“Organizations are composed of people, and if the people do not change, the organization does not change,” says Dr. Randal Pinkett, CEO of the diversity, equity, and inclusion consultancy BCT Partners.

That sentiment is a key tenet of Pinkett’s forthcoming book Data-Driven DEI, which, as the name suggests, offers a framework for workplaces and workers alike to measure their diversity, equity, and inclusion efforts. With many employers now slashing their DEI programs and staff amid layoffs and budget cuts, the question has taken on new urgency: How can individual employees push themselves to change, and how can they do so in a way that moves their organizations forward? Here is a transcript of our conversation with Pinkett about just that, lightly edited for clarity.

To start, can you walk me through your framework?

Data-driven DEI, as the name implies, zeroes in on how data can be an enabler for every step of the diversity, equity, and inclusion life cycle—from conducting an assessment, to developing objectives and goals, to benchmarking promising and proven practices, to deciding what you're going to do, to then evaluating both progress and impact. It's very simply laid out in a five-step process that is all centered on the letter ‘I.’ First is what I call Step Zero, because it's not part of the cycle: What are your incentives? And then you get into the cycle where the first step is your inventory. That's your assessment. Then your imperatives. Those are your objectives and goals. Then your insights, how you're looking at what works in other contexts before you figure out what to do in your context. Then your initiatives: What are you going to do? And then your impact: How do you determine that you've made progress that you've hoped to make?

This data-driven DEI methodology is not just for organizations. It's also for people. How does a person use data to improve their diversity, equity, and inclusion journey? And how does an organization do the same?

You write that organizations do not change, people change. Can you explain more?

I believe we've done an excellent job of articulating the business case for diversity, equity, and inclusion, why it matters to an organization. We talk about how it impacts the bottom line and how it enhances recruiting and retention and employee engagement and productivity and teamwork and innovation. The list goes on and on and on. But I don't think we've done as good a job, if any job, of articulating the value to people. Why should you care about a more diverse, more inclusive, more equitable life? Put aside whether your employer cares or not. But the canonical approach is the, ‘Well, my employer cares, so I should care.’ Well, no, let's flip it on the script. You should care whether your employer cares or not.

And the reason that's so important and so valuable is because people are the building blocks of any organization. Organizations are composed of people, and if the people do not change, the organization therefore does not change. And so what I call the personal case for diversity, equity, and inclusion—not the business case, but the personal case—is it enhances your life experiences. It expands your worldview. It mitigates your blind spots. It also improves your ability to be a better team member. Your chances for promotions and advancement and even compensation, studies have shown, are enhanced when you are more diverse, more inclusive, and more equitable in your personal and professional life.

What does that data collection look like on an individual level?

There are a growing number of tools that can measure two things that you should care about. The first thing you should care about is your preferences. And that's neither right nor wrong, good nor bad, but a preference. You like water with lemon? I like water without lemon. You like it warm? I like it cold. But if I think about the Implicit Association Test out of Harvard, it's measuring a range of different preferences—a preference for associating men with being leaders and women with being supporters, a preference for associating men with math and science and women with the arts. I want to know if I have those preferences because they have implications for my decision-making. And the Herrmann Brain Dominance Instrument will measure your left-brain or right-brain preference, left logical, right creative. I want to know that because if I have a preference for logical thinking, I need to partner with somebody who's better at creative thinking in order to create a more cohesive team.

So there are all these tools out there. I've only mentioned two that will measure your preferences. And by knowing my preference, I mitigate my blind spot. If I prefer logic, I have a blind spot for creative. If I associate men with being leaders, I have a blind spot for interviewing women to become leaders.

The second thing you want to measure is your competences. That is, in some ways, a value judgment. A competence is knowledge, skills and abilities. And the value judgment says, do you have the competence or don't you? Are you good at it? A good example: The Intercultural Development Inventory can measure your intercultural competence, your ability to navigate different cultures. I want to know that, because it's going to tell me if I have areas for improvement, how effectively I can navigate different cultures, especially those different than my own.

