5 Questions on Workday Insight Applications

Workday today announced Workday Insight Applications, a brand new approach to business analytics. Workday’s Dan Beck, vice president of technology products and Adeyemi “Ade” Ajao, vice president of technology strategy, answer five questions about how the applications work─and the talent and technology behind them.

Workday Leaps Forward with Machine Learning

Dan Beck, vice president of technology products, and Ade Ajao, vice president of technology strategy.

How would someone use Workday Insight Applications?

Ade: Let’s say you’re an HR leader and you want to know, “Are my top performers at risk of leaving, and what can I do to keep them?” How the application will deliver this answer starts with uncovering patterns about your workforce that already exists in Workday, such as employee tenure, time between promotions, and performance review data. These insights are enhanced with external data we’ve pulled, such as indexes of public job postings that highlight high-demand positions in your industry or region. Then, Workday does the heavy lifting and complex math to illustrate which top performers are most likely to leave. From there, you’re able to pull up recommended job changes for each person ranked by impact on retention risk. And right within Workday, you can start the process to make that job change. We think it’s pretty exciting stuff for our customers.

What makes Workday Insight Applications different from other types of analytics applications?

Dan: I’ll put it this way; charts or graphs are often necessary, but the most valuable analytics are those where the hard work is happening behind the scenes. So the system can understand your unique organization─and even your behavior as a user─to deliver recommendations on your next course of action. That’s what really makes Workday Insight Applications different─the recommendations and the ability to act on them in one system. Our belief is that you can’t get to recommendations without knowing the context of the user: each one’s role, security rights, and even the decisions he or she faces. Workday has all of this user context already.

If Workday Insight Applications are so different, will there be a heavy learning curve for customers?

Dan: Actually it’s quite the opposite. We think this is the first time an enterprise technology company will deliver recommendations on your next business move with the level of simplicity offered by consumer applications. Think of something as simple as looking at a map application on your smartphone to figure out the fastest way home. The application describes the routes and predicts how long each route will take based on historical patterns of data. It then makes new, faster route recommendations given heavy traffic on your normal route. Cracking that code for the enterprise has been difficult, but we’re doing it.

Why has this been so hard to do up until now?

Dan: It’s well established that large organizations have a lot of finance and people data, and there’s a lot of value in that data. The issue is trying to make sense of it all. Finding a method in the madness requires talent and technology specialized in understanding data, classifying it, and applying algorithms that continually pull the most relevant and useful insights to the top. Our ability to do this was greatly enhanced by our acquisition of Identified in February. We gained an incredible team of experts in data science and machine learning─ literally the science of teaching machines to learn─who developed a technology called SYMAN. We have evolved SYMAN within the walls of Workday to find patterns and deliver predictions and recommendations that become more accurate and relevant over time based on the behavior and patterns of each person.

Are you growing this team of data science and machine learning experts?

Ade: Absolutely. Not only are we tackling some of the intellectually toughest and most intriguing problems out there, but also the solutions to these problems have the potential to make a real impact in people’s lives. Workday has a fascinating dataset, and we plan to continue to recruit experts as well as up-and-comers in the areas of advanced data science, machine learning, and data engineering to Workday. The consumer technology world has consistently done a better job at attracting the most brilliant minds in this area, but we have more ideas in development to keep attracting the best and the brightest. It helps that Workday is known for its fantastic culture and consistently takes top ranking in workplace surveys.