Today we launched Workday Next, a new initiative that serves as the hub for information and stories about our technology advancements, as well as the experts and up-and-comers behind them. Here’s a little background on what Workday Next is and why we decided to roll out this initiative.
Today we launched Workday Next, a new initiative that serves as the hub for information and stories about our technology advancements, as well as the experts and up-and-comers behind them.
Here’s a little background on what Workday Next is and why we decided to roll out this initiative.
When we announced Workday Insight Applications last November, followed by the availability of Workday Talent Insights in April, we went quite deep in our discussions about the technology and strategy behind these applications. We also shared stories on experts within Workday who applied data science and machine learning methods to build these predictive and prescriptive analytics capabilities.
We soon learned that people wanted to know more. Customers, potential employees, media, and analysts let us know they were intrigued by what Workday was doing in data science. This also prompted more questions about our efforts in areas such as user experience and mobile initiatives, and ongoing development of our core technology foundation.
We saw an opportunity to talk more about tech. Not just the innovation we’re delivering today, but what’s coming next for Workday and our customers—and that’s our hope for Workday Next.
We want this to be the focal point for you to find information and hear stories about our technology efforts, inventions, teams, and breakthroughs we believe are driving a new way for people to work and businesses to grow.
We’ve categorized this content into four pillars that best represent our focus areas: Workday Labs, Workday Sigma, Workday Stack, and Workday Ventures. Take a look below to find more content about each pillar. And please continue to follow Workday Next webpage to see our latest tech perspectives, news, and events.
Workday Labs
Workday Labs represents our team focused on deep research and customer partnerships in areas including user-centric design, mobile-first strategy, and design-thinking methods in order to deliver the next wave of user experience innovation.
“We’re building products for the future, not just products for today. What are people going to want and how are they going to interact with these things in the future? That forward-thinking aspect is something that really attracted me to Workday.”—Christen Penny, Product Designer, Workday
Workday Sigma
Workday Sigma represents our team focused on helping customers answer their biggest business questions by infusing the latest methods in data science, data engineering, and analytics into our platform and applications.
“The data science team here has a great opportunity to do some really groundbreaking work in the enterprise industry. And if you want to be part of it, and if you like challenge in terms of the variety of problems you get to see and variety of data sets that you get to see, this is the place to be.”—Vivek Tawde, Product Manager, Data Science
Workday Stack
Workday Stack represents Workday’s core technologies and underlying architecture, driven by a team that is continually testing ways to optimize the Workday experience as we help our customers grow.
“We have the opportunity for somebody to work on every type of technology you can think of. To me, that’s one of the biggest selling points of working in the stack development organization in Workday.” —Catherine Renwick, Vice President, Platform Engineering, Workday
Workday Ventures
Workday Ventures is our first corporate ventures fund that will be used to invest in early stage start-ups that are leveraging data science and machine learning to tackle enterprise challenges.
“We started Workday Ventures because we saw a gap in the enterprise world. On one hand, there were a lot of young companies with strong machine learning and data science backgrounds trying to solve enterprise problems, but on the other hand, we didn’t see any enterprise-focused corporate fund with a focus on machine learning and data science.”—Adeyemi ‘Ade’ Ajao, Vice President, Technology Product Strategy, Workday
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