Talent Acquisition Metrics

Is attracting the best #talent proving costly? How do you keep #talentacquisition costs low? Efficient talent acquisition isn't just about saving costs; it's about finding the right individuals who will contribute to your #organisation’s success. Let me share some ideas which will help you— ♦️ Use employee referrals- They are a great way to find qualified #candidates at a lower cost. Offer your employees incentives for referring qualified candidates to your company. ♦️ Refine Your Job Descriptions- Craft precise and compelling #jobdescriptions that attract the right candidates. This reduces the number of unqualified applicants. ♦️ Use Social Media- Harness the power of social media for cost-effective job postings and promoting your employer brand. Platforms like LinkedIn, X , and Facebook can be very helpful. ♦️ Build your employer brand- A strong employer brand can help you to attract top talent without having to spend a lot of money on recruitment. Create a positive image of your company by highlighting your culture, values, and benefits. ♦️ Refine the Interview Process- Streamline your #interview process to minimize time and resources spent on unnecessary stages. ♦️ Automate your processes- There are a number of tasks in the talent acquisition process that can be automated, such as #resume screening, interview scheduling, and background checks. Automating these tasks can save you a lot of time and money. ♦️ Employee Training and Development- Invest in training and development to upskill your existing workforce, reducing the need for external hiring. What other cost-effective strategies do you suggest? #Recruitment #Efficiency #EmployerBrand LinkedIn for Creators LinkedIn

Racial representation becomes increasingly homogeneous at more senior levels We recently posted about gender representation and how it varies by job level. In short, the more senior the level, the higher percentage of the employees who self-identify as men. More here: https://lnkd.in/gsBEvNGT Today, let’s look at the same pattern but around the dimension of racial diversity by job level. ___________ Perhaps unsurprisingly (but unfortunately), a very similar pattern exists today with race as the one with gender. 𝗜𝗻 𝘀𝗵𝗼𝗿𝘁, 𝗮𝗰𝗰𝗼𝗿𝗱𝗶𝗻𝗴 𝘁𝗼 𝗮𝗻 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝗼𝗳 𝟵𝟱𝗸 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗲𝘀 𝗶𝗻 𝗣𝗮𝘃𝗲’𝘀 𝗱𝗮𝘁𝗮𝘀𝗲𝘁 𝘄𝗶𝘁𝗵 𝘀𝗲𝗹𝗳-𝗿𝗲𝗽𝗼𝗿𝘁𝗲𝗱 𝗲𝘁𝗵𝗻𝗶𝗰𝗶𝘁𝘆 𝗱𝗮𝘁𝗮, 𝘁𝗵𝗲 𝗹𝗮𝗯𝗼𝗿 𝗽𝗼𝗼𝗹 𝘁𝗼𝗱𝗮𝘆 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗶𝗻𝗴𝗹𝘆 𝗰𝗼𝗺𝗽𝗿𝗶𝘀𝗲𝗱 𝗼𝗳 𝗪𝗵𝗶𝘁𝗲 𝗮𝗻𝗱 𝗔𝘀𝗶𝗮𝗻 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗲𝘀 𝘁𝗵𝗲 𝗺𝗼𝗿𝗲 𝘀𝗲𝗻𝗶𝗼𝗿 𝘁𝗵𝗲 𝗹𝗲𝘃𝗲𝗹. For instance, 74% of P1s analyzed self-report as White or Asian whereas 88% of P6s and 92% of CXOs self-report as White or Asian. ___________ The next question thus becomes, why? What is the underlying cause of this pattern? It is likely a combination of one, some, or all of the following: [A] Promotion rate disparities between races [B] Hiring rate disparities between races, especially at the more senior levels [C] Turnover/attrition rate disparities between races as you advance on the career ladder We will take a look at all three of these hypotheses soon to best empirically identify the underlying cause today in the labor market of the increasing racial homogeneity at senior IC and Management levels. ___________ Methodology: Ethnicity classifications made using US census classification guidelines. Only incumbent datapoints in the USA with self-reported ethnicity data were included. This made the analysis sample size 95k incumbents. Also, as a general disclaimer, Pave’s dataset today skews largely towards technology companies. #pave #race #benchmarks

