Yale Case. By: Daniel Lazier, Jacob Thomas, and A. J. Wasserstein
This Yale School of Management study analyzes whether industry selection meaningfully influences financial performance in ETA SFs. The authors examine data from SF-backed companies across several industries and evaluate outcomes using two key metrics: IRR and MOIC. The central question is whether choosing the “right” industry can significantly improve returns for entrepreneurs and investors.
The study builds on previous research about ETA CEO demographics and financial outcomes. While collecting data for that earlier project, the researchers also gathered information about company industries, which allowed them to investigate whether certain sectors systematically outperform others. The industries analyzed include software, healthcare, food & beverage, education, business services, blue-collar services, and consumer services.
A major challenge acknowledged by the authors is the difficulty of classifying companies into precise industry categories. Many ETA businesses operate in niche markets that overlap multiple sectors. For example, a software company serving business clients may also resemble a business services firm, while landscaping companies could fit either consumer or blue-collar services. Because of this subjectivity, the researchers caution against drawing overly rigid conclusions.
The analysis relies heavily on descriptive statistics, box plots, histograms, and regression testing. The researchers compare the financial performance of each industry against all other sectors combined. They emphasize that the study is descriptive rather than fully causal and that readers should avoid assuming industry alone determines success.
One of the most important findings is that industry selection explains only a small portion of ETA financial outcomes. The multiple regression analysis shows that industry variables account for approximately 6% of the variation in IRR results, and the overall regression model is not statistically significant. This suggests that while industry may influence business context and opportunity sets, it is not the primary driver of investment performance.
Among all sectors, healthcare demonstrated the strongest overall performance. Healthcare companies showed higher median IRRs and MOICs than non-healthcare firms, stronger upside potential, and tighter performance distributions. The regression analysis also indicated positive directional strength for healthcare, with marginal statistical significance. Examples of successful healthcare ETA targets included dental practices, hospice care businesses, concierge medicine, and dermatological services. The authors suggest that healthcare’s attractiveness may come from favorable market dynamics and the sector’s resilience.
By contrast, food and beverage was the weakest-performing sector. Although the sample size was very small, the industry consistently underperformed across both descriptive and statistical analyses. Median and mean IRRs were negative, MOIC outcomes were poor, and regression coefficients showed statistically significant underperformance. The findings imply that food and beverage businesses may involve operational challenges and risks that make them less attractive for ETA investors.
The study also challenges common assumptions about software businesses. Software is often considered an ideal ETA target because of recurring revenue, scalability, and low capital expenditure requirements. However, the data showed that software companies performed almost identically to non-software firms in terms of IRR and MOIC. The authors note that advances in artificial intelligence may be reducing the competitive advantages traditionally associated with niche software providers, making software businesses less defensible than before.
Business services, another highly popular ETA category, also failed to meaningfully outperform other sectors. Median IRRs and MOICs were almost identical to the comparison groups. Similarly, blue-collar services and consumer services showed mixed results with no consistent evidence of superiority. Education appeared strong in some metrics, but the sample size was too small to support reliable conclusions.
The report additionally examines top-decile and bottom-decile performers. The researchers created “Hall of Fame” groups for exceptional IRR performers and “griffin” groups for companies achieving MOICs greater than 10x. However, no industry consistently dominated these elite categories. Likewise, no major industry consistently populated the worst-performing group. This further reinforced the idea that success is widely distributed and not concentrated in any single sector.
Ultimately, the authors argue that firm-level execution is likely much more important than industry selection itself. Factors such as leadership quality, operational discipline, strategy, customer service, organizational culture, capital structure, and CEO experience may explain outcomes better than broad industry categories. The study concludes that there are no “magic” industries in ETA and that entrepreneurs should focus more on building exceptional companies rather than relying on sector selection alone.
The final message of the paper is optimistic but realistic: entrepreneurs should choose industries thoughtfully, but sustained success in search funds depends primarily on execution, managerial effectiveness, and adaptability rather than simply operating in a fashionable or high-growth sector.
Read the full case in: https://som.yale.edu/sites/default/files/2026-03/An%20Analysis%20of%20Industry%20Economic%20Performance%20in%20Search%20Funds.pdf
