Workforce Analytics Tools

Introducing the web's first market map of the Product Analytics Market: I was floored when I couldn't find one of these online. Surely, Gartner or CBInsights or A16Z would have created one? It turns out not. So I spent the past 3 months: • Talking with 25 buyers • Researching the space myself • Interviewing 5 product leaders at key players This is what I learned about the most significant players in each space: (that PMs and product people need to know) 1. Core Product Analytics Platforms     The foundational tools for tracking user behavior and product performance Amplitude : The leader, an all-in-one platform for PMs to master their data Mixpanel : The leader in easy UX and pioneer in event-based analytics Heap | by Contentsquare: The automatic event tracking and real-time insights leader 2. A/B Testing & Experimentation     Platforms for analysis Optimizely : The premier tool for sophisticated A/B and multivariate testing VWO : The best for combining A/B testing with heatmaps and session recordings AB Tasty: The all-in-one solution for testing, personalization, and AI-driven insights 3. Feedback & Session Recording     Capture qualitative insights and visualize user interactions Medallia: The top choice for comprehensive experience management Hotjar | by Contentsquare: The go-to for visual feedback and user behavior insights Fullstory: The best for detailed session replay and user interaction analysis 4. Open-Source Solutions     Customizable, free analytics platforms for data sovereignty Matomo: The robust, privacy-focused open-source analytics platform Plausible Analytics: The lightweight, privacy-first analytics solution PostHog: The versatile, open source product analytics tool 5. Mobile & App Analytics     Specialized tools for mobile and app performance analysis UXCam: The best for in-depth mobile user interaction insights Localytics: The leader in user engagement and lifecycle management Flurry Analytics: The comprehensive, free mobile analytics platform 6. Data Collection & Integration     Gather and unify data across platforms Segment: The top choice for effortless customer data unification Informatica: The enterprise-grade solution for data integration and governance Talend: The flexible, open-source data integration tool 7. General BI & Data Viz     Non-product specific tools for data analysis and visualization Tableau: The leader in interactive, rich data visualization Power BI: The best for deep integration with Microsoft tools Looker: The modern BI tool for customizable, real-time insights 8. Decision Automation & AI     Systems for automated insights and decisions Databricks: The unified platform for data and AI collaboration DataRobot: The leader in automated machine learning and AI Alteryx: The comprehensive solution for analytics automation Check out the full infographic to see where your favorite tools fit and discover new platforms to enhance your product analytics stack.

📈HR is evolving — and so should our metrics!! Gone are the days when HR was just about hiring and payroll. Today, HR drives business value — but only when we track what really matters. 💡 Whether you’re building a high-performing team or improving culture, your data should tell the story. 👉Here are key HR KPIs that matter across every stage of the employee lifecycle: 🔍 1. Recruitment & Talent Acquisition • Time to Hire – Average time from job posting to offer acceptance. • Cost per Hire – Total recruitment cost divided by number of hires. • Offer Acceptance Rate – % of candidates who accept the offer. • Source of Hire – Performance of different hiring channels (LinkedIn, job portals, referrals). • Quality of Hire – Performance and retention rate of new hires (after 3 or 6 months). ⸻ 👋 2. Onboarding • Time to Productivity – Time it takes for new hires to reach expected performance levels. • New Hire Retention Rate (30/60/90 days) – How many new hires stay. • Onboarding Satisfaction Score – Feedback from new hires on onboarding experience. • Completion Rate of Onboarding Tasks – % of employees completing orientation, document submission, etc. ⸻ 💼 3. Employee Engagement & Experience • Employee Engagement Score – From surveys (e.g., eNPS or pulse surveys). • Participation in Engagement Activities – Attendance/feedback from events, programs. • Internal Mobility Rate – % of employees moving to new roles internally. • Manager Feedback Score – Employee feedback on direct supervisors. ⸻ 🧾 4. HR Operations & Compliance • HR-to-Employee Ratio – Number of HR staff per total employees. • Policy Compliance Rate – % adherence to HR policies/processes. • HR Request Resolution Time – Average time to resolve employee queries. ⸻ 📈 5. Performance Management • Completion Rate of Performance Reviews – % of employees reviewed on time. • Goal Achievement Rate – % of employee goals/KPIs met. • Performance Distribution – Breakdown of rating levels (e.g., top, meets, needs improvement). ⸻ 📚 6. Learning & Development • Training Participation Rate – % of employees attending programs. • Training Effectiveness Score – Feedback scores post-training. • Learning Hours per Employee – Average hours spent in development activities. • Skill Acquisition Rate – % of employees acquiring new skills/certifications. ⸻ 🚪 7. Retention & Offboarding • Employee Turnover Rate – Monthly/annual % of employees leaving. • Voluntary vs. Involuntary Turnover – Who left by choice vs. termination. • Regrettable Loss Rate – % of high-performing employees who left. Which of the following HR metric do you track most closely? #HRStrategy #PeopleAnalytics #HRKPIs #EmployeeExperience #PerformanceManagement #Recruitment #LearningAndDevelopment #HRLeadership

