Tech & Innovation Blog
Women Engineer Magazine Top 50 Company.
Recognition, Awards, Women in STEM
ADP is thrilled to earn a place on this year’s 30th Annual “Top 50 Employers” in Woman Engineer Magazine for a second year in a row.
Readers of Woman Engineer Magazine chose top US companies they would most like to work for and/or whom they believe would provide a positive working environment for women engineers.
They chose ADP as one of the Top 50.
ADP is proud to build diverse teams that represent the diversity of our clients to drive innovation. At ADP, we focus on inclusion and reflect a diversity lens within our products.
Our focus on such programs as our partnership with Girls Who Code and our Women in Technology Leadership Mentoring Program has led to distinctions such as AnitaB.org naming ADP a 2020 Top Companies for Women Technologists Winner in the Large Technical Workforce category.
AnitaB.org recognized ADP for making the most progress toward women’s equity among companies with large technical workforces. We know that having a more diverse organization makes us stronger, and we are proud of supporting women in technology.
Our Global Product and Technology (GPT) organization stays close to industry benchmarks and has adopted measures to continue to drive progress. ADP also supports philanthropic organizations that nurture the career development of girls and women in the technology field, helping them fulfill their potential as future tech leaders.
Our technology leaders are committed to driving diversity, including recruiting and developing women technologists while providing opportunities for them to grow their careers.
Some recent product examples include the ADP DataCloud Diversity, Equity & Inclusion (DEI) Dashboards to help companies see real-time workforce demographics. Some other products to promote a diverse workforce include our Candidate Relevancy tools and the award-winning Pay Equity Explorer.
We strive to offer personal development opportunities through self-driven platforms, and our International Women’s Network and our Empower Committee focused on Women in STEM. Regardless of your role, we offer opportunities for women technologists. Meet Some of the Women of ADP DevOps and how they drive data-centric development.
Some recent product examples include the ADP DataCloud Diversity, Equity & Inclusion (DEI) Dashboards to help companies see real-time workforce demographics. Some other products to promote a diverse workforce include our Candidate Relevancy tools and the award-winning Pay Equity Explorer.
Visit us at tech.adp.com and learn more about what we do.
Tech & Innovation Blog
Meet Roberto! One of the brilliant ADP Machine Learning developers behind our new payroll app, Roll™ by ADP®
Machine Learning, Brazil Labs, Roll by ADP
We had a chance to catch up with Roberto at ADP’s Brazil Innovation Lab in Porto Alegre. He shares his career journey, why he chose ADP, what keeps him excited, and why it’s a great time to work in machine learning.
On February 25, 2021, ADP unveiled an exciting and groundbreaking new payroll app called Roll™ by ADP® to help small businesses run payroll anywhere, anytime, quickly, and compliantly with no experience needed. The app’s artificial intelligence-backed conversational interface allows users to complete payroll on their mobile phones in less than a minute simply by texting, “Run my payroll.” Full press release. Watch a quick video of the app.
We had a chance to catch up with Roberto, a Machine Learning developer and one of the brilliant minds at ADP’s Brazil Innovation Lab in Porto Alegre.
Congratulations to you and your team on the launch of Roll™ by ADP®! We’d love to learn a bit about you. How long you’ve been at ADP, what brought you here, and what do you do here?
Yeah, sure. I’m working with machine learning here and part of Brazil’s Innovation Lab. I’ve been with ADP for three and a half years, so I started in 2017. I worked previously at HP, you know, the printer company, right? In their research lab.
I came here to start building the chatbot—a product complete within itself. A system where we can leverage the intelligence to make life easier for people that are using it. I’ve used chatbots, and sometimes they can be painful. Our job is to take the pain away. During development, we closely followed what our clients saw in production and what they said. When they are happy, that made us happy. We tried to understand our pre-production clients, make sense of what we learned, and iterate improvements before he launched.
So, our team is global and is split between here, the US, and India. We have about 13 people in Porto Alegre, but only four are working on just machine learning. We have around 32 people in Roseland, New Jersey, and about 20 colleagues in India. Our job here is to take care of the chatbot and help customers when they have questions. It’s kind of like using Alexa or Siri. When users ask questions, the AI is doing other things while trying to reply.
We’re also trying to extract insights from what customers are doing. For example, when you hire someone, we get the information behind the scenes, and then we do some tricky calculations to assist. The bot checks on things like gender and pay equity and offers data-driven insights to the client. For instance, in this location, you should offer a higher salary.
Tell us a bit about your career journey.
Sure. It’s a little bit messy. I’m an electrical engineer and worked a little bit in the automotive industry. I started as a hardware engineer working for Johnson Controls on a project for Fiat. Then I moved to a semiconductor company as an engineer and spent some time there. After that, I decided to move into technical marketing.
