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NEW: The 2025 AI & ML Compensation Trends & Practices Report is here! Our data team mined Pave’s real-time dataset of 8,500+ customers to find the most valuable insights about these hot jobs to bring compensation leaders a clearer picture of the market. With thought leadership from our partners at Nua Group LLC, this is a can’t-miss resource for any compensation professional with AI/ML roles in their organization. Download your copy today: https://lnkd.in/gTqszUsN #Pave #Compensation #AI #ML

Compa ratios of tenured employees vs. new hires: do candidates get preferential treatment? When I was a software engineer, I used to joke with my coworkers that the easiest way to get a raise would be to resign, re-interview with the same company, and then re-negotiate a new cash & equity package (not to mention a fresh sign-on bonus). Is this fact or a fallacy? Do candidates get preferential treatment over loyal, tenured employees? One way to analyze this is under the lens of compa ratios. Let’s take a look. __________________ The Results: Our data science team took a look at compa ratio distributions for companies in Pave’s dataset where we have access to reliable salary ranges. And they broke down the results into two mutually exclusive groups: [A] “New Hires” – employees who joined within the last 12 months  [B] “Tenured Employees” – all employees who have more than 12 months of tenure In theory, employees from group B have been at the company (and also in their current levels) longer and thus had more time to progress to higher compa ratios in their salary range. But in practice, this theory breaks down. According to Pave’s analysis of 66k real-time incumbent datapoints, it is Group A–the “New Hires”–that somewhat consistently has the higher compa ratio across nearly all IC levels. __________________ Takeaways: 1️⃣ 𝗘𝗺𝗽𝗹𝗼𝘆𝗲𝗲𝘀 𝗵𝗮𝘃𝗲 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗻𝗲𝗴𝗼𝘁𝗶𝗮𝘁𝗶𝗼𝗻 𝗹𝗲𝘃𝗲𝗿𝗮𝗴𝗲 𝘄𝗵𝗲𝗻 𝘁𝗵𝗲𝘆 𝗮𝗿𝗲 𝗰𝗮𝗻𝗱𝗶𝗱𝗮𝘁𝗲𝘀, 𝗮𝘁 𝘁𝗵𝗲 𝗽𝗼𝗶𝗻𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗼𝗳𝗳𝗲𝗿 𝗹𝗲𝘁𝘁𝗲𝗿. Some may view this as inconsistent or unfair with existing, tenured employees. Others may view compa-ratio-flexing as the elbow grease required to win great talent. 2️⃣ 𝗖𝗼𝗺𝗽𝗮 𝗿𝗮𝘁𝗶𝗼 𝗱𝗶𝘀𝗽𝗮𝗿𝗶𝘁𝘆 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗻𝗲𝘄 𝗮𝗻𝗱 𝘁𝗲𝗻𝘂𝗿𝗲𝗱 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗲𝘀 𝗮𝘀 𝗮 𝗻𝗲𝘄 𝗮𝘀𝘀𝗲𝘀𝘀𝗺𝗲𝗻𝘁 𝗼𝗳 𝗺𝗮𝗿𝗸𝗲𝘁 𝗱𝗲𝗺𝗮𝗻𝗱. If you break down the “compa ratio disparity” benchmarks between new hires and tenured employees across the dimensions of job family and/or location, it can offer a new metric to help assess the hottest or coldest jobs. For instance, Pave’s Data Science team analyzed the AI/ML Engineering job family and found that the median compa ratio is 1.05 for “New Hires” and 0.97 for “Tenured Employees”. This is yet another signal of the rising market demand for AI/ML talent. 3️⃣ 𝗢𝗳𝗳𝗲𝗿 𝗹𝗲𝘁𝘁𝗲𝗿 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 𝘃𝗮𝗿𝘆. I meet some companies who have a philosophy of bringing in candidates from “min to mid” (i.e. 0.85 to 1.0) compa ratio. Other companies believe that in practice, it should be “whatever it takes” (i.e. min to max). The findings of this post suggest that there is more of a bias towards the latter than the former, but we can take a more detailed look at the breakdown between these philosophies in a future post. #pave #compa #benchmarks

📣 Calling all comp leaders: We want to hear from you! We’re expanding our Pave Pulse Survey program in 2025 to bring together even more insights from the total rewards community. We're kicking off this year's series with a survey on U.S. Sales Incentive Plan Design for individual contributor roles, open through Friday 2/14. Participants will receive a comprehensive report on research findings once the pulse survey is closed, so join now to make sure you’re the first to know the results. Drop a comment below or send a DM to receive a link to take the survey! #Pave #Compensation #Survey

Whether you’re implementing a pay-for-performance strategy at your organization, or looking to improve the strategy you have, you won’t want to miss this webinar! Join Pave and Culture Amp next Tuesday 2/11 for a session on Integrating Performance Reviews and Compensation Decisions. Our experts Alex Cwirko-Godycki, Hannah Liss and Nicklaus Salzman will share insights to help you enhance your performance management and compensation strategies, and drive success. Register here: https://lnkd.in/gg6WsAWc #Pave #CultureAmp #Compensation

