Veterans, Technology
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ADP is on a mission to give Veterans and military spouses a career they can be proud of. Whether it’s solving business challenges for our clients, keeping our data secure, or adding to our growing client list. Meet Fred, a former Marine, has been at ADP for 22 years, where he currently works in end-user computing, where he makes an impact every day. Hear what he loves about ADP and why he stays.
https://eng.lifion.com/yes-culture-does-eat-strategy-for-breakfast-638ae19fc506
“The best employees love what they do”, former PepsiCo CEO Indra Nooyi once responding to a crowd of bright-eyed summer IT interns. Quite a simple answer to the question “what do the best employees do, and how can I be like them?”. The more you think about the fast response Indra had given, the more you realize it extends to more than simply ‘what’ we do. As one of those interns, I didn’t quite understand the depth of this statement until I had exposure to different roles later in my career.
Loving what you do is inherently important, yes, but it’s not exactly the single most important aspect to making you an incredible employee. Whether people want to acknowledge it or not, what you do for work becomes part of you. For example, I may have been called a ‘tech bro’ once or twice after being asked what industry I’m in, to which I usually respond: “I’m not fixing your computer”. After the laughter calms down, I usually begin talking about the work I do, and then inevitably, the “are you happy?” question arises. Most people respond fairly quickly, and to varying degrees, but if you stop and think about the rounded picture of happiness at your job, it usually comes down to one thing: personal fulfillment based on the investment of your time. Many concepts can be abstracted from this — work relationships/enjoyment, culture-driven benefits, monetary compensation, societal impact, etc. How many start-ups have you heard say that they’re going to change the world? Have you ever stopped to think about this as a marketing ploy, rather than a vision statement?
We all have different opinions on what’s heavier when it comes to our personal happiness, but I’ve found that one particularly weighs more than others, and that’s culture. From an organizational perspective, culture is tough to get right and easy to ruin, but when fostered correctly can truly breed the best and happiest employees. Culture is something that’s created organically, targeting the basic human desire to belong, fit in, and feel like a contributor to the group. A group that allows for the dynamism of thought, and freedom to express it without judgment, enables each individual to feel heard while allowing the best outcome to become possible. This, in turn, opens up avenues for new and personal discussions between individuals, potentially turning into friendships. When an employee goes into work every morning, considering his/her coworkers to be people he/she looks forward to working with, that’s where the magic happens, and culture is born. Good relationships grow general satisfaction with a person’s environment. Happy employees are much more likely to go out of their way to make the organization succeed, which full circle, makes them a good employee in the eyes of the organization.
How often in pop culture is work-life balance portrayed with someone comically saying “I don’t know any of you outside of work”. Now, full disclosure, I’ve never once heard anyone explicitly say this, but have seen individuals act in this way. This mentality simply doesn’t instill a sense of trust, no matter what organization or industry you work in. Don’t get me wrong, separation is good and healthy to have, but communication is key.
At Lifion, by ADP, we’re in the business of ‘Human Capital Management’, and we understand that if an organization doesn’t manage its resources correctly, the strongest culture won’t prevail. Everyone wants to be treated as an individual, rather than just another employee. No inhuman litmus test for happiness should ever suffice for a one on one, a drink together at happy hour, or a sincere “hey, how are you doing?”.
In summary, you never know the amount of impact you have on someone’s daily work experience. People are more than just resources to get a job done and respond well when treated as an individual. At the end of the day, you can have the best strategy in the world, but with no one to build it, it’s not worth anything. Simply put, whether you are a company, a manager, or a coworker, the best advice I can give: be human.
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.
https://eng.lifion.com/lets-talk-about-sets-813dfeb2185
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.
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(['
https://eng.lifion.com/lifions-cloud-transformation-journey-2333b7c0897d
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.
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 Amazon.com 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 Amazon.com 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.
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:
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:
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:
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.
https://eng.lifion.com/promise-allpocalypse-cfb6741298a7
There is nothing quite like the existential dread of realizing you may have a performance issue. Months, possibly years, worth of codebase are suddenly now failing you in a live environment. Reproduction is difficult, and even if you can reproduce it on your dev machine your usual methods of debugging are likely useless. Sure, you can litter your code with entirely too much analytics, or leverage Node’s own profiling, but this results in a data hose that takes a deep understanding of Node, V8, and data science itself to make sense of it. This is a rather dire situation.
