1 00:00:07,880 --> 00:00:11,920 Speaker 1: From WBZ News Radio in Boston. This is New England Weekend. 2 00:00:12,200 --> 00:00:14,720 Speaker 1: Each week right here, we come together and talk about 3 00:00:14,720 --> 00:00:17,160 Speaker 1: all the topics important to you and the place where 4 00:00:17,200 --> 00:00:19,600 Speaker 1: you live. Thanks for tuning in again this week. I'm 5 00:00:19,680 --> 00:00:24,279 Speaker 1: Nicole Davis. Massachusetts and especially Greater Boston is often seen 6 00:00:24,320 --> 00:00:26,440 Speaker 1: by people around the world as a hub of innovation 7 00:00:26,560 --> 00:00:29,240 Speaker 1: and progress when it comes to wage equity, though the 8 00:00:29,320 --> 00:00:31,920 Speaker 1: progress is not moving quite as quickly as we're used 9 00:00:31,920 --> 00:00:35,159 Speaker 1: to in other areas. The Boston Women's Workforce Council is 10 00:00:35,159 --> 00:00:37,360 Speaker 1: out with its latest report about the wage gap in 11 00:00:37,400 --> 00:00:40,159 Speaker 1: the region, and it does show the gap is getting smaller, 12 00:00:40,320 --> 00:00:42,800 Speaker 1: but it also shows there are major disparities that have 13 00:00:42,840 --> 00:00:45,440 Speaker 1: to be tackled, especially when it comes to Hispanic and 14 00:00:45,479 --> 00:00:48,320 Speaker 1: Black employees. The Council is doing that work by teaming 15 00:00:48,400 --> 00:00:50,840 Speaker 1: up with businesses all over the region, getting in there 16 00:00:50,840 --> 00:00:53,680 Speaker 1: helping c suites take a closer, more impactful look at 17 00:00:53,720 --> 00:00:56,680 Speaker 1: inequities within their own ranks while offering solutions to help 18 00:00:56,720 --> 00:00:59,800 Speaker 1: close those gaps. Executive Director Kim Borman is here to 19 00:01:00,040 --> 00:01:02,200 Speaker 1: talk with us about this now. Kim, thanks for the time. 20 00:01:02,760 --> 00:01:04,760 Speaker 1: Give us a bit more detail if you could, about 21 00:01:04,800 --> 00:01:07,040 Speaker 1: the council and the work you're doing on this issue. 22 00:01:07,240 --> 00:01:11,920 Speaker 2: So we are a partnership between the Mayor of Boston, 23 00:01:11,959 --> 00:01:15,959 Speaker 2: whomever that may be, and employers in Greater Boston that 24 00:01:16,040 --> 00:01:19,319 Speaker 2: are dedicated to closing gender and racial wage gaps. And 25 00:01:19,520 --> 00:01:22,959 Speaker 2: we do that in many different ways, but one of 26 00:01:22,959 --> 00:01:26,400 Speaker 2: the most important is that every two years we ask 27 00:01:26,480 --> 00:01:29,320 Speaker 2: our members to give us right off their PERO systems 28 00:01:30,760 --> 00:01:35,280 Speaker 2: data about their employees that includes compensation, and we are 29 00:01:35,319 --> 00:01:39,600 Speaker 2: able to see them and report on an aggregated basically 30 00:01:39,720 --> 00:01:42,880 Speaker 2: community progress made to close gender and racial wage gaps. 31 00:01:43,880 --> 00:01:45,200 Speaker 3: So that's who we are. 32 00:01:45,240 --> 00:01:48,360 Speaker 2: In addition, we share best practices and we really are 33 00:01:48,360 --> 00:01:52,560 Speaker 2: the go to resource for employers who are interested in 34 00:01:52,960 --> 00:01:53,560 Speaker 2: pay equity. 35 00:01:53,880 --> 00:01:56,200 Speaker 1: Yeah, we're going to talk about your compact and you 36 00:01:56,200 --> 00:01:58,040 Speaker 1: know who your signers might be. We'll touch on that 37 00:01:58,080 --> 00:01:59,880 Speaker 1: in a couple of minutes. For people who may not 38 00:01:59,920 --> 00:02:02,960 Speaker 1: be familiar with the concept of gender pay equity, I 39 00:02:03,000 --> 00:02:05,040 Speaker 1: mean there is a simple term. It's you know, people 40 00:02:05,040 --> 00:02:06,920 Speaker 1: of all genders making the same amount of money for 41 00:02:06,960 --> 00:02:09,280 Speaker 1: the same job. But there are a lot of factors 42 00:02:09,320 --> 00:02:11,239 Speaker 1: in history behind this. So if you could break it 43 00:02:11,280 --> 00:02:12,559 Speaker 1: down a bit for us. 44 00:02:12,680 --> 00:02:15,240 Speaker 2: Of course, So the way we look at it is. 45 00:02:15,360 --> 00:02:18,640 Speaker 2: It's almost like a raw gender wage gap. And what 46 00:02:18,680 --> 00:02:21,880 Speaker 2: does that mean. That means we look at, honestly, the 47 00:02:22,000 --> 00:02:26,799 Speaker 2: average of all the working men versus the average salary 48 00:02:26,960 --> 00:02:29,520 Speaker 2: of all working