From there, I decided to get a master’s degree in Technology Management. I’ve lived with my wife in Lausanne – Switzerland, for two years. That was the initial plan. Then I got a job at Texas Instruments in technical sales. We stayed three more years before moving back to Brazil in 2015 and getting a job with HP. That was a big shift. I went from technical sales to software engineer. I had a colleague there that was working on machine learning. I fell in love with it, and I studied more about it. Then I got this opportunity at ADP to work 100% on machine learning. That’s why I came here. We pay 1 in 6 people in the US. There’s a lot of data here and good stuff we can do with it. So, I’ve been here since 2017.
I’m 41, almost 42, now. I have a daughter (Gabriela), she’s one year old. She is definitely my biggest project!
What still excites you about working here?
The team still energizes me. Before the pandemic, I enjoyed working with people globally and meeting the US teams in person when we still could travel to New York. We are trying to build this culture of applying available technologies and bridge the gap between open source and what folks in academia are doing with practical, real-life applications in our product, Roll™ by ADP®. Using this outside perspective, we filter what makes sense into our products to mature our technology.
I think the dynamics and openness of the machine learning domain are really driving the market right now. There’s a lot available in open source, and it’s our job to be up to date on the latest developments. It’s an exciting time to be working in machine learning.
Tell us a little about your project.
We beta tested with clients for almost two years. Last year, we did many internal demos based on our work with a gourmet ice cream company recommended by our Business Anthropologist, Martha Bird. We expanded and started working with our Small Business Services group and built our client list to 70 before we launched in February.
As we scaled for our GA release, we matured the product using input from a small number of clients. ADP’s executive team was happy with the product, and yeah, we hope people like what they see. As I mentioned, I go into production logs every week and see what customers are saying. Sometimes you get some nice comments, which is lovely, right? People talking to the chatbot and just saying, “Thank you!” I love seeing that. Martha measured pre-release net promoter scores (NPS), and they were really good. But we will keep the ball rolling and bring new features to future releases.
If someone asked you why they should choose ADP over other tech companies, what would you say?
I can say one of the things comparing ADP with the other companies where I’ve worked, and maybe it’s just specific to our product or my leader, but something I value a lot is openness. When I worked at other companies, there were a lot of layers. I think people are pretty open here also in terms of technology choices. I know that engineers like to experiment and test to see if stuff works. We try to do that here, experiment with things.
We are shifting from a service company to a more technology-oriented company. Here in Brazil, we are trying not only to apply technology but also to share ideas across the company. 
We created a machine learning discussion group. There are about 12 of us. We discuss papers, review articles, create challenges to learn new skills. We sometimes do presentations, attend or present at conferences. Everything is online today, which makes it easier. We get to exchange ideas and nurture our learnings across teams. We’ve discussed starting to produce some technical articles, and I’m happy that we can use the tech.adp.com blog to share them in 2021. I wish I had more time to write, but I don’t have as much time with my little one.
We also did our first internal developers conference in 2020, and I presented Uncertainty in Deep Learning. It was an amazing experience, great to share, but also to get feedback.
When I mention that we do these things during interviews and other things we are trying to do, candidates like this. I know in some companies people work in silos, but you cannot do that here in Brazil. We share as much as we can here. The openness I mentioned, it’s important.
Above, you mentioned exploring open-source and academia. Are there any projects outside of ADP that excite you right now?
Great question. Yes, there’s an open-source project called Open Mined and a course I’m interested in related to privacy with machine learning. The program is called “The Private AI Series.” Facebook is one of the course sponsors. They have a framework behind the scenes that helps people take care of customer privacy. In case you are interested, here’s the link: https://courses.openmined.org/.
Our team also continues to study and review new technologies. We are following Harvard CS224W online for graph neural networks and Causal Inference (lots of interesting applications will come out of this domain for sure!). For neuro-linguistic programming (NLP), we follow a vibrant startup and open source community called Huggingface. (https://huggingface.co/).
One last question! If you could advise your younger self or someone starting their career, what would you say?
Be inquisitive. Study. Help others.
Thanks for your time, Roberto!
Tech & Innovation Blog
ADP Wins 2020 Breakthrough AI Award
Recognition, Artificial Intelligence, Data Science
Accessible Video Controls
Video: AI and machine learning to help our clients
[TEXT] Welcome to ADP DataCloud
[DESCRIPTION] In animation, a man speaks.
[TEXT] Hi, I’m Jack. I’m excited to share some of the recently launched DataCloud Features that are helping our clients navigate the Dynamic Workplace.
[DESCRIPTION] The word “Start” on a screen. Underneath it, the numbers 1 through 4. Jack touches number 1.
[TEXT] We’re helping Organizations Understand how their workforce has been impacted by Covid-19. How? Data Mashups. Data Mashups – Covid Workforce Impact. Data Mashup refreshes daily, displaying the # of Covid-19 cases documented by Johns Hopkins. This has helped organize and understand how their workforce has been impacted by Covid-19.
[DESCRIPTION] Jack presses 2.
[TEXT] We’ve identified Millions in tax credit opportunities for our clients. How? Say Hello to Storyboards. Storyboards – Employee Retention Tax Credit. Storyboards helps clients easily identify if they are eligible for Employee Retention Tax Credits. The platform will automatically calculate the tax credit opportunity based on eligible employees. E.R. T.C. has proactively surface to millions and tax credit opportunities for our clients.
