Tech & Innovation Blog

Next-Gen Payroll Captures the 2020 Top HR Product Award

Recognition, Awards

Human Resource Executive Winner 2020: Top HR Product

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.

Read the full press release.

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ADP Uses Amazon Neptune to Model the Agile Modern Workplace


ADP Uses Amazon Neptune to Model the Agile Modern Workplace


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

Advancing Your Career

Lifion, Career Journey, Leadership

Video: One Product Manager's Take on Advancing Your Career

Meet Chintan, one of our product managers in our New York City Innovation Center. He started at ADP as a Developer and since that time has grown into new roles, like his latest one as Product Manager. ADP has the ability to offer new experiences and untapped opportunities for those who want it.

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Disability Inclusion in the Workplace

In this second blog in a series focusing on breaking barriers and influencing social change, we celebrate International Day of Persons with Disabilities and offer ideas for promoting disability inclusion in your organization and in our communities.

December 3rd is International Day of Persons with Disabilities. The annual observance was proclaimed in 1992 by the United Nations General Assembly. It aims to promote the rights and well-being of persons with disabilities in all spheres of society and development, and to increase awareness and disability inclusion in every aspect of political, social, economic and cultural life.

This year also marks the 30th anniversary of the passing of the Americans with Disabilities Act (ADA). The ADA prohibits discrimination against individuals with disabilities in all areas of public life, including jobs, schools, transportation and places that are open to the general public to ensure that people with disabilities have the same rights and opportunities as everyone else.

You are no doubt familiar with the need to comply with the ADA in all areas of your business, but disability inclusion reaches far beyond compliance with the law. Proactively supporting inclusivity in your organization can have important and meaningful impact for your employees, customers and communities. CEB, now part of Gartner, found that highly diverse and inclusive organizations had a 26% increase in team collaboration and an 18% increase in team commitment. A study by Harvard Business Review showed that companies with higher-than-average diversity had 19% higher innovation revenues. So, how can you effectively and respectfully promote disability inclusion in your organization?

These are our clients, prospects, coworkers, and employees. How can your organization think about greater equity and inclusivity, especially during these times?

– Giselle Mota, board member of the ADP BRG, Thrive

Practice inclusivity

Be sure that your staff and leadership includes a diverse a range of employees and perspectives. When developing anything from internal policies to new products to client-facing marketing campaigns, getting input from employees and clients with disabilities helps ensure that you are addressing their needs rather than operating on assumptions. Martha Bird, Chief Business Anthropologist at ADP says, “It is important to design WITH excluded and diverse communities, not FOR them. Seek their expert input in the process.”

Representation is key to meaningful and genuine inclusion. If you have Employee Resource Groups (ERGs) or Business Resource Groups (BRGs) in your organization, you can partner with them on inclusivity initiatives to get valuable firsthand perspectives. At ADP, the Thrive BRG has a mission to understand the diverse impact of disabilities, end the stigma, and bring awareness and education to ADP associates about people living with disabilities. Susan Lodge, a Thrive board member and mother to a son with a genetic disease says, “This BRG has given me a new appreciation for the company I work for and the people that I work with. I no longer feel like I am the only one who faces the challenges that disabilities can bring. We are all in this together.”

Work to overcome bias

Inclusivity isn’t an “issue” just for people with disabilities; it’s important for everyone in your organization. Once you set the goal and expectation for a diverse and inclusive organizational culture, follow up with education aimed at promoting understanding and awareness of unique challenges of people with disabilities as well as the importance of inclusion. For example, adopt a policy of using people first language (PFL). People first language is a way of communicating that shows respect for people with disabilities by focusing on the individual and not their disability. For example, if you were discussing modification to your retail space for your clients, instead of saying “disabled customers”, you would use “customers with disabilities.” This recognizes that they have disabilities and allows you to be inclusive and respectful in your planning but doesn’t use their disabilities to define them entirely.

