It’s no secret that business is evolving rapidly. The current work landscape is so different from pre-pandemic times that it’s hard to even begin listing all the changes. Do we start with permanent work-from-home positions? How about the historic candidates’ market? With circumstances changing daily, companies are looking for ways to use technology to become more efficient.
Employee selection is a great example. According to one survey, 49% of companies listed talent selection tools as one of their technology needs. And the supply of talent selection technology is just as overwhelming as demand. The sheer number of solutions makes one question loom large: How can companies make the right decision?
It’s more than possible to make technology part of the selection process. But some methods are not as helpful as they seem. One option is to use AI algorithms. These algorithms determine which features of resumes, essays, or other materials are related to performance. Then, the algorithms scan candidates’ materials for those features.
AI’s efficiency is appealing, but there’s no guarantee that it will use features that make sense for the job. For example, an essay-scoring algorithm factored word count into its scores. That’s not exactly something a company would be comfortable using to make a five-, six-, or seven-figure decision.
Even more concerning, some algorithms have used traits like race and gender in their decisions. Developers had to stop working on one algorithm after discovering that it penalized words like “women’s” in resumes. AI might be efficient, but efficiency is a poor substitute for quality and fairness.
Even so, companies do need a way to make selection more efficient. Fortunately, an effective approach is to substitute an in-person hurdle with a reliable, valid online assessment. In an online assessment, candidates answer a series of deliberately selected questions, choosing the answers that best describe them.
Like AI, online assessments make recommendations based on features that predict performance. But with AI, a machine is in charge of deciding which features are important. With online assessments, people are.
Through careful research, developers of online assessments create a tool that both predicts performance and measures meaningful patterns of thoughts, feelings, and behaviors. Companies get the big picture of what to expect from each candidate. This helps them better understand their candidates, improves the selection process, and sets the stage for employee development.
So, how can organizations make technology part of selection responsibly? It’s all about choosing a solution that treats candidates like people, not data points. AI makes prediction efficient, but it reduces candidates to a series of numbers. Online assessments add meaning to prediction by measuring easily understood, job-relevant characteristics.
Top performers want to be understood. Companies need to know not just whom to select, but why. Online assessments meet all these needs with the efficiency we expect from modern technology.
Why settle for prediction alone when you can predict and understand?