Analyzing Recruitment Metrics

I’ve Applied to 100+ Jobs—Here’s What’s Wrong with LinkedIn’s Job Board As a job seeker, I’ve spent months applying to roles on LinkedIn. Over 200 applications. Countless hours tailoring resumes and writing cover letters. And yet, here’s what I’ve found: 60% of the jobs I applied to were reposted weeks later—often with the exact same description. 30% of the roles I interviewed for were suddenly put "on hold" or canceled. 10% of the postings were for roles that didn’t even exist. This isn’t just frustrating—it’s a systemic issue. Many companies use job boards like LinkedIn to collect resumes, gauge market interest, or create the illusion of growth. Meanwhile, job seekers waste time and energy on roles that were never real to begin with. What LinkedIn Can Do to Fix It: ✅ Verify Job Listings: Require companies to prove they’re actively hiring before posting. ✅ Expiration Dates: Auto-remove job postings after 30 days unless employers confirm they’re still hiring. ✅ Transparency Metrics: Show how many applicants have been interviewed or hired. ✅ Feedback Mechanism: Allow job seekers to flag suspicious postings. We need real accountability in hiring. Job seekers deserve better. What’s your experience been like? How many ghost jobs have you encountered? Let’s share our stories and push for change. #JobMarket #GhostJobs #Transparency #LinkedIn #HiringReform

Have you ever heard of Goodhart's Law? It makes for a fantastic example on why metrics — when used blindly — can mislead. In leadership, Goodhart's Law states: "When a measure becomes a target, it ceases to be a good measure." Like in the picture below — 👉 When the manager judges his team on the number of nails made, they produce tons of tiny, useless nails. 👉 When judged on weight, they produce a few giant nails that no one can use. This plays out in modern leadership too: ✅ When you measure sales teams only by the number of calls, they’ll focus on dialing - not necessarily closing. ✅ When you measure content teams only by quantity, you risk sacrificing quality. ✅ When you push marketing teams for leads without qualifying them, you end up with numbers that don't convert. When a specific measure is used as a target, people are incentivized to optimize their behavior to achieve that target, regardless of other consequences. Their focus shifts from the goal itself to just achieving the metric/number itself. Metrics are necessary — but they should guide, not dictate. Because at the end of the day, numbers are only meaningful when they align with the real goal. Have you ever been part of a team where the wrong metric became the obsession? Would love to hear your experience. 👇 #leadership #law #culture #team 

Talent Acquisition Metrics and Analytics!! Talent acquisition metrics and analytics are essential tools for optimizing and improving the recruitment process. By analyzing data, talent acquisition teams can make more informed decisions, enhance recruitment strategies, and ultimately attract and hire the best talent. Here are some Key Metrics in Talent Acquisition to consider when discussing talent acquisition analytics: ▶️ Time to Fill: Measures the time from posting a job to making an offer. Shortening this time improves efficiency and reduces hiring costs. ▶️ Time to Hire: The time taken from the initial interview to the candidate’s acceptance. A shorter time indicates a smooth hiring process. ▶️ Cost Per Hire (CPH): The total cost involved in hiring, including advertising, recruiter fees, and onboarding expenses. Tracking CPH helps manage recruitment budgets. ▶️ Offer Acceptance Rate: The percentage of candidates who accept job offers. A low rate could indicate issues with compensation or cultural fit. ▶️ Quality of Hire: Measures the performance and retention of new hires, typically assessed through performance reviews and turnover rates. ▶️ Candidate Experience: Involves metrics like satisfaction scores and response time, which impact employer branding and can affect future candidate engagement. ▶️ Diversity Metrics: Tracks the diversity of applicants and hires, including gender, ethnicity, and other factors, to ensure fair and inclusive hiring practices. ▶️ Recruitment Funnel Analytics: Analyzes conversion rates between stages of recruitment, like from application to interview or interview to offer. Identifies where candidates drop off and allows for process optimization. ▶️ Predictive Analytics: Uses historical data to forecast hiring needs, job performance, and candidate success, helping to make more proactive recruitment decisions. ▶️ ROI of Talent Acquisition: Measures the return on investment of recruitment activities by comparing recruitment costs to the value brought by new hires (e.g., performance, retention). Benefits of Analytics in Talent Acquisition: ▶️ Improved Decision-Making: Data-driven insights help recruiters make more informed choices about candidates, processes, and strategies. ▶️ Process Optimization: Analytics help identify bottlenecks, inefficiencies, and areas for improvement in the recruitment workflow. ▶️ Better Candidate Fit: By tracking metrics like quality of hire and predictive analytics, recruiters can identify candidates who are likely to succeed and stay with the company long-term. ▶️ Enhanced Employer Branding: A positive candidate experience, measured through feedback and response times, enhances the organization’s reputation as an employer of choice. By tracking these metrics and leveraging analytics, talent acquisition teams can refine their recruitment processes, improve candidate experiences, and ultimately make better hires.