Disability inclusion in post-COVID business

Inclusion is particularly important right now. The global health crisis has highlighted inequities for people with disabilities. Routine healthcare needs like diagnostic testing and therapies are no longer as easy to access. Virtual and masked communications also present challenges that disproportionately affect people with disabilities. As Giselle Mota, board member of ADP’s Thrive BRG, Principal Consultant at ADP on the Future of Work and moderator of an ADP webcast on disability inclusion said, “These are our clients, prospects, coworkers, and employees. How can your organization think about greater equity and inclusivity, especially during these times?”

Learn more

Register for or replay this webcast for more discussion of this question and tips from ADP experts: Disability Inclusion in the Workplace: Best Practices for Engaging and Supporting ALL of Your People.

To learn more about ADP’s commitment to diversity, equity and inclusion, please visit our Corporate Social Responsibility site.

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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.

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.

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Low Code GUI

Podcast: ADP’s John Marcantonio on Low-Code Development and HR

Mark Feffer: Welcome to PeopleTech, the podcast of the HCM Technology Report. I’m Mark Feffer.

Mark Feffer: This edition of PeopleTech is brought to you by ADP. Its Next Gen HCM is designed for how teams work, and helps you break down silos, improve engagement and performance, and create a culture of connectivity. Learn more at

Mark Feffer: Today, I’m speaking with John Marcantonio, head of platform evangelism and federated development at ADP Next Gen. We’re going to talk about low-code development, where it’s at, and what it could mean  for HR and HR technology.

Mark Feffer: John, thanks for visiting.

Why is it that you, and someone in your position, would care about low-code development?

John Marcantonio: It’s a great question. I really view low code as the next frontier of software development. Actually, earlier in my career and my education, I was a computer scientist and definitely thrust into more traditional software development. Low code is a way to really not only increase efficiency of development, but broaden who can participate in that process and how great new ideas can get more rapidly developed and brought to market.

Podcast: @ADP Next Gen’s Head of Platform Evangelism John Marcantonio on low-code development, where it’s at, and what it could mean for #HR and HR technology. #HRTechCLICK TO TWEET

Mark Feffer: How do you define low-code development? What is it?

John Marcantonio: It’s a development methodology, where instead of, again, typing out code line by line, it’s more of a visual representation of the software development process. Instead of text, it’s visual blocks that represent app logic or data elements, things of that nature, where users can string together and create applications for either mobile, web, whatever the target is, within that type of drag-and-drop paradigm.

Mark Feffer: I’ve seen material that talks about it being applied in a lot of places around the organization. But how, in particular, do you think it can be used by HR?

John Marcantonio: I think HR [is in] actually, a rather unique position, as far as low-code development. I think of HR in the environment, just taking a step back, they’re oftentimes viewed as a cost center, obviously critical to the organization as far as managing people and talent. But compared to, let’s say, product development or sales and marketing, which are more revenue-driven, I think that oftentimes HR can sometimes struggle to really take ideas or initiatives they want to take as far as building new applications or integrating with systems or delivering new ways of engaging with the user base, because they’re fighting it out with the rest of the organization for resources or dollars or whatever it is.

John Marcantonio: Looking at low code, I think if we can broaden the base of who can modify or build applications, either as part of an organization or even HR themselves, I think it gives them a lot more control to not only consider these new ways of pushing forward people, operations and the HR function, but putting that control in their hands, really letting them go to town and potentially build up the skills and capabilities to make those ideas realities and continue to iterate without a lot of the overhead that exists in many other functions today.

Mark Feffer: When you think about HR practitioners, these are the people who still often rely on spreadsheets to do things. Do you think that HR practitioners are going to embrace this kind of thing or are companies going to have to nudge them along to adopt it?

John Marcantonio: I think there’s going to be a little bit of both. I think there’s certainly going to be a spectrum of individuals. Let’s say you’re right. Let’s say individuals more comfortable with the spreadsheet and more traditional models may have a little more of a leap, or may not be as comfortable with jumping into this type of technology or tool set. But I think there’s a lot of room, particularly for those up and coming, or maybe individuals more of like a business analyst or a broader background that are coming to HR organizations to embrace this type of flexibility, the ability to create applications or modify those things that can bring value to the organization.

