If your business is just getting big enough to bring on full-time employees, hiring might be an exciting prospect. You get to search for the best people to build your vision and take things to the next level.
After a while, though, hiring can be a bit of a slog. You have to painstakingly craft a job description and figure out how to advertise it to get noticed by the right people. If you’re lucky enough to get multiple qualified candidates, there are numerous rounds of interviews and tough decisions.
Then despite your time and effort, your hire may or may not work out. Their actual abilities may not match up with the promise of their resume. Or your hire’s personality might be a poor fit for the work culture you’ve established. Or perhaps the new employee decides it’s not the right role for them after all. The hiring cycle begins again.
After a few rounds of hiring, the process tends to lose its luster. Technology has tried to help find employees most suited to a business’s needs; this has come in the form of personality tests. These tests have been used for years by companies, and are not always useful in the hiring process. But overall, technology in hiring hasn’t progressed much since—at least, not in any widespread manner.
New hiring tech tools are starting to appear, however. Two Story—a performance analytics innovator—has been seeking to find a better way to match employers with candidates. This new hiring solution is called Performance Story.
Using a robust combination of behavioral assessment and skill analysis, Performance Story uses the newest findings in machine learning and behavioral science to diagnose what each role needs and predict a candidate’s fit. When used properly, this tool can change the way businesses hire.
Creating A Story Rather Than A Profile
Performance Story, as its name implies, gives a comprehensive picture of an employee rather than a list of attributes. It’s a huge advancement that better reflects the complexity of humans. Performance Story avoids boiling candidates down to their skills and whether or not they’re extroverted–which has never given a complete picture.
Performance Story looks at a job seeker’s talent profile to evaluate their predictive job fit and what potential they may have. Gaps in that profile can be filled after the candidate completes Two Story’s behavioral assessment. These assessments use non-obvious questions to get to the root of a person’s behaviors, values, acumen and habits. They also can give insight into how well they handle criticism and confrontation.
Traditional personality tests tend to have obvious and leading questions. Candidates may be tempted to answer in the way they think will get them the job instead of answering honestly. So if an employer is looking at a resume with vague language and a faulty personality report, it’s harder to predict job fit.
Knowing what makes a person tick can also help employers communicate expectations on both sides. Maybe a candidate has a history of leaving jobs after about two years, which is lower than the US average. It’s possible even the candidate doesn’t know why that pattern has emerged. Performance Story can play a huge part in providing an explanation and a remedy.
Reviewing The Candidate’s Story
Performance analytics could show the person in question needs a clear advancement path to remain engaged long term. Performance Story generates a list of key questions to ask interviewees in order to confirm or adjust candidate profiles. In this case, it might not be useful to ask the interviewee about a time they overcame adversity at work. It would be far more insightful to inquire if they’ve ever had a path of advancement in their prior jobs.
If they’ve never had a clear career path with their past employers, it might provide a mutually beneficial solution for everyone. The prospective employer would need to review and assess performance analytics to see what advancements are possible for that person or position within the business’s five-year projection. If advancements are feasible, then it needs to be clearly relayed what the employee will need to do in order to attain them.
Additionally, the interviewee has had career advancement laid out by previous employers, then something else is behind the job hopping pattern. If the candidate’s short tenure tendency is not something employers can easily fix with job modifications, they may not be a good fit.
If The Employee Succeeds, Everyone Succeeds
One of the central aspects of Performance Story is asking a very simple question for candidates. What type of placement is going to give each person the best chance of success? And this goes far beyond the basic functions of the job itself.
For example, let’s say a business named Pencil Supply is growing and needs to hire an HR and benefits coordinator. Performance Story’s AI systems can isolate key traits of successful HR coordinators and factor in variables relating to Pencil Supply internal nuances. Although it may seem counterintuitive, that process can actually open up the hiring pool to a greater number of applicants.
In Pencil Supply’s case, maybe they were previously requiring applicants to possess a master’s degree or MBA. Performance Story might reveal that the most successful HR leaders have at most a bachelor’s degrees and, more importantly, one specific personality trait. That vital information could inspire Pencil Supply to lower the education requirement and get more applicants in the system.
Another game-changing facet of Performance Story is its predictive capabilities. The powerful combination of behavioral analytics and AI projections will first assess performance analytics on how a candidate might perform in a certain position. Next, it provides information to the employer about how they can customize their processes to get the best output from their new hire. From job responsibilities to career path to education opportunities, employers will know what will keep an employee on board and engaged.
Very rarely is an employee’s success in the workplace one-sided. If an employer has predictive analysis on their side to keep a worker engaged for the long term, they can minimize turnover. When an employer places emphasis on the success of their individual workers, the company as a whole should see the benefits.
Using Science, Not Guesswork
There are all sorts of vague ways that employers or hiring managers make hiring decisions. They can be based on feelings, first impressions, or the candidate being the local mayor’s sister-in-law. Those methods may be better than pulling a random resume and extending an offer, but data and analysis can change the game. Using an approach that offers performance analytics, behavior analysis, and AI predictive abilities can make hiring more efficient and facilitate a better job/candidate fit.
So if you want to keep long hiring cycles and high turnover rates, keep doing what you’re doing. For better results and less headache, change the way you hire.
Featured Image Credit: by RODNAE Productions; Pexels; Thanks!