So the way data drives diversity, equity, inclusion for people is first by conducting an assessment or inventory of your preferences to know where you may have blind spots, so you can stretch yourself challenge yourself to go beyond your preferences, and then measuring your competences to know where you can improve in your knowledge, your skills, and your ability. And therein begins your journey for data, baselining you for where you are and where you can go.

So is the idea that these tools are more objective in diagnosing something you couldn’t discover yourself through self-reflection?

These are tools, but they're not the only game in town. Those are more quantitative. And the book does a balance of quantitative and qualitative. What you can also do is seek feedback from family, friends, and colleagues. In the book we talk about what I call a diverse 360. A traditional 360 is where I have a direct report, a peer, someone who I report into. A diverse 360 says I'll get a woman, I'll get a Latina, I'll get an immigrant, I'll get a member of the LGBTQIA community, and I will ask them for feedback. That gives me a diverse set of perspectives on how well I function as a leader, as a manager, as a colleague, as a friend, as a loved one. And that gives me another set of data. So these assessment tools are part of the solution, but also seeking feedback, whether it's through interviews or even a lunch conversation, gives you valuable feedback from diverse perspectives.

Is an ideal strength of the relationship there as you build this 360? Presumably my best friend, for example, would be more biased, whereas an acquaintance might give me less straightforward feedback…

Look at a couple of different dimensions. One dimension is the level of familiarity or frequency of interactions. I think you want people on both sides of that spectrum, people who know you very well and people who know you loosely. And think about all demographics and identifiers—so ethnicity, gender, age, disability status, sexual orientation. You also want to make sure you go global, that you don't want to just confine that feedback to someone from your nationality, but that you're seeking feedback from individuals who come from a range of cultures, national backgrounds, et cetera.

When using these more objective tools or scales, how do you evaluate what is quality and what is not?

For the more formal assessments, you have validity and reliability measures. Validity is essentially saying, does this measure what it intends to measure? If it says it's measuring my personality, how well does it do at measuring personality traits? Reliability is saying, if I were to take it more than once, am I going to get the same results? Because if I take it twice and I get dramatically different results, it's not reliable when you want validity and reliability. But even in validity, there's this other concept known as face validity. And face validity says when someone takes the assessment and then they are to receive their results, how many people say, ‘Now that sounds about right, you got me, you nailed it’? That's face validity. And so many of these tools will publish their validity, reliability, and their face validity. They will survey people and say, ‘How well do you think this did in describing who you are?’

How can organizations encourage their employees a) to collect that data, and b) put it to use?

You want to give people freedom within a framework. So the framework says we have to have some semblance of standardization of the tools that are available. If everyone has a different tool, we're not speaking the same language. So we have to say, ‘Okay, for preferences, we're going to use the Herrmann Brain Dominance Instrument. And for competencies, we're going to use the Intercultural Development Inventory.’

Now having set that framework, give people freedom: How would you like to conduct your journey based on the results that you've received? You may say, ‘Well, look, my results came back and said I have a high preference for creative thinking. I don't really prefer logical thinking. I'm not really into math or numbers or quantitative. So I need a journey that says, how do I stretch my thinking abilities, my cognitive diversity, to be more appreciative of people who are more numbers and quantitative?’ I want to choose that path for me, which might be different than your path, but we had the framework within which to operate.

How would you counsel people to make sure they’re open to what these tools show them about themselves, versus reacting defensively?

I see that all the time in delivering learning and development. I say two things to people: First, don't see an instrument as trying to pigeonhole you or define who you are. See an instrument as one particular lens on where you are or where you may be. And then second, and perhaps most importantly is: See it more as a conversation than a lecture. If you see it as a lecture, then it's telling me who it thinks I am or what I do well or what I don't do. Well, no, it's not a lecture, it’s a dialogue. The instrument is saying, ‘I think you might have a blind spot. Now I'm not certain of it, because I'm not perfect, but I think you might have a blind spot.’ Maybe that's the case or maybe it's not. But I don't draw conclusions from the assessment. I see it as an advisory. Here's something for you to think about. And if you are willing and open to listen, sometimes it might be right.