John Marcantonio: I also think, too, it gives some more options to not only the practitioners themselves, but the broader organization, to think about who they can bring on to help augment that type of development. It could be the team. It could be a different class of consultancy or development shops that may not have the same overhead or cost structure, [as those that are doing] more heavy lifting, let’s say CRM or big marketing or rather costly external contractors that have a lot of expertise and knowledge. In a potentially low-code environment, you could have a broader pool of individuals that may not have to be as deep or as technical to execute the same level of value within those systems. I think the options definitely grow.

John Marcantonio: The last point in regards to practitioners, I’d say: I’d like to see a shift, not only in what can be delivered, but I would hope also that it broadens the horizons of HR organizations to think not only in terms of just the regular people operations or HR functions, but if they had the option to extend applications or create applications that can augment or improve existing processes, that becomes more of their day-to-day thought process. If they can make it better, great, then let’s think of those ideas. Let’s curate those. Let’s test them. If they can do that quickly and somewhat easily, the ideas become a virtuous cycle, where it’s like agile development. Let’s put it out there, let’s test it, let’s see what our users say. Let’s improve it and hopefully continue that from there.

Mark Feffer: What do you think the state of play is today? Are HR departments that you know of actually starting to do this? Are they starting to bring some of their tool development in-house with this kind of platform?

John Marcantonio: I think they’re starting to. I think there’s certainly been a lot of interest in even our own Next Gen HCM platform, as far as the possibilities of being able to modify and bring this type of rapid development iteration to market. If you asked me that question six months ago, I’d have one answer. Given the state of the world over the past few quarters with COVID and the rapid changes in work-from-home and different employee policies that have come to light, I think a lot of organizations have realized that the ability to shift rapidly and to provide information that’s very relevant now and really reach out to their employee bases is an incredibly powerful thing.

John Marcantonio: If you look at more traditional development models, if one wanted to go off and build, let’s say, an employee outreach mobile app that talked about work from home and new policies and updates that are going on, I’m sure the dust will settle from COVID by the time the contracts could be wrapped up. If you gave organizations the power to move very quickly and, again, roll that out, make it tailored to them, I think that’s a very compelling opportunity to really move the needle for their organization, help them stay ahead of things. Again, I think that mindset or those questions are starting to pop up more and more. The past few months have really brought it to light in a way that I don’t think many organizations have seen in the past.

Mark Feffer: One of the things that strikes me is the role of the HR practitioner has really been changing the last several years. They’re having to work more with data. They’re having to work more with mobile technology. Actually, all kinds of technology has become integral to what HR does. How does this impact the overall role of HR, the HR practitioner? Is there a real redefinition of the role going on?

John Marcantonio: I think there is. I think looking at the skillsets and, you’re right, what HR practitioners, organizations need to understand or be in tune with is definitely broadening. I think data was the first big step. We’re looking at what’s available in the organization. How do they leverage it to understand their talent base and where they need improvements or how to foster top performers is certainly more data-driven now that it’s available and they can start to rationalize it.

John Marcantonio: But then you take it one step further beyond, let’s say, very traditional, basic HCM systems, there’s certainly a lot more that can be done, can be tailored to the organization and make those practitioners that are more in tune to what are those possibilities or how do you, like you said, leverage things like mobile technologies to really integrate to the workflow.

John Marcantonio: I think it begs of the HR community to really start asking or thinking about those questions a little more deeply and seeing where they can start to improve and differentiate even in their own organizations. Not only for efficiency, but for employee satisfaction, their efficacy, just how they can react and continue to evolve within an ever-changing and increasingly changing landscape.

Mark Feffer: One of the things that strikes me about HR is they’re very concerned about how they’re perceived by people outside of the HR function. If they begin to do more coding on top of understanding data more, do you think other parts of the organization will start to look on HR in a different way?

John Marcantonio: I think they will. I think also it’s a balance, like any other organization. I think, again, a lot of peer groups in most companies—not only HR, again, sales, marketing, other ops, functions—I think it’s a balance on what’s the core value-add versus, like you said, what’s development, for example.