Enter Clinic.js; a tool from NearForm that utilizes Node and V8’s own internal profiling, as well as inserting probes into the JavaScript itself, to analyze and produce easy to consume diagnostic information as well as recommend next steps. The power and capabilities of Clinic.js can be seen in great detail on its website, though as the title implies, I am going to employ Clinic.js to focus on the danger of misusing Promise.all().
A common scenario in any service is you may have some asynchronous operation that you need to perform on a data set of unknown length. Your first instinct may look something like this:
You quickly discover that this is not very fast. Simple interrogation of CPU utilization will show Node is spending a lot of time waiting. Depending on your lint rules, you may not even be able to get this code past a CI build. The solution for many is to simply fire all the promises then await all of them. That, in and of itself, is not a bad thing; for example, say you know that every time you execute a given route, you need to make 3 unrelated calls to other services. Since you know it will always create 3 promises, this is bounded and safe. The problems arise when the promise creation is potentially unbounded.
You test your code and discover it is much faster, Node is not spending time waiting around, and the lint error is gone. You merge and deploy your code, all the integration tests pass, and you go home to watch The Expanse. Suddenly, right when the Rocinante (a legitimate salvage) is entering a tense battle, you start getting PagerDuty alerts. Your services containers are getting restarted constantly due to Out of Memory exceptions, the container host is experiencing socket exhaustion, and your response times are through the roof. You have a major performance and scalability issue.
This is a nice clean scenario, so the suspect code is easily identified, but what if it isn’t? Why does this code fail to scale? This is where Clinic.js shines. For the sake of exercising Clinic.js, I created 6 scenarios that all perform the same asynchronous work some n times using different strategies. They are using for…of, the new ES2018 for await…of, the Promise.all() scenario described above, using Bluebird.map() with a concurrency limit set, the promise-limit module, and the p-limit module.
For the test, I start a clustered web server that accepts a get and post request. Both verbs will perform some arbitrary work before completing the request. In the test itself, I get the data, do arbitrary work, and post the results back. In both cases the work is primarily parsing JSON and manipulating the object in an attempt to simulate a common Node workload. Each test run does this work 500 times, for each element in a mock collection. For the limiting modules, they are all set to allow 10 concurrent promises. All tests were performed using Node v12.14.0. The average execution times over 10 test runs can be seen below.
╔═══════════════╦══════════════════════════════════╗
║ Test ║ Average Execution Time (Seconds) ║
╠═══════════════╬══════════════════════════════════╣
║ await-for-of ║ 6.943 ║
║ bluebird-map ║ 4.550 ║
║ for-of ║ 6.745 ║
║ p-limit ║ 4.523 ║
║ promise-all ║ 4.524 ║
║ promise-limit ║ 4.457 ║
╚═══════════════╩══════════════════════════════════╝
The results here certainly reflect the performance improvement when going from for…of to issuing concurrent promises, but the limiting libraries have similar execution times. Let’s dive deeper into what is going on.
In the for await…of and for..of scenarios (respectively), the CPU utilization is bouncing around and is averaging well below 100%. This means the Node process is spending a lot of time waiting around. The execution time is also non-ideal at roughly 7 seconds averaged over 10 runs. Clinic detects this and reports a potential I/O wait issue bottlenecking the process. It recommends running a ‘bubbleprof’ to better identify the issue.
Note the light blue segment in the graph, this represents network I/O waits. It is spending quite a bit of time waiting for network operations. Perhaps we can speed this up by issuing them concurrently.
In the Promise.all() scenario, execution time has improved dramatically to 4.5 seconds on average. The CPU is now being efficiently utilized. However, notice the memory usage spiking up much higher with incredibly high event loop delay. Clinic detects this issue and reports a potential event loop issue. Why is this?
It is a common misunderstanding that promises are concurrent. While there is some threading in V8, JavaScript itself is executed synchronously. When a new promise is created, it is eagerly executed until it reaches a truly asynchronous operation or the end of the JavaScript code path. Consider the below example.
As you can see, the promise callback is invoked first, then it executes to the end of the block. Only after that do the `then` blocks fire. This, however, is only part of the story.