women, and we look at it in 49 00:02:29,600 --> 00:02:34,400 Speaker 2: terms of base compensation and also in terms of performance pay. 50 00:02:34,440 --> 00:02:36,200 Speaker 3: And why do we do it that way? 51 00:02:36,320 --> 00:02:38,760 Speaker 2: I mean sometimes people ask us about, well, what about 52 00:02:38,880 --> 00:02:42,160 Speaker 2: education and experience? We do it this way on purpose, 53 00:02:42,280 --> 00:02:46,200 Speaker 2: because we are looking not only horizontally. I call it 54 00:02:46,360 --> 00:02:49,720 Speaker 2: equal pay for equal work, which has been the law 55 00:02:49,760 --> 00:02:54,799 Speaker 2: since nineteen sixty three, frankly, and it was strengthened in 56 00:02:54,800 --> 00:03:00,600 Speaker 2: twenty eighteen in Massachusetts through the Massachusetts Equality Pay Act. 57 00:03:00,600 --> 00:03:03,480 Speaker 2: If you're familiar with that, equal pay for equal work, 58 00:03:03,520 --> 00:03:06,600 Speaker 2: you can be fined a lot by if people can 59 00:03:06,639 --> 00:03:11,200 Speaker 2: prove that. What's harder and more difficult to see is 60 00:03:11,240 --> 00:03:14,880 Speaker 2: what I kind of call vertical, which is our people. 61 00:03:15,560 --> 00:03:18,360 Speaker 3: Being advanced fairly. 62 00:03:18,960 --> 00:03:22,440 Speaker 2: So are the groups that usually don't get attention paid 63 00:03:22,440 --> 00:03:27,920 Speaker 2: to them not getting advanced as quickly as other groups 64 00:03:27,919 --> 00:03:29,919 Speaker 2: that usually do get a lot of attention paid to them. 65 00:03:29,960 --> 00:03:33,080 Speaker 2: Because if that is happening, you will never be able 66 00:03:33,120 --> 00:03:36,800 Speaker 2: to close the gap, even if you're paying everybody The 67 00:03:36,840 --> 00:03:40,720 Speaker 2: same is at the administrative support level. If only certain 68 00:03:40,840 --> 00:03:45,240 Speaker 2: people lead the administrative support level to more senior positions 69 00:03:45,400 --> 00:03:47,760 Speaker 2: where they actually make more money, you're going to have 70 00:03:47,800 --> 00:03:50,640 Speaker 2: a huge gap. So that's why we do it. 71 00:03:50,680 --> 00:03:51,840 Speaker 3: The way we do it is. 72 00:03:52,040 --> 00:03:55,960 Speaker 2: We look at the average compensation of men versus the 73 00:03:56,080 --> 00:03:58,400 Speaker 2: average compensation with women, and we also do it by race. 74 00:03:58,640 --> 00:04:02,240 Speaker 1: When you're looking at all this data on pay equity, 75 00:04:02,280 --> 00:04:05,080 Speaker 1: do you include research on transgender women or people who 76 00:04:05,120 --> 00:04:07,480 Speaker 1: identify as non binary? How does that all work? 77 00:04:07,840 --> 00:04:10,720 Speaker 2: We do ask the question, and this is something that 78 00:04:11,720 --> 00:04:14,920 Speaker 2: our employers give to us. The fact is that the 79 00:04:14,960 --> 00:04:18,799 Speaker 2: employers ask it themselves. They don't get that information very often, 80 00:04:19,160 --> 00:04:21,479 Speaker 2: especially now I have to tell you, so, yes, it 81 00:04:21,560 --> 00:04:24,320 Speaker 2: is something that we look at non binary in particular, 82 00:04:25,040 --> 00:04:29,359 Speaker 2: but we get such few responses that we aren't able 83 00:04:29,400 --> 00:04:31,039 Speaker 2: to do a whole lot with that information. 84 00:04:31,360 --> 00:04:33,680 Speaker 1: That's understandable. So let's talk about the report that you 85 00:04:33,760 --> 00:04:37,440 Speaker 1: recently put out and in some areas there has been 86 00:04:37,520 --> 00:04:39,680 Speaker 1: major improvement. Here. You know, women are now up to 87 00:04:39,680 --> 00:04:42,520 Speaker 1: earning eighty eight cents for every dollar a man earns 88 00:04:42,560 --> 00:04:44,880 Speaker 1: in Greater Boston. Tell us a bit about how that's 89 00:04:44,920 --> 00:04:46,600 Speaker 1: improved over the past few years. 