John Marcantonio: Obviously I don’t think any org wants to over-index with an HR team that’s just building software all day, even if it’s done in a low-code environment. But, again, I think it gives them a little more insight and flexibility in how to operate. I think every organization will face this mix in the future of what do they tool up or do in-house, what capabilities or expertise do they want their organization to manage versus just making it easier to bring in resources to augment their staff or to even take on these projects on their own in a way that’s not, again, massive or a big budget lift or involve a lot of overhead that you see in other projects.

John Marcantonio: I think you’re right. That’s going to have a trickle-down effect. Then as practitioners in HR orgs get more savvy, not only in data, but in the underlying technology, what’s available, I think it puts them in a better position. You can understand how does the whole ecosystem come together, how do all the moving parts come together. As individuals are discussing, again, big projects or integrations or building out new initiatives, I think it gives them more, not only perspective, but I think also credibility.

Mark Feffer: It seems like over the last few years, HR has been working pretty hard to develop a good relationship with IT, especially as HR technology becomes more sophisticated and more grounded in the company. How will low-code development, do you think, impact the relationship between IT and HR?

John Marcantonio: I think it’s going to get deeper. I think there’s two sides of the story. On the one hand, I think there’ll be a continued partnership as far as just the nuts and bolts of what IT would need to do to support, let’s say, a low-code environment. There’s user management and security provisioning, and, just like any other system, to ensure that they get up and running and it’s maintained from a, let’s say, network infrastructure perspective. Things of that nature. I think that gives IT something else to get their skillset on, work with, gives HR a little more visibility to how they operate and what’s needed there.

John Marcantonio: The flip side I can see as well, and this is something that all orgs are, I think, going through as they evolve through this process, is the more control or flexibility you give to any team, let’s say HR in this case, in a low-code environment, [the more] they’re building or modifying applications, particularly ones that may integrate with other systems within the company. It begs the questions of where’s the checks and balances and how do we make sure that everything is at a proper quality level and that whatever is being rolled out works consistently? If something goes wrong, who’s the one on the other side of the phone to get that question?

John Marcantonio: I think as much as it’ll be excitement and another area of skillset and onboardings for IT to handle, I think there’s that flip side is just another area of management, if you will, that will need to get sorted out in a very different way. Because, again, a lot of this is not only the development process, but you think about all the operational components. How do these apps get tested? How do they get deployed? Where do they get deployed to? Are there different integration or policy considerations that go along with it? These are things that I think every company is starting to revisit and understand. Does that follow the current book? Is there new rules they have to adhere to? Then they’ll make that call from there. But overall I think there’ll be a tighter relationship as more of this comes in focus.

Mark Feffer: Do you think that HR is positioned to be a first mover with this within the organization? When data started to rise, I think a lot of HR departments found themselves unexpectedly being some of the first users of different types of analytics. I’m wondering if you think the same kind of thing might happen here or do you think they might follow?

John Marcantonio: I think it will depend on the organization, but I think in many cases they do have the opportunity to lead, mostly because many of the orgs in the company, again, for product development or the other operational groups, they have an established process. They have either internal resources they’re leveraging, they have contractor bases, they have a rhythm of what they’re building and maintaining. The machine is up and running, if you will.

John Marcantonio: In HR’s case they’re always, let’s say, potentially fighting for resources or it’s much more difficult to get projects staffed and built out. If this gives them an opportunity to do that, either with their resources or, again, a much more streamlined, external set of resources, again, they take a little more control for themselves. I think that control will start to lead to some experimentation. That experimentation will lead to results that can be evaluated and iterated on.

John Marcantonio: I don’t expect every org is just going to jump in with both feet and say, “Okay, every HR member is now a developer. Go modify everything under the sun.” But I think as these tools become available and the opportunity comes up, I think there’ll be room for experimentation and hopefully, too, I think, these teams will wade into the waters a little bit, saying, “Okay, what if we built this one little widget?”