🇨🇦 🇬🇧 Hello to our neighbors to the north and our friends across the pond! With our February data cut, our Calculated Benchmarks feature is expanding to international markets. Now Pave Market Data customers can access equity data coverage in Canada and the UK! Get started today and sign up for Pave Market Data: https://lnkd.in/gKkuAwSC #Pave #Compensation

Equity compensation is widely considered one of the most powerful tools for employee retention, and unvested equity is a key piece of the puzzle. An analysis of unvested equity is critical for compensation leaders looking to predict retention risks and build tailored retention strategies. For a deeper dive on this topic, we’re excited to share a guest post from Jon Burg at Infinite Equity, one of Pave’s consulting partners. Read the full article to explore the ins and outs of analyzing unvested equity: https://lnkd.in/gsXt38ye #Pave #InfiniteEquity #compensation

Equity compensation is widely considered one of the most powerful tools for employee retention, and unvested equity is a key piece of the puzzle. An analysis of unvested equity is critical for compensation leaders looking to predict retention risks and build tailored retention strategies. For a deeper dive on this topic, we’re excited to share a guest post from Jon Burg at Infinite Equity, one of Pave’s consulting partners. Read the full article to explore the ins and outs of analyzing unvested equity: https://lnkd.in/gsXt38ye #Pave #InfiniteEquity #compensation

Oftentimes in comp, the more precise you try to be (looking at revenue, industry, location), the less data coverage you get. This compromise hits hardest with equity compensation, where data is already scarce. That's why we've introduced Calculated Benchmarks, to ensure that you never have to sacrifice relevancy for coverage ever again. Join Zack Smetana and Nicholas Lepley next Wednesday as they dig into the updated equity insights (new hire, ongoing, unvested equity, and more) unlocked through Calculated Benchmarks. Save your spot today ➡️ https://lnkd.in/g4-HcYpR

2025 Compensation Budget Benchmarks – How Much is Your Company Planning to Spend? In Q4 2024, we invited a tightly curated list of ~300 of the most prominent technology companies to fill out a survey on their forecasted 2025 compensation budgets. We ended up with 118 respondents–53 public and 65 pre-IPO tech customers. Let’s take a look at a few high level results* *and if you’d like the full results, please shoot me a note at matt at pave dot com and I can send you the link to fill out the full survey and gain access to the comprehensive benchmarks. ______________ 𝟮𝟬𝟮𝟱 𝗖𝗼𝗺𝗽𝗲𝗻𝘀𝗮𝘁𝗶𝗼𝗻 𝗕𝘂𝗱𝗴𝗲𝘁 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁 𝗕𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸𝘀: ✅ Median 𝗼𝘃𝗲𝗿𝗮𝗹𝗹 company-wide budget increase % (merit/promo/market adjustment etc.) => 5.0% at private companies => 4.5% at public companies ✅ Median company-wide 𝗺𝗲𝗿𝗶𝘁 budget increase % => 3.5% at private companies => 3.5% at public companies ✅ Median company-wide 𝗽𝗿𝗼𝗺𝗼 budget increase % => 1.0% at private companies => 1.1% at public companies ✅ Median company-wide 𝗽𝗿𝗼𝗺𝗼𝘁𝗶𝗼𝗻 𝗿𝗮𝘁𝗲 (% of population) => 12.0% at private companies => 12.0% at public companies ______________ 𝗖𝗼𝗺𝗽𝗮𝗿𝗶𝗻𝗴 𝟮𝟬𝟮𝟱 𝗕𝘂𝗱𝗴𝗲𝘁𝘀 𝘁𝗼 𝟮𝟬𝟮𝟰 “𝗔𝗰𝘁𝘂𝗮𝗹𝘀”: One month ago, I posted the trailing 12 month “2024 Actuals” for compensation spend across Pave’s customer dataset. (Link to post in comments.) Let’s compare some of those findings with the forecasted 2025 compensation budgets. 1️⃣ The median 2025 Overall Budget is 5.0% at private companies and 4.5% at public companies. And the 2024 “Actual” median was 4.5%. Thus, I’d expect 2025 to largely look like 2024 from a compensation budgeting standpoint. 2️⃣ The median 2025 Promotion Rate forecast is 12.0% at both private and public companies. But the 2024 “Actual” value was 14.9%. As a caveat, I would take this comparison with a grain of salt since it’s not 100% composed of the same peer group across the two studies. This said, my best hypothesis is that companies may initially forecast a promotion rate of, say, 12.0%, but then when the rubber meets the road, the “Actuals” may creep a bit above that once retention concerns become “real” around the merit cycle. #pave #compensation #benchmarks

🥳 Today, we are excited to announce Calculated Benchmarks, a new feature in Pave’s Market Data product! Calculated Benchmarks applies machine learning algorithms to our extensive real-time equity grant database to ensure each job in our dataset has better, more reliable benchmarks. For Pave customers, that means: ✅ More relevant, timely, and accurate equity data—without the gaps often left by traditional survey data ✅ Less work for you and your team, since the tool smoothes the data for you Visit the blog to learn more about Calculated Benchmarks and how it works: https://lnkd.in/g7asG5yW #Pave #Equity #Compensation