Tech & Innovation Blog
Great Stories: From LEGO® Bricks to Data
Senior Leaders, Innovation, How We Work
ADP is in the enviable position to use our data to continue to make impactful and meaningful changes across organizations.
Great Stories: From LEGO® Bricks to Data
By Jack Berkowitz, Chief Data Officer, ADP
My kids loved LEGO® bricks when they were growing up. They’d play for hours separating the pieces to get the right sizes, analyzing what they had, and then putting them together to build massive cities. I’d watch as they’d use the structures to create stories about different places and events that would happen in the cities they built. It was exciting to see. They knew that individually, each LEGO® was important. They weren’t interesting when looked at as individual pieces. It wasn’t until the pieces were all together that they shined and were able to work together to tell a great story.
As ADP’s Chief Data Officer, I lead data and analytics management in partnership with service, product, and sales operations leaders. In my role, I have a unique lens into how we manage data across our products. ADP has the most comprehensive workforce data anywhere, and we’re able to take that data and help our clients create the stories they need to make real-time and long-term decisions.
Individually, like a single LEGO® piece, each element of data by itself means almost nothing. However, when it’s constructed together, we’re able to build stories, gain insights, take action and make informed decisions. With the right data, insights, and vision, we’re accelerating the use of data as an asset to help our clients.
When we look at our data strategy, we can break it down into four areas for our clients:
- Protect My Data: With a focus on data security and governance, we think like owners and can applaud how we protect our clients’ data. Our clients respect our processes and trust us to keep their sensitive information private. With a culture rooted in integrity, we are all privacy and data evangelists.
- Answer My Questions: ADP’s unmatched data platforms and analytics help clients make better decisions about their people. The amount of data across ADP’s platforms is astronomical. We serve data in meaningful ways for immediate evaluation, understanding, and action. For clients using ADP Human Capital Management (HCM) platforms with capabilities through ADP DataCloud, analytics help our clients explore data, get insights and benchmarks against which to compare themselves in a truly differentiated way. Without insights, it’s just raw data. ADP is committed to helping businesses take reliable insights from the right workforce data in a way they can understand and take action.
- Improve My Experience: Through our data transformation and initiatives, we are paving the way our data is used to proactively respond to client needs, solve problems that keep them up at night and help our clients make real-time decisions. We’re working on developing innovative products that use our workforce data to help organizations gain reliable insights to invoke action and achieve results. However, it’s beyond products. We continue to innovate and strategically centralize client data from their first through current interaction into one system, resulting in a better client experience.
- Guide My Future: We will expand our solutions to help shape business decisions and investments. We can identify new ways for businesses to tap into the massive ADP data set, including new use cases and user personas. For example, geographic income data may provide insights to help companies figure out where to build their next location, or this data could enrich valuation models for the investment community. The potential is endless, especially built with our commitment to data privacy at the foundation.
We’re continuously proving ADP is the undisputed leader in data. With solutions such as our award-winning ADP DataCloud, we can take our information and offer clients something no one else can. Recently, our ADP DataCloud Diversity, Equity and Inclusion dashboards won the Top HR Product from Human Resource Executive, marking the seventh consecutive year ADP earned this award. ADP DataCloud was additionally a recipient of the AI Breakthrough Awards, Data Breakthrough Awards, and Stratus Awards for Cloud Computing, owing to its powerful capabilities and latest enhancements.
The past 20 months have changed the world of work, and people’s data has never been as important as it is now. Businesses of all sizes across every industry are using (and asking for) people data at rates we’ve never seen before. There’s a massive global shift in hiring needs, patterns, and retention. Businesses need information about industry trends and their ability to match or exceed where the global workforce is shifting. Real-time people data is what drives clients’ decisions, product innovation, and the global economy. ADP is in the enviable position to use our data to continue to make impactful and meaningful changes across organizations.
I’ve never been more excited to work in this space than I am at this moment. I’m enthusiastic and focused on where we’re headed. It’s about taking data to tell a story, and it’s exciting. It’s not unlike the excitement my kids experienced when I brought them years ago to LEGOLAND® (both in California and the U.K.), where creations they made in their imaginations came to life in real-time.