90 00:04:46,880 --> 00:04:48,360 Speaker 3: We look at it well two ways. 91 00:04:48,400 --> 00:04:51,320 Speaker 2: But basically the gap then from that eighty eight sense 92 00:04:51,400 --> 00:04:54,919 Speaker 2: so that gap is twelve cents. That gap used to 93 00:04:55,000 --> 00:05:01,000 Speaker 2: be twenty one sense two years before, and actually it 94 00:05:01,120 --> 00:05:03,560 Speaker 2: was thirty cents, so it's gone down quite a bit. 95 00:05:04,279 --> 00:05:08,960 Speaker 2: And the base compensation in particular now it goes up 96 00:05:09,000 --> 00:05:12,080 Speaker 2: a little bit to eighteen cents when you add the 97 00:05:12,120 --> 00:05:15,000 Speaker 2: performance paid to it, but still that's a lot different 98 00:05:15,080 --> 00:05:19,400 Speaker 2: than the thirty cents we saw for total compensation in 99 00:05:19,400 --> 00:05:23,599 Speaker 2: twenty twenty three. So overall, yes, there has been a 100 00:05:23,720 --> 00:05:28,200 Speaker 2: huge decrease in the gender wage gap. Part of this 101 00:05:28,360 --> 00:05:32,400 Speaker 2: is because we saw seven percent increase in women moving 102 00:05:32,440 --> 00:05:35,520 Speaker 2: to more senior positions in fact the C suite in particular, 103 00:05:35,839 --> 00:05:38,960 Speaker 2: which means again that you're getting a higher salary. So 104 00:05:39,400 --> 00:05:44,560 Speaker 2: that makes the average. It brings the averages closer together, 105 00:05:44,600 --> 00:05:45,200 Speaker 2: shall I say. 106 00:05:45,360 --> 00:05:48,720 Speaker 1: Unfortunately, it's not a complete gain considering when it looks 107 00:05:48,760 --> 00:05:50,440 Speaker 1: when you look at the data for women of color, 108 00:05:50,720 --> 00:05:54,320 Speaker 1: the gap is still significantly bigger. So let's talk about 109 00:05:54,360 --> 00:05:57,560 Speaker 1: what you found for Hispanic women and black women specifically 110 00:05:57,560 --> 00:05:58,960 Speaker 1: here compared to white women. 111 00:05:59,520 --> 00:06:02,600 Speaker 2: Hispanic women in particular have a gap of fifty one cence, 112 00:06:02,640 --> 00:06:06,160 Speaker 2: we'll put it that way, and that's a forty nine, 113 00:06:06,200 --> 00:06:08,200 Speaker 2: So they bring home forty nine cents on the dollar 114 00:06:08,480 --> 00:06:10,880 Speaker 2: versus that eighty eight cent stuff on the dollar you 115 00:06:10,880 --> 00:06:14,800 Speaker 2: were talking about on average. Then black women they have 116 00:06:14,839 --> 00:06:17,760 Speaker 2: a gap of fifty three cents or bring home forty 117 00:06:17,839 --> 00:06:20,480 Speaker 2: seven cents on the dollar. I mean, you know, less 118 00:06:20,480 --> 00:06:25,560 Speaker 2: than half of that dollar. Interestingly though, well also you 119 00:06:25,680 --> 00:06:30,720 Speaker 2: probably noted, is that the biggest gap is actually for 120 00:06:31,160 --> 00:06:35,719 Speaker 2: black men. And we're comparing all of this to white 121 00:06:35,720 --> 00:06:38,240 Speaker 2: men and their salaries, and why do we do that, 122 00:06:38,400 --> 00:06:41,080 Speaker 2: Because there's just more of them, and they typically are 123 00:06:41,120 --> 00:06:44,160 Speaker 2: the people who get paid the most. But the black 124 00:06:44,279 --> 00:06:47,840 Speaker 2: man's gap is fifty five cents, meaning they bring home 125 00:06:47,880 --> 00:06:51,599 Speaker 2: forty five cents on the dollar. So there is definitely 126 00:06:52,360 --> 00:06:57,039 Speaker 2: a compound disparity when you look at gender and race. 127 00:06:56,960 --> 00:07:00,919 Speaker 1: Together here in Massachusetts. Obviously, we're seeing in Greater Boston 128 00:07:01,320 --> 00:07:05,039 Speaker 1: that this is a problem that is improving by the year. 129 00:07:05,600 --> 00:07:09,320 Speaker 1: How does Massachusetts fair or Greater Boston fair to other 130 00:07:09,400 --> 00:07:12,160 Speaker 1: major metros or just nationwide in general? 131 00:07:12,240 --> 00:07:15,880 Speaker 2: Do you know, Well, there is a national Equal Payday 132 00:07:15,920 --> 00:07:19,200 Speaker 2: that is in March, but it's not the number that 133 00:07:19,240 --> 00:07:22,320 Speaker 2: they use that they'll tell you about which I think 134 00:07:22,440 --> 00:07:27,120 Speaker 2: is nineteen cents comes right off the census. But the census, 135 00:07:27,120 --> 00:07:30,119 Speaker 2: as you know, it's just not that accurate. It's based 136 00:07:30,160 --> 00:07:33,000 Speaker 2: on whether somebody can remember what they were paid and 137 00:07:33,040 --> 00:07:35,800 Speaker 2: when they were paid it, and what the bonus structure was. 138 00:07:35,840 --> 00:07:39,200 Speaker 2: And the bottom line is we are the only organization 139 00:07:39,360 --> 00:07:42,640 Speaker 2: nationwide that does this really, So I wish I could 140 00:07:42,640 --> 00:07:44,360 Speaker 2: tell you that there are other groups out there. 141 00:07:44,480 --> 00:07:46,360 Speaker 3: We get calls all the time, whether. 