The world has never had access to more information. But it seems the more data we have, the clearer the gaps get. Anne Tolmunen, Portfolio Manager, AXA IM Framlington Equities, Kathryn McDonald, Head of Sustainable Investing, Rosenberg Equities and Marie Fromaget, Human Capital and Diversity Analyst, AXA IM delve into the challenges and opportunities datasets bring when it comes to diversity. In addition they look at the massive role information can play in shaping the future for the better.
AXA IM: One of the difficulties when it comes to making the case for improved diversity, is that high-quality data is not always easy to find. How big of a challenge is data quality when it comes to diversity?
Marie Fromaget: Getting good data is a challenge. For the most part, what we have in the market is data on women on boards and on executive committees. This is a good starting point, but we need more disclosure to provide us with a greater level of detail, such as women as managers – and/or potential targets – as well as a female talent pipeline. Ultimately, besides the granularity question, we would like data that is meaningful, comparable and actionable.
Kathryn McDonald: To properly study the effects of diversity, we need good datasets. We need them to be as broad as possible, covering as many companies as possible, over as long a time-period as possible. Certainly, we’ve had data available regarding gender diversity at a board level, for some time. We find such information to be very robust across global publicly-listed companies. I think what we need now is to go toward a more complete definition of diversity as we get different types of data coming to us. That is not to discount the work we’ve done in the past, but we can do something that feels more inclusive and robust in terms of diversity by considering more than just gender and going beyond a board-level view of companies.
Anne Tolmunen: I completely agree that the data we have around gender diversity tends to be at the top of the corporate pyramid. Having access to more granularity would facilitate further analysis in understanding which organisations are truly doing a better job of fostering gender diversity. For example, when we have access to data such as the representation of women in managerial roles across the entire organisation, I like to compare it to the representation of women across the broader workforce. What I am hoping to find ideally, is an even proportional representation throughout a workforce’s hierarchical pyramid but you don’t tend to have that at most companies.
AXA IM: Is the level of data quality improving?
MF: I think it’s getting better. Companies are beginning to realise that not only is the issue very topical, but investors are increasingly vocal about it. When we go and speak to companies, for example, it is something we mention every time we meet with them, even if the meeting is not about gender diversity. We also participate in collaborative investor engagement initiatives such as the Workforce Disclosure Initiative, which is a huge questionnaire of some 100 to150 questions about social metrics and human capital policies, which are sent to firms. We let them know that it’s important for us to have access to this kind of data. First comes the data, then the engagement.
KM: Companies themselves are waking up to the fact that investors want to see this information and investors are increasingly asking for this type of data. We have the data providers stepping in and really trying as best as humanly possible to collect the data that the asset owners are asking for.
AT: And it is not just companies and asset owners. I think it is important to also highlight the actions that governments are taking, and this is really helping. Even though they are limited, we’re seeing good initiatives in countries like the UK and France, to push companies for more transparency and more granularity. And, it becomes a virtuous circle, the more granular the data becomes, the more transparency you get. This helps allow for more meaningful comparisons across sectors and countries, which in turn leads to greater accountability – we believe this is a big step towards resolving these issues.
AXA IM: The other challenge at play is that diversity is a complex issue. It’s not just about which datasets to use but also the limits and implications of what’s being measured. How do you go navigate this challenge?
MF: I think the key thing is to ensure that we do not just rely on one metric. We always need to dig into the details and ask ourselves what the number we are looking at says in relation to other metrics. A good example is the gender pay gap. We must praise the UK for the regulation it brought in. It’s a good starting point but right now the data is not yet of very good quality and we believe it can sometimes be misleading. For example, I saw one company with a very high gender pay gap in favour of women. I was very impressed. When I looked more closely, however, I found that the company had only hired one woman and 300 men, but the woman was sitting at the board, so she had a very nice salary. So, we should also analyse the narrative and the context beyond the data. We need to understand the story behind the data, to read between the lines.
AT: Many companies will point to the fact that when it comes to the UK gender pay gap disclosure, they are not talking about an apple-to-apple comparison. What is being reported are averages and medians. But what it does do is send a strong message to companies. It tells them they’re going to be scrutinised on their gender pay gap. Employees and future employees, will examine these figures. What’s interesting is that in some cases – and I expect this will grow over the years – companies are providing additional information to shed light on their numbers and explain them. Also, they provide background information as to what they are doing to close that gap. So, once again, there is a virtuous circle kicking in, whereas before many companies might never even have perhaps looked at the numbers. It’s obviously going to be an evolution, but I think because we are starting to measure things, it’s going to lead over time to greater progress.
KM: That is true. There is always the danger with regulation that it just becomes a tick-the-box mentality. For example, a firm might say that once its gender pay-gap statistics looks okay, it may believe it doesn’t have to worry as a company. But instead, what we should be saying is that such a statistic that should be just one of many that companies look at, when they ask themselves about the question of diversity. The trick is convincing firms to really embrace the idea that employing a diverse group of people is going to be in their best interests as a business. We want to see companies starting with the big statistics but also going much further into the statistics, that are meaningful for their business. We want to see firms really embrace diversity in a bottom-up way, so that they attract a broad group of workers early in their careers. If it is really permeating the psychology of management, we will be able to see it well beyond any kind of tick-the-box exercise that quotes one or two summary figures.