Four Basic Steps to Getting Better Candidates
Quality of hire is an elusive concept that seems to defy definition. I can’t count the number of conversations I have had on candidate quality with no final answer. Yet everyone claims they know a quality candidate when they meet one.
Here are the two big questions: What defines a high-quality candidate? What makes a good candidate different from a great one?
The guidelines here attempt to help clarify and make the answer to these questions easier
Number 1: Establish a definition of quality with the hiring manager.
Most organizations have no definition of a “quality employee.” We often say we will know one when we see one, but we can’t articulate what that means. Let’s start by stating that if quality means performing well, then there also needs to be a way to measure performance as objectively as possible. While I could write a long column on the pros and cons of performance management systems and philosophies, suffice it to say that before any performance can be assessed, the organization has to have a clear idea of what good or exceptional performance looks like. But to do this objectively, you need data and lots of it.
Number 2: Quality is an output, not an input
Quality is more about what someone does, what they accomplish, and how they do it. We judge top CEOs by the success of their organizations. We judge a sports personality by their performance and win records. We measure a doctor by his success in curing patients. We don’t measure them by their degrees, personality, or by specific skill. We must define carefully what we expect an employee to accomplish and determine what enables them to do it well.
A manager should have a clear performance goal for a specified period. The goal should be measurable, objective, and can be confirmable by more than one person.
Number 3: Use data
You will need to collect data about employees who have achieved their goals over time to establish a pattern of actions, behaviors, and skills. You can define quality in many ways: performance, sales levels, customer satisfaction, or patents issued, for example. We often try to define quality by skill level, education, or cultural fit. In some cases, these may be important to consider, but they do not define quality.
Number 4. Use Artificial Intelligence
One of the most immediately practical uses of A.I. algorithms for recruiters is to analyze large volumes of data and look for patterns of behavior that can predict future performance. A.I. has the potential to determine candidate suitability across multiple dimensions. It can also reduce bias and make hiring more of a science than it is today.
Artificial Intelligence can analyze data such as resumes, social media activity, and past job performance. AI-based systems can use machine learning algorithms to identify patterns in this data that correlate with success within a specific role.
For example, an AI-powered recruitment tool could analyze a candidate’s resume and compare it to those of previous successful employees in similar roles. It could also evaluate assessment results conducted during the selection process to provide insights into personality traits common to top performers. Historical data helps recruiters prioritize which applicants are worth interviewing further.
Privacy, Bias, and Legislation
As A.I. becomes easier to use and incorporate into software, governments are working to legislate and regulate how it is used. This is likely to be poorly done as they are trying to legislate what they do not understand – what none of us really understand. We don’t know the long-term effects of A.I. or whether it will be a benefit or a curse. Right now, the use of A.I. is a political issue more than an objective one. Every new technical innovation has resulted in a backlash of legislation that tries to damper or stop its spread.
While there are legitimate concerns about a candidate’s rights and privacy and whether algorithms are biased, we can be hopeful that whatever legislation is passed will allow individuals to make their own choices and allow firms to continue improving and developing how it is used. Over time, results and public opinion will better regulate how A.I. is used than hastily enacted legislation based on incomplete understanding and fear.
As recruiters, we need to use A.I. with common sense and with an understanding that we are not striving for perfection but for improvement in how we hire. Using A.I. does not mean that we filter out everyone who does not profile perfectly. What it does mean is that we get a deeper understanding of a candidate’s skills and potential than we can using the crude tools we now have of the resume and the interview. These are far more skewed and biased than anything we see from algorithms.
A.I. will supplement and improve recruiting over the next few months and years. It will speed the hiring process, reduce bias, and enhance the quality of candidates.
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