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Tech & Innovation Blog
How ADP is Using Data to Make Our Clients—And Ourselves—More Diverse, Equitable, and Inclusive
Senior Leaders, Innovation, Future of Work
ADP has a culture where you can raise your hand and suggest something new no matter your role or background.
How ADP is Using Data to Make Our Clients—And Ourselves—More Diverse, Equitable, and Inclusive
By Giselle Mota, Principal, Future of Work
With more than 900,000 clients around the globe, we at ADP often notice shifts in the working world relatively early on—and that was certainly the case with the increase in corporate attention toward diversity, equity, and inclusion. To help our clients and internal teams track DEI, we launched the DEI Dashboard in December 2020, which offers insights and actionable recommendations to form more substantial teams.
Giselle speaking on TED Talk.
Getting Started: Data-driven insights
The ADP team tackles the DEI with a natural approach from a metrics point of view; we have always been a data-driven organization. By gathering time and attendance information, we can give clients helpful insights into things like managing overtime costs so they can make operational decisions. Our human resources platforms contain a wealth of demographics, including team members’ races, ethnicities, genders, ages, and disability statuses. What’s more is we help our clients understand the employee experience throughout their entire lifecycle, from interviewing, onboarding, leadership development to compensation and retirement.
Going Deeper: A push for accountability
Our team added filtering options that allow clients to get more granular with their newfound insights. One such resource is our new Candidate Relevancy app, which uses Artificial Intelligence (AI) and Machine Learning (ML) to help recruiters organize the thousands of résumés they receive. This tool has become critical for helping mitigate unconscious biases. We train the model to eliminate discrimination by focusing only on the skills and competencies needed for the roles. At the same time, we’ve made sure all hiring managers have access to make human decisions on pursuing candidates. The same is true with our AI-driven Chatbots that provide pre-screening functions for recruiters.
Giselle M.
Looking Inward: ADP’s journey
Our team recognized the DEI Dashboard project as transformative for both our clients and for ourselves. Like many organizations, we have long championed diversity, equity, and inclusion. But we knew there was room for a renewed and enhanced approach—and it had to begin with the people creating the DEI Dashboard.
While our Data Science team took the lead on the initial build of the platform, we brought in experts from each of our products to help us understand how we could reimagine through a DEI lens. Our goal was to expand on EEOC requirements and consider anything relevant to our clients and their employees, creating more equity across the recruiting space.
With our goals in mind, the insights we gathered from the DEI Dashboard on ADP have led to several new initiatives and processes, including surveys, mentorship, leadership development programs for underrepresented groups, and the job auditing process for discriminatory languages. Not only did we hire recruiters who specialize in finding diverse talents, but we also focused on disability inclusion, from raising standards for vendor products to rebuilding product features. ADP is committed to achieving a fully accessible user experience across our products.
What’s Next: The inclusive future of work
Giselle M.
We have continued to evolve the DEI Dashboard since it launched, and a long roadmap still lies ahead. One upcoming project is benchmarking—leveraging the unparalleled scale of ADP’s data and insights to help our clients understand how they stack up against other companies in their demographics.
My colleagues and I continue to ask questions, regularly creating new projects for ourselves. For example: Should remote and hybrid workers be paid differently apart from their in-office counterparts? How can we move beyond pay equity to true financial inclusion by giving employees the guidance they need to build wealth? We should have a lot to keep us busy!
With global and social changes happening during the last year and a half, I have seen our team move quickly and respond with solutions. ADP has a culture where you can raise your hand and suggest something new no matter your role or background. My Future of Work teammates and I are living proofs. With this mindset and institutional support in place, I believe we lead the way to a more inclusive future of work.
Interested in a tech career at ADP?
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Tech & Innovation Blog
GPT’s Jesse W. Won Built In’s Inaugural Tech Innovation Award
Lifion, Innovation, Award
Jesse joined ADP just over a year ago, and his work on the Engineering Reliability (EREL) team for Lifion had already created an impact. He shared insights on how ADP is pursuing new technologies to benefit the world around us.
