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!
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.
Tech & Innovation Blog
How ADP leveraged new technology to help users affected by COVID-19
Pandemic, CARES Act, Helping Clients
When the Coronavirus Aid, Relief, and Economic Security Act, or CARES Act, became law on March 27, 2020, teams across ADP had already been hard at work for weeks preparing for the flood of new policies tied to this legislation. Here’s an example of how Cary Feuer and his team jumped to our clients aid.
By Cary Feuer, Director of Product Management, ADP Small Business Services
When the Coronavirus Aid, Relief, and Economic Security Act, or CARES Act, became law on March 27, 2020, teams across ADP had already been hard at work for weeks preparing for the flood of new policies tied to this legislation. In Retirement Services, we’d started with the simplest—and highest-impact—changes, such as initiating loans and withdrawals for users affected by COVID-19. By mid-March, we had successfully worked through those immediate projects and then turned our attention to a provision we knew would be much trickier: payment suspensions for 401(k) loans.
Since long before the pandemic, the IRS had allowed 401(k) owners to borrow money from their accounts for what it deems “immediate and heavy financial need,” such as a medical expense or a looming foreclosure. Now, under the CARES Act, borrowers affected by COVID-19 could choose to pause payments on those 401(k) loans until 2021. We knew up to 175,000 ADP users might qualify, and their average monthly payment was $800—a significant amount of money for many families. And we also knew that if even 10% of that group decided to suspend their payments and had to call us to do so, it would likely put a significant strain on our team. More importantly, it would be a headache for users during an already-difficult time. We wanted to give them an easy, self-service option, instead of making them wait on hold.
It was clear we needed a technical solution. But speed was critical—and because suspending payments is a multistep process (including self-certification of COVID-19-related hardship)—it wouldn’t be as simple as checking a box. On the backend, we needed to update money-movement databases and multiple payroll products, reamortize the loans, and create an audit trail, all of which we knew we could do relatively quickly. On the frontend, though, we would normally take our time on development and testing, ironing out every wrinkle to ensure the best user experience. A UI build of this scale might take several sprints to ship across mobile, web, and legacy web platforms. In this case, we didn’t have that long.
Instead, we turned to a new piece of third-party technology, which ADP had recently integrated to allow for faster deployment of simple features like pop-up guides and mini-surveys. Designed for product managers and others to use without the help of an engineer, this technology offers templatized, customizable design patterns—and it had already been vetted by ADP’s Technical, Security, and Legal teams. It was our best, and perhaps only, option to get the frontend of payment suspensions up and running on an accelerated timeline. However, because of all the backend changes each payment suspension would trigger, we’d need to learn how to work with the product in an entirely new way, pulling information out of its API and into our own infrastructure.
Our lead developer joined with our lead development team for a quick feasibility study, and within a couple of days they’d determined our plan could work. So, with added help from one of ADP’s resident experts on the 3rd party software, we all got to work building. Our colleagues in Service Ops helped us develop the content, a UX teammate gave the frontend flow their blessing, and in less than two weeks we were almost ready to ship.
But then we ran into a snag. In order for the third-party product to know which users should see a payment suspension option, it needed to refer to a list of qualified users’ anonymized IDs—and with so many people facing financial hardship and taking out new 401(k) loans, that list was changing every day. Because of the time crunch, we’d decided to upload up-to-date CSVs of user IDs to the product each morning by hand. But this seemingly simple fix was a use case that the product—a relatively new technology still in its startup phase—wasn’t built for. Each day’s upload was taking hours to complete.
Rather than delay the release, we decided to ship our new feature and keep handling the CSVs manually. Contemporaneously, we started work on a mini-app that could automatically break up and upload the CSVs. After a few days of testing, we finally had a feature that was not only fully self-serve for our users, but fully automated for us. Thousands of people have now paused their loans without needing to call in, saving them time and potential frustration—and saving ADP the equivalent of adding two full-time employees. Over the course of the program, our uploading solution will save hundreds of additional hours.
Meet Cary’s four-legged office mate
Even better, our team is more familiar with a brand-new technology that we can now leverage in other creative ways. The next time we’re responding to a fast-developing situation, such as a hurricane, we’ll have this 3rd party technology in our toolbox. We’re currently validating it for other use cases, where time to market is less of a concern. With just a few weeks of work, we were able to expand our team’s development toolset, better serve our users when they needed it most, and make an investment in the future of ADP.
