When faced with decisions to make — no matter the topic or implication — it’s human nature to seek data. We all want information to help us make the right choice, to prove our assumptions, to validate the courses of action we’re about to take. In business, data is driving important decisions in marketing, operations, logistics and other essential business functions. We’ve seen that the insights drawn from data can provide a reliable path to better outcomes.
But data about people has perhaps never been valued like it is today. People data is propelling better assessments about the workforce and the global economy. From hiring to compensation to promotion and everything in between, each data point reveals a truth that can help business leaders and human capital management (HCM) professionals make better choices when it comes to their workforce. Collectively, such data-driven decisioning can unlock the doors to a more diverse, equitable and inclusive world of work.
With the technological tools we have today, we can mine and use real-time data to track important HR metrics, but more importantly, we can proactively help solve HR issues like turnover and retention. Through aggregated and anonymized real-time data, we can start to see trends emerge and even predict the likelihood. Data detailing how long people stay at a job, how much they earn and how often they get promoted can help businesses get a clearer picture of where they stand against the backdrop of the global economy. For example, analyzing their people data enabled one company to discover the reasons for involuntary turnover in their organization. Using these insights, they changed processes, procedures, and policies, which resulted in a 20% reduction in turnover.
Benchmarking data – knowing what other businesses in your industry or geography are paying – can also mean the difference between attracting talent to your organization or losing them to a competitor. Today’s labor marketplace has more jobs than candidates and is in constant flux. Companies need to know how they compare to others on compensation, benefits, and other key employment factors. In this environment, having up-to-date HR intelligence is crucial.
There’s no question that having access to this level of detail in your people data can help make your organization more competitive in the talent marketplace. But perhaps more importantly, this transparency into your people analytics can help you identify gaps in representation and equity and take meaningful steps to close them. There’s a need in society to continue to push forward with creating an inclusive environment for everybody, and the first way to advance that goal is by measuring progress. If you can’t measure progress, then you can’t adequately assess whether you’re making improvements to people’s situations.
Examining a critical DEI challenge, let’s consider pay equity. At the end of the day, there’s nothing more important than making sure that people are paid correctly and fairly for their contributions. In the past, it’s been difficult to accurately assess differences in compensation. We’ve known for some time about gender pay inequities but they’re often too high-level for companies to tangibly action against. The resulting discussions around the root of the issue and how to fix it also become too high-level in response. This doesn’t help leaders and HR professionals who want to reduce pay inequity in their organizations. By analyzing internal HR data and then comparing it to benchmarks across industry, demographic, geography, function and job titles, companies can now pinpoint where their organization is missing the mark.
One misconception is that hiring people at a better rate of pay will help close the gap. If you bring people in, you’re not actually creating upward mobility inside of the organization. By examining compensation across a wide range of job titles and companies and evaluating what it really means for somebody to move up, organizations can better understand where they might need to adjust course.
Pay transparency is another important and often forgotten element to closing pay gaps. Data can empower and giving employees more information about the pay of their colleagues and for similar roles in their industries can help workers across underrepresented groups gain negotiating leverage.
Data can help organizations resolve these inequities proactively, resulting in higher employee retention and better talent acquisition. Data helps you see around corners and acts as a flashlight into dark places on your path forward. We can use data to identify when people aren’t paid to the level that they should be paid. We can create tools to plan and budget to adjust for those pay gaps. Ultimately, the goal is to turn real-time data into actionable insights and workplace solutions that help businesses and people thrive. By February 2022, 75% of clients using the solution have shown improvement in pay equity, making a $1.1B impact on communities in the US.
It’s important for organizations to reflect on what’s visible within their people analytics, looking for the context and connections that create uneven effects. When patterns emerge, examine what happened earlier to understand potential causes and tailor proposed solutions. When it comes to creating a better, more equitable world of work, focus on removing barriers to progress and building programs and policies into your workplace culture that allow your employees to show up as their best selves. By using data to channel your efforts, you can effect meaningful change and become part of the benchmark that challenges others to follow suit.