142 00:07:46,160 --> 00:07:50,280 Speaker 2: It be from Governor Newsom's wife in California or her organization, 143 00:07:51,520 --> 00:07:54,680 Speaker 2: the mayor's office in Chicago. How do you make this happen? 144 00:07:54,960 --> 00:07:57,480 Speaker 2: How have you all been able to do this? It's 145 00:07:57,520 --> 00:08:02,600 Speaker 2: really because of this partnership between the City of Boston 146 00:08:02,760 --> 00:08:07,040 Speaker 2: and employers wanting to make a difference. So I wish 147 00:08:07,040 --> 00:08:09,640 Speaker 2: I could tell you Nicole that, yes, you can compare 148 00:08:09,680 --> 00:08:11,920 Speaker 2: it around. The only thing that's really out there is 149 00:08:12,120 --> 00:08:15,720 Speaker 2: again a number that's put out by different organizations, but 150 00:08:15,800 --> 00:08:18,080 Speaker 2: they do it the same way through the Census. 151 00:08:18,200 --> 00:08:19,840 Speaker 3: We are the only ones who do it. 152 00:08:19,680 --> 00:08:22,920 Speaker 2: Accurately, we feel, or more accurately right off of a 153 00:08:23,040 --> 00:08:23,800 Speaker 2: peril system. 154 00:08:24,040 --> 00:08:26,320 Speaker 1: Wow, I really hope that that changes, because that is 155 00:08:26,400 --> 00:08:28,720 Speaker 1: astounding to me that you are the only one. I mean, 156 00:08:28,720 --> 00:08:31,040 Speaker 1: I'm grateful you're here in doing it, but that is 157 00:08:31,080 --> 00:08:33,839 Speaker 1: astounding that you're the only ones doing it so far 158 00:08:33,920 --> 00:08:35,200 Speaker 1: in the year twenty twenty six. 159 00:08:35,720 --> 00:08:38,000 Speaker 3: I know. Wow, it is something that. 160 00:08:38,040 --> 00:08:40,800 Speaker 1: Is something Have you noticed through your research in your 161 00:08:40,840 --> 00:08:42,880 Speaker 1: work that it's a generational gap when it comes to 162 00:08:42,920 --> 00:08:46,479 Speaker 1: wage transparency, because I feel that Gen Z and millennials 163 00:08:46,520 --> 00:08:49,640 Speaker 1: are way more willing to talk about their wages than 164 00:08:49,800 --> 00:08:52,600 Speaker 1: perhaps Gen xers or boomers. Have you found that to 165 00:08:52,600 --> 00:08:53,720 Speaker 1: be the case, Yes. 166 00:08:54,320 --> 00:08:58,199 Speaker 2: We have, but we're not asking them individually, no, of course, 167 00:08:58,360 --> 00:08:59,839 Speaker 2: you know, it becomes. 168 00:08:59,679 --> 00:09:01,120 Speaker 3: An forget that they give us. 169 00:09:01,240 --> 00:09:05,320 Speaker 2: And but yes, in terms of the stories that we hear, 170 00:09:06,600 --> 00:09:10,400 Speaker 2: the younger employees are much more willing to say what 171 00:09:10,400 --> 00:09:12,640 Speaker 2: they're earning. And it's good for them because that's the 172 00:09:12,720 --> 00:09:15,320 Speaker 2: only way that you know and can find out if 173 00:09:15,360 --> 00:09:17,560 Speaker 2: you're not earning what you should be earning at your 174 00:09:20,679 --> 00:09:23,319 Speaker 2: job category. Now, of course, now you can because of 175 00:09:23,360 --> 00:09:26,160 Speaker 2: the way transparency bands that we're a part of the 176 00:09:26,200 --> 00:09:30,120 Speaker 2: Francis Perkins Workplace Equity Act. That will help, but you're 177 00:09:30,160 --> 00:09:31,760 Speaker 2: still going to have to find out where on that 178 00:09:31,840 --> 00:09:33,800 Speaker 2: band you are versus other people. 179 00:09:34,160 --> 00:09:36,719 Speaker 1: Yeah. I mean, are the businesses you're working with are 180 00:09:36,760 --> 00:09:39,760 Speaker 1: they recognizing this is happening and willing to make change 181 00:09:39,840 --> 00:09:42,400 Speaker 1: or are they just saying, well, this is the industry, 182 00:09:42,520 --> 00:09:45,000 Speaker 1: it's education, Like what is the excuse here for this? 183 00:09:46,200 --> 00:09:48,400 Speaker 3: So they definitely recognize it. 184 00:09:48,480 --> 00:09:56,720 Speaker 2: And it's very interesting cool because we have all sorts of. 185 00:09:54,840 --> 00:09:56,280 Speaker 3: Organizations that work with us. 186 00:09:56,280 --> 00:09:58,720 Speaker 2: We have the big companies in town, the State Streets, 187 00:09:58,760 --> 00:10:01,800 Speaker 2: the Vertex, the mass mutuals, and then we have smaller groups, 188 00:10:02,920 --> 00:10:10,040 Speaker 2: nonprofits and construction architecture. Because it was a data year, 189 00:10:10,200 --> 00:10:13,480 Speaker 2: and because it was a strange politically charged year, we 190 00:10:13,559 --> 00:10:19,720 Speaker 2: didn't know if we would get the same participation in 