The Wisdom of Vagueness: Why Approximations May Be More Precise Than Precision

The quote "I’d rather be vaguely right than precisely wrong" is famously attributed to the renowned British economist, John Maynard Keynes. This quote underscores a critical perspective on the value of approximate truth in the face of complex and uncertain situations, particularly in fields like economics and finance.

Keynes' Perspective on Approximate Truth

Keynes was emphasizing the importance of being directionally correct in economic theories and policies rather than being overly precise but fundamentally incorrect. This idea reflects the complexity inherent in economic systems, where many variables and uncertainties exist. A broad understanding or approximation is more useful than a detailed but possibly flawed analysis. Essentially, it suggests that flexibility and adaptability in thinking are crucial, especially when dealing with uncertain or dynamic environments.

Warren Buffett and Charlie Munger on Approximations

Warren Buffett, one of the most successful investors in the world, and his business partner Charlie Munger have adopted a similar philosophy. They believe that a vaguely correct model is often more reliable than a precisely incorrect one. It's better to use approximate models that align with reality, rather than exact models that assume to know more than is possible given the uncertainties involved. Neglecting the perfect values of wrong theories and equations in favor of not-so-perfect values or ranges of right theories can lead to better investment and policy decisions.

Robert Graves' Poem as a Modern Interpretation

Robert Graves' poem, "In Broken Images," provides a poignant modern interpretation of the value of approximations. In the poem, Graves contrasts two opposing approaches to thinking and understanding. One is quick and clear, but potentially lacking in depth; the other is slower and broken, but more likely to yield a deeper and more accurate insight into reality. This poem underscores the idea that in many situations, an accurate approximation is more valuable than a perfect but misleading detail.

Context in Financial Analysis

Warren Buffett, in his financial analysis, often emphasizes the importance of practicality over precision. In 2016, during an interview with the economist Paul Krugman, Buffett explained how he adjusts a company's cash flow for investment analysis. He was quick to point out that financial analysis is not a precise science; it's not about making calculations that work out perfectly every time. Rather, it's about using a trained eye to understand the knowable facts of the business, even if those facts are not perfectly clear.

Buffer suggests that rather than pretending to have exact answers or making unplanned guesses, evaluators should use their trained judgment to interpret the available data. The goal is to get to a directionally correct understanding, even if it is only approximate. This approach can lead to better investment decisions, as it accounts for the inherent uncertainties and complexities involved in financial analysis.

Flexibility in Decision-Making

The philosophy of being "vaguely right" rather than "precisely wrong" is particularly relevant in today's rapidly changing world. In fields such as economics, finance, and business, the decision-making process often involves dealing with incomplete and sometimes conflicting information. A flexible and adaptable approach, guided by approximation rather than precision, can be more robust and effective.

For example, in economic forecasting, it's often wise to consider a range of possible outcomes rather than predicting a single point. Similarly, in investment, it's better to have a clear understanding of what drives value and cash flow, even if the exact figures are not known with certainty. This philosophy encourages a broader perspective and a willingness to revise and refine understanding as new information becomes available.

Conclusion

The wisdom of vagueness lies in its ability to provide a flexible framework for decision-making in complex and uncertain situations. By prioritizing approximate truth over precise but flawed assumptions, decision-makers can arrive at more accurate and practical insights. Whether in economics, finance, or any other field, being "vaguely right" is often a smarter approach than striving for an artificial precision that may lead to incorrect conclusions.