Education & Academia / Academic Research / Research Methodology
Why Big Data Fails: The Overlooked Power of Case Studies
The Case for Case Studies: Methods and Applications in International Development
Think randomized trials and big data give you all the answers? Think again. A policy that works like magic in Kenya can completely collapse in India. A strategy that scales inside one company blows up inside another. Data gives you the average. But nobody lives in the average. Randomized Controlled Trials are crowned as the gold standard of modern science. Yet billions of dollars still vanish into failed reforms and blind experiments. The fatal flaw? Knowing that something worked is not the same as knowing WHY it worked. Numbers deliver anonymous evidence. Case studies uncover individualized reality. This breakdown tears into the landmark volume, The Case for Case Studies: Methods and Applications in International Development. Edited by Princeton professor Jennifer Widner, World Bank Lead Social Development Specialist Michael Woolcock, and public sector governance expert Daniel Ortega Nieto, this work dismantles the prejudice that qualitative case studies are mere anecdotes. Slide 1: The RCT Illusion Science tests whether an intervention worked somewhere once. Real life demands knowing if it will work right here, right now. Slide 2: Opening the Black Box Large datasets hide the mechanism. Rigorous case tracing reveals the exact gears, social structures, and tipping points that drive an outcome. Slide 3: The Power of Outliers Stop ignoring the exceptions. The positive deviants that ruin your statistical bell curve are usually holding the real blueprint for success. Slide 4: Context is King Scaling up is never copy-pasting. It is understanding the invisible support factors that make an idea survive outside the lab. Walk away with the analytical toolkit used by top global strategists to spot hidden failure points, decode messy real-world systems, and make decisions that actually survive reality.
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