New stories, Research, expert interviews, and the pulse of the industry are clear. The trends below will be most impactful in shaping how you hire in the years to come.
Diversity is the biggest game-changer and most embraced trend with over half of companies are already tackling it head-on. Companies of repute have taken upon themselves to appear more humane and just, without which they understand that they will not be able to protect their brand in the minds of hyper-connected and fairness seeking youth. The other big factor that unprecedented economic growth in 21st century has dried up traditional and limited talent pools. It has become doubly important to evaluate alternate talent pools across the world. The necessity of protecting brand and meeting the requirements of talent both get beautifully combined under umbrella of Diversity.
New interviewing techniques (e.g., soft skills assessments and job auditions) are gaining favor as ways to augment traditional interviews, but adoption is still early. With the arrival of SMAC, the hiring digital systems are bursting at seams with Candidate Applications. For many companies which are favorites in the job markets, there is simply no bandwidth available to be able to do personal-interview for every candidate to make hiring decisions. New models and tools are emerging to help do in a manner which saves time, money and travel.
About half see data as critical to the future of hiring, but consistent usage still isn’t widespread. So far, the candidate data was seen to have only temporal value. Organizations are now releasing that just like retaining and rewarding loyal customer there is value in retaining candidate data and building lasting relationships with them. However, this depends upon adopting right digital platform to first start maintaining data and then fulfilling organization objectives backed by right data tools to craft and execute relation building strategies.
AI is the least mature trend, but don’t be fooled: you’re probably already using AI in your job and it may just be the boldest disruptor of all. However, there is a general confusion in the market and among users about what is Machine Learning and what is AI. While Machine Learning is based on history of actions on limited data sets of company (and the attributes which were captured and not captured) and extrapolation onto future actions, it has serious limitation in perpetuating biases. Who can forget the infamous Gender Discrimination in Recruiting at Amazon.
AI while is at the nascent stage, holds the bigger and better promise, with abilities to proactively direct both its objectives and self-learning models.