GPT’s Jesse W. Won Built In’s Inaugural Tech Innovation Award
Jesse W., the Senior Director System Reliability Management, recently won Built In’s Inaugural Tech Innovation Award, honoring visionaries in tech space and making significant contributions to the world of tech.
Jesse helped created a Global Reliability Operating Model that gives developers clearer direction, more agency, and improved job satisfaction while allowing them to deliver more innovative codes to customers faster and with fewer mistakes. His contribution to ADP represents a new culture of ownership-driven outcomes rooted in document-driven engineering, self-service onboarding, and human-centered designing.
Jesse focused on his team, “I want to give credits to the teams we work with. Without them, we would not be able to execute this larger strategy.” He worked with engineering leaders from product-minded approaches to backend engineering, connecting technology capabilities to business goals. Together, they build faster and safer software.
What are some fun facts about you?
I am an innovation leader, a prop plane pilot-in-training, and a vintage Japanese watch collector.
Could you tell us about the Engineering Reliability (EREL) team?
The EREL team is a platform engineering group that builds tools and infrastructure with a vision to help enable an outstanding developer experience at Lifion. It offers capabilities for feature teams to manage their security and develop their cloud-native infrastructure. My team works with them to provide self-service incident and change management.
A vital part of this success is the Global Reliability Operating Model (GROM), a holistic approach to building complex software in the cloud. GROM has allowed software teams to work autonomously, pushing collaboration to the max and minimizing complexity within Lifion’s systems. EREL is constantly building upon its systems, focused on feedback to understand what tools and pipelines can evolve to improve the user experience.
What words would you use to describe engineers at work?
Simplify, Innovate and Grow. EREL actively measures its impact based on real data available to them within the systems. Utilizing real-time data makes this possible and provides a creative space for all engineers at work.
Jesse (right) with his family
What advice do you have for those with a focus on innovation?
Separate the ideation and inspiration from the execution allows your leadership and individual contributors to devote their full intellectual capacity towards solving problems in the most innovative way.
Don’t limit yourself to what you think is possible. Look out three, four, five, or even twenty steps ahead of what can be done right now, then figure out the north start you need and inspire your teams to meet the larger business goals.
Congratulations, Jesse and the EREL team!
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Tech & Innovation Blog
Innovating Retirement: How ADP Uses Machine Learning to Plan for the Future
How We Work, Culture, Team Collaboration
At ADP, people don’t have to be a leader by title. If there is an idea, and you can think big and innovate, that’s all you need.
Innovating Retirement: How ADP Uses Machine Learning to Plan for the Future
As one of the country’s leading HR technology companies, ADP uses its unmatched data in exciting and new ways. We had an opportunity to catch up with two people critical in recognizing the opportunity to innovate and create a machine learning product for Retirement Services.
Hemlata R., Director of Product Development, oversees the entire product development process. In addition to managing scrum masters, architects, developers, and tech leads, she also heads web development, mobile development, and the machine learning strategy for the entire Retirement Services team.
Sanjay V.R. is the Lead Application Developer and oversees the machine learning practice within Retirement Services.
We asked them how their small team creates cutting-edge technology to build data-driven solutions for their customers, and here’s what they said:
First, let’s hear a bit of what brought you to ADP.
Sanjay V.R.
Sanjay: I started at ADP as an intern while I was attending school in upstate New York. Once I completed my internship, I actually had multiple offers to join other companies. I chose to stay at ADP because getting good opportunities is one of the most challenging obstacles in today’s job market, and at ADP, if you put in the work, getting rewarded is the easiest thing.
Hemlata has been my director for 80% of my career, and I’ve been able to turn to her if I have an idea or if I want to pick up a new role or responsibility. She’s always encouraged me. My senior leaders make sure to recognize me for my hard work. I’ve been promoted three times in my three years at Retirement Services, and that speaks volumes.