In the case of the Promise.all() code above, it will create a request for every item in the collection before any `then` block is resolved. This is true even if the early requests complete before it reaches the end of the collection. It will not process the responses until the event loop ticks over. This is due to I/O callbacks not being invoked until the event loop ticks into its I/O phase. It is only at this point `.then()`, or the code block proceeding `await`, is executed.
Ultimately the creation of an unbounded number of promises will result in all of the response objects becoming queued in memory and waiting for the event loop to tick over. This can swamp the Node process with excessive memory allocations, or worse, cause out of memory events. When these objects go out of scope, it will freeze up when the garbage collector executes as it is primarily a blocking, O(N) operation. It also means when the event loop finally does tick over, all of the `.then()` callbacks of completed requests fire synchronously. If this contains heavy work, the event loop will be stuck in the callback phase until this work is completed or another truly asynchronous operation is encountered. This means any events, inbound requests, timers, etc. will not be handled until the ‘.then()’ callbacks are all completed. The biggest concern here is that response times can spike to several seconds. To solve this, we need to limit the number of concurrent promises created.
As indicated in the graphs, Bluebird.map() with a concurrency limit pretty much eliminates the event loop blocking and the high memory usage while maintaining efficient CPU utilization. It matches the performance of Promise.all(), completing the test in 4.5s. Bluebird however has lost its performance edge in recent versions of V8 when compared to native promises and is a rather heavy complete Promise replacement. Let’s consider some other native promise options.
The promise-limit module also resolves our issue, and against matches the performance of Promise.all() at 4.5s. This is due to the aforementioned pressure on Node’s memory system creating unnecessary memory allocations and complex garbage collection events. The overhead of this module does get flagged by Clinic.js as creating some event loop blocking. It notably also is nowhere near as popular as the last module, p-limit.
The p-limit module has the least amount of event loop blocking of all the options, while providing the same performance as Promise.all() at 4.5s. Given the popularity compared to promise-limit and the performance of this module, this is the clear winner.
Clinic.js enables introspection into how your Node application is performing beyond simple top line execution times. It introspects not only your resource utilization, but what the code itself is doing. By no means have I explored all the capabilities of this tool here, however it grants us insight into why a specific codepath may appear to perform without issue on its own, but wreak havoc inside of a live service. NearForm presented this to us during Node Day 2019 and it has quickly become an indispensable debugging tool for us. Its ease of use and clear presentation helps not only quickly identify problematic code, but also convey the “why” to others who are not deep into the debugging process with you. It was the obvious choice to illustrate the issues with unbounded promise creation.
Promises and the async/await syntax lead to far clearer, more maintainable JavaScript code. Its appearance of parallelism is an easy trap to fall into, especially for polyglot developers who are used to similar features in other languages. While unbounded thread creation has its own problems, unbounded Promise creation will bog down an entire service, affecting all code paths in the application, and will cause out of memory events as you scale. Usage of modules that allow you to limit concurrent promises can provide even better absolute performance than Promise.all() and enable your application to scale better. It’s this engineer’s perspective that Promise.all() should be banished from your code in all scenarios where you cannot guarantee at the time of coding how many promises will be created.
https://www.adp.com/spark/articles/2020/01/the-word-on-ces-whats-really-driving-nextgen-technology.aspx
ADP’s business anthropologist, Martha Bird, reports on the top five themes at the 2020 Consumer Electronics Show that are important for today’s industry leaders.
With over 4,000 exhibiting companies, 2.9 million square feet of exhibit space, attracting more than 180,000 attendees and 307 Fortune 500 companies, there was a lot to take in at CES 2020 in Las Vegas. Some of the most innovative technologies to come included a flying taxi (Hyundai), electric multi-modal transportation, electric vertical take-off and landing craft (Uber), cool and creepy robotics, green and sustainability tech, 8K bezel-less TVs (Samsung), AI attended drive thru (McDonald’s lab), 150 digital health exhibitors and so much more. Within this tech frenzy, it was my great pleasure to represent ADP on stage and in studio where I discussed how natural language processing, machine learning and artificial intelligence (NLP/ML and AI), in general, is impacting the workplace – the tools, the processes and the people.
While it was impossible to see everything given the sheer magnitude of the event, there are some high-level reflections on what I consider to be the pervasive themes from this year’s event that industry leaders should keep their eyes and ears open for moving into 2020. These are my top five:
1. 5G: Data, data, and more data
On the CES floor, data was the common denominator across products and services on display and those demoed. Given the explosion of data contingent technologies, online privacy and security was a central talking point. How different regions address security concerns around data and privacy was less explicitly articulated although a continuum of highly private to blatantly public could be surmised. Along with a definite trend toward the true consumerization of AI.
