Why Averages Can Be Misleading: The Drowning Dilemma
Abdulaziz Alghamdi, PhD
Driving business transformation through an innovative sustainability paradigm.
Imagine a 6-foot-tall man standing in a river that's 3 feet deep on average. Sounds safe, right? But what if the river's depth fluctuates between 1 foot and 10 feet?
Averages often oversimplify data and can hide important outliers or disparities. Whether you're looking at employee salaries, customer satisfaction scores, or project timelines, focusing solely on the average can lead to flawed conclusions. The same applies to sustainability ratings in the real estate sector. Without considering the intrinsic characteristics of a project—like its location, altitude, climate, or surrounding community needs—a high average sustainability score can create a false sense of achievement. You might be excelling in certain areas while critical factors go unnoticed.
It’s the distribution of data that tells the full story. A project might appear sustainable overall, but the hidden details can make or break its true impact.
Next time you’re given an average, ask: "What’s the real spread?" As Nobel laureate Daniel Kahneman once said, “We are blind to the obvious, and we are blind to our blindness.” Understanding the full picture is key to making smarter decisions—whether it's in business or sustainability.
To achieve continuous performance and truly transform sustainability from a side corporate function into a core strategy, a data-driven approach is essential to guide decision-making at every level.
#DataAnalysis #Sustainability #RealEstate #DecisionMaking
PhD | Board Member | Director General | Environmental Management | Policy Advocacy | Academic Leadership | EHS Consultancy | Top 2% Most Influential Scientists by Stanford University & Elsevier
5 个月Absolutely insightful article dear Dr. Abdulaziz. Your river analogy powerfully highlights how averages can obscure critical insights. This resonates with the concepts of false positives and false negatives in decision-making. Relying solely on averages can lead to false positives—where we mistakenly assume a project is sustainable due to a high average score—while ignoring underlying issues. Conversely, we might encounter false negatives by dismissing projects that could be impactful because their average metrics don’t capture their true potential. Understanding the full distribution of data is vital to avoid these pitfalls and make informed, nuanced decisions. Thank you for emphasizing the importance of a comprehensive approach in sustainability and beyond!