I'm calling BS on applicant tracking systems. Let’s call it for what it is: Resume-based hiring is failing organizations everywhere. Every Applicant Tracking System (ATS) works essentially the same way. They parse resumes for keywords, education credentials, and specific phrases that match job descriptions. This means they completely miss the soft skills. The intangibles. The things that actually determine success. These systems lead to gamification, where candidates stuff their resumes with the right keywords rather than demonstrating their true capabilities. (And we wonder why hiring feels broken!) What we really want to know about candidates goes far deeper: 🧑💼 How does this person actually work? 🧑💼 Are they reliable? 🧑💼 Will they show up and give their all? 🧑💼 Can I trust them? 🧑💼 Are they a team player? 🧑💼 Does their purpose align with our organization's mission? These intangibles are precisely why we should hire people. The hard skills matter, yes, but the reality is that most job success comes from soft skills. You can learn technical abilities (maybe not brain surgery or quantum computing overnight!), but character, reliability, and purpose-alignment? Those are much harder to teach. It's time for a hiring revolution that prioritizes who people are over, not just which keywords they've managed to cram into their resume. Resumes and ATS may be easy, but they’re also deeply flawed. If we truly want to hire for potential and impact, we need to rethink how we evaluate candidates—starting with deeper conversations, real-world assessments, and a hiring process that values people for who they are, not just the words on a page. – ♻️ If you liked this or learned something, be sure to share with your network—and follow me for more insights on leadership and disruption. 

Recruiting is sales, just with higher stakes. You're already doing the work - sourcing, nurturing, managing stakeholders. The issue: sales gets credit because they speak in forecasts. TA gets questioned because they speak in activity. The best TA leaders translate the work they're already doing into the language execs understand. Here's the playbook: 1. Stop reporting hires reactively. Start forecasting proactively. You already know your funnel. This week: formalize it with your hiring manager. Sourced → Engaged (replied) → Screened → Interviewed → Offer Out. Pull the last 30 days and calculate conversion rates at each stage. When you know 20% of prospects engage and 50% of engaged candidates screen, you can work backwards from any hire date.  That's a forecast. Same work you're doing, different framing. 2. Work forecasting into your weekly syncs with Hiring Managers. Same agenda every week: volumes at each stage, conversion rates, what's working by source, where you're short, and what you're testing. When they say "we need this faster," reply with options: "We convert 15% to qualified. To speed up, we need better rates or 50 more prospects weekly. Which should we focus on?" You're not changing your process. You're changing how you communicate it. 3. Goals without weekly math are just theater. Two hires in 90 days? Work backwards. If offer acceptance is 80%, you need 3 offers. If 25% of interviews convert, you need 12 interviews. If 30% of your screens interview, you need 40 screens. Across 12 weeks = 3-4 screens per week. Though, in reality, you need to front-load those screens if you want to make your hires on time, so aim for 6-7. Do this for every open req this week. Teams at Unity cut time-to-fill by 10 days by turning goals into weekly commitments. You're already tracking this work - now you're showing the math behind it. 4. Track qualified-candidate yield by source. Stop measuring activity. Measure yield. When a hiring manager questions your budget, show the data: targeted outreach converts at 18% to qualified while career page posts convert at 2%. One costs $200 per qualified candidate, another costs $50. This week: tag every candidate with their source. You're not adding work. You're adding attribution to work you're already doing. KEY LESSON: When you forecast timelines with the same rigor sales commits to quota, everything shifts. Hiring managers stop asking if you're working on their req and start asking what they can do to help you hit the date. The work doesn't change. The appreciation does.

