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Home HR and Marketing Workday’s Response To AI and Machine Learning: Moving Faster Than Ever

Workday’s Response To AI and Machine Learning: Moving Faster Than Ever

This week we met with Workday at the company’s annual Innovation Summit and I walked away very impressed. Not only is Workday clear-eyed and definitive about its AI product strategy, the company is entering one of its strongest product cycles in years. I have never seen so many Workday features reach maturity and it’s clear to me that the platform is hitting on all cylinders.

Let me start with an overview: the ERP market is big, important, and changing. Every company needs a financial and human capital system, and these platforms are being asked to do hundreds of things at once. We expect them to be easy to use, fast, and instantly configurable for our company. But we also want them to be easy to extend, open to integration with many other systems, and built on a modern architecture. How can Workday, a company founded 18 years ago, stay ahead in all these areas?

It’s actually pretty simple. Workday is not an ERP or software applications company: it’s a technology company that builds platforms for business solutions. In other words, Workday thinks “architecture first, applications second,” and this was reinforced again and again as we went through Workday’s offerings. Let me give you a few insights on what we learned, and I encourage you to contact us or read more from Workday on many of the things below.

First, Workday is quite clear that AI and Machine Learning will, over time, reinvent what business systems do. The traditional ERP world was a set of core business applications which include Financials, Human Capital (HCM), Supply Chain, Manufacturing, and later Marketing, Customer Analysis, and others. Almost every vendor who starts in one of these areas tries to move into adjacencies, primarily with the goal of “selling more software to existing customers.”

Today, while companies want to consolidate these applications (a big opportunity for Workday), the bigger goal is reinventing how these applications work together. As Workday describes it, their goal is to help businesses improve planning, execution, and analysis. When it’s hard to hire, like it will likely continue to be for years, we want the HCM system to help us find contractors, look at alternative work arrangements, and arrange financial and billing solutions to outsource work or tasks, and also find and develop internal candidates. So the “red lines” between these applications is blurring, and Workday understands this well.

In a sense this is the core of our new Systemic HR Operating Model. We want these various HCM systems, for example, to look at all four of these elements and help us manage them together. Workday’s new HCM demo actually showed some of this in action.

Beyond ERP To AI And ML At The Core

But the platform market is even moving faster. Not only do companies want a suite of apps that work together (Workday, Oracle, SAP, and others do this), they want AI and machine learning to operate across the company. And this will change what ERP systems do. Workday listed more than 50 different “machine learning” experiences the company is already delivering, and the take the form of “recommendations” or “forms pre-filled out” or “workflows pre-designed” that don’t look like magic, they just look like intelligent systems that help you run your company better. And this is where Workday is focused.

The new Workforce Management system (labor optimization), for example, can predict hiring and staffing needs based on month, weather, and other external inputs. It can then schedule workers based on their availability, skills, and wages. And it can automatically create a workforce schedule, decide when contract labor is needed, and then automatically create hiring portals and candidate experiences to find people. This is really “AI-enabled ERP” not a fancy demo of Generative AI to make emails easier to write.

Workday HCM Continues To Mature

The Workday HCM suite is in the strongest shape I’ve seen in years. The Workday Skills Cloud is maturing into a “skills intelligence platform” and it now has features that make it almost essential for a Workday customer. It can import data from any vertical or specialized skills database, it gives companies multiply ways to infer or assess skills, and it gives you dozens of ways to report on skills gaps, predict skills deficiencies, and create upskilling pathways for each employee or workforce group. I’ve watched this technology grow over the years and never before have I seen it so well put together and positioned to do what companies want.

This is not to say, by the way, that companies still need specialized skills systems for recruiting (Eightfold, Beamery, Phenom, Seekout, Paradox, iCims, others), mobility (Gloat, Fuel50), learning (Cornerstone, Docebo, Degreed), pay equity (Syndio, Trusaic, Salary.com), and many more. In some sense every HR tech platform now has a skills engine under the covers (remember, a “skill” is a series of words that describes attributes of a person) and these systems leverage these data elements for very unique purposes. Skills Cloud, in its more mature position in the market, is intended to be a “consolidation point” to bring the taxonomy into one place. (And it’s the skills engine that the Workday HCM tools rely upon.)

I know, by the way, that all Workday customers have a multitude of other HCM systems. Given the innovation cycle taking place (vendors are getting on the AI bandwagon in very creative ways), this is going to continue. But Workday’s role as the “core” remains strong, particularly because of my next point.

Workday Is Now Truly Open

I was also impressed with Workday’s progress with Extend and Orchestrate, the external APIs and development tools that enable customers and partners to build add-on applications. Workday as a company is not planning on building a lot of vertical solutions, rather they are now pushing partners (Accenture, PwC, and clients) to contribute to the app ecosystem. This creates a “force multiplier” effect where third parties can make money by building a dev team around Workday. (This, by the way, is why Microsoft is so ubiquitous: their reseller and partner network is massive.)

In addition to these programming interfaces, Workday has made a serious commitment to Microsoft Teams (Workday Everywhere). You can now view Workday “cards” within Teams and click on deep links within Teams that take you right to Workday transactions. While the company is still committed to continuous improvements in its user interface, I think Workday now understands that users will never spend all day figuring out how Workday works. I believe this trend will continue, and I encouraged Workday to consider Chat-GPT as the next major interface to build. (They were non-commital).