[TEXT] 3. We are helping millions of Practitioners monitor employee sentiment about returning to the workplace. How? Meet Return to Work. Return to Work – Readiness Survey. Practitioners can now send short surveys to collect worker Readiness and sentiment about returning to the workplace. Surveys are delivered to workers through the easy-to-use a. D. P. Mobile app. Practitioners are monitoring employee sentiment about returning to the workplace.
[TEXT] 4. We’ve helped Practitioners Answer key questions about their organization. How? With Organizational Benchmarks. Benchmarks – Organizational Benchmarks. Clients can take a deep-dive into their organizational data and benchmark their company against peers. Uncover organizational questions like what percentage of labor cost do my peers spend on sales and marketing. Discover how their head count breakdown compares to their industry. ADP DataCloud, Learn, Get Inspired, Join the Conversation
Congratulations to our DataCloud team! Recognized for its impressive capabilities and significant value it brings to businesses, ADP’s DataCloud won a 2020 AI Breakthrough Award in the “Best AI-based Solution for Data Science” category. Watch the video.
In a constantly shifting world of work, businesses, now more than ever, are looking for a solution that helps them make informed decisions about their organization. Enter ADP DataCloud, a powerful people analytics solution.
Utilizing Artificial Intelligence (AI), the solution analyzes aggregated, anonymized HR and compensation data from over 30 million workers in more than 730,000 organizations to allow companies to benchmark and compare compensation data, turnover rate, and overtime. Endless possibilities open for better managing a global workforce when pairing this empirical data with the power of machine learning (ML) and AI.
The AI Breakthrough Awards recognize the top companies, technologies, and products in the Artificial Intelligence industry today. As more and more companies join the growing global AI market, this awards program honors those that stand out among a crowded field of competitors. In other categories, winners included IBM, Capital One, NetApp, and others.
Congratulations to the team for all your hard work to deliver amazing solutions and real-time trends to our clients. Way to break through!
Tech & Innovation Blog
Brazil Lab’s Carlos Nascimento Wins First Round NASA International Space Apps Challenge
Voice of Our People, Recognition, Innovation
Creating something out of this world almost came naturally to Carlos Nascimento, literally while he slept. Read about his innovation here.
Carlos recently won the first stage of the NASA International Space Apps Challenge. Yes, that NASA – the National Aeronautics and Space Administration…
Carlos developed a solution responsible for dynamically organizing the entire circadian cycle of astronauts, using Convolutional Neural Networks, being able to interpret brain frequencies, predict and stimulate the next stages of sleep.
“I could not have done this without the experience and knowledge I earned by working at ADP Brazil Labs,” said Carlos. “At the innovation center, we are working on a project that uses machine learning, which gave me the necessary knowledge and inspiration that I used for the NASA competition.”
NASA’s hackathon was the largest globally to develop an innovative app for its astronauts. With only 48 hours of active development, Carlos decided to focus on machine learning and brain signals. He gathered a team of his friends to select the challenge. They thought: “You know what? Everybody has some kind of sleep problem! Let’s help with that!”
Carlos will represent Brazil on the global stage, where they will choose the six best solutions.
At ADP, Carlos and his team work on a product that leverages machine learning. According to Carlos, “The best thing about working with Machine Learning is that the field is always evolving with new ideas and updates.”
Before Carlos travels to spaces and places, we caught up with him to learn just a little bit more:
What advice do you have for someone looking to participate in a global challenge?
These events are about innovation and teamwork, so choose your team wisely with professionals from different fields like designers, developers, and data scientists and read a lot about the subject you plan to solve.
What is your must-have app personally?
Brave Private Browser. We should always be very careful with our data. Like we are at ADP.
What is your favorite movie?
Interstellar.
If you could only eat one food for the rest of your life, what would it be?
Chocolate. I probably wouldn’t live much, but it would be a happy life.
What is the best advice you ever received?
Treat everyone the way you would like to be treated.
What’s the best place you’ve ever traveled to on vacation, and why?
That would be Arraial do Cabo. It’s close to my hometown, Rio de Janeiro. It has the most beautiful beaches I’ve ever seen.
Carlos will receive an award from the U.S. Embassy in Brazil for his work in the NASA Challenge. Results for 40 finalist teams, and six winning global teams, will be revealed in January 2021!
Congratulations, Carlos! Good luck to you and your team in the next round!
Learn more about working at Brazil Labs.
Tech & Innovation Blog
Next-Gen Payroll Captures the 2020 Top HR Product Award
Recognition, Awards
ADP’s products continue to earn awards at a time when our clients need our innovative products the most. We are proud to be named a “2020 Top HR Product” by HR Executive.
ADP’s products continue to earn awards at a time when our clients need our innovative products the most. We are proud to be named a “2020 Top HR Product” by HR Executive.
