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Speaker 1: Now, the Equal Employment Opportunities Commissioner has penned an op

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Speaker 1: ed in the defense of DEI, which is obviously diversity,

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Speaker 1: equity and inclusion. Earlier this year, Judith Collins announced she

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Speaker 1: wants to remove DEI requirements from the Public Surface Act.

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Speaker 1: Winston Peters has long been railing against it, and both

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Speaker 1: say that we shouldn't stand in the way of hiring

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Speaker 1: the best people for the job. You need to stop

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Speaker 1: putting labels on people. Gail Pachaco is the Equal Employment

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Speaker 1: Opportunities Commissioner and with us. Hey, Gail, Hello, Now I'm

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Speaker 1: fascinated by the fact that you say it's good for

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Speaker 1: productivity to implement the DEI. How does that work?

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Speaker 2: Well? As you said, I'm an EEO commissioner, but I'm

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Speaker 2: also I've been a professor of economics for many years,

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Speaker 2: and i was a former Productivity Commissioner. So I've looked

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Speaker 2: at the evidence through all of these lenses, and the

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Speaker 2: evidence sort of consistently shows, whether it's international evidence or

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Speaker 2: even New zeal And evidence that I've researched that I've

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Speaker 2: led that DEI policies, when they're embedded into the workplace,

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Speaker 2: they're actually good for ensuring meritocracy, they help with productivity growth.

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Speaker 1: How do we know that? How can we measure it?

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Speaker 2: Well? The research papers have worked with data from thousands

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Speaker 2: of firms, So there's McKinsey data, there's work with thousands

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Speaker 2: of firms. There's Odd data as well, and there's New

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Speaker 2: Zealand data that we've recently done as well, and that's

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Speaker 2: worked with two decades of administrative data from across all

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Speaker 2: of New Zealand firms and in that we find a

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Speaker 2: very clear and positive link between workplace diversity and productivity growth.

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Speaker 1: Okay, so you done. You've compiled some data yourself, have you.

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Speaker 2: Yes, So we've done data using the administrative data from

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Speaker 2: the longitudinal Business data frame.

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Speaker 1: Okay, now, how do you know that it's definitely about

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Speaker 1: the DEI.

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Speaker 2: Well, in this research, so we use econometric methods where

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Speaker 2: we also control for other characteristics of the firm, so

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Speaker 2: you can kind of control for things like size or

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Speaker 2: other firm characteristics that might also be related to productivity.

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Speaker 2: And if you can control for those things and you

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Speaker 2: still find a positive link between diversity and this matches

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Speaker 2: with dozens of international studies, that's very clear signal that

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Speaker 2: DEI is actually good for productivity and economic growth.

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Speaker 1: But what is it about DEI that's creating productivity growth?

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Speaker 1: That's the thing I don't understand. I mean, you've got, sure,

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Speaker 1: you've got. I mean you get yourself a new staff member,

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Speaker 1: which presumably is good for productivity anyway, because they are,

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Speaker 1: you know, excited about the job. But then what about

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Speaker 1: being a woman, or being brown or you know, being

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Speaker 1: less able suddenly makes productivity shoot up.

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Speaker 2: Well, having a diverse range of ideas, diverse range of expertise,

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Speaker 2: and diverse DEI policies in of themselves mean that you

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Speaker 2: ensure the best people get to the the role. So

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Speaker 2: it's not just about particular groups getting into roles. It's

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Speaker 2: about ensuring the best people get to the role. And

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Speaker 2: DEI policies ensure that you remove some of those barriers

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Speaker 2: that sometimes might mean the best people aren't getting to

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Speaker 2: the role. Okay, So well in the column, I'm focused

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Speaker 2: on sort of showing how DEI actually supports meritocracy.

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Speaker 1: Okay, so when you did the study and yet you

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Speaker 1: saw that there was some sort of a link between

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Speaker 1: you know, DEI and productivity, did you have a comparison

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Speaker 1: group that was less diverse and therefore less productive.

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Speaker 2: Yeah, well that's what the study does. It looks at

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Speaker 2: those with lower productivity and the difference that happens when

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Speaker 2: or as well as those with higher productivity, and looks

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Speaker 2: at the differences in terms of workplace diversity. And so

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Speaker 2: it looks at the full range.

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Speaker 1: Okay, and so how this is going back years? So

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Speaker 1: you're telling me that for years, you guys have been

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Speaker 1: able to access the data of like whether the employees

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Speaker 1: are women, whether the employee brown, whatever.

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Speaker 2: Yeah. So the data in the stats New Zealand, the

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Speaker 2: administrative data on firms allows us to look at firm characteristics.

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Speaker 2: It also allows us to link with individual information and

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Speaker 2: you can see the characteristics of the employees by gender,

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Speaker 2: by ethnicity, etc. And this is data that we've used

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Speaker 2: even in my previous role when I was director of

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Speaker 2: the New Zealand Policy Research Institute for dozens of different

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Speaker 2: projects that were focused on evidence of different policy evaluation,

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Speaker 2: whether the firm level policy, where the labor market policy,

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Speaker 2: where the health policy, etc.

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Speaker 1: Okay, Gail, I'm really open to being convinced, but I'm

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Speaker 1: not convinced yet. Have you got one example, just one

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Speaker 1: example of this in practice, Like these guys hired a

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Speaker 1: woman and therefore they were more productive because she did this.

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Speaker 2: Well, these are averages of course across the econotry. But

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Speaker 2: what's really important, I mean, a really good example I

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Speaker 2: find to point to is the public service did right.

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Speaker 2: So the public service had a very concerted effort towards

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Speaker 2: DEI between twenty twenty one and twenty twenty four. In particular,

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Speaker 2: actually started back in twenty eighteen. And when they had

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Speaker 2: a concerted effort and they introduced requirements for public sector agencies,

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Speaker 2: for instance, to report on pay gaps, they provided a

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Speaker 2: lot of concrete guidance on DEI, They provided guidance on

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Speaker 2: removing bias from generation human resources policies, et cetera. The

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Speaker 2: impact that had over those six years was immense. Like,

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Speaker 2: the pay gap fell markedly.

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Speaker 1: The pay gaps are not product of ADEL.

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Speaker 2: Yeah, well, the pay gap, well, the data they had

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Speaker 2: showed the pay gap fell markedly. They also corrected for

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Speaker 2: salaries of similarly skilled employees in the same or similar role.

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Speaker 2: So in that race, in that piece of work, they

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Speaker 2: had really good results in terms of closing the gap.

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Speaker 2: And I mean the other thing to consider here, he Heather,

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Speaker 2: is that you know what our workforce is going to

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Speaker 2: look like in the next twenty years. So if we're

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Speaker 2: not tapping onto this talent pool of different ethnic communities,

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Speaker 2: et cetera, that's not going to be good for our

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Speaker 2: productivity in the long run. Just from a pure demographic

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Speaker 2: point of view, like within twenty years, sixty percent of

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Speaker 2: our workforce are going to be either Mari, Pacific or Asian.

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Speaker 2: And if we don't tap into that workforce capability and

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Speaker 2: capacity now and start building into that now, what is

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Speaker 2: going to happen to our productivity in the long run? Right? Gal?

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Speaker 1: Thank you, Gal Pacheco Equal Employment Opportunities Commissioners. For more

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Speaker 1: from Hither, Duplessyell and Drive, listen live to news talks.

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