John Marcantonio: The COVID scenario is a great example. It’s like, “What if we just built a little app that allowed us to talk about work from home policies and link out to what we need? Great. Build it. Push it out. See what happens.” It doesn’t have to be a monumental undertaking, but with relatively low cost and risk, really standalone, isolated applications could be built, give the team some experience and confidence and use that as an test for the next.

John Marcantonio: If we live up to the promise of low code, say citizen developer, relatively low barrier to entry in development, I think it gives the opportunity for those HR teams to jump in potentially ahead of the curve. If all goes well, I can very much see them being the beacon for other teams in the organization to see what was their experience and were they successful and is this something that they may want to pursue or start migrating from other, let’s say, development practices or systems that are established.

Mark Feffer: John, thanks very much.

Mark Feffer: That was John Marcantonio, head of platform evangelism and federated development at ADP Next Gen.

Mark Feffer: And this has been PeopleTech, from the HCM Technology Report. This edition was sponsored by ADP. Next Gen HCM, designed for how teams work. Learn more at

Mark Feffer: And to keep up with HR technology, visit the HCM Technology Report every day. We’re the most trusted source of news in the HR tech industry. Find us at www-dot-hcm-technology-report-dot-com. I’m Mark Feffer.

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ADP logo

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:


Transcript provided by We Edit Podcasts. Software Engineering Daily listeners can go to 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.

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Two ADP employees having a casual conversation

Does culture really eat strategy for breakfast?

Yes, Culture DOES Eat Strategy for Breakfast

Jude Murphy

Jude Murphy

Nov 6, 2019 · 3 min read

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Illustration of African American women

Let’s Talk About Sets


Let’s Talk About Sets

A re-introduction to JavaScript Sets and the new Set methods

Edgardo Avilés

Mar 1, 2019 · 5 min read

Let’s talk about you and me and how we used to find unique items before ES6. We really only had two ways to do it (if you had another one let me know). On the first one, we would create a new emtpy object, iterate through the items we wanted to deduplicate, we would create a new property using the item as the key and something like “true” as the value, then we would get the list of keys of that new object and we were done. In the second way, we would create a new empty array, iterate through the items, and for each item, check if the item existed in the array, if it was already there, continue, if not, add it. By the end the array would contain all the unique items.

ES6 introduced Sets, a new data structure with a very simple API to handle unique items that is not just convenient but also very fast. The intention of this article is to introduce you to some new methods coming to Sets soon that will make them even more useful, but before, let’s remember the basics.

Here in Lifion we are big users of JavaScript, about 90% of our platform services are Node.js-based. If you are interested to see some examples of how Sets are used in our codebase, check our open source projects in Lifion’s GitHub profile.

The basics of Sets

To create a new set we only need to use the constructor. We can optionally pass any iterator, such as an array or a string, and the iterated items will become elements of the new set (repeated items will be ignored).

const emptySet = new Set();
const prefilledSet = new Set(['

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Person on ladder reaching up into the clouds

Lifion at ADP’s cloud transformation journey


Lifion’s Cloud Transformation Journey

On moving to managed services in a microservice architecture

Zaid Masud

Zaid Masud

Mar 26, 2019 · 5 min read

Since Lifion’s inception as ADP’s next-generation Human Capital Management (HCM) platform, we’ve made an effort to embrace relevant technology trends and advancements. From microservices and container orchestration frameworks to distributed databases, and everything in between, we’re continually exploring ways we can evolve our architecture. Our readiness to evaluate non-traditional, cutting edge technology has meant that some bets have stuck whereas others have pivoted.

One of our biggest pivots has been a shift from self-managed databases & streaming systems, running on cloud compute services (like Amazon EC2) and deployed with tools like Terraform and Ansible, towards fully cloud-managed services.

When we launched the effort to make this shift in early 2018, we began by executing a structured, planned initiative across an organization of 200+ engineers. After overcoming the initial inertia, the effort continued to gain momentum, eventually taking a life of its own, and finally becoming fully embedded in how our teams work.

Along the way, we’ve been thinking about what we can give back. For example, we’ve previously written about a node.js client for AWS Kinesis that we’re working on as an open source initiative.