Top 3 takeaways from average passthrough rates (PTRs) from our latest benchmark report:  → ~1/4 of pre-onsites lead to an onsite — if you’re far from 25% in either direction, you may need to be more selective in your screening process (otherwise you could be taking up precious interviewer time), or you’re being too selective (losing out on quality candidates).    → ~1/3 of onsites (38%) lead to an offer — if your conversion rates are outside this range, you may be conducting too many or too few onsite interviews.    → PTRs are down YoY across pretty much every stage of the funnel (likely bc companies are being more selective), and offer accept rate is up YoY (likely bc candidates have fewer opportunities). Important to note that company size, department, location, industry, source (inbound vs outbound) can all have an important impact on PTR. I’ll try to share more takeaways in the coming weeks as I dive deeper into the data myself. But feel free to check out the data yourself in our free / open source benchmark report! (link in comments 👇 )

"Hi Mark, we received this CV 5 times this week." This scenario never fails to bemuse me. Let's set aside terms of business for a moment—whether retained, exclusive, or contingent—because this issue cuts across all recruitment models. Here’s the heart of the problem: We’re dealing with multiple factors that create this mess: 1️⃣ Candidate Behavior: Some candidates apply through multiple channels for the same role without disclosing their prior applications. Transparency matters here—if you’ve already applied, just say so! 2️⃣ Rogue Agencies: Certain agencies mass-send CVs with attached terms, often locking candidates out of the process entirely. Worse still, this can leave companies caught up in avoidable disputes and duplicate charges. Misrepresenting a candidate isn’t just unethical—it’s illegal. 3️⃣ Too Many Cooks: Engaging too many agencies for one role leads to chaotic processes where it’s all about "first past the post." Spoiler alert: this never ends well. 4️⃣ Stale Roles: When roles stay open for months, candidates get re-submitted over time, creating confusion. The same candidates think it’s a different job and apply again, perpetuating the cycle. 5️⃣ The "Magic Mystery": Here’s one that will blow your mind. I’ve seen agencies resend the same candidates’ CVs every 6 months as terms expire, then claim a fee when one of those candidates gets hired—without the candidate even knowing! Shockingly, some companies have lost in court over this tactic. 🚨 Duplication is the silent killer of recruitment efficiency. Finding the right candidate can take 30-60 days, only to discover duplication derails the process. So, what’s the fix? There is a solution, but it requires action from all parties: ✅ Candidates: Protect your CV. Always ask where your details are being sent and give explicit consent before representation. Work with recruiters who discuss roles in depth and are clear about where they’ll submit your profile. ✅ Companies/HR/Hiring Managers: Streamline your agency pool. Limit the number of agencies per role—2-3 specialized agencies should suffice. Have a “B-list” for backup - But if you insist on using multiple agencies - Get an ATS system to upload candidates too, which will alert the recruiter ASAP. There are few out there, some not that expensive. ✅ Agencies: Retained or exclusive search is often the way to go. Retained ensures focus, while exclusive keeps it simpler and less intense - but as long as the process is good, will yield a fair result. Both approaches reduce duplication headaches. But if you open a role up to another agency, ask yourself why. what is happening? Finally, choose wisely. Don’t default to “first past the post.” Insist on proof of representation—signed or emailed consent from the candidate. Quality recruitment is about partnership, not speed. Let’s stop duplication from undermining the process and elevate recruitment to the professional standard it deserves. What are your thoughts? 

Collecting Your Job Search Data Could Be the Game-Changer You Need—Here's Why As a data career coach for over three years, I've helped clients consistently land jobs—averaging more than one placement each month. Recently, I analyzed a client's job search data over a 3-month period, and the insights were eye-opening. 📊 𝗧𝗵𝗲 𝗗𝗮𝘁𝗮: • 200 applications sent • 6 interviews received (4 were from referrals) • 350 connection requests sent • 175 new connections made • 27 conversations started (0 with hiring managers) • 10 informational interviews conducted • 20 referrals received • 2 interviews from new connections • 2 interviews from informational interviews 🔎 𝗪𝗵𝗮𝘁 𝗪𝗲 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝗲𝗱: • Applications to Interviews: Approximately 1 interview for every 90 applications—slightly above the average 1% conversion rate. • Referrals to Interviews: 1 interview for every 9 referrals—below the desired 33% success rate. • Warm Referrals: Every warm referral (directly passed to the hiring team) led to 1 interview—exceeding the 33% average. • Connection Acceptance Rate: 50% of connection requests were accepted—above the typical 33% average. • Conversations Started: Only 15% of connections led to conversations—below the 33% average. • Informational Interviews to Referrals: 20% of informational interviews resulted in referrals—below the 33% benchmark. 🚀 𝗔𝗰𝘁𝗶𝗼𝗻 𝗦𝘁𝗲𝗽𝘀 𝗪𝗲 𝗧𝗼𝗼𝗸: • Optimize Outreach Messages • Began A/B testing messages to hiring managers to improve response rates. • Focus on Genuine Networking • Shifted efforts toward building meaningful relationships rather than directly asking for help, aiming to increase conversation rates. • Enhance Informational Interviews • Invested more time researching individuals and companies to make informational interviews more impactful. • Refine Networking Strategy • Reduced direct requests for assistance from new connections due to low conversion, focusing instead on providing value first. 💡 The Result? By collecting and analyzing job search data, we pinpointed areas for improvement and implemented targeted strategies to enhance success rates. Your Turn: Do you track your job search data? What insights have you gained from analyzing your efforts? Let's discuss! Share your experiences or ask questions in the comments below.