Which brings me to 5G. In the next two to three years, networks will expand out exponentially. The first commercial deployments are already being seen but 5G is still in its infancy so it won’t be a matter of simply “flipping a switch” from 4G to 5G.
Along with 5G – increased speed, greater capacity and lower latency – comes huge possibilities for disruptive innovations. There was no limit to 5G talk and imagination at CES 2020. And, of course, there were both pronouncements and announcements on the topic around the coming of 5G handsets. AT&T and Verizon are aggressively developing the infrastructure in an attempt to get out ahead of competition across the globe.
5G will be the “central nervous system of the data age,” according to Steve Koenig, VP, Research at the Consumer Technology Association (CTA).
Martha Bird and others and CES 2020
[Inset above] ADP’s Business Anthropologist Martha Bird (right) took the stage at CES 2020. Bird’s panel “Emerging Technologies Enabling Enterprise” was moderated by Michael Miller, Editor-in-Chief at PC Magazine (middle) joined by fellow panelist Yonatan Wexler, Executive VP of R&D at OrCam Technologies (left).
2. IoI (Internet of Intelligence): The Decade of Connected Intelligence
Just as we were getting accustomed to the term IoT (Internet of Things) the talk this year was around IoI or “Internet of Intelligence.” This new way of thinking is a direct response to the way AI is being integrated into all facets of our technology and consumer culture.
We were told in the plenary keynote that as networks grow, we can expect 5G to unlock more opportunities for enterprise. Building upon what we’ve seen with IoT technologies (think smart home apps that rely on little bits of discrete data), the expansion of 5G and AI capabilities will provide multiple nodes of data informing a much more complex and inter-dependent data landscape. Enterprise applications are expected to lead in IoI in part because of massive data resources and the ability to form mutually beneficial partnerships between OEM, software and engineering. IoI covers things like remote robotic surgery and smart cities. Activities with a heavy data lift and, generally speaking, much higher stakes than let’s say a voice activated light in your home.
3. XR: The New Reality Training Our Future Workforce
XR – the latest technology encompassing augmented, virtual, and mixed reality technologies. Think virtual world up, down, left, or right, and experienced in 360 degrees. Form factors delivering this technology ranged from 5K gaming chairs to sleek eye glasses very much unlike the early Google glasses. Again, enterprise will have a big stake in this area with many use cases including B2B workforce training, safety inspections, AR glasses used by an architect to design a room, training surgeons across geographies, and in travel and tourism where you are able to take a trip to a tropical island right from your living room. Frankly, I prefer the actual trip but foregoing the lines at the airport and customs does sound appealing. Regardless of my preference, there was a lot of excitement for XR in commercial and industrial settings. Not to mention eSports which realized $1 billion in net revenue last year alone.
4. Culture: Pragmatics of Technological Innovation
While attending a panel discussion on “Future Cities” I was struck by a similarity between re-architecting an existing urban space to accommodate new technologies and the work we do at ADP.
A former secretary of transportation listed one of the greatest challenges to innovating cities as the pre-existing roadway infrastructure. He went on to say that between the legacy streets and traffic patterns it was actually the inability to imagine new ways of mobility that was the major barrier.
People get accustomed to “how things are done here” and find it difficult to adapt to changes in the system. This is a cultural and technical matter. Culture, at the most basic level, is the collection of practices and beliefs we take for granted. These habits are slow to change. New technical opportunities can catalyze innovation and cultural change, but this process is never a one-to-one.
Which brings me to humans.
5. Humans: Agency in a Data-driven Era
Humans (people like you and me) when faced with the explosion of new technologies – tech that augments our vision, our speech, our bodies and, even, our memory – begin to question their own reason for being. The existential ponderings around what it means to be human are concomitant with those group of technologies loosely described as “AI”.
Talk of “machine-human partnership” was pervasive on the CES exhibition floor and in panels and keynotes. For my part, I welcome the question as it points to a shared humanity that we often overlook. Yes, partnerships between people and technology will continue to evolve. Who has agency over the relationship will remain a critical point of personal reflection and public debate.
Female coders were encouraged to put their own self-doubt aside and to relentlessly pursue their education and dreams.
