Managing Costs
No one wants to make a bad hire.
But nearly 3 out of 4 employers say they’ve hired the wrong person. Yikes.
It is no secret that bad hires are expensive. So… why is it so pervasive? Why is everyone still making bad hires?
Just hire better people, simple right?
Not so simple, it turns out. While it is a complicated issue, the answer likely lies in your hiring process. Putting in the work to improve here will benefit your culture and your bottomline. People are your most important asset.
The goal should be to be super selective and quickly identify the best candidates.
Your recruiters are not mind readers. Hiring managers need to know exactly what they’re looking for instead of relying on a job description that is likely outdated or just not specific enough.
Solution?
Try using SmartRank.
✅ 100% of applicants are screened
✅ Applicants are stack-ranked to show you top talent for your specific hiring manager and role
✅ No resumes = no subjective interpretation of skills or qualifications
Data Analytics & Reporting
Relationships with hiring managers can be… tricky.
Recruiters- Do you ever feel like a scapegoat?
Salary requirement conversations are a great example of where the dynamic breaks down.
This first example is probably familiar to every single one of you. It’s called an anecdotal conversation and it goes like this:
Recruiter: We’re finding it hard to find people for that $60k – $70k range you gave me
Hiring Manager: Well that’s the salary we have to work with because that’s what I was given (but what they might be thinking is “maybe you’re not looking in the right places”…”maybe you’re not talking to the right people”…”how many people have you actually verified this with?”…etc.)
Recruiter: Okay well I’ll keep looking
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What if you introduced technology so you knew the exact salary requirements of every single applicant for that specific role?
That’s called a data-driven conversation and it goes like this:
Recruiter: Okay hiring manager, we’ve had 142 applicants apply for this role, we’ve asked 100% of those applicants what their salary expectations are for this role and here’s what the data tells us…only 6% of applicants are willing to accept $60k – $70k. And by the way, would you like to know how many of those 8 applicants are even 50% qualified per your exact qualifications….zero. So, that leaves us with a few options:
1. You can hire one of the 8 applicants knowing they are less than 50% qualified, but at least your expectations will be lower going in
2. We can hold on this salary and wait until we get an applicant that is both willing to accept this salary and has the qualifications you’re looking for, but again with setting expectations you might want to buckle in because it could be a while
3. We can take this data to both of our bosses, show them the data, and explain that if we at least increase the salary range by $10k that triples our applicants pool, but frankly the majority of the applicants are clearly saying they need $91k – $100k
Any of these options are fine with me, but just know this has nothing to do with me and everything to do with what the applicants are telling us. So which option do you want to go with?
Hiring Manager: Let’s go with option 3
In summary:
Anecdotal conversation – revolving door, doesn’t get anywhere, takes longer, no hard decisions can be made, and opinions and blame run rampant
Data-driven conversation – drives a productive conversation, creates accountability for all stakeholders involved, facilitates faster and more educated decisions, and everyone is moving forward as opposed to in a circle
Which conversation are you having today?
Which conversation would you rather have?
Talent Acquisition Problems
The definition for “root-cause” is “the fundamental reason for the occurrence of a problem.”
So, 3 questions:
1. Do you have any of the problems ChatGPT mentions?
2. Have you identified what the root-cause (as opposed to symptoms) of those problems actually are?
3. Have you evaluated solutions that fundamentally solve the root-cause instead of symptoms?
When is the last time you have OBJECTIVELY looked at your entire systems and processes?
Talent Acquisition Problems
Multiple sources of data, including the Zippia article this graphic data came from, show that talent acquisition and HR have some of the highest turnover out of any department, especially over the past few years.
While we could speculate all day about reasons, let’s just look at some additional data points first.
According to some recent data by Aptitude Research:
Activities that take up recruiters’ time (in order):
1. Reviewing applicants
2. Finding applicants
3. Scheduling interviews
4. Screening applicants
5. Communicating
Resources that recruiters need (in order):
1. Better tools to automate processes
2. More time to engage candidates
3. Simple technology
4. Less time doing admin work
5. Data to drive decisions
And, “1-in-2 recruiters would leave their current role for better technology.”
So what does that all mean?
Recruiters spend A LOT of their time on manual and tedious tasks that SHOULD be automated, and they know it. Recruiters need (not want) innovative technology to help them do their job better.
TA and HR leaders are solely responsible for making their teams happier, more fulfilled, and removing barriers to their success. “We don’t have the budget” is just not an acceptable excuse.
Why?
Turnover is EXTREMELY expensive, and that alone justifies the additional cost. Leaders owe it to their teams to make the business case for better technology.
And by the way, we’re not talking about replacing a “traditional ATS” with a “newer traditional ATS” because that will probably only help with some of the symptoms rather than the root cause. We’re talking about transformative and disruptive technology that solves the root causes of the biggest problems in talent acquisition. Leaders need to stop following what everyone else is doing and start leading!
Uncategorized
? If your company is talking about an “innovative” plan to improve the hiring process by getting AI to read resumes for you… Run.
What is that telling potential applicants? What are you really selecting for? Unless you’re hiring for a professional resume writer, this is not the answer.
On the flip side, how do you know you haven’t missed out on a great candidate because they’re not an excellent resume writer?
Spoiler: AI can certainly read resumes quicker and find you those keywords but it doesn’t solve any real problems.
A truly innovative idea?
– Allow candidates to be compared apples to apples
– Screen 100% of applicants (give ’em all a fair shot)
– Ditch the resume and get rid of unconscious bias with it
