The News: Workday, Inc. announced on July 12 that the next generation of its patented Elastic Hypercube Technology (EHT), the intelligent modeling engine that powers Workday Adaptive Planning, is now generally available to its customers. EHT in Workday Adaptive Planning is now enhanced with new embedded AI and performance improvements that efficiently calculate complex models by adding memory and compute power as needed, resulting in dynamic, automatic scaling, while also supporting highly complex, multi-dimensional planning requirements and a high level of concurrent users without sacrificing speed or performance. You can read the original Press Release on the Workday website.
Workday Announces Elastic Hypercube Technology for Workday Adaptive Planning
Analyst Take: Workday announced the latest version of its intelligent data modeling engine, Elastic Hypercube Technology (EHT), which powers Workday Adaptive Planning, its enterprise-focused planning software. Workday highlights several new features and design attributes that address issues faced by large organizations that often need to incorporate a wide variety of data sources, while ensuring users across the enterprise can be assured of real-time, concurrent access to the platform without sacrificing speed or performance.
Increasing Data Volume and Types of Data Are Driving Complex Planning Scenarios
As the use of new and more varied data sources used in corporate planning has become more commonplace, enterprises often struggle with increasing complexity, from a data management and an application performance perspective. Today’s enterprise planning goes beyond simply looking at internal company data, such as sales forecasts, marketing activity, and current resource allocations, and has expanded to include a wide range of external data sources. It is common for large enterprises to incorporate external data sources such as microeconomic forecast data, weather data, labor statistics, competitor data, and micro-regional data.
The addition of greater dimensionality, new types of data and data sources, and the emergence of AI and machine learning (ML) technologies have led to greater complexity in the planning process. Further, as a wider range of users are involved in planning, more demands are placed on the tools used for planning.
New AI Tools and Scaling Technology to Help Meet Demanding Planning Scenarios
Workday’s latest EHT is designed to add memory and compute power as the complexity and scale of the model or forecast increases. This enables fast response times for analytics, calculations, and data updates, ensuring that users across the company can access and work with the information when they need to. Further, EHT allows near-unlimited dimensions and versions to drive more complex planning as well as scenario analytics, while supporting a high level of concurrent users, without sacrificing speed or performance.
The expanded processing power ensures that reports, dashboards, and sheets will open quickly, without any performance degradation, including for very large, multi-dimensional views. The incorporation of embedded AI in EHT is designed to anticipate and compute calculations based on past behaviors and inspect the overall model to identify empty data cells where analysis is not required, further optimizing compute resources.
Workforce Planning Complexity Will Only Increase Over Time
As enterprises continue to capture and integrate data from an increasing number of internal and external sources, workforce planning will continue to increase in complexity. The ability to scale compute resources to account for more complexity is a key feature that buyers and users will need to consider, particularly as organizations incorporate real-time data, which can rapidly overwhelm traditional systems.
Additionally, given today’s expectation for enterprises to respond quickly to deviations from planned or expected scenarios – consider the drastic, near-instantaneous changes seen at the start of the COVID-19 pandemic shutdowns – organizations need to be able to quickly ingest new data and then quickly generate reports immediately, and ensure that key stakeholders can respond quickly. In such a case, speed or performance issues with planning software can have significant operational and financial implications.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
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Author Information
Keith Kirkpatrick is Research Director, Enterprise Software & Digital Workflows for The Futurum Group. Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