What is the right altitude for addressing organizational blind spots? Let’s say, for example, that I’m a leader who notices my workplace’s recruiting pipeline is very white and male. Should I tackle that problem by pushing hiring managers to do their own personal DEI data collection?

I'm a firm believer that it's easier to remove bias from a process than from a person. Now, I don't want to ignore nor diminish the important value of inviting individuals to undertake their own journey. Because while it might be more effective to remove it from a process, it's most effective to remove it from the process and the person.

But if I focus on process, process can sometimes—not always, but sometimes—for lack of a better word, legislate what people have to do. So if my process says I have to have a woman as a part of my diverse candidate slate, then there's no way the person can deny a woman being in the mix. Now, does that guarantee a woman gets hired? No, it does not. But think about the example in Blink by Malcolm Gladwell, where the big five orchestras were 5% women, 95% men. That's unacceptable. That's appalling. They put up a barrier between the auditioners and the evaluators, so they couldn't see who was performing. And that single change to the process improved women's chances. It was a 500% increase of women in the big five orchestras. It went from 5% to 25% just off that process change. If you asked people who were evaluating talent in the orchestras, are you biased against women? They would say no. Of course they would say no. ‘I'm a good well-intentioned person.’ Let's make one change to the process. So you can't see who's performing. Let's see if it makes a change. Lo and behold it did, which means somebody had to be biased and unaware that they were biased. So by the process change, you root out the bias in people. Now, I also want to change the people, but at minimum change the process.

How would you advise organizations to apply your framework to the way that they think about their own DEI initiatives?

Step zero: DEI incentives. You have to do some organizational introspection and self-reflection, primarily amongst leaders. Why does this matter to us? Does it matter to us? And is that an intrinsic motivation, meaning it's a reflection of our organization's DNA, our mission, our vision, our values? Or is it extrinsic—we're feeling pressure from employees or pressure from what's happening in society? Clarifying that incentive extrinsic or intrinsic is step zero.

Step one: DEI inventory. Conduct an assessment to know where you are. If you don't know where you are, you don't know where you can go. So you have to do a full assessment of culture, climate, policy, practice to know exactly where you stand.

Now we can begin to set DEI objectives and goals. Objectives are a qualitative articulation of what we want to do: We want to improve our culture and climate. A goal is a quantitative measure to know we've accomplished it: We want to improve our inclusion index by 10% over the next year. That's step two.

Step three: DEI insights. Look to what works. For other organizations, it could be employee resource groups, it could be unconscious bias training. It could be using virtual reality. It could be studies that will tell you what has worked for other organizations. Don't reinvent the wheel.

Step four: Now decide what you're going to do for your initiatives. What strategies are best for your organization, given where your assessment told you you need to do better?

And lastly is DEI impact: Re-administer the same assessment. That's the cycle. So if you assessed your culture and climate to produce an inclusion index a year later, do it again. Did the initiatives work to boost that index by 10%? And if it did, in what departments, what divisions, and where did it not boost it? Now we know what to do for the next cycle and the continuous loop continues. I see a never ending cycle, as it should be.

Would this process be a fruitful one if the motivation is extrinsic?

The research tells us that intrinsic motivations are more durable, more sustainable, and more lasting than extrinsic. But the right extrinsic incentive can go a long way. If I tell you that your bonus is tied to improving your inclusive culture scores and you want that bonus, you're going to do the work to get the bonus. So I think there is something to be said for aspirationally seeking an intrinsic motivation. There's something very altruistic about it, very authentic about that.

And I would challenge, invite, encourage people to find, where do your personal values align with the tenets of diversity, equity, and inclusion? It could be your religious upbringing, it could be how you grew up in a household that was oriented around community service. It could be you just fundamentally believe that people should be treated fairly or given a fair shot or you were given an opportunity and you want to see that for others. I think it is important to ask those deeper penetrating questions, because I would be hard-pressed to think that you could not find a value alignment between one's personal values and the tenants of DEI, if you're willing to find that alignment. But if that just doesn't align, then I do think it's also worth asking, well, are there other extrinsic motivations? Do I want more compensation as studies show? Do I want to advance? Do I want to be more innovative and make better decisions? If the intrinsic thing doesn't do it for you, the extrinsic and the studies and the research that might be convincing, and maybe even dare I say a combination of both.