JOBS & UNEMPLOYMENT
Bridging the Talent Gap With Data-Driven Technology
OCT 20, 2022 1:53PM EDT
You Could Grow Your Money Without the Stress of Stocks
By Don Weinstein, Corporate Vice President of Global Product and Technology at ADP
With their priorities shifted by the pandemic, today’s workforce wants more from their employers, including greater flexibility, better work-life integration and a heightened focus on diversity, equity and inclusion – and they are willing to make a change to get what they want. We’ve seen more workers re-evaluating their place of employment, with seven in 10 workers saying they’ve considered a career move in the past year. Despite anecdotes to the contrary, we remain in a tight labor market, and the best way to get in front of the ongoing hiring challenge is to start by holding onto your experienced workers. By leveraging new data-driven technologies to create engaging work environments, today’s business leaders can confidently bridge the talent gap and create a more engaged workforce.
In this age of the employee, it is critical HR leaders continually assess their employment brand to find ways to improve the worker experience. Is your workplace environment truly inclusive? Are you giving employees challenging work that leverages their strengths? Are you taking care of their health and welfare needs? Leaders need to ask themselves these questions, while deploying data-driven HR technologies that can help identify the right solutions. For example, personalized worker surveys can help employers better understand their workplace culture and predict potential retention challenges. Another important tool is skills mapping, which breaks down jobs into a set of inter-related skills, enabling employers to mine internal applicants for potential fits as well as career development opportunities. The same technology can also assist your external recruiting function, by broadening potential talent pools to look at all relevant candidates, including those from non-traditional backgrounds.
The evolution of HR tech accelerated when our ways of working were upended a couple years ago. But these changes have kept the industry dynamic and ignited new innovations. As we look to the future, we see a lot of promise in these areas of HR tech:
AI and machine learning for sourcing talent in hard-to-fill jobs: Algorithms are being deployed to find novel talent pools to source candidates through skills matching and retargeting. These algorithms also play a bigger role in upskilling tomorrow’s workforce, providing insights on skills-based learning and career pathing that can help guide and advance employees’ careers.
Technology-driven advancements for building more diverse and inclusive workforces: Skills matching can help uncover capable candidates from non-traditional backgrounds. Sentiment analysis can be used to assess employee perceptions on the overall level of inclusiveness in the workplace. And machine learning can help identify and correct workplace equity gaps.
Of course, these approaches will be effective only if companies remain agile during times of change. Leaders need to ensure that the right systems are in place to optimize their teams’ ability to deliver good work and to adapt as the environment shifts. Essentially, businesses need technology designed for how work gets done, so they can more easily adjust at the pace of change.
You can hear more about these emerging HR technology trends, what’s to come and how to stay agile in my Nasdaq TradeTalks interview below:
Welcome to PeopleTech, the podcast of the HCM Technology Report. I’m Mark Feffer.
My guest today is Bob Lockett, chief diversity and talent officer at ADP. He’s responsible for the company’s diversity and talent strategy and oversees performance management, leadership development, engagement and culture, among other things.
We’re going to talk a lot about data and its relationship with DEI, from helping determine where a company’s at, to initiating new programs. That’s on this edition of PeopleTech. Bob, welcome. It’s great to meet you.
How does one attack the task of leading on diversity for a company the size of ADP?
Well, Mark, the first thing I’ll tell you, it’s a very challenging task, because you have so many different constituents and everybody wants their own piece of the pie. What about us? What about us? What about us?
As you can imagine, DEI is a very emotional topic, for that reason. So, the approach that I’ve taken, that we’ve taken at ADP, is really tied to doing a couple of things.
Number one is using the scientific method. You know that thing, Mark, that we learned about back in middle school, that many of us did those experiments?
You would say, develop your hypothesis. Then from the hypothesis, you allow data to prove or disprove your beliefs. And then once you do that, then you really define the problem.