On a crisp autumn Saturday, 110 students arrived early to the New Jersey Institute of Technology (NJIT) campus center in Newark, New Jersey. They gathered to participate in the first-ever ALL-women 24-hour hackathon (where ADP was the diamond-level sponsor). There was a lot of excitement and anticipation in the air, both from the attendees and the Women in Computing Society organizers.
Don Weinstein, ADP Corporate Vice President and Chief Product and Technology Officer, kicked off the hackathon with a rousing keynote speech touting the importance of creating an inclusive work environment.
“I’m proud of ADP’s ability to continue to innovate as we lead the way in supporting the global workforce. Our edge comes from including varied perspectives and talent as demonstrated through events like this one,” Weinstein said. “We genuinely believe that diversity and inclusion will continue to fuel the future of work, and we remain committed to empowering a workforce that truly represents all walks of life.”
Next up was Isabel Espina, Vice President of WorkMarket Product Development (WorkMarket is an ADP company). Isabel shared her inspiring journey through the obstacles she had to overcome as one of a small handful of female engineering college students in a male dominated field. Her experience is familiar and relatable to many women in the STEM field. Isabel described how ADP has supported her career, as a technologist and as a mother, and that helped her find balance between both worlds.
Seema Murthy and Foram Shah from ADP’s enterprise architecture team conducted a very well-received hands-on workshop called Design Your Own API. The students found the material informative and immediately put their real-world coding skills to work in creating their projects. Lisa Schmidt from ADP’s college recruiting team brought a lot of energy and enthusiasm as students visited with her to learn more about internship opportunities at our company.
The judges evaluated the projects and had the difficult task of choosing the top five teams. The top five teams presented their ideas, and each team’s project was evaluated on the quality of the code, design appeal, functionality and creativity.
The first-place team, four NJIT computer science graduate students, created a Sign Language Alphabet Prediction Translator application. The application takes American sign language images, predicts what alphabet the image is depicting, and prints the predicted alphabet along with the confidence score. The use case and inspiration for the team was a fellow classmate who is deaf and mute. The team wanted to create an application for the specially-abled student to communicate more easily with professors and her classmates. This application would eliminate the need for a human translator to help the student make the technical language used in class understandable. The students used Google Cloud Platform’s Auto ML API with Tensorflow and Python for coding. It was a very creative idea!
In addition to winning cool prizes, the first-place team was invited to visit the ADP office to learn about the next generation of award-winning ADP solutions and experience our workplace culture. At the close of the event, I encouraged ALL student participants to put their own self-doubt aside and to relentlessly pursue their education and dreams. I reminded them that they alone have the biggest impact on their own education and career.
Through this Hackathon sponsorship (and the ones we plan to sponsor in the future), and our significant partnership with Girls Who Code focused on closing the Gender Gap in tech, ADP demonstrates our commitment to promoting and supporting women in technology careers.
Learn more about internship and career opportunities at ADP.
Manjula’s mantra: “Don’t focus on fitting in; figure out how to stand out.” After reading about her hard work, success and leadership, you’ll see Manjula walks the talk — and encourages others to do the same.
Growing up, Manjula Ganta wanted to be a doctor. She loved science and biology and was fascinated by how the body works as a machine. But med school was financially out of reach, so she chose a career in mathematics. Manjula’s mother encouraged her and her sisters to learn computers.
“My mother was a visionary and could see technology evolving even before the internet existed,” Manjula said. “From her experiences and struggles as a homemaker, forgoing a job opportunity due to culture constraints, my mom inspired her four girls to be independent and encouraged us to pursue our careers. She is the greatest influence on who I am today.”
From India to Omaha
Manjula grew up in a small town in southern India near Hyderabad. In school, she was very outgoing, smart, and well-rounded – a trait she carried into adulthood and her career. Manjula pursued a bachelor’s degree, majoring in mathematics. She simultaneously enrolled into a Diploma in Systems Management program that introduced her to computers. Manjula later earned her MBA with a major in finance, and graduated as class valedictorian.
She moved to Hyderabad to work for a financial services company as a management trainee. Manjula was quick to learn the intricacies of the business and even as an intern courageously presented her ideas. Soon she had an opportunity to design the development of an integrated app to better manage the company’s branch reports. “Curiosity and rapid technology changes led me to learn relational databases and the integrated enterprise application software,” Manjula recalls.
