliably.
- Complex problems like raising a child. A complex problem involves many factors that interact with each other in unpredictable, ever-changing ways. What works in one case often doesn't apply to the next. Deep expertise helps but only to a limited extent, because each situation is unique and outcomes are uncertain.
Section: 1, Chapter: 3
Book: The Checklist Manifesto
Author: Atul Gawande
Diagnose Problems To The Level Of The Machine
When diagnosing problems, Dalio recommends asking:
- Is the outcome good or bad?
- Who is responsible for the outcome?
- If the outcome is bad, is the responsible party incapable or is the design bad?
Drilling down to the specifics of how the machine (designs, processes) and the people (responsible parties) either failed or succeeded is key to understanding root causes and making improvements. You have to connect problems to specific people or processes.
Section: 3, Chapter: 12
Book: Principles
Author: Ray Dalio
The Right Understands The True Meaning Of Climate Change
The political right engages in rampant climate change denial not because they are ignorant of the science, but because they understand all too well the revolutionary implications of the science. They understand that truly reckoning with the climate crisis means abandoning many core tenets of their free market worldview - a prospect they find intolerable.
While many progressives optimistically argue that climate solutions can be a win-win that doesn't seriously challenge business as usual, the right correctly perceives that climate change means the end of the world as they know it. Progressives would do well to learn from the right's frankness about the true implications of climate change.
Section: 1, Chapter: 1
Book: This Changes Everything
Author: Naomi Klein
Clear Thinking Depends On Defining The Right Problem
The first step in effective decision making is to ensure you are solving the right problem. Too often, we jump straight into identifying solutions without fully understanding the issue at hand.
The author recommends applying two key principles at this stage:
- The Definition Principle - As the decision maker, take responsibility for defining the problem yourself. Don't just accept someone else's framing. Do the work to understand the situation firsthand.
- The Root Cause Principle - Don't just address surface-level symptoms; dig deeper to identify the underlying cause of the problem. Solutions that don't tackle the real source of the issue are doomed to fail.
Section: 4, Chapter: 1
Book: Clear Thinking
Author: Shane Parrish
The Two Types Of Checklists That Help Manage Complexity
Gawande outlines two types of checklists construction teams use to achieve consistent success with complex projects:
- Task checklists that define the minimum necessary steps in a process. They ensure critical tasks are not overlooked or skipped. For example, a checklist that reminds builders to confirm the dimensions of a roof truss before installation, or to test the concrete mix for proper consistency.
- Communication checklists that specify which teams must talk to each other to identify and deal with developing problems. For example, a checklist that requires engineers, architects, and builders to discuss any deviations from the blueprint before implementing them, to ensure they are viable. Communication checklists prompt the collaboration needed to catch errors and handle the unforeseen problems.
Section: 1, Chapter: 3
Book: The Checklist Manifesto
Author: Atul Gawande
Seek Out Experts Who See The World Differently
Our own knowledge is always limited. That's why seeking out expert perspectives is so valuable when making an important decision. But not all expert advice is created equal. Look for experts who:
- Have deep experience in the specific domain you are operating in. Recency matters too.
- Think from first principles, not by analogy. They can break a problem down to its fundamental parts and reason upwards, not just pattern match.
- Are intellectually honest about what they don't know. Beware those who claim expertise they don't have.
- Can take an outsider's view and question assumptions. You don't want someone so steeped in conventional wisdom that they can't see new angles.
Section: 4, Chapter: 3
Book: Clear Thinking
Author: Shane Parrish
Why Medicine Needs To Learn From Construction's Approach To Complexity
Gawande contrasts the approach taken to complexity by medicine versus construction. Historically, both relied on the "Master Builder" concept - a single highly-skilled individual who uses their expertise to design and oversee the entire project. But by the mid-20th century, construction projects became immense in scale and complexity and so the construction industry transformed itself. Instead of relying on individual experts, they developed systems to coordinate teams of specialists using standardized procedures and checklists.
Yet in medicine, Gawande argues, we still largely take the "Master Builder" approach, expecting individual physicians to manage immensely complex situations using their memory and individual judgment. Like construction, we need to embrace the power of systems and checklists to support and enhance physician expertise.
Section: 1, Chapter: 3
Book: The Checklist Manifesto
Author: Atul Gawande
Thinking in Diffuse Mode
"But as long as we are consciously focusing on a problem, we are blocking the diffuse mode."
Section: 1, Chapter: 1
Book: A Mind for Numbers
Author: Barbara Oakley
The Mistake of Treating Complex Problems as Complicated Ones
Many intractable modern challenges arise from failing to distinguish between the merely complicated and the genuinely complex. Complicated problems can be hard, but with enough data and planning they can be "solved." Complex problems, by contrast, have no permanent solutions - only better or worse responses. Common mistakes:
- Seeking perfect, stable solutions rather than dynamic adaptations
- Excessive faith in more data leading to prediction and control
- Reductionist "divide and optimize" approaches that generate unintended consequences
- Expecting things to add up in a linear way rather than combining in unexpected ways
Instead, leaders must embrace uncertainty, focus on resilience and adaptability, and take an experimental, iterative approach.
Section: 1, Chapter: 3
Book: Team of Teams
Author: Stanley McChrystal
Adapt With Root Cause Analysis
The Five Whys is a technique for getting to the root cause when something goes wrong. By asking "why" five times, you can peel back layers to find the human problem at the source. For example:
- Why aren't customers using our new feature? Because they can't find it.
- Why can't they find it? It's only accessible from an obscure screen.
- Why is it only accessible there? Because the senior designer thought it would be better.
- Why did he think that? He wasn't properly briefed on the goals.
- Why wasn't he briefed? Because the PM was busy with other features.
Five Whys helps you build an adaptive organization that fixes processes, not just symptoms.
Section: 3, Chapter: 11
Book: The Lean Startup
Author: Eric Ries
Break Big Problems Down Using Fermi Estimates
To make impossibly complex problems tractable, superforecasters often use "Fermi-style" analysis, named after the physicist Enrico Fermi. The steps:
- Clearly specify the thing you want to predict (e.g. "How many piano tuners are there in Chicago?")
- Break the problem down into smaller, easier parts. ("How many pianos are there in Chicago? How often are they tuned each year? How many can one tuner service per year?")
- Make a reasonable guess for each component, based on whatever information you have or can gather. Focus on quantities you can approximate, even if crudely.
- Combine your component estimates into an overall estimate, using simple math (e.g. # of pianos * # of tunings per piano per year / # of tunings per tuner per year = # of tuners)
The resulting estimate won't be exact, but it's often surprisingly close - and much better than a wild guess. By breaking big mysteries down into small, knowable parts, Fermi estimates make unknowns more manageable.
Section: 1, Chapter: 5
Book: Superforecasting
Author: Philip Tetlock