After you define that problem, then start to put plans in place to achieve the outcomes. You tweak as you go, as needed, based on feedback.
So what we’ve done is taking that exact approach and say, let’s take the emotion out of it as best we can. Let’s focus on the data. Let the data be our guiding light, to help us understand where we need to focus and what we need to do.
Now, this doesn’t just apply from a US standpoint. Think about it. This is a global opportunity that we’ve embarked upon. The way I view it is, there are needs everywhere, for people to feel like they are seen, valued and heard for all that they are.
So, not only do we think about diversity… You can measure diversity very easily. You can look at demographic data. How many of these do you have? How many of those do you have?
You can measure equity by looking at pay, but the key is also to measure inclusion. So, we take this holistic approach, all data driven.
The inclusion piece is all sentiment driven, but it’s really leveraging the scientific method and leveraging data, to help tell our story.
Can you expand a bit on how data is used in DEI work? I mean, you mentioned that this is a pretty emotional subject. It always strikes me as interesting when you apply data to an emotional subject. How do they work together? So can you talk about that?
Sure. I could tell you the stories of how we landed where we are, with some of our things.
The first thing that we did as an organization, when I took over the role, I wanted to understand how we looked, because I have a vision that our associate population in our company is reflective of the communities in which we operate and the clients that we serve. That’s very specific and very clear.
How do you test that, your hypothesis about that? How do you make it a realistic vision?
We looked at about three or four different datasets. One dataset was a census data. And as you know, the census data doesn’t mean that everybody’s working.
So, we looked at the census data and we say, “What’s the representation for African Americans, Hispanics, Asians, white women, everybody in our organization?” Let’s lay that out to understand it.
Then we looked at the Bureau of Labor statistics data. Of the people in the workforce, let’s take a look at how that compares and then let’s compare that against our information.
So, we compared it against our information, I’m talking specifically in the US and said, “Huh? Where do we have gaps?”
My hypothesis was that we didn’t look like the communities in America, but the reality of it was, we did. So, I was really impressed. I was like, wow, this is great news.
But as you look at the data, we also found that when you look up in the organization, you don’t have parity in representation for two populations in particular, which were African Americans and Hispanics.
We said, they represent 15% of the overall workforce in the US, for Hispanics. Let’s say it was 11% for African Americans.
Well, we noticed a gap in our company of about four percentage points each way, for African Americans and Hispanics.
We said, well, we should close that gap, because as you come to an organization, you also want to be able to see if there are opportunities for you to advance.
If you don’t see anyone that looks like you, in management level positions, then you start to wonder if you have a real future there. So, that was our quest.
This is how we use data to really understand and tell our story and to put plans in place to do it.
Now, notice the nuance here. Because again, if you go back to my original hypothesis, that we didn’t look like that, we did, but then we pivoted very quickly, because the data told us a different story. We said, that’s where we’re going to focus our efforts.
Now, some people use, Mark, data to try and boil the ocean. You can’t do everything. You can’t be all things to all people. That is a recipe for failure, particularly in DEI.
So, that’s why we have a very narrow focused approach. We have multiple initiatives that we work on, but suffice it to say, that was our main effort, for us to be able to say, we’re moving the needle when it comes to leadership representation in our company.
Now, do you think your company is an outlier in that, or do you think that more corporations are starting to get on board with the idea of using data in this regard?
Yeah. I think it’s a mixed bag, Mark, is probably the best way to describe it. Most organizations will take a look at their data. They’ll focus on where they think their opportunities are.
But it depends on where they are in their journey, their DEI journey, which I always talk about, that not everybody’s at the same place.
For us, I believe we’re an outlier. We’re an outlier because if you think about DEI, it’s one of our values. The things that really resonate in our organization, is that each person counts. In order for each person counts, by default, you have to have a DEI strategy.
Some organizations don’t put as much interest or effort into it, so there at varying stages.