A few years later, Manjula married her high school sweetheart, who had moved to Omaha, NE. She moved from Hyderabad to Omaha, and they started a family. “It was a big adjustment for me, both culturally and professionally,” Manjula said, “and it took a while to figure out how to balance my career and family.”
Manjula began working in Boston as a Peoplesoft consultant for the state of Massachusetts, going home only every couple of weeks. “It was a very challenging time in my life, being a young mother with a traveling job – staying away from home and my toddler son,” she recalls.
Manjula then worked as a Peoplesoft technical consultant for a project with General Electric (GE) in New York in variety of roles. She successfully implemented various Peoplesoft modules, leading offshore teams. After a few years, Manjula’s husband took a new job and they moved to Atlanta, where she continued to work with GE remotely.
Have grit and break your own expectations – expectations can be a weight on your shoulders.
– Manjula Ganta, Director of Application & Development, GPT
After her nine-year project at GE, Manjula joined ADP National Accounts Services (NAS) Outsourcing (COS) division as a senior business systems analyst. “It was a big shift going from development to a business systems analyst role,” Manjula recalls. “I would still get into the code and give the developers inputs about the issues.” She laughingly added, “I think they got frustrated sometimes, but it also helped improve our communication.”
Manjula’s role soon expanded to managing the same development team across analytics, robotics process automation (RPA) and other web/cloud tools and technologies, and she was tasked with managing diverse virtual teams as a single global team. “I was responsible for helping the team see and execute the vision, removing any roadblocks and partnering with other leaders to make it successful,” she recalls. Manjula’s ability to combine business acumen and technical competency, along with her pragmatic approach, enabled her to be decisive and impactful across the COS business.
Manjula then became the Director of Strategic Initiatives for the NAS Tools & Technology Operations, where she worked on several technology and transformation initiatives to develop, support, and enhance ADP’s internal and client-facing tools.
Manjula says she’s taken this approach throughout her career: “As a thoughtful leader, I strive to create a positive and collaborative work culture with emphasis on employee recognition – helping teams to look beyond their differences. Celebrating associate birthdays, work anniversaries and key project milestones helps everyone feel valued and included.”
Currently, Manjula is a Director of Application Development, Global Product & Technology (GPT), where she takes an even broader responsibility for building ADP’s core products from a technology architecture, design, quality and user experience standpoint, to make them more effective for ADP’s clients.
Developing Self and Others
“ADP has a unique culture in which they put their associates first,” she says. “Prior to ADP, most of my development was self-initiated, but here we have many career development opportunities, mentorship programs, stretch assignments, networking events through employee resource groups, technical workshops, etc. You just need to be motivated and find the time to develop yourself.”
Manjula had the opportunity to enroll in an external Pathbuilders mentorship program. “The program helped me to become more self-aware, building my own personal brand inside and outside of ADP,” she says. Manjula is thankful to the leaders, mentors and sponsors who invested their time by providing her exposure at the business unit level.
Carrying it forward, Manjula helps mentor others at ADP and through various non-profit organizations. She is an active volunteer for Women in Technology based in Atlanta, which helps girls and women succeed from the classroom to the boardroom. Manjula recently joined the ADP GPT Women in Technology Leadership Mentoring Initiative (WiTL) that helps develop a diverse leadership talent pipeline through a formal mentoring program. She also volunteers for the American Heart Association, Special Olympics of Georgia, and leads several ADP business resource group events in the Alpharetta location, creating awareness and raising donations for causes she cares about.
Best Advice
Manjula offers this advice for women starting their careers in STEM: “Have grit and break your own expectations – expectations can be a weight on your shoulders. Don’t be afraid of making mistakes; it’s important to learn. Life is not just about success; it’s also about failure, difficulty, and learning to recover. Focus on the present, stay positive, and keep going.”
Manjula also recommends finding a mentor. “Mentors have helped me realize my worth and have inspired me to speak up, be myself, and encouraged me to take on the next challenge. One of my leaders would say, ‘I wish you had had your voice earlier.'”
“Always find your support system, family, friends or coworkers and don’t be afraid to seek help or delegate,” Manjula said. “You don’t have to be a perfectionist or do it all.”
She is very grateful for her husband, Ranjith, and two sons, Abhitej and Ritvik, who have always supported her career, helped at home, and offered new and different points of view.
