Across the corporate world, small companies are struggling and large ones are thriving. Over the last three decades, the annual rate of new startups has fallen from 13% to less than 8%. Meanwhile, the revenue share of the top 5% of businesses has increased 10 percentage points since the 1980s. What accounts for this discrepancy?
One possible explanation, according to a new study by MIT Sloan School of Management’s Maryam Farboodi, is rooted in the growth of Big Data. The study posits that Big Data, which refers to the immense amount of digital information we generate and have an increasing ability to store and manipulate, disproportionately advantages large companies over small ones.
Today’s investors rely on Big Data to help them make smarter investment decisions,” says Farboodi, Assistant Professor of Finance at the school. “Because big companies produce more data relative to smaller companies, investors have more information to go on. This abundance of data, coupled with faster computer processing speeds, helps investors view these large companies as a less risky bet. As a result, big companies get more than their fair share of financing.”
Farboodi, and her coauthors, Juliane Begenau of Stanford University’s Graduate School of Business and Laura Veldkamp of Columbia University Business School, calibrate a model to demonstrate how the growth of Big Data influence the evolution of firm distribution. Their findings are published in the latest issue of the Journal of Monetary Economics.
The key insight of our model is that the benefits of Big Data are not spread evenly among companies: small, young companies benefit less—much less,” she says. “In some ways, this is understandable. Big companies, after all, have more economic activity and longer company histories so they have more data to process and analyze. In contrast, all the computing power in the world cannot inform an investor about a small company that has a short history and fewer disclosures. The problem, though, is that as Big Data technology improves, large firms will continue to attract a more than proportional share of data processing, and investor support and interest.”
Advances in information technology have already exacerbated this trend, she notes. “Faster and faster processing speeds have enabled investors to crunch ever more data—macro announcements, earnings statements, competitors’ performance metrics, export market demand, anything and everything that might conceivably forecast future returns—in a matter of seconds,” says Farboodi. “More data processing lowers investor uncertainty and thus lowers the cost of capital for big companies. This helps the big companies flourish, but the smaller firms can’t hope to compete.”
The study has multiple implications for how policymakers “grapple with the cost of the IT Revolution,” she says. “Leaders and lawmakers need to consider how the explosion of Big Data is both helping the economy and hurting it. One of their top priorities must be to support companies that are being disadvantaged and identify ways to help them grow and compete
“At the same time, small firms should view the data that they generate as an asset—an asset that helps investors learn about them, and can help them raise financing at lower costs.”
Download study: Big Data in Finance and the Growth of Large Firms
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I wanted to take a moment to thank you for your thought-provoking blog post titled “New MIT Study: Big Data Disproportionately Benefits Large Companies” on Inside Big Data. Your article delves into the significant impact of big data on large companies and raises important questions about the potential inequalities that may arise from its usage. Your article serves as a reminder of the importance of addressing these disparities and striving for a more inclusive and equitable landscape in the era of big data. It encourages us to explore ways in which smaller businesses and organizations can leverage data analytics to their advantage and bridge the gap between large and small enterprises.