Imagine the following situation: at a board meeting of a large financial service organization the poor performance
Question:
Imagine the following situation: at a board meeting of a large financial service organization the poor performance of the company is discussed – for the fourth year in a row the company performs below the average for its sector and none of the interventions to improve this situation has worked. The HR director of the firm points out to his colleagues – all white, 50 to 60-year-old men with MBAs – that companies with a more diverse workforce tend to perform better. To substantiate his claim, he refers to a report by McKinsey & Company – the United States’ largest and most prestigious consulting firm – entitled Why Diversity Matters.1 This report examines the data of 366 public companies across a range of industries in Canada, Latin America, the United Kingdom, and the United States. The findings of the report are clear: companies in the top quartile for ethnic diversity are 30 percent more likely to have above-average financial returns for their respective industries.
Taking an evidence-based approach, the board asks 10 experienced professionals within the company whether they support the claim that investing in an ethnically diverse workforce will lead to substantially better financial performance, with an increase of at least 10 percent. Most professionals state that, based on their experience at work, they strongly believe that this claim is likely to be true.
Next, the scientific literature is consulted. A comprehensive search of the scientific literature yields five meta-analyses that all demonstrate very small (and sometimes even negative) correlations between ethnic diversity and financial performance. The organizational evidence shows a similar picture. There seems to be no difference in financial performance between the teams and departments with ethnically diverse workforces and those that have a more homogeneous makeup.
However, a sample of eight of the most important stakeholders, including regulators and institutional clients, indicates that they too believe increased ethnic diversity will have a substantial impact on the company’s financial performance. In addition, they point out that the McKinsey report was based on the data of 366 companies, and that this evidence should count heavily in the board’s decision.
The company’s CEO now sees himself faced with a difficult problem. He and his colleagues have taken an evidence-based approach, but now the evidence seems to be far from equivocal and even contradictory in some ways. So, what should he decide? Should he assign more weight to the evidence from the practitioners and stakeholders? They all seem to be very confident, but, on the other hand, human judgment, even from experienced professionals, is often flawed. And what about the five meta-analyses? They are all based on cross-sectional studies (not longitudinal or controlled research), although findings all point in the same direction. The same goes for the evidence from the organization where higher performing units do not tend to have a more diverse workforce. And, finally, what about the report by McKinsey? Surely the United States’ largest and most prestigious consulting firm can’t be wrong – can they?
The CEO in the example above is faced with several challenges. First, he must weigh the different sources of evidence. Not all evidence is created equal, thus some may count more than others.2 But how should the CEO balance the evidence from different sources, especially when they contradict each other? Second, how can he combine the evidence into one overall probability score? And, finally, how can he make a decision based on this probability score?
A. What are the initial probabilities for the hypothesis to be true and false, based on McKinsey’s report?
B. How do the initial probabilities for the hypothesis to be true and false change, based on evidence from 10 professionals?
C. How do the initial probabilities for the hypothesis to be true and false change, based on evidence from scientific literature?
D. How do the initial probabilities for the hypothesis to be true and false change, based on evidence from stakeholders that were consulted?
E. How do the initial probabilities for the hypothesis to be true and false change, based on evidence from organizational data?
Management Accounting Information for Decision-Making and Strategy Execution
ISBN: 978-0137024971
6th Edition
Authors: Anthony A. Atkinson, Robert S. Kaplan, Ella Mae Matsumura, S. Mark Young