Hemlata: I also had several offers when I was looking for a change after my last job. I was attracted to ADP because I’d heard that it was moving toward being more of a technology company that valued innovation—and that its leaders prioritized diversity and inclusion. I’ve seen first-hand that you don’t have to have an impressive title to be a leader here. You can be a leader at any level. You can innovate at any level, and ADP supports and invests on that front. I’m so happy and thrilled that everything I had heard about ADP turned out to be more than true.
Speaking of innovation, tell us about the Retirement Services product you built.
Sanjay: People Like You is a new feature based on machine learning algorithms; it helps participants better prepare for their retirement by offering benchmarks on how people similar to them are planning their retirements. For example, we can show you what percentage of your coworkers are contributing to their 401(k)s and how much of their income they’re contributing. Maybe you contribute 5%, and when you see that your peers contribute 8%, you have the confidence to invest more.
In the retirement industry, advisors usually group people by age or salary and then start giving advice. We wanted to answer the question better and offer advice based on what others in similar socioeconomic situations are actually doing.
Hemlata: ADP pays one out of six Americans; the amount of data we possess is unparalleled. When I joined the company, we discovered that many of our clients’ employees do not contribute to 401(k)s. Since we work for Retirement Services, we saw this as a problem. People often look at their peers and follow them, so we asked ourselves how our data could help create a solution.
How did you go about building People Like You?
Hemlata: We tried to combine the mind and the machine by leveraging our experts’ expertise at ADP and machine learning.
Sanjay: We have folks at ADP who have over 20 and 30 years of experience in Human Resources and Retirement Services. As much as data is our strength, our people and their expertise are equally valuable. So first, we talked extensively with our internal stakeholders since they already know the ins and outs of the industry intimately. Then we conducted market research to understand people’s motivations and concerns better about retirement investing.
After that, we went back to our data sets—everything we have from our payroll and retirement resources—and we started looking at this socioeconomic information to see any relevance between multiple parameters. For example, does age or compensation influence your retirement decisions? What if you’re married, single, or have kids? Based on our internal and external research, we were able to identify somewhere around 30 factors that make an impact; we then narrowed those factors based on the extent of their influence on an individual’s decision. Once we started analyzing that data and built models to create the personas, we realized that we had something worth integrating with our existing retirement products.
When we began this project, it started on a small scale. It was just one other data scientist and me. The two of us created the machine learning part of it, but as we built specific pieces of code for the APIs, we pulled in engineers as we needed them.
Were there any complications you had to work through?
Hemlata R.
Hemlata: The tricky part for me was to make sure that we were compliant with all the security olicies. People trust ADP. It’s our brand. That’s why they come to us for payroll, compliance, workforce management, legal, and security solutions. ADP knows what to do and takes excellent care of its customers, and we take this to heart and always obtain the consent of our clients and employees before we include their data. We’re extremely careful to keep all the data anonymous and not look into any specific client or individual employee data.
Sanjay: Yes, ADP is very sensitive toward privacy laws, so we were very specific about reading only as much data as people were comfortable with. One of the biggest advantages we had was that we partnered with ADP’s DataCloud team. They acted like a data custodian in the project and were responsible for making the data anonymous. They also made it possible to identify an employee—only with their consent—if I needed to access that data to connect specific pieces of information.
I’m a millennial, and I’m one of those people who always clicks on “Do Not Sell My Info” on websites. So, I’m particular about my data, and I think I always had that in the back of my mind. DataCloud made my job easy in that regard.
How do you think machine learning will affect your future work?
Hemlata: We are looking at leveraging this concept of combining the mind and the machine on other aspects of our business, such as compliance processes. As of now, we have used descriptive and prescriptive analytics. Next, we are planning to use predictive analytics to help our clients predict the upcoming required actions. ADP and our clients can solve any predicted problems upfront. We’re always trying to see how we can take our ideas and solutions to the next level.
Sanjay: This is the beginning of an entirely new way of thinking about improving our clients’ experience. We want to look beyond traditional solutions to ensure our clients and their employees feel empowered by our products. ADP also has a general excitement to identify pain points to be resolved and processes we can enhance using machine learning.
