A recent review by two business professors has cast doubt on a series of studies conducted by McKinsey and Company, which advocated for increased racial and ethnic diversity among executives in publicly traded U.S. firms.
The professors concluded that the studies' findings, which suggested that such diversity could enhance financial performance, were not replicable and thus lacked credibility.
The review was conducted by Professor Jeremiah Green from Texas A&M's accounting department and Professor John Hand, an accounting professor featured in Econ Journal Watch. They scrutinized four studies released by McKinsey and Company in 2015, 2018, 2020, and 2023. "We conclude that caution is warranted in relying on McKinseys findings to support the view that U.S. publicly traded firms can deliver improved financial performance if they increase the racial/ethnic diversity of their executives," the professors noted in their review.
All four scrutinized studies were co-authored by Dame Vivian Hunt, who served as McKinsey's managing partner in the UK and Ireland during the release of the first three studies. The professors highlighted a statement by Hunt during a Bloomberg interview, which they believe encapsulates McKinsey's stance on the issue. "What our data shows is that companies that have more diverse leadership teams are more successful. And so the leading companies in our datasets are pursuing diversity because its a business imperative and driving real business results," Hunt stated.
In a separate video with Meta for Business, Hunt argued that a "meritocratic" approach in business is insufficient due to inherent biases. She advocated for businesses to actively promote "antiracism." "A neutral position that's meritocratic that is good and treating people evenly isn't good enough," Hunt declared. "You have to proactively stand for an antiracism environment, an anti-bias environment, to positively include people who've been historically excluded."
The professors' review of McKinsey's 2020 study, "Delivering through Diversity," was a "quasi-replication" due to their inability to access the original datasets used by the consulting firm. McKinsey reportedly utilized data from 186 large public firms in the U.S. and Canada. However, due to the firm's refusal to disclose its datasets, the professors opted to use data from the S&P 500 list.
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