“Have fun, no matter how hard things can get. Humor and fun can always make the journey (personal or professional) easier.”
Through all the learning and big changes as an Asian Indian immigrant and a woman in STEM, Manjula’s best advice is: “Don’t focus on fitting in; figure out how to stand out.”
Read about other ADP Women in STEM and learn about careers at ADP.
Inventor of the Year, Voice of our People, Career Path
Through ADP’s patent program, Anshuman’s name appears as an inventor on ten patent applications filed within the last five years, seven of which have registered.
Anshuman Gaur was named ADP’s Inventor of the Year. Through ADP’s patent program, his name appears as an inventor on ten patent applications filed within the last five years, seven of which have registered.
Since joining ADP 11 years ago in Hyderabad, India as a Test Analyst, he’s been an amazing contributor to our organization. We recently caught up with Anshuman to ask him about the patent process, his advice for other inventors, his cricket experience, and more!
What different roles you’ve had during your time at ADP?
I started as a Test Analyst in the Next Gen PayExpert team. From there, I moved to a business analyst role, and then a Sr. Business Analyst role within the same group. By this time, PayExpert had transformed into a single database Workforce Now (WFN) solution with HR, Payroll, Time & Benefits all running on the same platform.
In 2014, I moved to Alpharetta, Georgia, as a Product Manager for WFN shared products such as reporting, analytics, PaaS, etc. In this role, I had the opportunity to work on the launch of DataCloud, an HCM analytics product targeted at mid-market clients. After a short stint with the DataCloud product team, where I had the opportunity to pilot ADP’s compensation benchmarking and predictive analytics features, I went back to the WFN team as a Director of Product Management in Parsippany, New Jersey.
Video call with the team
In early 2018, life came full circle when I received the opportunity to lead the WFN Next-Generation product. We work on the future of work and pay every day, including some cool features like on-demand pay, punch to pay real-time calculations, etc. We have an awesome opportunity to challenge the status quo and lead in the market with a competitive next-gen offering.
In a nutshell, I’ve had so many roles and so much fun! 🙂
What did you think when you first learned you were ADP’s Inventor of the Year?
It was quite surprising, to be honest! Many great products and features are being built across the organization, so it’s an honor to be recognized with this award. Also, being on the same list as Frank Villavicencio, VP, Product Management, is an absolute privilege.
What’s your process for coming up with ideas that would be great for a patent?
That’s a great question, and something we focus on quite a bit in our day-to-day work. It’s a combination of client need awareness, market and competitive awareness, and problem-solving skills. I am lucky to have a great team of developers, UX designers, and product owners who bring these skills to the table. We look at how we can solve problems that give the customer a delightful solution and, at the same time, gives us a competitive advantage.
We recently filed a patent for a solution that not only eliminates some key challenges and pain points but also exceeds the competition. It’s worth securing those features with a patent.
What is the patent process at ADP?
It’s quite straight forward. Once you have identified a feature or an idea for a patent, you can submit an invention brief on our internal associate portal under the ADP Patent Program. In this document, you provide a brief summary of the invention, the problems it solves that couldn’t be solved before, and how the solution is unique.
Once this is submitted, IP lawyers make the magic happen coming up with claims, preparing the filing documentation, etc. You need to participate in reviewing these documents during the process. Once the application is submitted, you can easily track progress on the portal.
What advice do you have for other inventors?
We solve many large-scale problems here at ADP. Our inventions are unique to our size and our business, and so I encourage everyone to take a moment to ask a couple of questions as they discover new ways to solve problems:
“Am I creating an intellectual property?” If the answer is yes, “Does the solution solve a problem in a unique way that can be secured by a patent?”
These questions are a simple way to guide inventors through the decision-making process of securing IPs. There is no doubt that inventions are happening here. We need to take the additional and essential step in securing it.
What do you like best about working at ADP?
There are many things, from passionate people to amazing culture to great opportunities. But if I were to pick one, I would say it’s the large-scale problems that I love to solve working with various cross-functional teams.
What advice would you give to your 16-year-old self?
Don’t ever stop playing cricket no matter how hard and busy life gets! For the cricket fans out there, I used to bowl right arm, medium-fast.
What is your must-have app? Yelp & YouTube
Anshuman Gaur is a Senior Director, Product Management at ADP based in New Jersey.