₹1 Crore spent on ads, yet 50% of seats remain empty. What's going wrong? Every year, colleges invest crores into digital advertising, hoping to fill their seats. Yet, many institutions find themselves struggling with enrollments even after spending massive budgets. The root problem isn’t a lack of leads—it’s a broken marketing funnel. Most colleges focus on generating inquiries but overlook what truly matters: ● How many of those leads actually convert into enrollments? ● Where are students dropping off in the application journey? ● Are leads being nurtured effectively, or are they slipping through the cracks? The Harsh Reality ● 70% of leads generated by colleges never make it past the inquiry stage. ● 80% of students prefer personalized communication, yet most colleges still rely on generic email blasts. ● Students today expect instant responses, but many institutions take days or even weeks to follow up. ● This disconnect between marketing and admissions results in low conversion rates and wasted ad spend. How This Can Be Fixed Instead of focusing solely on lead generation, shifting attention to conversion strategies can make all the difference. A few key steps include: ▶️ Identifying where leads drop off in the journey, from ad clicks to inquiry forms to actual enrollments. ▶️ Optimizing landing pages and CTAs to improve conversions, ensuring the application process is seamless and engaging. ▶️ Running targeted campaigns rather than broad, generic marketing efforts. ▶️ Personalization and precise audience segmentation can significantly boost effectiveness. ▶️ Leveraging WhatsApp and AI chatbots to provide instant engagement, as real-time responses can increase the likelihood of application by three times. ▶️ Implementing retargeting and nurturing strategies, ensuring students stay engaged throughout the decision-making process rather than losing interest. The ImpactWhen done right, this approach can lead to: ▶️A significant increase in high-quality leads—not just random inquiries. ▶️ A 30% reduction in acquisition costs through smarter targeting. ▶️ Higher enrollment rates without increasing the marketing budget. Colleges don’t have a lead generation problem—they have a lead conversion problem. Are you tracking where your leads drop off? Let’s discuss in the comments!

Onboarding is killing your velocity, not hiring. Most #GCCs obsess over offer rollouts and interview velocity. Then Day 1 arrives and your star hire spends 2 weeks hunting VPN tokens, tool access and “who owns what.” That’s not culture; that’s a latency tax. What to fix (and what to measure): Time to First Meaningful Commit (TTFMC): Target: ≤ 7 days for engineers; ≤ 10 days for analysts to ship a first insight. If you don’t track it, you’re guessing. Access in One Hour, Not One Week: Pre-provision prod-safe sandboxes, repos, dashboards, experiment tools. If it needs an email chain, it needs a policy change. Onboarding Pods, Not Orientation Decks: Pair every new hire with a buddy + product owner + SRE for 14 days. Goal: one real task shipped, one pager rotation shadowed. 90-Day “Evidence > Excuses” Plan: Week 1: ship something tiny. Week 2–4: own a bug class or dashboard. Day 30–90: lead one small change end-to-end (with a post-ship write-up). Kill the Tool Maze: Publish a single launcher (links, creds, APIs, logs, style guides). If your new hire needs to ask “where is X?” twice, the doc is broken. Scoreboard to make this real (post it publicly in the #GCC): TTFMC median (weekly) % new hires shipping in Week 1 Access SLA met in 60 minutes Drop-off in “where is…” tickets after 30 days Bottom line: If Day 1–30 is chaos, your “cost arbitrage” evaporates into backfills and burnout. Make onboarding a product. Ship value in Week 1. Everything else is theatre