ADP’s Next-Gen Payroll Platform enables companies of all types – from local small businesses to global conglomerates – to pay their employees their way. This real-time global payroll platform gives clients and their employees unprecedented transparency into how they are paid, along with predictive insights and suggested actions. Companies no longer need to guess the impact of regulatory changes but can proactively model these changes in real-time and plan for the future. At the same time, employees, contractors, and gig workers all have complete visibility into how their pay is calculated along with actionable tips on improving their financial wellness. Who couldn’t use that?
Built natively on the public cloud, this real-time global payroll platform:
- Gives practitioners and employees unprecedented transparency into how they are paid;
- Empowers practitioners to more easily understand the effects of regulatory and policy changes, enabling a stronger strategic partnership with business leaders by demonstrating bottom-line impact; and
- Delivers a breakthrough employee experience with predictive insights to model and understand the effect of potential life changes.
Winning solutions at the HR Technology Conference are selected based on several criteria, including their level of innovation, value-add to the HR professional, intuitiveness for the user, and ability to deliver on what they promise.
ADP Uses Amazon Neptune to Model the Agile Modern Workplace
ADP Uses Amazon Neptune to Model the Agile Modern Workplace
2020
Global human capital management (HCM) solutions provider Automatic Data Processing (ADP) recently took a bold step as part of its strategy to be on the “innovation offensive.” ADP’s digital transformation unit, Lifion, launched ADP’s next gen HCM, a system designed to model a dynamic modern workplace where work gets done in teams rather than traditional hierarchal structures. But the system’s original database solution used multiple self-managed databases—including relational databases like multimaster MySQL clusters—and wasn’t ideal for completing the complex queries that ADP needed to deliver advanced capabilities to its customers. Plus, the effort of managing those databases was a burden on the next gen HCM staff.
Having already used Amazon Web Services (AWS) for self-managed database provisioning, the company looked to AWS for a fully managed database solution, and it found one in Amazon Neptune, a fast, reliable graph database that makes it easy to build and run applications that work with highly connected datasets. This purpose-built, high-performance graph database engine is optimized for storing billions of relationships and querying the graph with milliseconds latency. By using Amazon Neptune, ADP’s next gen HCM cut costs by eliminating database licenses and increased staff productivity and time to market while delivering customers a unique set of customizable HR solutions.
We like app-level encryption in addition to database-level encryption. When we use Amazon Neptune, the data is already encrypted before it gets to the database, and then it’s encrypted again at rest.”
Zaid Masud
Chief Architect, ADP’s next gen HCM
Using a Purpose-Built Graph Database to Model the Modern Workplace
ADP offers HCM software solutions for automating payroll, core human resources (HR), talent management, benefits, and workforce management for companies ranging from small businesses to global corporations. Since its founding in 1949, ADP has stayed on the cutting edge of HCM technologies, which led to the launch of next gen HCM. “Today there are many types of workplace structures, and traditional HCM systems have not embraced that,” says Zaid Masud, chief architect for ADP’s next gen HCM. The Dynamic Teams features of ADP’s next gen HCM aim to help organizations break out of the traditional workplace hierarchy by taking team members out of silos, improving engagement and performance, and creating a culture of connectivity.
Building such a solution required a database that could seamlessly manage an extensive network of complex data points. Yet ADP’s next gen HCM first launched using dozens of various self-managed databases with a microservices-driven architecture running on Amazon Elastic Compute Cloud (Amazon EC2), a service that provides secure, resizable compute capacity in the cloud. The collection of databases included relational databases like multimaster MySQL clusters, distributed key-value stores, and column family stores. “We have more than 200 microservices,” Masud explains, “and each domain has its own data storage needs. As you can imagine, this grew in complexity and became unmanageable very quickly.”
The company knew it needed a managed database solution to reduce staff workload. It also needed to move away from a relational database to a graph database. Querying relational databases is challenging and required the next gen HCM team to denormalize the data, or add redundant data, in order to speed retrieval, which wasn’t efficient. “When you start trying to ask relational databases complex questions like approval flows, it becomes pretty unwieldy,” explains Masud. In contrast, a graph database offered ADP’s next gen HCM the agile storage it needed. “Graph databases naturally represent your structure in the way it’s designed or visualized, which enables us to build much more dynamic queries.”
The next gen HCM team had a number of requirements for a graph database in addition to a fully managed service. It needed a low-code app development framework that would enable it to develop highly customizable HCM applications without writing code. “We needed to manage people, data, benefits, parallel integrations such as time and attendance, vacation balances, and time off,” explains Masud. “So many things must be customized at every level to account for client-specific needs, regional needs, and compliance needs.” ADP’s next gen HCM also wanted a graph database with open-source standards, which would help the team avoid lock-in. The team first heard about Amazon Neptune when it was announced at the 2017 AWS re:Invent conference. “We felt that Amazon Neptune was a slam dunk because our application was already using these open standards,” says Masud.
