UPDATED 09:00 EDT / MARCH 20 2018

CLOUD

Oracle overhauls interface and adds candidate-recommendation engine to human capital cloud

Oracle Corp. today gave its Human Capital Management Cloud a social network-style “news feed” interface and bulking up artificial intelligence features for hiring and professional development.

The news feed metaphor is the most dramatic change current users will notice. It uses machine learning to highlight the data and details people care about most. Relevant analytics can be displayed and updated automatically and people can find employee-related more easily than before. The software’s search capabilities have also been improved, and the experience made more consistent across devices.

The new interface is being combined with a responsive-design overhaul aimed at making the experience more consistent across devices, said Gretchen Alarcon, group vice president of HCM Strategy at Oracle. “People have gotten used to the scrolling paradigm instead of clicking through pages,” she said. Managers can choose which tasks appear in employees’ news feeds, and machine learning algorithms promote or demote tasks based upon user preferences, in the same way that social networks promote friends’ activities in other people’s news feeds.

New AI-enabled features are primarily focused on hiring and retention. Candidates can now search for jobs and get questions answered directly through a Facebook Messenger chatbot. They can also receive alerts about updates and needed actions on for jobs of interest. Machine learning capabilities reduce the time it takes to fill open positions by highlighting best-fit candidates and proactively identifying candidates and employees who should be invited to apply, Oracle said.

The recruiting features build upon filtering capabilities that have existed in Oracle HCM Cloud for several years that apply about 200 different elements to a candidate in order to determine the best fit for a particular job. Factors might include the length of time since candidates’ last vacations, the performance level of their previous supervisors and the time since their last salary increase.

With machine learning, Alarcon said, “over time, the engine will tune to see which factors have more of an impact in a particular organization. It’s about using adaptive intelligence to identify best-fit candidates not only based on how they line up against the requisition, but also based on all the information we have about other people in the organization.”

Machine learning is also being applied to performance manage to ensure that employees are getting all the feedback they need to succeed. New performance “check-in” capabilities ensure that coaching and feedback are aligned to goals, and a “self-driving” promotion process helps employees reach objectives by providing proactive alerts.

The features build up an “anytime feedback” concept that was added to the product several years also to provide a means for supervisors to give employees unstructured feedback at any time. That capability is being extended with a more rigorous check-in process that includes such factors as ratings and responses to questionnaires. “The idea is that a manager can go back at any time and check on whether appropriate feedback was given,” Alarcon said.

The base price for HCM Cloud is $13 per user per month. Additional pricing information is here.

Image: Oracle

A message from John Furrier, co-founder of SiliconANGLE:

Your vote of support is important to us and it helps us keep the content FREE.

One click below supports our mission to provide free, deep, and relevant content.  

Join our community on YouTube

Join the community that includes more than 15,000 #CubeAlumni experts, including Amazon.com CEO Andy Jassy, Dell Technologies founder and CEO Michael Dell, Intel CEO Pat Gelsinger, and many more luminaries and experts.

“TheCUBE is an important partner to the industry. You guys really are a part of our events and we really appreciate you coming and I know people appreciate the content you create as well” – Andy Jassy

THANK YOU