It became a great corporate buzzword two years ago. Prior to that, many organizations weren’t making headway, with respect to that. So, my belief is, we’re certainly an outlier with our use of data.
Of course, Mark, that is our middle name. So, we use data to make sure that we can tell our story, to solve the problem, to understand all of those things. We’re all about measuring success. How do you measure the effectiveness of what you’re doing?
Having said that, I think we’re a bit of an outlier. I think there are other organizations that are doing great things, but I think there are some that are not doing anything because they don’t know where to start.
If that’s the challenge for them, then a great place to start is, understand your data at least. Then, think about where you want to have an impact.
Can you think of any particularly surprising things that you’ve learned from data?
I can give you a couple of examples of things that I think we’ve learned. Number one is that it’s never enough. Here’s what I mean. We had to put plans in place to do this.
I’ll just give you this example, Mark. We launched our talent task force. It was a specific focus on the African American and Hispanics/Latino community.
Well, as soon as we put that out, the first question that came was, hey, what about the Asian community? I said, “Huh? I’ve got a story for you. Asians represent 5% of our population, but yet they represent 8% of leadership.” So, there’s no problem there.
Then the next call came from the LGBTQ+ community. I said, “Huh? Tell me what the data says.”
The reason we couldn’t make a decision and put a plan in place to improve representation for that community, is because we didn’t have any data. So, that’s one of the things that will surprise you about that.
And when you don’t have enough of it, everyone wants to do these things, which is back to my point about, people get involved in this. They want to represent their constituents.
But at the same time, without the data, you can’t get involved and create corporate programs to improve something.
The second piece still ties to self-ID. If you take this to a global scale, so typically in numerous countries, they don’t collect the same data that we do in the US. They don’t collect it because their philosophies are different. It could vary, country to country.
However, there’s renewed emphasis on understanding your workforce and being inclusive. So, just imagine, you’re a multinational corporation and you don’t understand the dynamics that exist in operating in Tunisia or the dynamics that exist in operating in France or Italy and who the underrepresented groups are. So, we’re trying to capture new data.
That’s one of the surprising things, is that we’re beginning a journey globally, to do a self-ID approach.
It’s not just us, by the way. There are multiple companies now showing renewed interest in this, to say, how do we understand our workforce? How do we become more inclusive, so we can appeal to the needs of various communities where we operate?
Are you satisfied with the kind of data that’s available to you today? What could be better?
Yeah. I’m in a unique position, Mark. I tell people this all the time. At ADP, because we’re a data company… again, it’s in our middle name, I have the unique opportunity that we have our own department that does all of the analytics, pulls the data, does the comparative analysis, the sensitivity analysis to whatever we want to do.
Now, for companies that don’t have that, we do have a diversity dashboard, that gives them insights into their own information, that they may not have thought about before.
They may not have the luxury of having a large DEI department, like we do. They may not have the luxury of having the analytic capability, but we can provide them with some insights about how their organization looks, what their leadership makeup is. Oh, by the way, with pay equity too, we can take a look at that data as well.
So I think I’m in an enviable position. I’ve got all the data that I need. The key for me, is staying focused and executing, to ensure that we make a difference with our DEI efforts.
What are your overall goals for your DEI efforts? I mean, what kind of changes are you hoping to enable or enact? What has to happen for you to be able to get there?
Yeah, it’s a great question, Mark. I’ll go back to my vision. The vision that, we want our associate population to be reflective of the communities in which we operate and the clients that we serve.
That is the most important thing, because I believe that the efforts that we take to do that, will have a great cyclical impact on the environment.
Here’s what I mean. I’m not in the DEI business because I’m a social justice warrior. I’m in the DEI business because I believe that there are economic opportunities in a capitalistic society, that we can get everyone to participate in and grow the pie. I firmly believe that.
In many cases, it starts with employment. So, what do we do as part of our DEI, some of the work that we’re doing? Well, we want to hire in those various communities.