Enabling Dynamic Queries with Amazon Neptune
Amazon Neptune easily builds queries that efficiently navigate highly connected datasets, enabling the next gen HCM team to build applications that use ADP’s wealth of data to answer complex workplace questions for a variety of use cases. For example, a company that wants to internally fill an open position can use ADP’s next gen HCM to search for existing employees who satisfy the skill sets and requirements for the role. “Writing a query, plugging in criteria, and viewing a list of employees who qualify are things that Amazon Neptune is very well suited for,” says Lucky Jain, engineering manager, next gen HCM. “It can answer these questions and quickly return the data.” Users of ADP’s next gen HCM also can access a range of capabilities such as data reporting based on specific use cases and criteria-based authorization. This enables customers to build their own teams, or groups of employees, and then create authorization rules for that group, limiting or granting them permission to view information like salaries, personally identifiable information, and business plans. “It has given us broader use cases in our current features for customers that we never thought we could have accomplished in our early products,” says Jain. Key to this customization are next gen HCM’s low-code development platform and Amazon Neptune’s flexible query capabilities. “One of the really powerful things about our low-code app development platform is that it enables you to build no-code graph traversal queries,” adds Masud. “That’s what we use Amazon Neptune for.”
The migration to Amazon Neptune decreased next gen HCM’s total cost of ownership, eliminating the need to have skilled people operating database clusters 24/7. Now staff can focus on cloud infrastructure and site reliability engineering operations, enabling ADP’s next gen HCM to further grow its platform without adding additional staff. “We were self-managing everything from operating system–level things like patching, backups, and point-in-time restores to security vulnerabilities,” says Masud. “Spending less time on those things significantly improves our time to market.” ADP also avoids paying for database licensing and reduces spending on Amazon EC2. Amazon Neptune provides high availability using a minimum of two nodes compared to three with next gen HCM’s former solution. “We expect an increase in reliability and availability with Amazon Neptune, which means that we’re running less of an exposure risk.”
Amazon Neptune has multiple levels of security, including encryption at rest, which is important in securing next gen HCM’s sensitive data, such as personally identifiable information. On an encrypted Amazon Neptune instance, data in the underlying storage is encrypted, as are the automated backups, snapshots, and replicas in the same cluster. “We like app-level encryption in addition to database-level encryption,” says Masud. “With Amazon Neptune, sensitive data is already encrypted before it gets to the database, and then it’s encrypted again at rest.” Amazon Neptune also satisfies end users’ requirements for compliance with Service Organization Control and General Data Protection Regulation. “We’re very comfortable telling our customers that we are on AWS,” says Masud. “They can even register and download AWS Service Organization Control compliance reports on their own.”
Optimizing Workplace Management
ADP’s next gen HCM is exploring multitenancy using Amazon Neptune to better represent the structure of its customer data: currently, each customer has its own isolated graph. Masud says AWS has been very responsive to ADP’s needs: “AWS has a way of getting things out to market quickly and then refining that and iterating over that. We were able to give some direct service feedback to the Amazon Neptune team.” The company is also investigating serverless frameworks on AWS.
With the fully managed Amazon Neptune, ADP eliminated database licensing, reduced Amazon EC2 costs, and enabled its team to focus on core business operations rather than database maintenance. But most importantly, it was able to use the purpose-built graph database to power complex queries and deliver to its customers advanced HR applications that it wouldn’t have been able to otherwise.
About ADP
Founded in 1949, ADP designs cutting-edge products, premium services, and exceptional experiences informed by data for HR, talent, time management, benefits, and payroll that enable people to reach their full potential.
Benefits of AWS
- Reduced costs
- Boosted time to market
- Improved staff productivity
- Eliminated database licensing fees
- Secured sensitive data
- Provided Service Organization Control and General Data Protection Regulation compliance
Tech & Innovation Blog
Meet The Team Who improved our Year-End Testing for 401K Clients
Voice of Our People, Why ADP
Meet one of our teams who helped build a better customer experience through cross-functional collaboration
Why did you choose ADP?
Karen H. (Tech Lead; 21 years at ADP): I joined ADP because of its reputation in the industry and as an employer. I saw the opportunity to grow my career with a company that is among the best.
Gina G. (Product Owner; 7 years): After earning my master’s, I heard about an awesome graduate internship program at ADP. ADP’s mission, vision, and values aligned closely with my personal interests—and that’s still true today. We have a constant focus on ensuring the client experience is best-in-class, and we offer endless career opportunities to our team; we want everyone to grow and remain passionate about what we do.
David Z. (Director, Application Development; 17.5 years): Back in the early 2000s, a few former co-workers told me that ADP’s retirement services business was growing quickly and that the company was positioned to grow market share. And that’s certainly been true—our client base has tripled since I joined. The role was also a chance to bring my experience designing, creating, and testing similar processing for healthcare plans for our retirement products.
Bhargav A. (Scrum Master; 5.5 years): As a software engineer, I’m passionate about adopting new technical skills. ADP offered a rewarding career, with challenging opportunities to understand our core business and develop products with the latest technologies.
Pradip P. (Principal QA Engineer; 5 years): ADP is a growing organization with many opportunities. I knew the role would be challenging and that I’d learn a lot.
Karan N. (Technical Lead; 4 years): I was looking for a role that would help me grow my technical skills and personally. Luckily, I met someone from ADP who shared his experience and told me about the fantastic culture. That’s exactly what I’ve found here.
