Do women improve decision-making on boards?

25 Nov 2023 | A fact is not data, A statement is not fact, Confirmation bias, Diversity

Last week, Harvard Business Review published an article entitled “Research: How Women Improve Decision-Making on Boards”. It was widely shared on LinkedIn and someone tagged me in it, given my research on diversity, equity, and inclusion. When I became Managing Editor of the Review of Finance, I appointed the first women to its board of editors in our 20-year history, so I’d like to believe the findings. However, it’s important not to take claims at face value, particularly when we’d like them to be true, because confirmation bias may be at play. I read both the article and the research underpinning it, and unfortunately the evidence doesn’t come close to supporting the headlines. My analysis below is based purely on the quality of the evidence, and not at all by the claims or my beliefs on diversity.

1. The Study Doesn’t Measure Decision-Making Quality

Despite the title (“improve decision-making”), the study doesn’t measure the quality of decision-making. Nor does it  measure the quantity of decision making. Nor does it measure anything to do with decisions at all, nor anything related such as firm performance. It simply asks board members how women behave in the boardroom. Reported performance is very different from actual performance, as I have explained in a previous post. Given the unstoppable push towards more board diversity, and the widespread claims that diversity improves performance (even if based on cherry-picked evidence), respondents may well report superior behaviour because they believe it to be true.

The underlying paper has a much more accurate title, “Women Directors and Board Dynamics: Qualitative Insights from the Boardroom”. However, as usual, HBR went with something more click-baity.

2. The Sample Selection is Highly Skewed

For a study on board diversity, the sample selection is highly non-diverse. Out of the 49 directors interviewed, 73% (36) were women and 27% (13) were men. Moreover, the individual responses cited in the paper are highly skewed. For the “supporting evidence” for the topic “Politics in board meetings”, the authors cite statements from five women and no men. For “Point of attention”, it is eight women and no men. For “Openness to different points of view”, it is 8-1; for two other questions it is 6-2; for two more it is 5-2. The study essentially finds “female directors claim female directors behave better”. (Similarly, a study should not overrepresent men, as it might also lead to biased findings).

Moreover, how the 49 directors were chosen is highly suspect. They first reached out to “personal contacts through our universities and alumni networks”. Since a study claiming that diversity improves performance is more likely to be published, a respondent may be skewed towards giving results that would benefit his/her alma mater. Even worse, then they “asked initial interviewees to suggest other board members from their networks”. This may lead to completely the opposite of cognitive diversity, as interviewees are more likely to suggest others who will reinforce their responses.

I am very open to qualitative research, and have conducted it myself in a recent survey of directors and investors on CEO pay. However, in qualitative research, where you obtain people’s subjective opinions, it is crucial to ensure an unbiased sample. We attempted to contact every director of a FTSE All-Share company, and every fund manager of a UK equity fund.

3. The Data Collection is Highly Suspect

The authors conduct interviews with open-ended questions. Thus, their interpretation of the responses to the questions is highly subjective and may be skewed by the authors’ own biases. Indeed, this seems to be the case. Consider, for example, the response “I have never sat on a board where a woman says nothing. Whereas I have sat on boards where men say nothing”, which is highlighted not only in the paper but also the HBR article. This is used as evidence that women contribute more.

In my TED talk, I recommend asking yourself how you’d react if a statement was the opposite. What if a respondent said “I have never sat on a board where a man says nothing. Whereas I have sat on boards where women say nothing?” This may be interpreted as evidence that men talk too much and feel they have to say something regardless of expertise. Indeed, in the very same table row in the paper, there is a quote ” ‘I have absolutely no knowledge in this area, so I am looking forward to hearing what you have to say.’ And I thought to myself that not many men would have said something like that”. Thus, listening is initially praised, but a couple of lines down listening is then condemned as a lack of contribution.

Second, there are no statistical tests anywhere in the paper. We don’t know whether the number of respondents who claimed women contributed more is significantly higher than those who did not. The paper only contains cherry-picked quotes, and every single quote given is in favour of the authors’ hypothesis (for a paper on diversity, the views presented are non-diverse). This contrasts a standard empirical paper, where authors will often include a couple of specifications with insignificant results.

Third, the interviews are in-person, and both authors are women. Even though none of the interviewees is identified in the paper, it would still be very unlikely for respondents to say out loud that women are less effective directors.

For this reason, interviews are almost never used as the primary data collection method in economics. The main way of obtaining qualitative insights is through surveys. Here, questionnaires are distributed to respondents. This has the following advantages:

  • Every respondent is given the same questions.
  • Every question is worded in exactly the same way. This is particularly important since slight variations in the question, or even the tone of voice, can skew a respondent’s answer. The researchers rigorously beta-test the wording beforehand to ensure no biases
  • Respondents fill in the surveys themselves, without the pressure of researchers being in the room
  • Respondents choose a number (often between 1 or 5) for how strongly they agree with a statement, meaning no subjective interpretation by the researcher is necessary (or possible)
  • Since these responses are numerical, they can be statistically analysed

Sometimes survey reseachers will conduct follow-up interviews on a small proportion (e.g. 5%) of respondents to find out why they answered in the way they did, to ensure correct interpretation of their responses. But the responses have already been made, and the main inferences are obtained from a statistical analysis of the numerical responses.

Unfortunately, these concerns mean that we can take little away from the study. Women directors might still contribute more than male directors. And even if they don’t, there could be societal, moral, or ethical reasons for pursuing boardroom diversity. But this particular paper does not make either case.

Inside the Ivory Tower

Inside the Ivory Tower

In May Contain Lies, I highlight the value of academic research. While it's far from perfect, it can be more reliable than practitioner studies for a number of reasons: Its goal is scientific inquiry, rather than advocacy of a pre-existing position or releasing findings to improve a company's image. It's conducted by those with expertise in conducting scientific research. Papers published in top scientific journals are peer-reviewed, which helpsimprove their accuracy. However, authors, journalists, and practitioners will sometimes cite research as if it bears the hallmark ...
Does only 2% of VC funding go to female founders?

Does only 2% of VC funding go to female founders?

A widely quoted statistic is that only 2% of VC funding goes to female founders. For example, this Forbes article highlights that "only 2% of all VC funding goes to women-led startups" and asks "Why is only 2% of VC funding going to female founders"? If true, this statistic is substantial underrepresentation and needs to be urgently addressed. However, it's problematic for several reasons. 1. The Statistic Ignores Diverse Teams The 2% statistic actually refers to companies founded solely by women. It ignores diverse companies founded by both men and women. This is strange, because ...
An unhealthy obsession with organisational health

An unhealthy obsession with organisational health

Two leading asset management firms drew my attention to the McKinsey Organizational Health Index as a potential tool to evaluate a company. A book, "Beyond Performance 2.0: A Proven Approach to Leading Large-Scale Change", written by two McKinsey partners, claimed that companies with high scores on this Index trounced their unhealthy peers along a range of performance measures. For example, their shareholder returns were three times as high. But as I wrote in an earlier post, rather than being more impressed by big numbers, we should be more sceptical. If it were really possible to ...