Speaking of your customers, do you see any results from People Like You? Are more people signing up to contribute to their 401(k)s?
Hemlata: The results are way better than what we expected. Employee contributions and new enrollments have definitely increased. We also saw this product gain so much attention internally within ADP that several other teams contacted us to see how they could leverage similar solutions within their departments. It’s been fascinating to see the outcomes and the interest from all the other teams.
Sanjay: It’s funny because a bunch of my peers was like, “Oh, I don’t really need a 401(k). I’m too young for that.” Then, two or three months after we released People Like You, someone remarked during lunch, “Hey, did you know that I just signed up for my 401(k)?” Then others joined in—four people also signed up. It’s just a wonderful experience when you hear people say your solution impacts their lives.
After we launched, Don Weinstein pinged me on Webex Teams and said what a great job I’d done and that he was looking forward to what I’d build next. It was a total fanboy moment for me.
Hemlata: This goes to show you what I was saying earlier. At ADP, people don’t have to be a leader by title. If there is an idea, and you can think big and innovate, that’s all you need. Once you have that, you can take it to any level, and people will be so open to talk to you, encourage you, and help support any of these thoughts. It’s really amazing to see that!
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Tech & Innovation Blog
CI/CD at ADP: Going Global with GitOps
Engineering, Innovation, What We Do
Leo Meirelles first worked at ADP for more than six years as a lead technical analyst and senior software programmer. Then he left for stints at Google and The New York Times, where he had the opportunity to learn new environments, improve his knowledge, and refresh his tech stack—all benefits he brought with him when he returned to ADP in 2016. Below, Leo discusses the continuous integration and development (CI/CD) process he implemented with his team and the company-wide plans for adopting it.
As we globalize and streamline GitOps, we are laying the foundation for our future.
CI/CD at ADP: Going Global with GitOps
By Leo Meirelles, Principal Software Engineer and Principal Architect
As a principal software engineer and principal architect at ADP, I work on multiple projects and provide support as needed. Since ADP has a lot of products, one of our biggest challenges is streamlining our processes. Our engineers work on payroll systems, retirement services, and pension services, to name some, for both small and large companies—and that’s just in the United States. Each country we support has different portfolio options for companies that integrate ADP products. Since we continue to evolve our technology, we’re never short on opportunities.
I worked at ADP for close to seven years the first time. When I returned in 2016, I got involved with a great project to aggregate multi-country payroll; we integrated with in-country providers, with internationalization (i18n) and accessibility (a11y) support. I’d spent a few years at The New York Times and then eighteen months at Google, and I was excited to bring that skillset back to ADP. At ADP, I’d always liked the people I worked alongside, and with ADP’s pivot to a technology-first company, I knew I could have a real impact here. In particular, I had the opportunity to implement continuous integration and continuous deployment (CI/CD), first with one group, then two, and now we’re looking at global implementation throughout the company.
CI/CD combines continuous integration and delivery practices, relying on automation to guarantee that code changes are efficient and that application deployments are reliable. With the project I was initially working on, we had teams in multiple countries and multiple time zones, and when you have such a large amount of people spread out like that, you need to stay efficient.
Before this project, to deploy in a QA environment, we needed a UI Development Lead and a Backend Development Lead to approve a deployment release request since they were the most likely to be aware of any issues that could hinder QA work. They had to give the green light and say, “Hey, this code is good to go.” But when you have 30 developers, things get more complicated since you have to merge multiple pull requests. On top of that, we have eight microservices in the backend and three micro frontends—the login, the old application, and the new application, because we’re migrating a few things toward a new Angular version. This level of complexity underscores why ADP needed a global, automated solution that can work for everyone—and why we started the CI/CD implementation via our GitOps project.
