Farsighted

“Making decisions is not just about solving a problem — it’s about understanding the forces that shape our choices and their potential outcomes.”

1. Blind Spots in Decision-Making

We all face blind spots in decision-making, where emotions and biases cloud our judgment. Even historical figures like George Washington fell into these traps. Facing the British forces during the Revolutionary War, Washington was influenced by "loss aversion"—the tendency to avoid losses rather than seek gains, even when a different course of action might be more beneficial in the long run.

Humans are hardwired with such decision-making flaws. Loss aversion, for example, makes people hold onto underperforming stocks, fearing the regret of loss, even though selling might yield better results. Similarly, fear of public failure or embarrassment often leads us to defend poor decisions rather than admit defeat.

Washington initially made the mistake of trying to defend New York, despite being outnumbered and outgunned. The better decision would have been to abandon it and retreat inland. Although this misstep resulted from his blind spot, his ability to adapt and retreat ensured he could fight another day and eventually achieve victory.

Examples

• Washington's choice to defend New York due to pressure from Congress and personal pride.
• People holding onto failed investments due to fear of admitting loss.
• Persistent defense of outdated business strategies despite mounting evidence to the contrary.

2. Diverse Perspectives Lead to Smarter Decisions

Relying on a range of viewpoints improves decision quality. Significant choices benefit from bringing together individuals with different expertise and experiences to challenge assumptions and explore all angles of a problem.

When Vancouver's water department needed to expand its freshwater resources, they approached diverse groups from environmentalists to Indigenous tribes. Through collaborative input, they designed a pipeline that not only secured water supplies but also addressed ecological, cultural, and political concerns, highlighting the results of inclusive decision-making.

Psychologist Samuel Sommer's research reinforces this. His experiments found that diverse juries outperformed homogeneous ones, resulting in longer, more thoughtful deliberations and greater factual accuracy. This principle of diversity holds true for group dynamics beyond the courtroom.

Examples

• The Vancouver water management project incorporated feedback from local communities and technical specialists.
• Diverse jury teams in Sommer's study recalled facts better and avoided biased interpretations.
• Multidisciplinary teams in innovation hubs drive better product design through varied input.

3. Experts Struggle as Much as Amateurs to Predict the Future

People often assume experts have an edge in predicting outcomes. However, political scientist Philip Tetlock's decades-long research reveals otherwise. His "forecasting tournaments" showed that experts perform worse than generalists at predicting future political and economic events.

Experts often suffer from overconfidence and narrower focus in their specialist fields. For example, economists rigidly adhered to their biases about capitalist growth or collapse, failing to consider external factors such as technological or social shifts. Meanwhile, non-experts who considered a wide range of domains often achieved more accurate results.

The human limitation in forecasting future events is clear. A simple algorithm predicting no change or steady trends often outperformed human forecasts, showing that an open mind and varied perspectives matter more than expertise in many cases.

Examples

• Tetlock's research showed experts making more errors than non-experts in forecasting political outcomes.
• Economists misjudging long-term impacts of social and environmental changes.
• Algorithms surpassing human judgment in predicting the likelihood of events continuing unchanged.

4. Unforeseen Convergences Shape the Future

Future events don’t just follow straight-line trends—they result from unpredictable intersections of various factors. George Orwell’s dystopia 1984 reflected his fears of dictatorship persisting post-WWII, but he didn’t foresee democratic resilience or the unexpected collapse of global fascism.

Breakthrough technologies, like personal computers, emerge from converging developments across unrelated fields. Early computer invention depended on advancements in mathematics, silicon circuits, and even microwave signal processing, none of which could be predicted in isolation.

Unpredictability remains a hallmark of innovation and societal progress. While we can speculate, anticipating intersecting developments is nearly impossible, making adaptability and imagination essential for decision-making.

Examples

• Orwell predicted authoritarian regimes in 1984, missing post-WWII democratic trends.
• The rise of personal computing hinged on breakthroughs in circuits, programming, and communication signals.
• Unforeseen collaboration between biotech and AI advances medical research exponentially.

5. The Role of Red Teams in Testing Plans

Red teams play the role of a hypothetical adversary to test strategies for flaws and weaknesses. They’re commonly used in military contexts but can apply across industries. By attacking an organization’s strategy, red teams uncover vulnerabilities and improve decisions.

The successful raid on Osama bin Laden’s compound illustrates their importance. As the United States developed plans, the red team pointed out risks, such as the need to navigate potential diplomatic fallout with Pakistan. This foresight allowed planners to prepare contingency options.

Organizations leverage similar red-team strategies to test cybersecurity measures or marketing campaigns, ensuring every possible threat is addressed before execution.

Examples

• American intelligence relied on a red team to anticipate complications in Pakistan during the Bin Laden mission.
• Businesses employing red teams to simulate cyberattacks on critical IT infrastructure.
• Marketing campaigns tested by posing as a competitor to predict responses.

6. Cost-Benefit Analysis Balances Complex Decisions

Cost-benefit analysis is a structured way to weigh options based not only on costs but also the broader impacts. Reagan’s Executive Order in 1981 cemented its place in U.S. policymaking. By evaluating economic, social, and alternative impacts, this approach ensures decisions are well-founded, even across political divides.

For environmental concerns, cost-benefit analysis has been instrumental. Under Obama, experts calculated the per-ton social cost of carbon dioxide emissions to justify regulations. Factors like rising sea levels and reduced crop yields were assigned values, influencing policies to reduce emissions.

This method helps guard against emotional or impulsive choices, grounding decisions in measurable evidence.

Examples

• Reagan's cost-benefit mandate shaped U.S. regulations beyond monetary considerations.
• Quantifying climate change costs led to more enforceable environmental policies.
• Businesses use this model to decide between expanding product lines or cutting operational inefficiencies.

7. Linear Value Modeling Simplifies Tough Choices

Linear value modeling assigns quantitative values to different options, helping to clarify decisions involving multiple variables. By systematically weighting factors like job prospects, health benefits, or personal values, the preferred choice becomes clearer.

Self-driving cars already employ this method in real-time. For instance, when faced with a jaywalker, the car calculates options like braking, swerving, or maintaining current speed, weighing risks and impacts of every outcome based on probability models.

This method is also useful for personal decisions, like buying a house or changing career paths, by clarifying priorities and calculating trade-offs.

Examples

• Linear modeling allows job seekers to choose between salary, work-life balance, and commute time.
• Self-driving cars use it to minimize harm in split-second accident scenarios.
• Businesses use the approach to decide between cost-cutting measures versus expanding investments.

8. Mulling Things Over Works Too

While mathematical models help, traditional contemplation remains valuable. Giving the brain time to process information subconsciously often leads to better decision-making.

For instance, leaders in high-stakes situations, such as Obama deliberating on the Bin Laden mission, benefit from weighing options over days or weeks. The process allows them to explore scenarios and use intuition as a final guide.

Taking breaks and letting the mind work in the background during mundane tasks, like walking or cooking, often yields surprising clarity or novel solutions to tough problems.

Examples

• Obama administration’s slow, careful weighing of the Bin Laden strike decision.
• Problem-solving breakthroughs occurring during relaxing or unrelated activities.
• Artists and writers often finding inspiration while engaged in routine tasks.

Takeaways

1. Include diverse inputs whenever forming a team or tackling a complex challenge to improve your judgment.
2. Use both structured tools like cost-benefit analysis or linear modeling and unstructured contemplation when deciding.
3. Test your decisions by thinking like an adversary or forming "red teams" to uncover potential pitfalls.