If you’ve been navigating the job market for a while, chances are you’ve heard about match scores in recruitment systems (ATS). You’ve probably also come across plenty of advice on how to “beat the ATS” or optimise your resume to land a high match score. The reality is that companies often use match scores to streamline the initial screening process by ranking candidates based on how closely their qualifications align with the job description. It can be a useful tool for dealing with high application volumes, and, to be fair, the technology is improving every year. Reality also is that they are still far from being perfect. Some match scores we've seen would have told us to overlook great people - people we ended up hiring. Other companies know this too and move forward with candidates despite low match scores, understanding the technology’s limitations. What I find is that technology doesn't always consider nuanced factors such as someone's career progression, their transferable skills, and the different work environments people have worked in. They may also undervalue candidates with unconventional career paths or those transitioning between industries, even though they may bring significant value to the role you're hiring for. And over-relying on these tools means we risk missing the hidden gems. The ones with unconventional paths and great experiences and the ones that don't always fully optimise their resumes. That said, I believe technology will continue to evolve and continue to play a valuable role in talent acquisition. Now I know, people say shortlisting people based on their resumes is pretty much like flipping a coin - and I agree but I also believe (and maybe I'll revisit this post in a year or so when AI has gotten amazing at this) that humans still do better at spotting potential and recognising the nuances of someone’s story. And to job seekers - there is nothing wrong with optimising your resume but keep telling your story and showcasing your unique value and personality. It's still the best way to stand out. #ats #matchscore #recruitment #talentacquisition

Most HR leaders would hate me for saying this, but 90% of hiring metrics are useless. You don't need a dashboard with 47 KPIs. Here’s 7 numbers that actually predict whether your hiring is working: 1. Quality Applications Track how many candidates meet minimum qualifications versus total applicants. If you're getting 200 applications but only 10 are qualified, your job postings or employer brand need work. Quality beats quantity every time. 2. Time to Fill Days from requisition to accepted offer. Every day a role stays open costs productivity and team morale. Track by role type to identify bottlenecks…is sourcing slow? Interview scheduling? Decision-making? 3. Interview-to-Offer Ratio What percentage of interviewed candidates receive offers? If you're interviewing 20 people to make one offer, your screening process is broken. This reveals whether your pre-interview assessments actually work. 4. Offer Acceptance Rate What percentage of your offers get accepted? Low acceptance rates signal problems with compensation, candidate experience, or employer brand. Track by seniority level to see where you're losing top talent. 5. 90-Day Retention What percentage of new hires are still engaged and performing after 90 days? Early turnover is expensive and usually preventable. This metric reveals misalignment between expectations and reality. 6. Hiring Manager Satisfaction How do managers rate the candidates you deliver and the hiring process? Your internal customers' satisfaction predicts whether hiring best practices will stick. Low scores mean misaligned expectations. 7. Cost Per Hire All-in recruiting costs divided by hires made. Include recruiter time, tools, assessments, and external fees. Understanding true cost-per-hire enables better resource allocation and ROI discussions. TAKEAWAY: Most hiring teams measure activity instead of outcomes. These 7 metrics focus on quality, efficiency, and long-term success. Track what matters, improve what you measure.