GitOps is an evolution of infrastructure as code, where you build the whole environment from a configuration/definition file, and it stays together with the application source code. Later, it can be run by machines and build new environments without human intervention. The idea of GitOps is to use tools that you already use every day, which makes things easier since you don’t have to add new tools to your stack or change how you get work done. Instead of emailing, messaging, or calling someone to say, “Hey, can you deploy that version for me?” now you do that using Bitbucket and make a pull request, make a commit, and merge your code. After that, everything else happens automatically behind the scenes, and you can skip trying to find people for approvals. Because both the infrastructure and your code go into Bitbucket—in fact, the whole process for a new release—we’re able to have a new deployment in 10 minutes for the local environment using GitOps once the code review is finished, approved, and merged. From that point onward, QA owns the release management for their environment; they control what goes into the environment without involving DevOps and managers, giving more autonomy for the team to manage releases.
We knew that having GitOps would make life easier for DevOps and allow them to focus on other things, like maintaining production and improving monitoring and availability. Also, engineers deserved to oversee their code. But we had to figure out the best way to introduce the new process. So, we started slowly to minimize disruptions with the current software development process and give people time to adjust to a new way of doing things.
We had to get developers over the fear of breaking something. Everybody wanted to be either first or last. If they were first, they wouldn’t have to merge their code, and if they were last, they could make sure everything was working before adding theirs. Until we got into a rhythm, it was a stressful time. But once the teams started adopting the new process, things changed dramatically in a positive way. Instead of making considerable changes in the last few days of a sprint, we slowly transitioned to making several small changes every day. And if something didn’t work, it was a straightforward process to revert changes. Since everything is on Bitbucket, we can see the previous versions, making the long-term management much easier.
I talk to team members often, and we’re in a sweet spot right now. What really helped adoption was implementing a process when everyone was ready and open to trying a new process. I prefer to lead by example rather than trying to force people to do something. But as time passed, we built trust when it became obvious the new system worked. Now people have the flexibility to start working in whatever time zone they’re in and look at our online chats to see what’s changed since they last looked. We even have a bot that judges the quality of a pull request. We have twenty to thirty deployments in our development environment every day, and no one even notices. And if we need to make a production fix, we can do it in 20 minutes using GitOps and our other automation tools.
I’m looking forward to the full adoption of GitOps globally. We have a lot of products on a lot of platforms, so that will take time. But there are a lot of exciting things happening right now at ADP. We’re an evolving tech company and developing a cohesive development engineering team. Since I’ve been back, I’ve seen the environment grow stronger. We communicate and share between teams, do a lot of cross-team collaboration, and help drive innovation and ideas through events like global hackathons. As we globalize and streamline GitOps, we are laying the foundation for our future.
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Tech & Innovation Blog
Roll Forward: How breakthrough products are redefining ADP as a tech innovator
Senior Leaders, Innovation, Future of Work
For ADP as a tech innovator, this is just the beginning of the journey.
Roll Forward: How breakthrough products are redefining ADP as a tech innovator
Roberto Masiero, SVP Innovation Labs
From my long tenure at ADP, I’ve learned that when a company gives you the latitude to move around—either within the technology space or from technology to business or sales—you get plenty of chances to reinvent yourself. And reinvention on the individual level influences the reinvention of the company as a whole, which I think we really see now with Roll™.
Roll™ is a mobile chatbot platform that uses AI and natural language processing technologies to anticipate users’ payroll needs intelligently. It’s the first-ever DIY payroll technology, and it’s so intuitive that our clients just download it and go; a lot of them never even talk to a customer service rep. But while we designed Roll™ to seem effortless, it’s the product of years of creative work with a unified team. The idea for Roll™ was to simplify payroll and HR using a novel UX and platform. I run the Innovation Labs at ADP, where we develop new products as quickly as possible. We’re a relatively small team, around 30 people from diverse backgrounds and with no hierarchy, allowing us to pull together tightly as a group. It’s important to me to have a flat organization because the moment you create hierarchies, you create ways to point fingers. In the way we work, everyone shares responsibility.
We came up with the product idea for Roll™ about four years ago when we were finishing up ADP Marketplace and wondering what to do next. At the time, most of our lab projects were satellite projects, adjacent offerings to our existing core services. I thought, “What if we reinvented the core?” We saw an opportunity to improve multiple facets of our payroll platform—the architecture, the design, the user experience. We had a chance to envision a whole new system.
