Predictive analytics talent management is now the new technology advancement to talent analytics in HR. HR departments have been sitting on a huge pile of data, collected over the years. This treasure chest has never been utilized to drive insights and add value to the company. Having the data is not enough, analyzing the data towards specific goals is crucial.

Artificial Intelligence is the computer’s ability to start thinking for itself based on the data it is fed. AI is the umbrella term that covers machine learning as well as deep learning. These advanced technologies have the capability to continuously learn from data and adjust itself so that it gets more accurate with time. AI thenis the computer’s ability to think for itself and make decisions based on the new data it has access to.

What is AI and Predictive Analytics

Predictive analytics can predict future outcomes based on previous data patterns. Predictive analytics in talent management is proving invaluable to organizations in 3 ways

  • Finding ways to make organizations more attractive to new hires
  • Identifying trends to lower attrition rates
  • Improve levels of employee engagement

The Potential of AI in talent management

Predictive analytics in talent management will be a gamechanger in 2020. This is because of its potential to improve employee attrition rates by identifying possible problem areas and giving HR the foresight to put it right. Talent analytics takes raw data and extracts insights that can be applied to employee experience and productivity in these ways

  1. AI in recruitment: AI toolswere first adopted for talent acquisition.  It allowed the mundane tasks to be accurately taken over by AI and freed up recruiters to provide a more personalized experience to candidates. The results of using AI were measurable; Candidate screening process was cut from 28 minutes to 8 minutes. Another significant insight in talent acquisition in HR for 2019is that technology is used more in candidate sourcing (88%) and less in onboarding (49%).Social candidate discovery tools are already in use to scout out passive candidates. Future trends will see AI used much more widely for daily processes.
  2. Employee development: Predictive analytics in talent management is now being used to identify current skills set and career growth needsand then recommend training needs exactly when required. This intelligence will go a long way in retaining employees by providing them upskills that keep them engaged with their organization. AI will integrate this upskilling with succession planning and thus provide more growth opportunities to in-house candidates. This will improve recruitment costs as well.
  3. Better understand employee sentiment: For long, employee sentiment was completely subjective. AI has brought in a more evaluated understanding of employee sentiments. It does this by using numerous parameters such as analyzing workplace forums, emails and social listening. Predictive analytics can help HR to identify those at risk of attrition and personalized retention methods can be devised for different levels of employees.  For example, looking at data such as commute time, performance problems and satisfaction rates can help HR to addressspecific areas of concern. This will, in turn,  reduce attrition and prevent panic hiring which in turn will bring down recruitment costs and improve productivity.

While AI can take over the mundane jobs and provide for better data-driven decisions, employees can be hesitant about AI intrusion. HR must take care to ensure that AI tools adhere to tenets of non-bias as well as privacy and confidentiality.  AI in recruitment has great potential in transforming the workplace, it is still important to realize that its power lies in giving human interactions more space to flourish.