Yesterday’s talent technology reports on yesterday’s data, but today’s innovations can turn your sights forward.
By The Editors
Talent tech solutions change nearly as fast as the speed of light, leaving some organizations in the dark. But many TA leaders have embraced innovation and are leveraging today’s AI and predictive analytics offerings instead of relying on yesterday’s data.
Consider what has changed. In the past, TA leaders would have access to several metrics and KPIs—but very little insight into what that data meant to the business. Looking at internal data about past performance, making assumptions based on broad averages, and depending on manual research will not lead to knowledge-based decisions around needed skills, the associated costs, and, ultimately, improvements to the TA process.
Analytics capabilities have evolved over time to help organizations identify challenges and offer possible solutions. As a result, AI-driven predictive analytics platforms can suggest actions based on the insights gleaned from the data. According to a report from Aptitude Research and Sevenstep, a predictive analytics system allows companies to:
- aggregate all talent data from different systems into one platform;
- identify what data applies to the specific question being asked or problem being solved;
- reveal where changes are needed, along with possible outcomes and the best path of action;
- build confidence with TA and HR teams presenting data to business leaders; and
- use data to prevent future challenges.
An AI-driven data aggregation and analysis solution can quickly deliver detailed intelligence addressing specific questions and demands. For example, data can explain how long each step in the hiring process takes, allowing for critical improvements. If a TA leader knows how many days a hiring manager takes after an interview stage—and it’s too long because valued candidates are dropping out—then they can make a data-driven adjustment to hit hiring goals.
Data can be leveraged even further to create a forward-looking view. Once a channel or source of legacy data is integrated and analyzed with external data sources, organizations can use predictive analytics to project hiring needs and outcomes based on resources. For example, if an organization has a goal of 50 hires per month, having access to data and predictive analytics will empower them to know how many recruiters will be necessary and how long it will take to achieve business results.
TA leaders can gain visibility into industries and the costs for skills based on internal and market data. Combining this data in a single-view dashboard allows TA leaders to access refined details by skill and location. This visibility also enables organizations to pinpoint problems. For example, suppose a hiring goal is to increase the diversity of candidates. In that case, an AI-driven solution will be able to identify if there is a particular point in the screening or interview process where drop-off occurs and suggest how to course correct.
A predictive analytics platform can solve another talent challenge: time to fill. With detailed data to guide decisions, TA leaders can understand why outliers occur. By understanding which roles or locations are time-consuming challenges, organizations can assign their highly-skilled specialized recruiters to solve them.
Advances in AI and analytics are providing organizations with the competitive advantage needed to get ahead in today’s market. The top platforms and solutions partners deliver market intel and problem-solving capabilities that allow TA to predict the path forward.