You write about creating a personal DEI mission statement. What is that, and how might someone formulate one?

One of the tactics I recommend in step zero, which is DEI incentives, is to clarify why this matters. I recommend developing a personal DEI mission statement. Mission being purpose, mission being calling. I often say the two most important days of your life are the day you were born and the day you figure out why you were born. And a DEI mission statement is a more nuanced personal mission statement which says, what do I believe is my calling, my mission, my purpose in a more diverse, inclusive, and equitable world? Is it my calling to be a more inclusive leader in my organization? To create a culture where people feel included? Is my DEI mission to be an example of an ally for women to break down the barriers that prevent them from having equal opportunity?

And again, that's a very personal conversation. If I've seen unfair treatment of women and believe as a man, I can do more to be an ally for them, then maybe that is what I see as my calling. But if I don't take the time to reflect and then to write, I don't know if I fully capture and clarify what that personal DEI mission is. When I say get it on paper, they say that 80% of people don't write down their goals. And I'm sure even more don't write down their DEI mission. And so I strongly encourage people to take that time and get it on paper, because I think it's an enormously clarifying and valuable exercise.

Do those ladder up to an organization creating its own DEI mission statement?

The first step that we recommend to our clients after they've completed their assessment is typically to develop what we call a DEI framework. Some might call it a DEI charter. It's a DEI mission, vision and values. And then they say to us, ‘Well, we have a mission and vision and values.’ I said, ‘Well, no, we're talking about a DEI-specific mission, vision, and values. Because that reshapes the identity of your organization. It clarifies how DEI relates or interrelates to who you are as an organization and where it is situated within the overarching context of your organizational identity.’

Mission is purpose. It answers the question, why do we exist? Why do we serve to create more diversity, more inclusion, and more equity? Vision answers, what is the picture of the future we seek to create? So we envision an anti-racist organization in the future. We envision an environment of psychological safety where all voices are honored and heard. That's vision: What's the picture we see? Mission is more purposeful, purpose-oriented. Values would be how. Values is, how should we behave in a way that is consistent with our mission along the path to achieving our vision?

Do you have any examples of organizations that have gotten it right in terms of using data to drive their DEI commitments, especially since so many made big claims following the murder of George Floyd in 2020?

Bristol Meyers Squib made a $300 million commitment. That's data. I can measure it, I can quantify it, I can evaluate it, I can know where I stand. So there were commitments that were made that weren't just talk. It was numbers behind those commitments, and accountability built into those. The other way I think it showed up is that one of the most difficult things for organizations to commit to is to tie these measures to compensation. To say, ‘We're going to spend a billion dollars with diverse suppliers. If you don't make that number, you don't get your bonus.’ And Nike is one example who said, post George Floyd, ‘We're not only going to make commitments to DEI, we're going to tie compensation to meeting those goals.’ That's what you can take to the bank.

As you note in your book, data is not fully objective. There is bias in data. Can you say more about that?

Data is a mirror. Data has the perception of being objective, but data is only as good as the source. And if the source of the data has any human involvement, which almost every data point does, bias is built in. If I'm conducting a focus group to try to understand culture and climate, and I only have white men in my focus group, there's a bias. I only have one perspective, and if I center my results on that data, it's skewed.

So we have to remind ourselves that while data often carries this perception of objectivity, data itself can be highly subjective. And it's only when we're intentional about making certain that data is representative that we can begin to mitigate the bias. Do I have multiple perspectives? Do I have multiple genders, ethnicities, nationalities, ways of living and knowing and existing? If I can engender that diversity into the perspectives from which my data is sourced, I can begin to mitigate the bias in that data. Still not perfect, but definitely trending in the right direction.