We have outreach efforts to every community, to make sure that we’re attracting the best and the brightest for our organization.
Then of course, once you get there, you have to walk the talk. So, culture is really important, Mark, in this space, to ensure that if you said you’re going to do it, then you have to do it.
My saying is, don’t talk about it. You have to be about it. So, if you’re about what you said you are, by bringing everybody together and giving everybody an opportunity, so they can be their true authentic selves, then that makes a tremendous difference.
So, that’s the talent piece of it. Getting them in, giving them the opportunities to grow and develop, and then seeing them get promoted and being able to contribute.
Now, I also talk about DEI from a business practice standpoint. Oftentimes in the past, organizations that I’ve worked for, DEI was all about some of the HR practices, which I just talked about briefly. It was all about talent practices,
But I also incorporate business practices. Business practices are really about, well, how do we tap into the ecosystem of businesses and communities?
Oftentimes, you have underserved communities, that don’t have the same opportunities to understand things.
Give you an example. We have a company that we partner with. What the founder shared with us, was the fact that for many minority-owned businesses, they only have one way to finance their business. That’s through loans from family members or debt.
So, they don’t get the full spectrum of how to do revenue-based financing for their business, or how to think about the debt market very differently, that others have had exposure and access to.
So, giving them exposure and access to the full gamut is really important, but that also requires some education. So, we partner with organizations, to do that, just so businesses can finance it.
Now, selfishly, because I am a capitalist, I believe that we should be able to capture some of that market.
We should be able to say, we’ll help them. There’s no guarantee that they’re going to come back and nor is there an expectation, but just imagine if we’re the ones that help them understand how to run payroll.
I said, “We want you to focus on your business. If you make pizzas or if you have a restaurant, we want you to focus on what you do best. Let us do what we do best, which is run payroll, help you do time and attendance and help you with all of those other things. That’s what we do”
So, I think it’s important for us to extend our reach into the underserved communities, such that we can help raise the tide for all boats. That’s really the impetus here.
Say, if we do this the right way, DEI becomes much more holistic, so it’s focused on the economic empowerment.
If you do that by getting people great jobs, what do they do? Well, they go spend money in their communities. If they spend money in their communities, businesses grow. And if businesses grow, for us it’s a great thing, because that means you have more people to pay from your payroll systems and the like.
So, this ecosystem approach that I think is really critical and important, when we think about DEI.
Now, the other piece, Mark, that I’ll share with you about DEI is, I’ll share two other avenues of this.
One is the environment. Our environmental practices now, have become relevant in the DEI equation.
Let me back up and give you the broader view. Most companies talk about ESG, environmental, social and governance. The environmental piece is really critical. That’s where you have, what are you going to do for greenhouse gas emission reduction?
This S is all DEI. The G is board governance or governance of whatever programs that you take a look at. So, that’s something else you have to consider as you think about DEI.
We have practices to reduce greenhouse gas emissions. The good news for us is that, we don’t manufacture anything. Probably, our facilities and employees driving to work are our largest contributors to this. But what we also focus on is, what can we do to meet target? We put together plans to do that.
The last thing I’ll mention is what we’re doing as an organization, to make a difference, as we think about DEI and the like.
We have the ADP Foundation. We make contributions to a variety of 501(c)(3)’s nonprofits, to help support them in the communities in which they operate. So, there’s this holistic view that we have about, we can do well and do good at the same time.
Bob, thanks very much. We appreciate your time today.
My guest today has been Bob Lockett, chief diversity and talent officer at ADP. This has been PeopleTech, the podcast of the HCM Technology Report.
We’re a publication recruiting daily. We’re also a part of the Evergreen Podcasts. To see all of their programs, visit www.EvergreenPodcasts.com.
To keep up with HR technology, visit the HCM Technology Report every day. We’re the most trusted source of news in the HR tech industry. Find us at www.HCMTechnologyReport.com. I’m Mark Feffer.