191 00:10:19,760 --> 00:10:22,680 Speaker 2: the data measurement as we have in the past. And 192 00:10:22,720 --> 00:10:25,679 Speaker 2: lo and behold, we did. I can't tell you which 193 00:10:25,720 --> 00:10:27,880 Speaker 2: companies because I don't even know that, because that's a 194 00:10:27,920 --> 00:10:30,320 Speaker 2: part of the whole confidentiality. I don't know who gives 195 00:10:30,360 --> 00:10:33,760 Speaker 2: us their data. But actually I know who gives us 196 00:10:33,800 --> 00:10:36,960 Speaker 2: their data. I don't know what their data says. I 197 00:10:37,000 --> 00:10:38,560 Speaker 2: know who gives us their data because I want to 198 00:10:38,559 --> 00:10:42,440 Speaker 2: thank them for it. The point is is that people 199 00:10:42,559 --> 00:10:45,160 Speaker 2: still care about this, people still want to do something 200 00:10:45,200 --> 00:10:48,760 Speaker 2: about this, but it's a long slog and people know 201 00:10:48,880 --> 00:10:53,319 Speaker 2: that too, and I think employees know that too. In 202 00:10:53,480 --> 00:10:58,319 Speaker 2: wage transparency is extremely important as a concept. It's something 203 00:10:58,360 --> 00:11:02,040 Speaker 2: you want your employer to be paying attention to. But 204 00:11:02,080 --> 00:11:04,520 Speaker 2: we've found over and over again that the employees aren't 205 00:11:04,600 --> 00:11:08,360 Speaker 2: expecting this to go away overnight. They know this takes years. 206 00:11:08,960 --> 00:11:13,800 Speaker 2: So yes to your question, employers are trying, and they're 207 00:11:13,840 --> 00:11:17,079 Speaker 2: trying everything they can, and they test different things because 208 00:11:17,080 --> 00:11:20,920 Speaker 2: there isn't a silver bullet. It depends on your culture, 209 00:11:21,440 --> 00:11:25,520 Speaker 2: it depends on your leadership, it depends on sort of 210 00:11:25,559 --> 00:11:29,840 Speaker 2: your workforce, and you know, are they frontline are they 211 00:11:29,880 --> 00:11:32,880 Speaker 2: backline these kinds of things. So that's why one of 212 00:11:32,920 --> 00:11:35,640 Speaker 2: the things we do is try to share as many 213 00:11:35,720 --> 00:11:38,600 Speaker 2: practices that are working out there with our members so 214 00:11:38,640 --> 00:11:40,360 Speaker 2: that they can test and learn as they go. 215 00:11:41,240 --> 00:11:44,080 Speaker 1: What is the City of Boston doing to try to 216 00:11:44,440 --> 00:11:46,640 Speaker 1: narrow these wage gaps? I mean, I know there's so 217 00:11:46,640 --> 00:11:50,240 Speaker 1: many different programs and a lot of assistance in place, 218 00:11:50,280 --> 00:11:52,640 Speaker 1: but when it comes to your work specifically, how is 219 00:11:52,640 --> 00:11:53,760 Speaker 1: the city helping you in this? 220 00:11:54,760 --> 00:11:57,840 Speaker 2: The city helps us, first of all by using our 221 00:11:57,880 --> 00:12:00,920 Speaker 2: research and our data whenever they can. In terms of 222 00:12:01,800 --> 00:12:05,640 Speaker 2: when they're talking to businesses. They also help us in recruiting, 223 00:12:06,600 --> 00:12:08,560 Speaker 2: and then they also help us by giving us their 224 00:12:08,640 --> 00:12:11,719 Speaker 2: data every couple of years, which is you know, it's 225 00:12:11,720 --> 00:12:14,000 Speaker 2: a big it's a big ask for them because there's 226 00:12:14,000 --> 00:12:20,520 Speaker 2: so many employees. So they've been very helpful. And no 227 00:12:20,600 --> 00:12:23,400 Speaker 2: matter how many mayors we've had since it started with 228 00:12:23,480 --> 00:12:27,160 Speaker 2: you know, Mayor Menino, every mayor has been very supportive 229 00:12:27,200 --> 00:12:27,760 Speaker 2: of our work. 230 00:12:28,200 --> 00:12:32,760 Speaker 1: So your members are called one hundred percent Talent Compact signers, 231 00:12:33,160 --> 00:12:36,120 Speaker 1: And I'd love to know what this compact includes and 232 00:12:36,240 --> 00:12:38,360 Speaker 1: you know, what are some of these practices that you're 233 00:12:38,440 --> 00:12:40,520 Speaker 1: leaning on here is we try to get closer to 234 00:12:40,640 --> 00:12:42,200 Speaker 1: equity and parity here. 235 00:12:42,280 --> 00:12:45,400 Speaker 2: So the one hundred percent Talent Compact was something that 236 00:12:45,520 --> 00:12:47,360 Speaker 2: was devised. I believe there was some kind of one 237 00:12:47,440 --> 00:12:51,720 Speaker 2: hundred percent compact during the two thousand and eight financial 238 00:12:52,120 --> 00:12:54,520 Speaker 2: crisis that we had, and so the idea of a 239 00:12:54,559 --> 00:12:57,440 Speaker 2: compact and that you know, there's something between the government 240 00:12:57,520 --> 00:13:00,439 Speaker 2: and employers to try to make society better. 