Damodhar M. (Manager, 13 years): I’m very excited to work for ADP. It’s an excellent company with plenty of opportunities to learn and grow. The business model ADP follows (Simplify-Innovate-Grow) provides me opportunities to work on multiple technologies.
Vasudeo J. (Consultant, 6 years): I heard about ADP from my friend, and he told me that ADP is the best place to work among all IT companies and suggested that I join. My decision was correct. I love working with ADP because of culture in every sense, i.e., work, fun at work, family day, and all other mega-events that happen when we are working in the office.
Shivani K. (Senior Member Technical, 5 Years): This is a super cool company to work for, and it’s been great to get a job here.
Gyan S. (Member Technical, 3 years): ADP has a fantastic work culture. It values its employees as much as the customers. Every day at work brings new challenges and learning.
Sunil K. (Member Technical, 1.7 years): It offers an excellent opportunity to learn and implement innovative ideas. I like the ADP work culture.
Preeti R. (Member Technical, 1.6 years): When I got hired, I felt my skills are particularly well-suited to this position. But I like ADP’s culture too.
Tell us a fun fact about yourself.
Karen H.: I love to ski. During the winter, I teach skiing in my spare time.
Gina G.: I’m a thrill seeker! I once sky-dived, and you’ll often find me hiking the mountains in Hawaii. I find thrills at work, too. I love being a part of digital transformation efforts that simplify client experience and streamline our internal business processes.
David Z.: Nineteen years ago, I formed a team in the Metuchen Softball League, and we finally became league champions. I also play on a 50 and over team that has won the Middlesex County champions a couple of times, and for the past three years, we’ve won the state championship.
Bhargav A.: I’m always eager to learn new things and implement challenging solutions. But when I get some free time, I love to disconnect from the world to visit wildlife.
Pradip P.: I like sports—watching them, but also like getting outside and playing them myself.
Karan N.: I love playing badminton and exploring new places with my friends.
Damodhar M.: When I’m off work, I love to follow current events across the world to stay updated.
Vasudeo J.: I love sleeping. A few months back, I got a call from my friend at around midnight, had a conversation, and had no memory of it the next day. I guess I made sense, he didn’t realize I wasn’t awake.
Shivani K.: Reading a new book or creating a craft.
Gyan S.: I try to add and refine my skills so that I can become more productive at work. I take time to analyze how can we improve as a team, raise the bar and have fun too.
Sunil K.: If the world is facing a big problem, I imagine myself as a hero who saves the world.
Preeti R.: I have a huge sweet tooth!
There you have it!
Team, thanks for sharing your ADP experience, and congratulation for a job well done!
Tech & Innovation Blog
Team effort: Building a better customer experience through cross-functional collaboration
How We Work, Voice of Our People, Team Collaboration
At ADP, every milestone is achieved–and celebrated—together. The work by Sachin Ghag and his team to improve the year-end testing experience for 401(k) administrators is no exception. Along with the Architecture Group, the “Agile Archers” and the “Avenging Explorers” worked across time zones and collaborated with other ADP teams to bring a brand new user experience to life in four short months. Hear from Sachin about how his team got it done.
By Sachin Ghag, Senior Manager, Global Product Development and Technology, Retirement Services
At ADP, every milestone is achieved–and celebrated—together. The work by Sachin Ghag and his team to improve the year-end testing experience for 401(k) administrators is no exception. Along with the Architecture Group, the “Agile Archers” and the “Avenging Explorers” worked across time zones and collaborated with other ADP teams to bring a brand new user experience to life in four short months. Below, hear from Sachin about how his team got it done.
****
At the start of every new calendar year, retirement plan administrators at millions of companies across the U.S. add the same pesky item to their to-do list: year-end testing. To ensure their businesses are compliant with federal law, they must confirm that their 401(k) plans are within a half-dozen or so Department of Labor standards, which cover everything from which employees qualify for a plan to how much they contribute. If administrators discover any issues, they must resolve them relatively quickly.
For years, this process was largely manual. Test results came in a single PDF, and companies that needed to take corrective actions had no online option to track whether those issues had been marked as resolved. Instead, administrators had to call ADP for a status update. But we saw an opportunity to save our customers time and better use our resources. It was clear that we could offer a better experience.
We’re always looking for ways to optimize our processes, so a self-service dashboard for year-end testing had long been on our list of projects to tackle. And the timing was perfect: ADP had just started accelerating digital transformations across the company. Our plan was ambitious: We wanted to give clients not just a real-time view of their status, but a central hub for every resource they’d need to resolve any issues. By September 2019, our team in Global Product and Technology (GPT) was ready to dive in. But we knew that the GPT team would need help from our colleagues along the way.
To kick things off, we held a discovery session with the dashboard’s product owner and the UX team, who had already created a mock-up of the end-to-end user experience. Once we made sure we fully understood what we needed to build, we broke the desired product down into features, created user stories for each one, and developed a timeline based on three-week sprints. We wanted to leave plenty of time to test every scenario before the January 10th launch, so we set a target date of December 12.
