Will Workday Disrupt Cloud Computing Using Machine Learning?

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For the third year in a row, cloud-based financial and human resources enterprise services provider Workday (NASDAQ: WDAY) was ranked as the leader in Gartner’s Magic Quadrant for Cloud Core Financial Management Suites for Midsize, Large, and Global Enterprises. Gartner recognized Workday for its Intelligent Capabilities, analytics, intuitive experiences and better business planning abilities. Workday’s recognition in the industry is also translating to higher revenues, as was evident in its first quarter result announcement. 

Workday’s Financials

Workday’s first quarter revenues grew 33% over the year to $825.1 million, ahead of the Street’s forecast of $814 million. Its net loss widened to $116.3 million, or $0.52 per share from $74.4 million, or $0.35 per share recorded a year earlier. On an adjusted basis, it recorded an EPS of $0.43 which was ahead of the Street’s forecast of $0.41 and grew over previous year’s $0.33.

By segment, Subscription services revenues grew 34% to $701 million, ahead of the management’s guidance of $692-$694 million. Professional services revenues grew 29% over the year to $124 million and exceeded the guidance of $120 million.

For the current quarter, Workday expects to earn subscription revenues of $746-$748 million and professional services revenues of $124 million. It expects to end the current year with subscription services revenues of $3.045-$3.06 billion and professional services revenues of $500 million. The market was looking for subscription revenues of $741.6 million for the quarter and $3.047 billion for the year.

Workday’s ML Focus

In its recent annual summit, Workday’s management focused on the growing importance of Machine Learning (ML) within cloud computing. It believes that ML will “disrupt the marketplace” as it helps customers make better decisions. It is already developing ML and graph processing capabilities that can be leveraged across all of its applications.

It is working with its customers and focusing on concrete use cases as are already apparent to them. The first application-specific use of ML and graph analysis is its newly launched Skills Cloud, which powers a Skills Insight feature that will discern team, employee, and candidate skills and offer-related recommendations on hiring, training, team building, and project planning. Workday is building its ML capabilities on open-source technology, and, in some cases, Workday-developed algorithms. These platform-level ML capabilities will help power augmented analytics and planning capabilities across its platform.

It is also working on deploying ML within the user experience arena. It is building a self-modifying user experience that will adapt to the customers as their needs change. The self-modifying user experience will be designed to learn from and adapt to that user.

Within the analytics segment, Workday released a unified reporting architecture for all Workday users, called the Discovery Board. The service leverages shared ML, graph and pattern-detection capabilities available across the platform and integrates it with natural-language generation capabilities to turn raw data into actionable insights. It plans to introduce multiple augmented analytics applications but has first started with a Workday People Analytics app. The app has been released to design partners and uses ML, graph, and NLG-powered insights to help organizations focus on hiring, workforce composition, diversity and inclusion, talent and performance, and retention and attrition.

The market is pleased with Workday. Its stock is trading at $199.60 with a market capitalization of $45.11 billion. It had touched a 52-week high of $217.73 last month. It had fallen to a 52-week low of $117.24 in June last year.

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