This is just one way that our tech teams have added new tools into our tech stack. This feature is now available for all ADP Retirement Services clients that offer CARES Act provisions to their employees.
Cary Feuer is a Director, Product Management for Small Business Services at ADP and is based in New Jersey.
ADP Wins Prestigious Ventana Research Digital Innovation Award for Next Gen HCM Platform
ROSELAND, N.J., July 30, 2020 /PRNewswire/ — Identified for having the most striking impact in the human capital management (HCM) market, ADP was recognized as a winner in Ventana Research’s 13th Annual Digital Innovation Awards for its Next Gen HCM platform. Named as winner for the HCM category, ADP was selected based on the award program’s stringent criteria, earning acclaim for Next Gen HCM’s advanced technology and ability to drive change and increase value for organizations worldwide.
Learn more about ADP’s Next Gen HCM technology
Ventana analysts examined vendor submissions for their innovative technology approach; how it applies to people, processes, information and technology; the best practices it supports; the degree of team involvement; and the technology’s business impact and value.
“The range of ADP’s Next Gen HCM innovation that merited the award includes dynamic teams and matrix organizational structures, AI-driven insights, and global compliance,” said Steve Goldberg, VP & research director of HCM at Ventana Research.
Differentiating ADP’s Next Gen HCM is the platform’s design for team-based, agile ways of working as a complement to traditional hierarchical structures, as well as its ability to adapt and scale. The customizable solution enables organizations’ flows of work while driving team performance and the ability to rapidly adapt to changing needs. Built cloud-native from the ground up, the global platform supports a personalized experience that cultivates fluid, dynamic work to unlock greater value for the organization.
“We’re incredibly honored that Ventana Research has recognized the impact our Next Gen HCM platform can have on businesses,” said Don Weinstein, corporate vice president of global product and technology at ADP. “Change is only accelerating in today’s business landscape, as we navigate a world that’s becoming increasingly uncertain. With our vast experience in supporting clients, ADP has studied what makes a business successful, and what can stand in its way. We’ve used this knowledge to deliver a flexible and adaptable solution that can support our clients as they evolve amid dynamic conditions and grow with their businesses as fast as needed.”
To help businesses thrive in a new world of work, ADP’s Next Gen HCM provides data-driven insights into how people work best; access to an ecosystem of mini-apps to personalize the workforce experience; benchmarking capabilities from aggregated and anonymized ADP client data spanning 810K+ companies and 30M+ employees; and the ability to react quickly to changing global compliance requirements.
For more information on the Ventana Research Digital Innovation Awards, visit https://www.ventanaresearch.com/resources/awards/innovation. To learn more about ADP’s Next Gen HCM platform, visit https://flowofwork.adp.com/.
About Ventana Research
Ventana Research is the most authoritative and respected benchmark business technology research and advisory services firm. We provide insight and expert guidance on mainstream and disruptive technologies through a unique set of research-based offerings including benchmark research and technology evaluation assessments, education workshops and our research and advisory services, Ventana On-Demand. Our unparalleled understanding of the role of technology in optimizing business processes and performance and our best practices guidance are rooted in our rigorous research-based benchmarking of people, processes, information and technology across business and IT functions in every industry. This benchmark research plus our market coverage and in-depth knowledge of hundreds of technology providers means we can deliver education and expertise to our clients to increase the value they derive from technology investments while reducing time, cost and risk.
Ventana Research provides the most comprehensive analyst and research coverage in the industry; business and IT professionals worldwide are members of our community and benefit from Ventana Research’s insights, as do highly regarded media and association partners around the globe. Our views and analyses are distributed daily through blogs and social media channels including Twitter, Facebook and LinkedIn. To learn how Ventana Research advances the maturity of organizations’ use of information and technology through benchmark research, education and advisory services, visit www.ventanaresearch.com.
About ADP (NASDAQ: ADP)
Designing better ways to work through cutting-edge products, premium services and exceptional experiences that enable people to reach their full potential. HR, Talent, Time Management, Benefits and Payroll. Informed by data and designed for people. Learn more at ADP.com
ADP, the ADP logo, and Always Designing for People, are trademarks of ADP, Inc. All other marks are the property of their respective owners.
Copyright © 2020 ADP, Inc. All rights reserved.
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SOURCE ADP, Inc.