241 00:13:00,520 --> 00:13:02,360 Speaker 3: So that's kind of how the name came about. 242 00:13:02,640 --> 00:13:04,680 Speaker 2: What it is is a pledge and it's a pretty 243 00:13:05,120 --> 00:13:08,040 Speaker 2: it's like two lines and we ask people one to 244 00:13:08,120 --> 00:13:10,120 Speaker 2: pledge that they will look at their numbers and do 245 00:13:10,200 --> 00:13:12,880 Speaker 2: the math and find out whether or not they have 246 00:13:12,960 --> 00:13:17,720 Speaker 2: wage gaps and then work towards closing those gaps, and 247 00:13:17,800 --> 00:13:20,440 Speaker 2: of course we will help them do that. There's also 248 00:13:21,800 --> 00:13:24,560 Speaker 2: a request for them to give us their data every 249 00:13:24,559 --> 00:13:25,560 Speaker 2: two years. 250 00:13:25,240 --> 00:13:26,080 Speaker 3: And most of them do. 251 00:13:26,480 --> 00:13:30,640 Speaker 2: Some of them don't usually because we hit them at 252 00:13:30,640 --> 00:13:32,640 Speaker 2: the wrong time of year and they just don't have 253 00:13:32,640 --> 00:13:35,400 Speaker 2: the staff to do it. And then the third thing 254 00:13:35,480 --> 00:13:38,600 Speaker 2: is that to share best practices and come to our 255 00:13:38,640 --> 00:13:41,960 Speaker 2: events and the networking. So that's really what it involves. 256 00:13:43,000 --> 00:13:46,920 Speaker 2: And you know, we will take, as I said, any organization, 257 00:13:47,120 --> 00:13:50,720 Speaker 2: any member, any employer out there that wants to be 258 00:13:50,760 --> 00:13:52,679 Speaker 2: a part of the contact. We'd love to have you 259 00:13:52,720 --> 00:13:56,480 Speaker 2: because the more data we have, the more projectable are 260 00:13:57,640 --> 00:14:01,640 Speaker 2: information is now when you say what works and what doesn't. 261 00:14:01,720 --> 00:14:04,080 Speaker 2: As I said, there's no silver bullet, but we give 262 00:14:05,280 --> 00:14:08,440 Speaker 2: they're called Wage Equity Impact Awards and we're about to 263 00:14:08,679 --> 00:14:12,960 Speaker 2: open the application for them for this year. We used 264 00:14:13,000 --> 00:14:15,600 Speaker 2: to call them innovative initiative wards, and then we realized 265 00:14:15,640 --> 00:14:17,079 Speaker 2: they don't need to be that innovative. 266 00:14:17,200 --> 00:14:18,240 Speaker 3: They just need to work. 267 00:14:18,360 --> 00:14:20,360 Speaker 1: It's pretty straightforward stuff if you ask right. 268 00:14:20,880 --> 00:14:25,320 Speaker 2: So what we find out honestly is the first step 269 00:14:25,360 --> 00:14:29,800 Speaker 2: is doing the math and needs to really like look 270 00:14:29,840 --> 00:14:35,160 Speaker 2: at your numbers and see, as I said, horizontally equal 271 00:14:35,200 --> 00:14:38,000 Speaker 2: pay for equal work, but also looking at it in 272 00:14:38,080 --> 00:14:41,680 Speaker 2: terms of advancement and our people being advanced at the 273 00:14:41,720 --> 00:14:47,080 Speaker 2: same rate as their colleagues. When people start to do 274 00:14:47,120 --> 00:14:52,200 Speaker 2: the math, and we call it wage Calculator dot org. 275 00:14:52,280 --> 00:14:54,960 Speaker 2: We put that together with the city so anybody, whether 276 00:14:55,000 --> 00:15:00,000 Speaker 2: you're a member or not, can go to that website 277 00:15:00,400 --> 00:15:03,320 Speaker 2: and put in their information and it'll spit it out 278 00:15:04,000 --> 00:15:08,440 Speaker 2: against our information. And we've updated it so that so 279 00:15:08,520 --> 00:15:11,480 Speaker 2: that you can just as a benchmark. But that's the 280 00:15:11,480 --> 00:15:15,760 Speaker 2: first place to start. Then there are other things to 281 00:15:15,840 --> 00:15:21,520 Speaker 2: look at. One year we gave a ward to Mass 282 00:15:21,520 --> 00:15:24,480 Speaker 2: General Brigham and was really Mass General and it was 283 00:15:24,560 --> 00:15:29,040 Speaker 2: very interesting. It was during COVID and there's something called 284 00:15:29,640 --> 00:15:32,760 Speaker 2: Grand rounds that doctors are expected to do. I was 285 00:15:32,880 --> 00:15:35,560 Speaker 2: kind of surprised. Doctors don't get promoted just because. 