The first step, we knew, would also be the hardest: Before we could build the APIs and UI that would make our self-service dreams a reality, we needed to move data from a highly complex mainframe system—which most of the Retirement Services GPT team had never worked with before—into SQL. So once our chief architect had offered some invaluable initial feedback, including new processes for transferring the mainframe VSAM data into SQL, we turned to ADP’s subject-matter experts: the Mainframe team. Together, we decided they would extract the millions of records we needed into a text file, updated daily, which we would then import into the SQL site. And of course, updates had to go both ways; we also needed to figure out how to send changes back to the mainframe—re-running tests as soon as possible after users completed corrective actions to ensure the two sources were synced.
Throughout the development phase, collaboration was key. A challenge with the time difference, when our India Global Product and Technology team was half a day ahead of our Mainframe colleagues in the U.S. Being flexible and thoughtful, we managed to meet jointly for an hour or two nearly every day, and were even able to turn the time difference into an advantage. Because our U.S. teammates worked while we slept, they would often have suggestions and solutions ready for us by the time we started the next day.
Once the initial development work was done, yet another phase of collaboration began. We asked our colleagues in Service Operations, who work directly with clients, to help us test the dashboard. Sure enough, their real-life experience helped them find issues we hadn’t—especially around ADP’s 401k Sponsor site, which is used by plan administrators. If a user clicked on certain links within their ADP Task Tracker, for example, we wanted to send them directly to the new self-service dashboard—but many of those links still needed updating. The Service Ops team recorded each issue they found in a spreadsheet, and we fixed them, one by one.
In the end, thanks to hard work from our team and our colleagues across UX, Mainframe, Service Ops, and beyond, what started as an ambitious plan turned into a success story for our teams and our clients. In early January, we launched smoothly, on time, and with a warm welcome from tens of thousands of happy clients—whose reviews ranged from “I love how easy this was to navigate” to “You made my freaking day!” ADP’s leadership team also recognized our work with an award of appreciation.
The new year-end testing dashboard.
Since that first release in January, we’ve already built out some additional features—and we have plans to add more for 2021, including web identification of data integrity issues, which will allow our clients to visualize and modify data within their web session. But even when we aren’t actively working on the dashboard, the experience of building it continues to benefit the GPT team every day. We’ve been able to use the technical knowledge we gained to improve our work on several other projects, both within and outside of compliance. And most importantly, we’ve built relationships with other ADP teams that will help us better serve our clients for years to come.
Given all the things 2020 has given us, our clients will have a smooth year-end. A nice gift after everything that has happened in the world.
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Tech & Innovation Blog
ADP’s Annual Developers Conference Video
Engineering, Innovation, What We Do
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GPT Connect: ADP’s Developer Conference
[MUSIC PLAYING]
[TEXT] GPT Connect. ADP’s Developer Conference. Cool People.
[SPEAKER 1] They built it, they ran it, and they owned it.
[TEXT] Cool people connecting with cool stuff. 3 days. 4 tracks – artificial intelligence and machine learning, product and user experience, clean code and reliability, and product showcases.
[DESCRIPTION] Slides filled with different speakers and information and graphs flash across the screen.
[TEXT] 5 keynotes.
[DESCRIPTION] Photos of 5 speakers.
[TEXT] Ian Swanson, Worldwide Leader, Artificial Intelligence and Machine Learning, Amazon Web Services (AWS).
[IAN] AI and machine learning have become more accessible to all businesses — champion an ML culture throughout all roles at ADP.
[TEXT] Teresa Torres, Product Discovery Coach for Product Talk.
[TERESA] Bringing the product manager, the design lead, and the tech lead together to be jointly responsible for making discovery decisions.
[TEXT] Andy Hunt, Author of the Pragmatic Programmer, Agile Manifesto Co-Author and Musician.
[ANDY] Learning and communicating, that’s exactly what we do all day. We communicate to other people and we learn new things. A team is a complex adaptive system of exploration and dialogue.
[TEXT] 114+ speakers, 20,000+ sessions views, unlimited connections…
[ANDY] We have amazing teams doing amazing work all around the world.
[SPEAKER 5] End to end, we have an opportunity to directly touch the lives of 2.9 billion people.
[SPEAKER 6] We’ve got to live in this world right now, right? We will actually be able to get much more done because of our converged system.
[SPEAKER 7] GPT is the backbone of the company. ADP’s data is so massive in terms of representative of the overall economy.
[SPEAKER 8] And how we can connect our innovations and our teams to shape that.
[TEXT] Innovating. Connecting. Developing. Designing. What’s Next? GPT Connect. Ready to design what’s next? Visit tech.adp.com/careers.
[LOGO] ADP, Always Designing for People.
[TEXT] ADP and the ADP logo are registered trademarks of ADP, Inc. All other marks are the property of their respective owners. Copyright 2020 © ADP Inc.