Vertical Applications

I asked the management team “what do you think about Oracle’s decision to buy Cerner, one of the leaders in clinical patient management? Do you think this threatens your vertical strategy?” Aneel Bhusri jumped up to argue “we would never buy an old legacy company like that – it would never integrate into our architecture.” This matters because Workday’s integrated architecture lets the company deliver AI at scale. In other words, Workday intends to be the pure-play architectural leader, and let the vertical applications come over time.

Today Workday focuses on the education market and has several vertical solutions in financial services, insurance, and healthcare (many built by partners). I don’t think the company is going to follow the SAP or Oracle strategy to build deep vertical apps. And this strategy, that of staying pure to the core architecture, may play out well in the longrun. So for those of you who want to build addons, Workday is opening up faster than ever.

What About AI In The Core?

Now let’s talk about AI, the most important technology innovation of our time. Sayan Chakraborty, the new co-president and a recognized academic expert on AI, has a very strong position. He believes that Workday’s 60 million users (many of which have opted in to be used for anonymous neural network analysis), give the company a massive AI-enabled platform already. So the company’s strategy is to double down on “declarative AI” (machine learning) and then look at Generative AI as a new research effort.

In many ways Workday as been “doing AI” since they acquired Identified in 2014, and many AI algorithms are built into the Skills Cloud, sourcing and recruiting tools, and myriad of tools for analytics, adaptive planning, and learning. Most of the product managers have AI-related features on their plates, and David Somers, who runs the HCM suite, told us there are hundreds of ideas for new AI features floating around. So in many ways Workday has been an “AI platform” for years: they’re just now starting to market it.

That said, Workday’s real data assets are not that big. Assume that 30 million Workday users have opted in to Workday’s AI platform. And let’s assume that the Skills Cloud has tried to index their skills and possibly look at career paths or other attributes. Compared to the data resident in Eightfold (over a billion user records), Seekout (nearly a billion), and systems like Retrain.ai, Skyhive, and sourcing systems like Beamery or Phenom, this is a very small amount of data. At some point Workday is going to have to understand that the HCM AI platforms of today are really “global workforce data” systems, not just customer data systems. So most of the AI we’ll see in Workday will make “your version of Workday” run a bit better.

Prism: Workday’s Strategy To Consolidate Data

Finally let me mention the growth of Prism Analytics (now referred to as just Prism), Workday’s open data platform for analytics and third party data. When the company acquired Platfora the original need was to give Workday customers a place to put “non-Workday data.” Since the Workday data platform is a proprietary, object-based database, there was no way to directly import data into Workday so the company needed a scalable data platform.

Since then Prism has grown exponentially. Initially positioned as an analytics system (you could put financial data into Prism and cross-correlate it with HR data), it is now a “big data” platform which companies can use for financial applications, HR applications, and just about anything you want. It’s not designed to compete with Google Big Query or Red Shift from AWS (at least not at the moment) but for Workday customers who want to leverage their investment in Workday security and existing applications, it’s pretty powerful.

One of the customers who spoke at the conference was Fannie Mae, who has more than $4 trillion in mortgages and loans in its risk managed portfolio. They are using Prism along with Workday Financials to manage their complex month-end close and other financial analysis. Last year I met a large bank who was using Prism to manage, price, and analyze complex banking securities with enormous amounts of calculations built in. Because Prism is integrated into the Workday platform, any Prism application can leverage any Workday data object, so it’s really a “Big Data Extension” to the Workday platform.

And that leads back to AI. If Sayan’s vision comes true, the Workday platform could become a place where customers take their transactional data, customer data, and other important business data and correlate it with Workday financial and HCM data, using AI to find patterns and opportunities. While AWS, Google Cloud, and Azure will offer these services too, none of these vendors have any business applications to offer. So part of Workday’s AI strategy is to enable companies to build their own AI-enabled apps, implemented through Extend and Orchestrate and fueled with data from Prism.

This is going to be a crowded space. Microsoft’s new Power Platform Copilot and OpenAI Azure Services also give companies a place (and method) to build enterprise AI apps. And Google will soon likely launch many new AI services as well. But for companies that have invested in Workday as their core Financial or HCM platform, there are going to be new AI apps that wind up in the Workday platform – and that drives utilization, revenue (through Extend, Prism, and Orchestrate), and even vertical apps for Workday.

Workday’s Position For The Future

In summary, Workday is well positioned for this new technology revolution. I did challenge the management team to consider ChatGPT as a a new “conversational front end” to the whole system and they agreed that it is on their list of things to look at.

(By the way, the creative solutions coming to HR in Generative AI are going to blow your mind. I’ll share more soon.)

For enterprise buyers, Workday remains rock solid. With only a few major competitors to think about (Oracle, SAP, UKG, Darwinbox, ADP), the company is likely to continue to grow market share for large companies. There will be pricing pressure because of the economy, but for companies that want a first-class technology platform for core Finance and HR, Workday will continue to be a leader.

Additional Resources

The Role Of Generative AI And Large Language Models in HR

New MIT Research Shows Spectacular Increase In White Collar Productivity From ChatGPT

LinkedIn Announces Generative AI Features For Career, Hiring, and Learning

Microsoft Launches OpenAI CoPilots For Dynamics Apps And The Enterprise.

Understanding Chat-GPT, And Why It’s Even Bigger Than You Think (*updated)

Microsoft’s Massive Upgrade: OpenAI CoPilot For Entire MS 365 Suite.

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