286 00:15:35,320 --> 00:15:37,400 Speaker 3: They save lives. They also have to do. 287 00:15:37,480 --> 00:15:41,240 Speaker 2: Extracurricular things, and there's something called grand rounds where you 288 00:15:41,440 --> 00:15:45,320 Speaker 2: either go to a different hospitals, say across the nation 289 00:15:45,680 --> 00:15:50,520 Speaker 2: or across the ocean for about six months and you 290 00:15:50,600 --> 00:15:54,200 Speaker 2: are a part of their doctor community and you are 291 00:15:54,280 --> 00:15:56,920 Speaker 2: supposed to be sharing with them what you know and 292 00:15:56,960 --> 00:15:58,560 Speaker 2: what you learn in your expertise. 293 00:15:59,120 --> 00:16:00,640 Speaker 3: And they just couldn't find. 294 00:16:00,400 --> 00:16:03,120 Speaker 2: Women, especially women between the ages of thirty to forty 295 00:16:03,640 --> 00:16:08,720 Speaker 2: who were doctors, to apply for the program, and because 296 00:16:08,800 --> 00:16:11,680 Speaker 2: they weren't applying for the program, they weren't getting promoted 297 00:16:11,720 --> 00:16:17,560 Speaker 2: to the next level. So during COVID mess general, I 298 00:16:17,600 --> 00:16:20,040 Speaker 2: mean it was they leveled the playing field because nobody 299 00:16:20,160 --> 00:16:23,760 Speaker 2: was I was traveling. So the grand rounds were done 300 00:16:24,520 --> 00:16:31,040 Speaker 2: through zooms and they encouraged women to become a part 301 00:16:31,080 --> 00:16:34,240 Speaker 2: of this program and to really apply for grand rounds, 302 00:16:34,280 --> 00:16:37,520 Speaker 2: and they got about thirty percent more women, and they 303 00:16:37,560 --> 00:16:42,680 Speaker 2: had ten percent more women promoted the next year. So 304 00:16:42,720 --> 00:16:45,120 Speaker 2: you could honestly see the difference there. 305 00:16:45,400 --> 00:16:48,480 Speaker 1: Look at that. It's simple stuff. This does not have 306 00:16:48,560 --> 00:16:52,360 Speaker 1: to be groundbreaking now. It's very simple things. You just 307 00:16:52,400 --> 00:16:54,680 Speaker 1: have to sit down and you know, take a few 308 00:16:54,680 --> 00:16:56,640 Speaker 1: minutes and really take a look at the numbers. Because 309 00:16:56,680 --> 00:16:59,640 Speaker 1: I'm sure if you're running a successful business, or even 310 00:16:59,640 --> 00:17:01,400 Speaker 1: if you're just in a startup and you're trying to 311 00:17:01,400 --> 00:17:03,760 Speaker 1: get things going, there are so many things that are 312 00:17:03,760 --> 00:17:06,240 Speaker 1: going around at one time, you may just not even 313 00:17:06,320 --> 00:17:08,960 Speaker 1: realize that this is happening exactly. 314 00:17:09,280 --> 00:17:11,320 Speaker 2: And that's why we say look at the math, because 315 00:17:11,320 --> 00:17:15,360 Speaker 2: you may be very surprised. And again, of course it's 316 00:17:15,359 --> 00:17:18,199 Speaker 2: the math not just gender, but it's also you know, 317 00:17:18,240 --> 00:17:20,280 Speaker 2: the racial wage gaps, and to look at those. 318 00:17:20,400 --> 00:17:22,600 Speaker 1: Right, right, and of course you know there are inevitably 319 00:17:22,680 --> 00:17:25,600 Speaker 1: going to be perhaps some people who are doing it deliberately. 320 00:17:26,240 --> 00:17:27,720 Speaker 1: How do we change that? 321 00:17:27,760 --> 00:17:29,960 Speaker 2: That is what the law is supposed to help in 322 00:17:30,080 --> 00:17:33,480 Speaker 2: terms of equal pay for equal work and MEPA that's 323 00:17:33,480 --> 00:17:36,359 Speaker 2: supposed to help that. It's much more hard, you know, 324 00:17:36,400 --> 00:17:39,479 Speaker 2: it's much more difficult to show discrimination that you're not 325 00:17:39,520 --> 00:17:47,880 Speaker 2: getting advanced because people are discriminating against you. So it's 326 00:17:48,480 --> 00:17:51,880 Speaker 2: there are laws, of course out there that are supposed 327 00:17:51,920 --> 00:17:54,320 Speaker 2: to help you, but they take. 328 00:17:54,240 --> 00:17:56,280 Speaker 3: Years and take a long long time. 329 00:17:56,440 --> 00:17:58,720 Speaker 2: So that's why we're pretty happy that we have two 330 00:17:58,760 --> 00:18:01,919 Speaker 2: hundred plus employers who are interested in doing it on 331 00:18:01,960 --> 00:18:05,040 Speaker 2: their own and figuring out how they can make these 332 00:18:05,080 --> 00:18:05,879 Speaker 2: gaps go away. 333 00:18:06,040 --> 00:18:08,280 Speaker 1: Well, and you're working greater Boston, so it's not just 334 00:18:08,400 --> 00:18:11,760 Speaker 1: Boston proper. Really, anybody I'd say, what within four ninety 335 00:18:11,760 --> 00:18:13,960 Speaker 1: five or one twenty eight, how far are you going 336 00:18:14,000 --> 00:18:14,440 Speaker 1: out here? 337 00:18:15,600 --> 00:18:17,000 Speaker 3: We go out to four ninety five. 338 00:18:17,200 --> 00:18:22,360 Speaker 2: Oh great, and we're talking about going statewide, but right 339 00:18:22,400 --> 00:18:25,120 Speaker 2: now we're within the four ninety five corridor. 