Those hiring algorithms screening your resume feel like the enemy—but they're not. After founding multiple job boards and working with countless employers, I've seen firsthand what happens behind the digital hiring curtain—and most job seekers misunderstand it completely. Here's what you might not realize: Algorithms don't reject you. They rank you. The ATS isn't designed to find reasons to discard your application. Its primary function is to organize applications based on relevance to the job description. When you don't make it through, that doesn't necessarily mean you were "rejected" by AI - it means your application wasn't ranked high enough to reach human eyes. The secret to this? Algorithms look for evidence you can do the specific job, not your overall impressiveness. I've watched talented people get overlooked because they showcased all their abilities instead of highlighting the exact skills mentioned in the job description. The system has serious flaws. A good candidate who doesn't know how to speak "algorithm" gets buried, while someone who knows the game gets noticed - regardless of who might actually perform better. That's why we're building something different at Lensa. A system that sees beyond keyword matching to understand your actual capabilities, not just how well you've optimized your resume. Until hiring technology evolves, remember: algorithms don't make judgments about your worth. They simply match patterns. Learn the patterns, and you improve your chances—dramatically. What's been your experience with application tracking systems? Have you found ways to navigate them effectively? #JobSearch #HiringTech #CareerAdvice #RecruitmentTechnology

The first time I presented a data-driven HR strategy to the board… They didn’t ask about culture. They didn’t ask about performance reviews. They asked: “How does this move the business?” That moment shifted my mindset forever. As HR leaders, we often talk about engagement, inclusion, and retention. But unless we connect people to performance, it’s all just noise. That’s where HR metrics come in. Not dashboards for vanity. Not numbers for compliance. But people data that drives real business decisions. Here are the 10 essential HR metrics every strategic HR leader must watch: ✅ Headcount – Are we staffed to meet strategic goals? ✅ Turnover – Are we leaking talent, and what’s it costing us? ✅ Diversity – Are we building inclusive teams that attract top talent? ✅ Total Cost of Workforce – Are we balancing efficiency with value? ✅ Compensation – Are we aligned with market realities and internal equity? ✅ Spans & Layers – Are we structured for agility or buried in hierarchy? ✅ Engagement – Are our people emotionally invested in our mission? ✅ Talent Acquisition – Are we hiring right—or just hiring fast? ✅ Learning – Are we preparing for the skills of tomorrow? ✅ Workforce Planning – Are we ready for what’s next? I’ve used these metrics to launch cultural transformations, align HR with corporate governance, and deliver real ROI—not just HR wins, but business wins. Because here’s what I’ve learned: 👉 You can’t improve what you don’t measure. 👉 You can’t lead without insight. 👉 And you can’t expect impact without alignment. If HR wants a seat at the strategy table, we need to speak the language of metrics. Because in today’s world, the most human organizations… are the ones who understand their people through data. #PeopleAnalytics #HRStrategy #DataDrivenHR #HRMetrics #FutureOfWork #BusinessImpact

The $2.3 million mistake just walked out the door. That's the average cost when an executive fails in their first 18 months. Yet most hiring managers are still using the same broken metrics to make these critical decisions. Here's what they're getting wrong: 1. Years of Experience ≠ Leadership Capability 20 years doing the same thing ≠ 20 years of growth. I've seen 10-year veterans outperform 30-year "experts" because they understood change, not just process. 2. Blue Blood Company Names ≠ Individual Impact A big logo on a resume doesn't tell you how they'll perform when they ARE the infrastructure. Many executives from large companies struggle without massive support systems. 3. Perfect Interview Performance ≠ Real Leadership The best leaders I know are often terrible at selling themselves. They're too busy solving problems to perfect their pitch. 4. Industry Match ≠ Cultural Fit Cross-industry leaders often bring the fresh perspective that stagnant companies desperately need. The executives who truly transform organizations rarely look perfect on paper. So what should you look for instead? They look like problems solvers, not resume builders. The real indicators of executive success? Adaptability under pressure, decision-making speed, and the ability to inspire teams through uncertainty. These don't show up in traditional metrics. What's one hiring criterion you've learned to ignore? P.S. If you're tired of expensive hiring mistakes, let's talk strategy. 15 minutes could save you millions. DM me. #ExecutiveHiring #Leadership #TalentAcquisition #HiringStrategy #ExecutiveSearch