[MUSIC PLAYING]
More than anything, over the past year, we’ve learned the power of connections! To keep our global teams connected, a group of Global Product & Development (GPT) associates raised their hands to lead ADP’s global, three-day, all-virtual developers conference. Check out our sizzle reel!
AI and Data Ethics: 5 Principles to Consider
As organizations develop their own internal ethical practices and countries continue to develop legal requirements, we are at the beginning of determining standards for ethical use of data and artificial intelligence (AI).
In the past 20 years, our ability to collect, store, and process data has dramatically increased. There are exciting new tools that can help us automate processes, learn things we couldn’t see before, recognize patterns, and predict what is likely to happen. Since our capacity to do new things has developed quickly, the focus in tech has been primarily on what we can do. Today, organizations are starting to ask what’s the right thing to do.
This is partly a global legal question as countries implement new requirements for the use and protection of data, especially information directly or indirectly connected to individuals. It’s also an ethical question as we address concerns about bias and discrimination, and explore concerns about privacy and a person’s rights to understand how data about them is being used.
What is AI and Data Ethics?
Ethical use of data and algorithms means working to do the right thing in the design, functionality, and use of data in Artificial Intelligence (AI).
It’s evaluating how data is used and what it’s used for, considering who does and should have access, and anticipating how data could be misused. It means thinking through what data should and should not be connected with other data and how to securely store, move, and use it. Ethical use considerations include privacy, bias, access, personally identifiable information, encryption, legal requirements and restrictions, and what might go wrong.
Data Ethics also means asking hard questions about the possible risks and consequences to people whom the data is about and the organizations who use that data. These considerations include how to be more transparent about what data organizations have and what they do with it. It also means being able to explain how the technology works, so people can make informed choices on how data about them is used and shared.
Why is Ethics Important in HR Technology?
Technology is evolving fast. We can create algorithms that connect and compare information, see patterns and correlations, and offer predictions. Tools based on data and AI are changing organizations, the way we work, and what we work on. But we also need to be careful about arriving at incorrect conclusions from data, amplifying bias, or relying on AI opinions or predictions without thoroughly understanding what they are based on.
We want to think through what data goes into workplace decisions, how AI and technology affect those decisions, and then come up with fair principles for how we use data and AI.
What Are Data Ethics Principles?
Ethics is about acknowledging competing interests and considering what is fair. Ethics asks questions like: What matters? What is required? What is just? What could possibly go wrong? Should we do this?
In trying to answer these questions, there are some common principles for using data and AI ethically.
- Transparency – This includes disclosing what data is being collected, what decisions are made with the assistance of AI, and whether a user is dealing with bots or humans. It also means being able to explain how algorithms work and what their outputs are based on. That way, we can evaluate the information they give us against the problems we’re trying to solve. Transparency also includes how we let people know what data an organization has about them and how it is used. Sometimes, this includes giving people an opportunity to have information corrected or deleted.
- Fairness – AI doesn’t just offer information. Sometimes it offers opinions. This means we have to think through how these tools and the information they give us are used. Since data comes from and concerns humans, it’s essential to look for biases in what data is collected, what rules are applied, and what questions are asked of the data. For example, if you want to increase diversity in hiring, you don’t want to only rely on tools that tell you who has been successful in your organization in the past. This information alone would likely give you more of the same rather than more diversity. While there is no way to completely eliminate bias in tools created by and about people, we need to understand how the tools are biased so we can reduce and manage the bias and correct for it in our decision making.
- Accuracy – The data used in AI should be up to date and accurate. And there needs to be ways to correct it. Data should also be handled, cleaned, sorted, connected, and shared with care to retain its accuracy. Sometimes taking data out of context can make it appear misleading or untrue. So accuracy depends partly on whether the data is true, and partly on whether it makes sense and is useful based on what we are trying to do or learn.
- Privacy – Some cultures believe that privacy is part of fundamental human rights and dignity. An increasing number of privacy laws around the globe recognize privacy rights in our names and likeness, financial and medical records, personal relationships, homes, and property. We are still working out how to balance privacy and the need to use so much personal data. Law makers have been more comfortable allowing broader uses of anonymized data than data where you know, or can easily discover, who it’s about. But as more data is collected and connected, questions arise about how to maintain that anonymity. Other privacy issues include security of the information and what people should know about who has data about them and how its used.
- Accountability – This is not just compliance with global laws and regulations. Accountability is also about the accuracy and integrity of data sources, understanding and evaluating risks and potential consequences of developing and using data and AI, and implementing processes to make sure that new tools and technologies are created ethically.
As organizations develop their own internal ethical practices and countries continue to develop legal requirements, we are at the beginning of determining standards for ethical use of data and AI.
ADP is already working on its AI and data ethics, through establishing an AI and Data Ethics Board and developing ethical principles that are customized to ADP’s data, products and services. Next in our series on AI and Ethics, we will be talking to each of ADP’s AI and Data Ethics Board members about ADP’s guiding ethical principles and how ADP applies those principles to its design, processes, and products.
Read our position paper, “ADP: Ethics in Artificial Intelligence,” found in the first blade underneath the intro on the Privacy at ADP page.