What happens when everyone in your business follows a different process? Let’s look at candidate feedback: → Consultant A gives feedback within 24 hours. → Consultant B gives feedback after a week. → Consultant C forgets entirely and the candidates never hear back. Now imagine that happening at scale. Some candidates feel valued, whilst others feel ghosted. Your brand? Inconsistent and forgettable. That’s what happens without process. But here’s the thing: Automation within recruitment = consistent experiences. And consistent experiences = scalable success. It’s how top agencies: ✔️ Build trust with candidates and clients ✔️ Stand out in a crowded market ✔️ Develop an excellent reputation ✔️ Increase their revenue Standardisation and process isn’t boring. It’s how you build a brand that people remember and recommend. Recruiters still lead the relationship. But automation ensures everyone follows the same script. What’s one process you wish your whole team followed?

I had a conversation with my client while recruiting for their engineering team and wanted to share an important insight we discovered... ➡ There’s a significant talent pool of candidates in Australia with extensive relevant experience from their home countries, essential accreditations, and permanent residency that many companies overlook before even having a conversation. Why? Because of a lack of Australian experience... We identified this "underutilized talent pool" and questioned whether NEM/WEM/NER/NSP/AEMO experience really needs to be an essential requirement. 🤔 We all know that relying solely on poaching talent from one company to another isn’t sustainable... These candidates are essentially on the bench, waiting to be called! 😊 The industry needs more people, and as consultants, it’s our responsibility to build bridges that connect our clients to a wider candidate pool - but we need you to be on board! Anyways, the conversation with my client concluded that local experience should be considered an additional requirement, not essential. By broadening our hiring criteria, we can access more candidates with relevant experiences and market rate salary expectations(this is a whole other conversation!!😅). I’ll leave this here to provoke some thought among hiring managers: If you’re interested in discussing how we can leverage this talent pool for your business, let’s connect! 💬 #talentacquisition #diversity #hiring #energy #recruitment #engineering

A challenge that People teams run into is how to be more data oriented. Credibility in the data we put forward depends on what it solves for. Some data is more for storytelling on cultural health whereas other data more directly ties to business impact. Examples under each 👇 𝗣𝗲𝗼𝗽𝗹𝗲 𝗱𝗮𝘁𝗮 𝗼𝗻 𝗰𝘂𝗹𝘁𝘂𝗿𝗮𝗹 𝗵𝗲𝗮𝗹𝘁𝗵 𝗯𝘂𝘁 𝗹𝗲𝘀𝘀 𝗱𝗶𝗿𝗲𝗰𝘁 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗶𝗺𝗽𝗮𝗰𝘁: ➡ Engagement data - important for culture but loose business connection ➡ Voluntary / regretted attrition - similar to engagement. Generally only a subset of attrition has a business impact and it’s variable by function ➡ Hires per month - gross hires devoid of any targets is activity but not impact ➡ Onboarding satisfaction - often is high and yet leaders feel differently ➡ Average tenure by function - a different way of conveying attrition and hiring ➡ Span of control - it’s high, it’s low….does it matter to the business? ➡ Performance rating distribution & talent density - not indicative of actual company / team performance. More a window into how a leader thinks about their team, decoupled from reality ➡ Demographic distribution - descriptive statistics with weak business impact ➡ Internal promotion rate - it’s high, it’s low….does it influence the business? ➡ Internal training completion rate & NPS of L&D offerings….activity and sentiment that only matters to L&D 𝗣𝗲𝗼𝗽𝗹𝗲 𝗱𝗮𝘁𝗮 𝘁𝗵𝗮𝘁 𝗺𝗼𝗿𝗲 𝗱𝗶𝗿𝗲𝗰𝘁𝗹𝘆 𝘁𝗶𝗲𝘀 𝘁𝗼 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀: ➡ Time to fill, quality of hire, offer acceptance rate, and cost per hire - are we bringing in the right talent at the right time at a cost that is acceptable to us? ➡ Critical hires filled to plan - hone in on the most important hires vs. plan ➡ Time to ramp - are (for eg.) our Sales and Eng hires getting to full productivity in time to affect the business vs. assumptions? ➡ HC & level composition vs plan - do we have the right talent in the functions to accomplish the roadmap for the upcoming quarters. Include skill composition in here if available ➡ Compensation benchmarking, burn rate, and talent cost vs. available market ➡ Team / function performance scores ➡ Leadership effectiveness scores over time ➡ Productivity metrics eg. average bookings vs. goal (Sales), bug rate & product ship rate (R&D), revenue per employee vs. benchmark, etc.