We Read a 500-Page Engineering Textbook. Here Are the 5 Most Surprising Ideas.

Introduction: Unlocking Wisdom from Unexpected Sources

We live in a world of overwhelming complexity. Making a good decision, whether for our business, our career, or our personal lives, feels harder than ever. We’re flooded with data, faced with endless options, and haunted by the fear of choosing incorrectly. In the search for clarity, we often turn to business books or productivity blogs. We rarely look inside a 500-page academic textbook on Systems Engineering.

And yet, that’s exactly where some of the most powerful and practical wisdom can be found. We dove into the dense, diagram-filled pages of Decision Making in Systems Engineering and Management expecting complex equations and niche technical advice. What we found instead were fundamental, counter-intuitive, and genuinely useful ideas on how to think and make better decisions.

This post shares the five most surprising lessons from that textbook. These aren’t about advanced math or engineering jargon; they’re about profound shifts in how we approach problems—ideas that can be applied by anyone, anywhere, to bring clarity to complexity.

1. To Make Better Choices, Stop Looking at Your Options

The most common way people make decisions is through what the textbook calls “Alternative-Focused Thinking” (AFT). We find ourselves in a situation, identify a few available options, and then analyze them to choose the best one. Whether picking a new software vendor or deciding on a career path, we typically start with the alternatives presented to us.

The book argues this is a fundamentally reactive and limited approach. It champions a more powerful method called “Value-Focused Thinking” (VFT). VFT completely flips the script. It begins by asking you to first define what you truly value—your core principles and objectives. What does success actually look like? What criteria matter most? Only after you have a crystal-clear definition of your values do you begin to create alternatives specifically designed to fulfill them.

This is a game-changing idea. AFT is reactive; it limits you to choosing from what is already available. VFT is proactive; it empowers you to design and create superior solutions that are custom-built to align with what is truly important, often leading to options you never would have considered otherwise.

2. A Flawless Process Won’t Get You an ‘A’

Given that this is an engineering textbook, one would expect a heavy emphasis on flawlessly executing a defined process. Follow the steps, get the right answer. But the authors have a surprising philosophy on what constitutes true excellence.

In the preface, they describe their grading rubric for student projects. A student who performs the entire decision process correctly, checking every box and following every instruction, will earn a grade of “C.” To get a “B,” the student must also demonstrate good context. And to earn an “A,” they must show “mastery of the process, appropriate creativity, and producing outstanding insights.”

As they state: “Creative ideas without a solid systems decision process will seldom be defended and successfully implemented. However, a wonderful, logical process is of little value without creativity and innovation.”

This is a powerful reminder for any professional in any field. The authors’ core belief is that one must impart “the importance of both process and creativity without sacrificing the benefits of either.” A robust process is the foundation, not the final product. It provides the structure necessary to make sense of complexity, but it doesn’t generate the breakthrough idea. True excellence comes from the fusion of a sound methodology with distinctly human contributions: insight, innovation, and creativity. Process gets you to the baseline; insight gets you to excellence.

3. The Secret to a Perfect Design Is Knowing It Will Fail

Tucked away in the chapter on System Reliability is something you would never expect to find in an engineering text: the full text of Oliver Wendell Holmes’s 1858 poem, “The Deacon’s Masterpiece or, the Wonderful ‘One-hoss Shay’.”

The poem tells the story of a Deacon who sets out to build the perfect carriage—a “one-hoss shay.” His logic is impeccable. He reasons that every carriage breaks down because it has a single weakest point. So, he resolves to build one where every single part is exactly as strong as all the others. The result is a masterpiece of logic and balance that runs perfectly for exactly one hundred years to the day, at which point it simultaneously and instantly collapses into a pile of dust.

The Deacon’s design philosophy is captured in this excerpt: “Fur,” said the Deacon, “’tis mighty plain Thut the weakes’ place mus’ stan’ the strain; ‘N’ the way t’ fix it, uz I maintain, Is only jest T’ make that place uz strong uz the rest.”

The poem serves as a brilliant metaphor for systems design. It teaches that the goal isn’t to create something that lasts forever, because nothing does. Failure is not just a possibility; it’s an inevitability. The true goal of a good design is not to eliminate failure but to understand it, manage it, and ensure the system performs reliably and predictably within its intended life cycle. The Deacon’s shay was a “perfect” design precisely because he understood its lifespan completely.

4. All Your Models Are Wrong (And That’s a Good Thing)

Chapter 4 on Systems Modeling opens with a now-famous quote from statistician George Box: “All models are wrong, some are useful.” This single sentence dismantles one of the biggest barriers to effective planning and analysis: the pursuit of perfection.

The textbook explains that a model—whether it’s a financial forecast, a project plan, or a software prototype—is an abstract representation of a system, not a perfect replica. Its purpose is not to achieve 100% fidelity, which is impossible. Its purpose is to provide useful insight and understanding to help make a better decision.

The book illustrates this with the powerful example of the Wright brothers. Before building their plane, they built a simple model: a small wind tunnel to test more than two hundred models of different types of wings. This simple, “wrong” representation of a full-sized airplane gave them the crucial understanding of aerodynamics they needed to achieve flight. Their model saved them time, money, and quite possibly their lives. They are contrasted with their contemporary Otto Lillienthal, who gathered his data from over 2000 glider tests, one of which ultimately failed and killed him.

This idea is incredibly liberating. It frees us from the paralysis of trying to create the perfect, all-encompassing plan. The real question is not “Is this model perfectly accurate?” but “Is this model useful for the decision I need to make right now?” We should embrace the imperfections of our models and focus instead on making them useful.

5. The Most Common Mistake? Solving the Wrong Problem

The introduction to Chapter 10 begins with an anonymous and deeply resonant quote: “A great solution to the wrong problem is . . . wrong.”

The textbook argues that the single most critical phase in any project is “Problem Definition.” More projects fail from a misunderstanding of the problem than from a failure of engineering. No amount of brilliant analysis or elegant design can rescue a project that is aimed at the wrong target.

As a real-world example, the text cites the IBM PC Junior. In late 1983, IBM announced its entry into the home computer market with a scaled-down version of its successful business PC. The product was an engineering solution that failed spectacularly because it didn’t solve the home user’s actual problem. IBM’s scaled-down business machine was neither easy enough to use at home nor affordable enough for the market, making it an elegant solution to the wrong problem.

This principle is universally applicable. In our work and lives, the temptation is always to jump immediately into solutions. This is almost always a mistake. The most valuable work happens at the beginning: resisting the urge to act and instead investing critical time in deeply understanding the problem, its context, its stakeholders, and its environment.

Conclusion: Think Like a Systems Engineer

These five ideas, drawn from a technical engineering textbook, share a common thread. They reveal that successful decision-making is less about finding the right answer and more about creating the right process for thinking. It’s about stepping back from the immediate options to define what truly matters, balancing process with creativity, understanding failure to design for reality, creating useful-but-imperfect models, and, above all, making sure you are solving the right problem from the start.

This is what it means to think like a systems engineer. It’s a structured, thoughtful, and profoundly practical way to navigate complexity.

What’s one complex problem you’re facing where stepping back to define your values, instead of just your options, could change everything?