Lou Adler Group - Originators of Performance-based Hiring
Lydia greeted Alex with a concerned look, the hum of the coffee shop blending with the gravity of their conversation. Lydia, once his boss and now a mentor figure, was someone who could help him figure out how to make important career decisions. Alex reached out to Lydia and asked if they could meet to […]
It turns out that the actual cost of hiring people who wind up in the bottom half is at least $100 thousand per bad decision and for managers it’s a big multiple of that! This is based on the fact that the average revenue per employee for those in the Fortune 500 is $1 million […]
If you can’t measure it, you can’t improve it. – Peter Drucker (Note: the following was written by our new Performance-based Hiring ChatGPT coach. You’re welcome to try it out, but it’s a bit funky. The improvements shown in the infographic above require two things. One is to define work as series of performance, not […]
After tracking the 10-year performance of 100s of candidates I placed in mid-management roles from 1980 to 2000, I finally figured out how to measure Quality of Hire. It’s described in detail in Chapter 16 of Hire with Your Head (4th edition, 2021, Wiley). The other day I asked ChatGPT if the approach was still […]
(I asked ChatGPT to write a story about the legal and diversity hiring implications of using Performance-based Hiring based on this whitepaper from Littler. I was shocked by the story it wrote with such a simple prompt.) In the heart of the corporate district, inside a spacious office adorned with contemporary art, John, the Hiring […]
Using a single sentence prompt I asked ChatGPT to convert this LinkedIn Learning course on embedding post-hire success into the pre-hire process into a compelling super short story. It follows below. Send us a link to one of your open job descriptions and we’ll show you how to make Amelia’s story yours. Converting Jobs into […]
When you consider that the top 25% is a definition of outstanding performance rather than a statistic, it’s possible for everyone to meet this threshold of performance: A top 25% person is someone who is fully competent or can learn fast, is intrinsically motivated to do the work that needs to be done, gets it done with limited […]
With AI, there’s a new math for hiring. It turns out everyone can now be in the top half of the top half. To get there candidates and hiring managers both need to be more discriminating and make wiser decisions. Getting to the top 10% takes a little more effort. For some it’s worth it. […]
According to ChatGPT everyone can now be in the top third despite the mathematical absurdity. These are people who are more motivated, more satisfied, more productive, stronger team players and more flexible. Here’s all you need to do to get started. When opening any new requisition, be sure to ask this question: What are the […]
I asked ChatGPT to write a story based on this postand the image below. It seems quite relevant today given that fact that most people are unhappy with their jobs. The theme: Time is your most valuable, don’t waste it. Given that. I’d rank number five as the most important. – LA, August 21, 2023. […]
I uploaded this PDF describing the 12 factors in our Hiring Effectiveness Index (HEI) into ChatGPT. I then asked if the scoring system would help a company identify potential problems in its current hiring processes.
Spoiler alert. This could be scary. It represents the future of hiring.
I just used ChatGPT to fundamentally change how job candidates will be sourced, assessed, recruited and managed in the future. Here’s how to get started. If you dare.
I recognize this is a bit self-serving, but I asked ChatGPT if our Quality of Hire Talent Scorecard could be used to improve hiring results. I was surprised it was so insightful interpreting relationships and ideas that were never written. You’ll see what I mean below.
Note: I asked ChatGPT to write this post in my style. It also came up with the title. It took less than one minute. It took me more time to cut and paste this into LinkedIn. What do you think?
It’s important to note that using behavioral interviewing #BEI without a detailed job analysis pretty much invalidates the entire interview. Without knowing how a skill, competency or behavior is actually used on the job, the assessment is left to the interviewer’s biases and perception of the job and how well the candidate presented their answer.
When creating a talent acquisition strategy it’s important to note that about 20-25% of those in the workforce are always actively looking for another job. This is the group companies need to target to fill open jobs as rapidly as possible. There’s another 20-25% who are always proactively passive. Don’t even attempt to contact these people unless you’ve worked with the person before. Given this, it’s obvious the candidates you’ll want to hire for your most important roles are in the other 50-60%. While this is the ideal talent market, these people won’t respond to your emails or calls unless you become an expert at passive candidate recruiting. This involves a number of critical skills, in particular:
As a recruiter I abhorred the idea that an outstanding candidate for an important job was being judged by a person who wasn’t a very good interviewer. Sadly, after having debriefed over one thousand different interviewers, I estimate that about two-thirds fell short. And too often the assessments of those who were valid were overridden or discredited by those who weren’t.
I’m getting nervous with the proliferation of all of these AI-infused chatbots that will change life and work as we now know it. Some of them are wrong. Really wrong.
I’ve always found it odd – maybe even dumb – to hire people based on their skills and depth of experience without telling them much about the job until they start. Then to determine if they are good or not after they’re hired, we assess them on their performance doing some job they weren’t assessed on.
If your tactics, techniques, and technologies don’t support your talent strategy, you won’t be seeing or hiring too many good people.
Long ago a CEO for a mid-sized company asked me how much experience a person needed to have to be the VP Operations for his company. My glib response then was, “Enough to do the job. It’s what people do with what they have, not what they have that matters. Some people need more experience to do the same job and others need less.”
In my mind, being more efficient hiring the same people you’re now hiring is a trivial use of ChatGPT.
Last month I was speaking to a senior director of software engineering for a major high-tech company. With over 200 developers in his department and years of experience hiring top performers this observation was earth-shattering:
A client recently asked if we could update our performance-based interview to assess remote and hybrid workers for different professional staff roles.
I was just talking to the director of engineering for a major consumer products company about new ways to improve the hiring decision for software developers. His first comment was profound and applicable to just about every technical role.
I’ve just wrapped up recording a new course for LinkedIn Learning (available in Q2, 2023). The core theme of this new program is that by embedding post-hire success into the pre-hire sourcing and interviewing process it’s possible to attract and hire a different type of candidate. These are people who are more diverse, who have less traditional backgrounds, who are more focused on learning and development and who are more interested in long-term vs. gig employment. Achieving this goal requires a different process at every step from how jobs are defined to how candidates are onboarded and managed.
The other day someone asked me if she should quit her job. I handed her the graphic shown above and told her to rank the six factors on a 1-5 scale from terrible to outstanding.
I was a guest on Simon Fagg’s excellent After Dinner Leadership podcast last week. Simon brings an oldie with a newbie to discuss how business ideas of the past might still be useful today. Simon’s first question to me was to highlight some early leadership lessons that I felt were still relevant. Here’s what I came up with from the early 1970s.
You might recall that this was formerly known as the most important interview question of all time.
As an old manufacturing guy it’s pretty obvious that when a machine is producing scrap you stop the machine and fix the problem before turning it back on.