How To Make Optimal Use Of Talent Data
Talent data is defined as information and insights that an organization has available on its talent that has been collected from its talent management system (TMS).
This includes data pertaining to recruiting, onboarding, learning, performance, compensation, succession, and workplace collaboration. In modern workplaces, this information can include demographic, mobility/activity, behavioral data associated with the talent from either internally or externally.
Given the rate at which technology has been adopted into the talent management ecosystem, the emergence of talent data as a defining parameter is unsurprising. This talent data also offers HR leaders deeper insights into their workforce.
Apart from analyzing talent performance, modern talent data platforms also empower workforce planners with a comprehensive view of workforce diversity & reskilling opportunities.
Here are some use cases where talent data/ analytics plays a crucial role:
Track your hiring metrics better: Talent data provides HR managers with quantifiable data on their average costs per hire, the average time to hire, most successful hiring source, etc.
These metrics help recruiters focus on hiring to further their business objectives rather than waste time on ineffective hiring processes.
Leverage predictive analytics: Predictive analytics is here to overhaul the entire hiring pipeline for good. While AI has been a trending topic for many years, it is only very recently that workforce planners have begun to leverage it.
Using data-powered predictive analytics, workforce planners can
- create a model for performance management
- effectively target and address training needs
- make forecasts for the future and predict what skills they look for in new candidates.
Improve employee retention: Using the insights garnered from predictive analytics, workforce planners can circumvent or fix existing enterprise culture gaps to plug talent leak.
One way that most companies have done this is by implementing a comprehensive reskilling strategy. Job roles at threat of disruption can now laterally move to another job role with wildly varying skill sets, thanks to robust reskilling tools.
Here is an example of such a reskilling journey, where a person can transform from a Systems Engineer role to a Big Data Analyst role. Obviously, such an investment by the company into their employees will drastically cut down their attrition rates.
Promote transparency and nurture diversity: Thanks to the robust data collection capabilities of modern talent data platforms, it is now possible for workforce planners to correctly identify diversity gaps – whether ethnic or gender-based – and pivot their hiring process to fix it.
Some talent intelligence platforms, such as Draup, also provide location-level intelligence. This enables companies to hire low-cost, highly-skilled talent from tier 2 and tier 3 locations.
By doing this, they are essentially establishing a monopoly on the talent market in the region.
Various case studies have proven that this is a very successful model to ensure a continuous supply of employable talent.
Draup for Talent provides workforce planners with actionable intelligence on location, hiring costs, and academic support for target roles.
Powered by data from 4000+ sources, Draup also enables HR teams to craft ideal reskilling journeys for their employees in disrupted using our proprietary Reskilling Navigator tool.