Our customers store their most sensitive people and financial data inside of Workday, and it’s not something we take lightly. If data is the new oil, then discovering, refining, and making data as useful as possible is vital to the smooth functioning and growth of any company. With this in mind, last October we announced the availability of Workday Prism Analytics, enabling customers to blend and transform any data—including Workday data and data from any outside source—to enrich their financial and people analytics, putting data into the hands of decision-makers.
With Workday Prism Analytics, we’re providing self-service tools across the entire analytics process, from data integration all the way to reporting. And today, Workday Prism Analytics has moved into primetime with the introduction of data discovery, an entirely new way to build reports and explore your data visually in Workday, enabling analysis at the speed of thought with drag and drop chart creation.
We asked Pete Schlampp, vice president, Workday Analytics, to provide an introduction to data discovery: why it matters to your organization, the benefits to customers, and what to expect in the future.
Data discovery is a new capability within Workday Prism Analytics that allows the user to quickly visualize data to understand their people and financials, detect patterns, and discover insights. It’s a visual, drag-and-drop interface with an intuitive UX, that enables users to distribute visualizations as Workday reports or as a worklet on a dashboard, and quickly share with just a few clicks.
Workday Prism Analytics extends the core capabilities of Workday, enabling users to explore data and search for insights, all within the same system. Because analytics are directly connected to the application, you can easily traverse from insight to action. So, if during the process of data discovery you uncover something interesting, you can click into the relevant worker or supplier for more context, and can even kick off a business process such as updating payment terms or worker compensation.
“With all of your data elements right in front of you, making changes is easy and fluid.”
Doing analysis within Workday also means that sensitive financial and people data stays secure, and the integrity of that data can be trusted. And, data that is brought into Workday can be secured as if it were native to the platform, enabling insights to be shared, securely and with the appropriate access controls, across the organization.
Workday Prism Analytics enables users to bring third-party data into Workday to enrich their people and financial analytics. And with data discovery, users have the right data at their fingertips to make better business decisions. For example, customers may seek to understand the operational drivers behind revenue and expenses, which often comes from industry-specific systems such as patient management or point-of-sale. Other customers are trying to get a big-picture view of all of their workers (who may not all be in Workday), or calculate the cost of their workforce. Still, others are bringing in operational data to better understand things like worker performance or looking at long-term trends in turnover or compensation. With all of your data elements right in front of you, making changes is easy and fluid. This video explains why organizations are becoming more data-driven:
Users often have a question in mind that they want to answer before they begin. They may have a hypothesis that they are looking to test. With data discovery, Workday is providing the self-service tools to enable users to do their job, ensure they are operating with the latest, real-time data, and have the freedom and flexibility to answer their questions, wherever the data takes them.
Our customers are already sharing numerous possibilities for data discovery, and while we’re just getting started, we’re excited for what’s to come. In future releases, we plan to expand the types of charts offered and the ways users can interact with them, as well as add further advanced analytics, and build in machine-assisted capabilities. Stay tuned!