As an engineering intern in an R&D department almost 60 years ago I learned that there are two basic ways to experiment to validate whether a new manufacturing or business process is effective.
The first is testing a specific theory – you think you know what works, so you design an experiment to prove it. Like when Bell Labs developed the first transistor based on a theory of quantum mechanics and semiconductor behavior. The second is more practical or Edison-style – try a bunch of different approaches and see what works best. No grand theory, just systematic trial and error until you find the answer.
It turns out HR departments don’t do either. They don’t even test their assumptions (“we need someone with 10 years experience”), and they don’t systematically try different approaches to see what actually works. Smart organizations combine both approaches. The theory tells you where to start looking; the experiments tell you what actually works in your specific situation.
Recognize that every failed hire costs real money. Every great hire who gets away or who didn’t see your ad or didn’t respond to your outreach message is a missed opportunity.
No other business function operates using a follow-the-leader or vendor-driven mindset to design mission-critical processes.
Why should HR be any different especially when it comes to hiring?
As a First Step, Consider a Performance-based Hiring Experiment
During a 10-year stretch in the late 1980s and into the ‘90s my search firm made almost a thousand placements. This is when we started giving a one-year guarantee. We also tracked our results. Only 73 didn’t make it through the first year. That’s 7.3%. Few were fired. Most of those who quit didn’t like the hiring manager. The others quit because the job wasn’t motivating.
So let’s experiment with these two ideas first. Just getting these two parts right will cut most of your hiring mistakes in half.
As an FYI, when it comes to experiments In-N-Out Burger was our first retained search client focusing first on reducing biases and then benchmarking best work practices. We then used a similar test-it-first approach at dozens of YPO and Vistage mid-sized companies. Those companies and hiring managers that followed the validated process got the same results. Those that didn’t fell into the same traps.
You’ll find all of these stories in the four editions of Hire with Your Head and in my most recent book, Hiring is Performance Management. Both include lots of simple experiments.
Unfortunately when it comes to experiments led by HR as soon as hiring managers complain recruiters and HR just give up rather than proving what works. But this can change if you use AI to design and validate your hiring experiments first.
AI and Performance-based Hiring Can Turn the Tide
Over the past few months we started using Lovable for coding and ChatGPT, Claude and Gemini to run all types of experiments in combo with the Performance-based Hiring Talent Hub.
For example:
- We redesigned the job posting by making them more compelling but harder for the unqualified to apply (example and peel the URL back for other examples).
- We made hiring managers believers by showing them what success looks like and how to interview and recruit stronger talent (example).
- Gave purple squirrels an exciting new color.
- Created a private job board as part a multi-step marketing program for direct sourced candidates.
- Created a customized sourcing planto find ideal candidates without wasting time looking in all of the wrong places.
- Opened up the talent pool to more qualified candidates by identifying the 3-4 Super Skills driving OTJ success. See the graphic below to understand the approach we used. Ensuring all your candidates have these skills – they’re different for each job – might be all you need to prevent all hiring mistakes! (This would be a great experiment.)
- Improved the candidate experience by telling candidates how they’ll be assessed and if they should apply ahead of time and then delivered on the promise (example).
- Figured out how to accurately predict Quality of Hire (example) before making an offer.
- Developed a new scorecard to prevent dumb, biased and incorrect hiring decisions (example).
- Provided candidates a tool to determine if an offer included the 30% non-monetary increase promised (example – peel this URL back for a different hiring point-of-view).
- Calculated the financial impact of hiring average candidates (example).
Now It’s Time to for HR to Become Engineers and Experiment
When it comes to using Performance-based Hiring, the problem has never been the methodology. It’s always been implementation. Without technology, Performance-based Hiring requires enormous discipline. When juggling 10 open reqs, it’s easy to slip back into posting and processing.
The Talent Hub changes that. It enforces the workflow, integrates sourcing tools, scorecards, hiring manager alignment, and candidate engagement. It makes the right behaviors default. But we need you to experiment with it using your real jobs and real constraints and with real cynical hiring managers who would rather trust their gut. This is the only way we can convert a good theory into a true business process.
But for these experiments you need to leave your ATS and HR Tech behind along with your biases, preconceptions and supposed compliance restrictions. This whitepaper from one of the most respected labor attorney’s in the U.S. will help ease your fears.
The future of hiring starts with a bunch of experiments. Some will fail. Some won’t. But nothing will change without taking the first step.