Justin Evans’ The Little Book of Data illustrates why data matters and how to navigate its web

In India, during the 1980s, many car owners sought to sell their old vehicles to upgrade to new ones; however, the second-hand car market was stagnant due to information asymmetry. People who were unsure about the condition of a car relied on mechanics they trusted to inspect it. Owners of good cars were afraid they would not get a fair deal because buyers were sceptical, so they were hesitant to sell. As a result, only people who had no other choice, often with lower-quality cars, entered the market, which made the second-hand trade less lively.

However, things have changed, and nowadays, along with the Vahan portal, some private platforms offer services based on ownership, loan status, service history and inspection assessments, providing partial solutions that enable a more vibrant second-hand car market. These platforms provide buyers with reliable information about ownership, registration and accident data, allowing them to make informed decisions. This demonstrates that filling in the information gaps can significantly enhance the market.

Economist George A Akerlof explains how information asymmetry can destroy the used car market and also affect insurance (insurers often lack complete information about a customer’s health risks, while individuals may know more about their medical history or lifestyle), employment market (employers, lacking complete information about a candidate’s skills or reliability, may rely on stereotypes or group-based assumptions), credit markets (lenders often cannot fully assess a borrower’s creditworthiness, leading to high interest rates to offset the risk of default).

Surprisingly, his seminal paper, ‘The Market for ‘Lemons’: Quality Uncertainty and the Market Mechanism’, was rejected for publication in not one, but three (American Economic Review, Review of Economic Studies and Journal of Political Economy) prestigious journals, before being accepted in The Quarterly Journal of Economics. Akerlof’s ideas, which earned him the 2001 Nobel Prize in Economics (shared with Joseph Stiglitz and Michael Spence), also apply to social and environmental problems, such as the excessive use of pesticides. Farmers often lack knowledge about the health and ecological risks associated with pesticides. In contrast, manufacturers, who are more aware of these risks, may promote their use for financial gain.

The creditworthiness of a country affects how easily it can get money from global financial markets. Credit rating agencies assign sovereign ratings from AAA (the highest) to D (the lowest). Since 2007, India’s rating from Standard & Poor’s (S&P) has remained unchanged at BBB — the lowest investment-grade tier — placing it just one notch above speculative-grade ratings, which indicate higher default risk. Investors use these ratings to determine the level of risk associated with an investment. If the rating is lower than the country’s actual credit strength (as some argue is the case for India), borrowing costs increase for no apparent reason. As a result, this limits the government’s ability to make critical public investments in health, education, infrastructure and climate resilience.

But what is Standard & Poor’s, and how did credit ratings begin? In the late 19th century, railroads were rapidly expanding across the United States. Building and operating them required massive capital, yet profits often took years to materialise, if they came at all. Many railroads failed, leaving investors wary and uncertain about where to allocate their funds.

Enter Henry Varnum Poor, a railroad expert and journalist who saw the need for reliable investment guidance. Drawing on his experience of editing a railroad trade journal, he published ‘Poor’s Manual of Railroads’, a comprehensive guide detailing track mileage, rolling stock, passenger traffic, freight volumes, and other critical data investors craved for.

Initially, Poor’s ratings focused solely on railroads, his area of expertise. Over time, however, the firm expanded its scope, eventually assessing other industries — and even nations — laying the foundation for the global credit rating system we know today.

Justin Evans’ ‘The Little Book of Data’ delivers an extraordinary compilation of fascinating, insightful and eye-opening stories. Drawing on his firsthand experience at Nielsen, Comcast, Samsung and a startup, Evans delivers a compelling and accessible exploration of data’s transformative power in solving real-world problems. He begins by illustrating how we unconsciously “shed” vast amounts of data daily — through emails, rideshare apps, GPS, streaming services and social media — and reveals the intricate infrastructure built to capture, store and leverage this information, commonly termed big data.

From there, he traces how big data has fuelled the rise of artificial intelligence.

Yet, Evans does not just celebrate data’s potential; he also exposes its darker dimensions. He tells us about data bullies, referring to big tech companies that exploit information gaps, and the secrecy surrounding AI development, such as when copyrighted material is used without permission to train large language models. But he also gives examples that inspire, like Priya, an activist who uses data analytics to break up human trafficking networks and reduce human suffering. His message is clear: data is like a Promethean fire, an instrument that can either give power or destroy, depending on who uses it and how it is used.

Part Four of the book, ‘How We Use Data’, is particularly enlightening. Evans takes readers on a journey from humanity’s earliest attempts at counting, such as ancient shepherds tallying their flocks, to the abstract leap of inventing numerals (e.g., how ‘3’ transcends ‘three dogs’ or ‘three trees’ to become a universal abstract concept). He then charts how numbers evolved beyond mere counting, enabling statistical analysis, scoring systems and the data-driven frameworks underpinning modern society.

Each chapter demonstrates a core principle of data-driven problem-solving, spotlighting experts such as Akerlof and Poor, who have tackled major challenges using data. Evans excels at breaking down complex ideas so that even those without expertise can understand them. Key summaries, thought-provoking questions and discussions about the future end each chapter, ensuring readers not only grasp the what of our emerging datafied world, but also how to navigate it.

— The writer is a Visiting Professor at IISER, Mohali