Speaker 1: We're going to be talking today about how you can start to use data as your best friend in DEI work. How can you start to measure and publish metrics around DEI? So I first want to start off with what are the roadblocks before we get into the opportunities? What are the challenges of using metrics in DEI? So when you start to get into numbers, you sometimes get resistance around the idea of quotas. And I want to be very clear in this course that I don't ever want to say you should hire a woman or a person of color because they are a woman or person of color. Instead, the goal of equity is to address structural inequalities and achieve equity in hiring, where you're trying to be anti-biased to ensure that everybody, no matter the background, has a fair chance and an equal chance for opportunities in your organization. Additionally, we use DEI metrics. You sometimes get some of a fixed pie mentality, where people feel that they'll be pushed away from the table if you start to diversify other candidates into your organization. And this could also lead to related concerns that you're going to lower quality if you start to diversify your organization. There's been a lot of research on this showing these concerns are not well-founded, that female candidates are equally qualified. We mentioned a study at one point in this course, for example, where you compared two resumes. They were identical other than the name. The woman got hired less of the time, as did the person of color, simply from their name. Quality was identical. There's been interesting research, for example, by Cindy Schiapane showing that when they diversify corporate boards, there were concerns that it would lower the quality of members on corporate boards, and they found no objective difference in the qualifications of these new female board members as boards sought to diversify in terms of gender diversity. So diversity creates opportunities. It creates win-wins. It will allow better quality outcomes for organizations, as well as being the morally right thing to do. So as you start to use metrics in your organization, anticipate some of the resistance, have talking points, understand how to address the emotions underlying this, as well as the concerns, and then still move forward, because it is the most important thing that you can do is start to put data to the problem. So why establish DEI metrics? Well, what gets measured gets done. It allows you to drive action, track progress, set goals. It creates accountability for yourself and for your stakeholders. It helps you see your blind spots. It helps you pinpoint where things might be going wrong within your organization around DEI. Additionally, it keeps organizations from reverting. For organizations that have had a long history of DEI work, like the University of Michigan, who's been very active in these issues for the last 50 or 60 years, you start to see cycles of how much this is valued. And so having data on this keeps you from sliding back when energy starts to get drained. So example reasons to implement DEI metrics. So for example, a company wants to expand its Asia operations to set to track representation of employees born or raised in Asia. Another example, a large mining company seeks to increase retention of female employees by implementing a flexible work policy and wants to track whether or not this actually works. So what's the right way to start to establish DEI metrics? Well, first off, understand the dimensions you want to measure and track. Make sure you have legal permissions to use these metrics within your company, that you're actually asking for consent from employees to use these metrics. And then actually start to track this. Many companies don't have data on the gender or race of their employees, and finding ways to start to access this data is important. And then choosing metrics for tracking. Is it the proportion of diverse candidates across ranks? Is it their salaries? Is it their likelihood to get promoted? Is it the number of diversity trainees in your company? We'll get into this in a second, but there's a host of metrics you could and should be tracking out there. And then start to have baseline measurements and then goal setting and tracking progress from your baseline towards your goal. Have people responsible for this, and better if you're using objectives and key results for your employees or your organization or equivalent structures. Make clear this is part of the goals of all your managers, is to be on top of those metrics and driving towards results. And then make sure that every quarter or so, you're taking the time to actually analyze your data, understand things, how things are changing as you try to make progress. So examples of DEI metrics. So one is diagnostic. This is a pipeline analysis, for example, over what is the percentage of women or people of color employees, able or disabled employees, at every stop in our HR pipeline. From the applicants, through the interviews, to offers, to acceptance of offers, to yearly evaluations, to promotions. Those are diagnostic metrics where you can understand the people that exist. You also have tracking metrics, such as looking at things over time and how numbers change over time. And also might be, for example, attendance and training sessions over time. But what are the things that you're tracking change on? You also have metrics when you're analyzing data on ROI. So I worked with a large company last summer, where we made a DEI toolkit for them to assess every quarter that looked at their diversity, their equity, as well as their inclusion. And then we relate that to bottom line performance of the different business units, and are able to show that there is a business case for diversity, in addition to the moral case. And we're able then to pinpoint which processes for equity and inclusion are both helping most in the diversity metrics, as well as the business outcomes. So this organization, for example, had a lot of impact from both inclusion and training managers on inclusion, as well as having formal mentoring programs. So best practices for DEI metrics. Clearly communicate the why. Anticipate the resistance that might arise, and make sure you're selling the why for why this is needed. As we've talked about in this course, diversity is hard but good. Different reasons exist to value diversity, including the business case, the learning case, and the moral case. Sharing all those reasons together is important. Then make sure people are championing the process of implementing DEI metrics, and you have stakeholders who can assist with this. Make sure that you're setting realistic and achievable short and long-term goals for all the metrics that you're tracking. Make sure that you have different reports out for the different units of your organization, because DEI can vary quite dramatically even within an organization. Have grace as the organization gets up and moving on this, but then drive performance towards those goals across levels. And make sure you're reviewing and reporting on them at least twice a year, if not quarterly, to see what's moving. If you're interested for your own organization over the types of metrics you can use, if you Google open diversity data or diversity best practices, those two websites have a wealth of information of hundreds of statistics, as well as organizations publicly sharing their statistics around DEI best practices. It's a great primer if you want more ideas for how you can start to use metrics in your organization.