AWS’s re:Invent conference is perhaps the largest global cloud community conference in the world. In late 2018, we presented our cloud transformation journey at re:Invent. As you can see in the recording, we described our journey and key learnings in adopting specific AWS managed services.

In this post, we discuss key factors that made the initiative successful, its benefits in our microservice architecture, and how managed services helped us shift our teams’ focus to our core product while improving overall reliability.

Why Services Don’t Share Databases

The notion of services sharing databases, making direct connections to the same database system and being dependent on shared schemas, is a recognized micro-service anti-pattern. With shared databases, changes in the underlying database (including schemas, scaling operations such as sharding, or even migrating to a better database) become very difficult with coordination required between multiple service teams and releases.

As CTO Werner Vogels writes in his blog:

Each service encapsulates its own data and presents a hardened API for others to use. Most importantly, direct database access to the data from outside its respective service is not allowed. This architectural pattern was a response to the scaling challenges that had challenged through its first 5 years…

And Martin Fowler on integration databases:

On the whole integration databases lead to serious problems becaue [sic] the database becomes a point of coupling between the applications that access it. This is usually a deep coupling that significantly increases the risk involved in changing those applications and making it harder to evolve them. As a result most software architects that I respect take the view that integration databases should be avoided.

The Right Tool for the Job

Applying the database per service principal means that, in practice, service teams have significant autonomy in selecting the right database technologies for their purposes. Among other factors, their data modeling, query flexibility, consistency, latency, and throughput requirements will dictate technologies that work best for them.

Up to this point, all is well — every service has isolated its data. However, when architecting a product with double digit domains, several important database infrastructure decisions need to be made:

  • Shared vs dedicated clusters: Should services share database clusters with logically isolated namespaces (like logical databases in MySQL), or should each have its own expensive cluster with dedicated resources?
  • Ownership: What level of ownership does a service team take for the deployment, monitoring, reliability, and maintenance of their infrastructure?
  • Consolidation: Is there an agreed set of technologies that teams can pick from, is there a process for introducing something new, or can a team pick anything they like?

From Self-Managed to Fully Managed Services

When we first started building out our services, we had a sprawl of supporting databases, streaming, and queuing systems. Each of these technologies was deployed on AWS EC2, and we were responsible for the full scope of managing this infrastructure: from the OS level, to topology design, configuration, upgrades and backups.

It didn’t take us long to realize how much time we were spending on managing all of this infrastructure. When we made the bet on managed services, several of the decisions we’d been struggling with started falling into place:

  • Shared vs dedicated clusters: Dedicated clusters for services, clearly preferable from a reliability and availability perspective, became easier to deploy and maintain. Offerings like SQS, DynamoDB, and Kinesis with no nodes or clusters to manage removed the concern altogether.
  • Ownership: Infrastructure simplification meant that service teams were able to develop further insight into their production usages, and take greater responsibility for their infrastructure.
  • Consolidation: We were now working with a major cloud provider’s service offerings, and found that there was enough breadth to span our use cases.

Evolutionary Architecture

On our Lifion engineering blog, we’ve previously written about our Lifion Developer Platform Credos. One of these speaks to the evolutionary nature of our work:

  • Build to evolve: We design our domains and services fully expecting that they will evolve over time.
  • Backwards compatible, versioned: Instead of big bang releases, we use versions or feature flags letting service teams deploy at any time without coordinating dependencies.
  • Managed deprecations: When deprecating APIs or features, we carefully plan the impact and ensure that consumer impact is minimal.

When we started adopting managed services, we went for drop-in replacements first (for example, Aurora MySQL is wire compatible with the previous MySQL cluster we were using). This approach helped us to get some early momentum while uncovering dimensions like authentication, monitoring, and discoverability that would help us later.

Our evolutionary architecture credo helped to ensure that the transition would be smooth for our services and our customers. Each deployment was done as a fully online operation, without customer impact. We recognize that we will undergo more evolutions, for which we intend to follow the same principles.