For further information: Leann McDonough, ADP, Inc., (973) 974-6861, Leann.McDonough@adp.com
Podcast: Insights into ADP Engineering with CTO Tim Halbur
ADP has been around for more than 70 years, fulfilling payroll and other human resources services. Payroll processing is a complex business, involving the movement of money in accordance with regulatory and legal strictures.
From an engineering point of view, ADP has decades of software behind it, and a bright future of a platform company used by thousands of companies. Balancing the maintenance of old code while charting a course with the new projects is not a simple task.
Tim Halbur is the Chief Architect of ADP, and he joins the show to talk through how engineering works at ADP, and how the organization builds for the future of the company while maintaining the code of the past.
Sponsorship inquiries: sponsor@softwareengineeringdaily.com
Transcript
Transcript provided by We Edit Podcasts. Software Engineering Daily listeners can go to weeditpodcasts.com/sed to get 20% off the first two months of audio editing and transcription services. Thanks to We Edit Podcasts for partnering with SE Daily. Please click here to view this show’s transcript.
Creating human-focused solutions in today’s product strategy
ADP Business Anthropologist Martha Bird sat down with Daniel Litwin, the Voice of B2B, at CES 2020, discussing a wide range of topics related to how her anthropological work and research impacts businesses and consumer needs.
Bird has worked for numerous companies in the field of business anthropology since the early 2000s, working to create human-focused solutions to business needs.
Bird and Litwin touch on their CES experience, a modern focus on human-centered and human-responsive products and how those concepts affect consumer product development, consumer longing for personalized experiences, and more.
Tech & Innovation Blog
ADP Help Clients Navigate the Way Forward to a Return to Work
Analyst Day, New Technology, Pandemic, Return to Work
During ADP’s annual Industry Analyst Day, members of the ADP executive team had the opportunity to host a virtual meeting with industry analysts to unveil the latest product developments to help our clients navigate the way forward as their employees return to work.
During ADP’s annual Industry Analyst Day, members of the ADP executive team had the opportunity to host a virtual meeting with industry analysts to unveil the latest product developments to help our clients navigate the way forward as their employees return to work.
Industry Analyst Day is an opportunity for analysts to learn what’s new at ADP so they can share it with their clients and in their published research. The highlight of our June meeting was showcasing our upcoming “Return to Work” solutions, including employee readiness surveys, daily health attestations, a return to the workplace dashboard, and touchless time kiosks with facial recognition.
The event had full exec leadership participation. Our CEO, Carlos Rodriguez, kicked off the call, followed by Matt Levin, our Chief Strategy Officer, who shared information from ADP Research Institute. Don Weinstein shared a demo of all the new technology and products we have in store. Maria Black focused on what ADP has done to assist and educate our clients throughout the pandemic. Finally, Debbie Dyson hosted interviews with several clients who shared how they partnered with ADP to navigate the global pandemic.
ADP traditionally hosts industry analyst day in the Fall. However, we felt a June meeting would be more timely and appropriate to highlight ADP’s rapid reaction to helping our clients during COVID-19. Based on what we’ve seen, the analysts were impressed. Some of the highlights on how ADP reacted swiftly to help our clients by delivering meaningful in-product solutions and leveraging our unmatched product portfolio and data capabilities:
- Enabled tax credits as part of the CARES Act within three days. By mid-June, 38,000 clients have used $600M in tax credits across 473K employees to aid those affected by the pandemic
- Provided a mechanism for 400K+ clients ran over 2 million PPP reports for SBA loan applications valued at $115 billion, plus over 200K loan forgiveness reports
- Stood up a COVID-19 site where over 700K visitors engaged with our PPP content, staying 5x longer than a typical visit to ADP.com
- VolunteerSurge supported by our WorkMarket product helped onboard 1K+ volunteers within two weeks from 45 states, Canada, and Mexico to fight COVID-19
- Launched workplace analytics to help measure COVID impact on businesses
- Offered extended free trials of our StandOut product to measure employee engagement
We serve clients all over the globe. Outside the US, our teams deployed solutions in many geographies and have partnered with government agencies to support our clients. To date, we have had multiple country teams address 1.4K feature changes resulting from almost 2,000 global and local legislation changes, a number that continues to rise.