340 00:18:25,560 --> 00:18:27,840 Speaker 1: Okay. So somebody owns a business and they're listening, and 341 00:18:27,880 --> 00:18:30,400 Speaker 1: they happen to be working in like Metro West or something. 342 00:18:31,119 --> 00:18:32,320 Speaker 1: You're happy to take their data? 343 00:18:32,880 --> 00:18:36,640 Speaker 3: Of course, of course, wonderful. Give me a call, we'll 344 00:18:36,640 --> 00:18:37,080 Speaker 3: talk to you. 345 00:18:37,200 --> 00:18:40,919 Speaker 1: We will happily take your data for good research, you know. So, 346 00:18:41,040 --> 00:18:43,480 Speaker 1: I guess my final question to you is, if somebody 347 00:18:43,520 --> 00:18:47,480 Speaker 1: is listening and they're having some doubts that they are 348 00:18:47,520 --> 00:18:50,399 Speaker 1: being paid properly, what is your advice to a worker 349 00:18:50,560 --> 00:18:53,800 Speaker 1: who either wants to make sure that they're getting paid 350 00:18:53,840 --> 00:18:57,080 Speaker 1: equitably or maybe they just aren't sure. 351 00:18:57,560 --> 00:19:00,560 Speaker 2: Again, our audience and our employers, So what I would 352 00:19:00,560 --> 00:19:02,960 Speaker 2: tell you from our employer's point of view is go 353 00:19:03,040 --> 00:19:06,080 Speaker 2: talk to your HR people, and especially now with the 354 00:19:06,119 --> 00:19:10,359 Speaker 2: passage of the Francis Perkins Workplace Equity Act, that is 355 00:19:10,400 --> 00:19:13,320 Speaker 2: the entire point is that these hard conversations are going 356 00:19:13,359 --> 00:19:15,560 Speaker 2: to have to start happening because there's going to be 357 00:19:15,680 --> 00:19:19,120 Speaker 2: transparency about what the band is in terms of what 358 00:19:19,160 --> 00:19:20,280 Speaker 2: your job should be paid. 359 00:19:20,680 --> 00:19:21,880 Speaker 3: And this is going to make a. 360 00:19:21,840 --> 00:19:28,560 Speaker 2: Real difference internally, so start having those hard conversations. Hopefully 361 00:19:30,040 --> 00:19:33,000 Speaker 2: the employers are being trained on how to speak about 362 00:19:33,040 --> 00:19:36,640 Speaker 2: these things. But employees should not feel in any way 363 00:19:38,040 --> 00:19:41,399 Speaker 2: threatened by going to HR and talking about this because 364 00:19:41,720 --> 00:19:43,000 Speaker 2: it's kind of expected now. 365 00:19:43,240 --> 00:19:47,679 Speaker 1: Wage Gap Calculator dot org is your website for employers 366 00:19:47,720 --> 00:19:50,600 Speaker 1: to go to and navigate that pretty straightforward if they 367 00:19:50,640 --> 00:19:53,280 Speaker 1: want to get that information. How else can people get 368 00:19:53,320 --> 00:19:55,439 Speaker 1: a hold of you? Employers are just people who are 369 00:19:55,440 --> 00:19:56,520 Speaker 1: interested in your work. 370 00:19:56,720 --> 00:20:01,240 Speaker 2: They can go to our website at the thhe BWWC 371 00:20:01,520 --> 00:20:05,959 Speaker 2: dot org and you'll see everything you need to about 372 00:20:05,960 --> 00:20:08,720 Speaker 2: our organization, but also a contact form and we will 373 00:20:08,760 --> 00:20:10,360 Speaker 2: get in touch as quickly as possible. 374 00:20:10,480 --> 00:20:14,960 Speaker 1: All right, VBWWC dot org. That's it, all right, Well, 375 00:20:15,040 --> 00:20:17,159 Speaker 1: Kim Borman, it is wonderful to have you here on 376 00:20:17,200 --> 00:20:21,560 Speaker 1: the show. Executive Director of the Boston Women's Workforce Council. Kim, 377 00:20:21,600 --> 00:20:23,600 Speaker 1: thanks so much for the time and the education. I 378 00:20:23,600 --> 00:20:24,280 Speaker 1: appreciate it. 379 00:20:24,400 --> 00:20:25,280 Speaker 3: Thank you very much. 380 00:20:26,600 --> 00:20:28,560 Speaker 1: Have a safe and healthy weekend. Be sure to join 381 00:20:28,640 --> 00:20:31,160 Speaker 1: us again next week for another edition of the show. 382 00:20:31,200 --> 00:20:34,960 Speaker 1: I'm Nicole Davis from WBZ NewsRadio on iHeartRadio,