We fixated on this idea of events—that everything done as an action within the system should be recorded as an event. In fact, we initially named the product “E” for “events.” For example, if you hire someone, pay someone, or terminate someone, we record each action as an event. This way, we know who did what, where they did it, what time of day, and from what device. All that information taken together feeds a machine learning engine where the system gets better the more it gets used. Instead of a system with a bunch of menus, forms, and reports, we imagined a vector of events where events cause other events. We basically built the software as a workflow.
But we didn’t stop there. We also wanted to transform the UI into something much simpler and more direct. People tend to design user experiences with a sense of engagement in mind, but that’s not what we needed here. We didn’t want people engaged; we wanted them to get the job done and exit the software. So with Roll™, the user goes straight to chat and tells the system what they need, and the software understands. If it’s to hire someone, change someone’s W-4, change a payroll schedule, the user asks, and the software guides them through the process using conversational UI.
We also built Roll™ to function 100% on mobile. We decided the UX would use a simple chronological timeline, similar to Facebook or Twitter. Clients love having one place to go to see their activity: “Yes, I ran payroll yesterday evening,” or, “Great, that new W-4 went through.” In addition to optimizing for mobile, we also wanted a strong desktop presence. We noticed our desktop users liked to grab info from the system and transfer it to Excel spreadsheets, so we decided to give them an Excel-like UX.
We finished Roll™ in July 2019 and got a pilot client in August. That fall, we presented the software to ADP’s executive leadership team. We got the feedback that we were sitting on something big that works for small to large corporations. But they encouraged us to focus on the smaller markets, those with one to ten employees. So we spent a couple of months designing an additional layer of software to cater to small businesses. In March 2020, we piloted Roll™ with about 50 smaller companies who all liked what we were offering, and then the executive committee told us to put Roll™ on the market and sell it as soon as possible. So we went from pilot program to full rollout in under a year, and today we’re getting dozens of new clients a day signing up for Roll.
A big part of what makes Roll™ stand out is integrating natural language processing with machine learning. We designed Roll™ to understand the mental model of our user’s meaning. We wanted the chatbot AI to talk the way people talk.
We brought in ADP’s business anthropologist, Martha Bird, and copywriters to advocate for the user, helping us to shape the Roll™ voice. We didn’t simply want AI to predict what our clients needed for payroll purposes––though that ability was definitely important. We wanted the voice of Roll™ to demonstrate human understanding. For example, Roll™ learned to respond more positively when addressing a new hire or giving someone a raise in pay, whereas it is more subdued when discussing termination. It’s that empathetic understanding that gives Roll™ an edge in human interaction.
On the backend, we decided that we didn’t want to run servers, or even containers, like Docker or Kubernetes. Instead, we made every event a function. The beauty of functions is that they only exist while that function is running. So our cost of running Roll™ is extremely low. Using cloud services and this idea of functions is another way Roll™ sets itself apart.
Of course, Roll™ didn’t come without its challenges during the development process. Fraud is something we have to consider whenever we engineer or develop a new product. But this is what I love about the Lab: We think of our challenges as opportunities to make our products better. How can we improve? How can we automate? How can we reduce the amount of burden on the system from someone trying to commit fraud? And when we meet a challenge, everyone jumps in to help. We either fail as a team, or we succeed as a team.
I’d say we’re succeeding right now, and the beautiful thing about Roll™ is that it’s always running. We change our models to pick up on new ways clients ask for things, and every new question pulls into Roll’s knowledge and experience. So the more clients we have, the better the software becomes. It’s an unprecedented level of automation.
A program like Roll™ can help further ADP’s digital transformation from merely a payroll company into a competitive tech company. What makes Roll™ exciting is that it almost creates its own category; it’s a technological solution no one else has. We can dominate this market and apply some of the same breakthroughs—machine learning, using functions—with other ADP products. For ADP as a tech innovator, this is just the beginning of the journey.
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