Ultimately, our goal has been to support our clients in the best possible way through this crisis. We’re proud that we have received significant positive feedback for our efforts, and analysts weren’t shy about tweeting during the session! Some things they loved:
- Insights from the ADP Research Institute that no other vendor could share
- Incredible response from the ADP team to help clients navigate the early weeks of the pandemic
- Impressed with the return to the workplace tool kit that’s under development
- Check out a full blog from Nelson-Hall here: https://research.nelson-hall.com/blogs-webcasts/nelsonhall-blog/
But it doesn’t stop there. We’re giving our clients a place to access resources quickly. Check it out here at www.adp.com/forward.
Stay safe!
The Technology Helping Companies Embrace The Future of Work
To embrace the future of work, companies need technology that mimics how their organizations are structured and how their workers relate to one another.
Today’s work relationships, for example, are complex and fluid. Using highly structured relational databases, which organize data hierarchically in rows and columns to represent these relationships, no longer makes sense.
Instead, we need adaptable technology that models data based on contextual relationships. Enter graph databases, a revolutionary technology that Gartner predicts will grow 100% per year over the next couple of years.
Early Applications Of Graph Databases
Graph databases may now be leveraged by giants like Google and Amazon, but they weren’t always popular. In fact, their popularity grew with the rise of social media.
Consider the complex relationships between people, places and things stored in social networks like Facebook or LinkedIn. Organizing these relationships based on hierarchies is problematic, as it doesn’t align with the world’s natural order. That not only leads to inaccurate data models, but also dramatically increases the amount of effort it takes for a program to locate any given object.
Let me explain: Say you’re searching a social network for the CEO of Company X. When a software program searching a graph database reaches Company X, it finds the CEO right away. After all, the CEO works at Company X — they are directly related.
Putting People First To Rebuild A Stronger Economy: A Conversation With Ochsner Health
When a software program searching a relational database reaches Company X, on the other hand, it finds a hierarchy of people, divided into teams, which it must scan to locate the CEO. Teams are further divided into types of teams. The CEO is located on the executive leadership team, which sits within the broader leadership team. It’s not until the program finally reaches Company X’s team of executives that it locates the CEO.
This complicated structure — an information architecture with at least four levels (just within Company X) — slows a social network’s data retrieval, resulting in a less-than-effective user experience.
In response to this challenge, Facebook’s engineering team developed a proprietary database that they called The Associations and Objects (TAO). This innovative technology allowed them to model the multifaceted relationships between people, places and things based on context instead of hierarchies. In other words, they no longer had to follow long data chains to retrieve specific information, which significantly increased the speed at which content was presented to users.
Modeling Work Relationships: Challenge And Solution
Given the complexity of human relationships, graph databases are much better suited to modeling the way companies operate than their predecessors were. The thing is, work is now done in teams, not hierarchies. In fact, 64% of workers now belong to more than one team, according to our company’s 2019 Global Study of Engagement report. And while hierarchical teams continue to exist, cross-functional, dynamic teams focused on achieving specific goals are more prevalent than ever.
In addition, today’s workers often have multiple roles within an organization, and their relationships aren’t limited to those they have with their supervisor and/or direct reports. Companies thus need technology that models these structures and relationships, empowering them to embrace cutting-edge business models built for the future of work.
A graph database can help empower companies to leverage both traditional and alternative workers (i.e., full- and part-time employees, temporary contractors, gig workers, and freelancers) across multiple teams (both functional and cross-functional) within the organizational model that best suits them, including one based on hierarchies, teams or projects.
So when should organizations consider a graph database? In our experience, we have found graph databases to be very useful when the datasets are associative in nature, as they avoid the often-expensive join operations that a traditional relational database will have to undergo. This nondependency on join operations helps them scale better, especially when dealing with growing datasets with an evolving data schema. While there are multiple vendors out there in the market, our company uses AWS Neptune for our managed graph database needs to conform to our overarching approach of going cloud-native.
Embracing The Future of Work
Innovative leaders at companies across the globe are already reimagining work with an eye to the future. HR technology powered by graph databases can empower these organizations to achieve their visions, enhancing performance and productivity along the way.
Based on what we’ve seen so far, it pays off: Deloitte’s 2019 Human Capital Trends (page 54) report found that over half of surveyed companies that make the shift to a team-based organizational model see significant improvements in performance. Moreover, because technology that leverages graph databases to represent a company’s workforce is more aligned with reality, the insights derived provide more accurate and actionable learnings, which is equally important to succeeding in the future of work.