Is the Nursing Shortage Really Just a Capacity Problem? It's easy to find posts, articles, leaders, and politicians who say, "We can't train enough nurses." But are we missing critical data that suggests the problem is further downstream? Here is some interesting data: ⏺️ Average RN turnover rate in 2025 is about 16.4% compared to the average US turnover rate for all jobs, which comes in at 3.3%. ⏺️ First-year RN turnover is brutal, with many new RNs (around 30%) leaving within the first 12 months. ⏺️ It costs a hospital over $60k to replace a single bedside RN. ⏺️ 138,000+ nurses have left the workforce since 2022, and nearly 40% of RNs report an intent to retire or leave in the next five years. (NCSBN) So, here's the uncomfortable question: Do we really have a nursing school capacity problem, or a retention crisis so deep that it renders capacity expansions moot? Here are my thoughts: ⏺️ You can build fancy classrooms and sim labs, but if 16%+ of your workforce leaves yearly, you're fighting a pipeline that leaks faster than you can fill it. ⏺️ More nurses churn out of the bedside due to problems in the healthcare system that they churn out of school. ⏺️The real bottleneck is sustainability - we must make the career worth staying in, day after day, shift after shift. So, should we double down on capacity expansions, or should our first investment be in retention infrastructure, such as culture, leadership, support systems, flexible work models, career pathways, and psychological safety? Because what good is "more nurses trained" if we can't keep them at the bedside? #nursesonlinked #nursing #healthcareonlinkedin #nursingshortage #nursingcapacity Source: (2025 NSI National Health Care Retention and RN Staffing Report)

We stopped squeezing every last patient slot out of our clinicians. Here’s what happened… About ten years ago, a cherished nurse practitioner came to me in tears. She told me: “I am working ALL the time. I run from patient to patient, barely get to eat or pee, then still take home a ton of work. It isn’t worth it.” That conversation changed everything. I introduced protected admin time. For every 8 hours of clinical work, my clinicians now get 2 hours of dedicated time for documentation, patient calls, portal messages, and care coordination. Yes. That means a salaried 40-hour clinician sees patients for 30 hours. The results have been powerful: Morale is higher. Clinicians feel trusted and supported instead of squeezed. Revenue hasn’t dropped; in fact, it’s improved. With space to think, they code correctly, capture care gaps, and are willing to add patients when needed. Patients are happier. They hear directly from their clinician, and messages get answered promptly. And Melissa Bradley, who was ready to walk away? She’s now one of the most important leaders on our team: our clinical liaison; a position we created as a result of that conversation. She has her finger on everyone’s pulse, knows who’s drowning, and when we need to shift. She knows this because she lived it. Too often, practices try to maximize “revenue-generating” time at the expense of everything else. My experience? Giving your team the breathing room to do their jobs well pays off for everyone—patients, payers, and providers.

"S&P 500 companies that excel at maximizing their return on talent generate an astonishing 300 percent more revenue per employee compared with the median firm" In many cases, these top performing firms are using strategic workforce planning to stay ahead of their competitors in the talent race, treating talent with the same rigour as managing their financial capital. In their article, Neel Gandhi, Sandra Durth, Vincent Bérubé, Charlotte Seiler, Kritvi Kedia and Randy Lim, highlight how the emergence of generative AI is making strategic workforce planning even more important (see page 3). The article highlights five best practices for building a holistic talent plan through SWP: 🔎 Prioritise talent investments as much as financial investments. 👉 "Successful organizations recognize that their workforce is a strategic asset and investing in talent development and retention is essential for long-term health. Employees represent both an organization’s largest investment and its deepest source of value." 🔎 Consider both capacity and capabilities. 👉 "To measure performance in critical roles, organizations can conduct an outside-in search to understand the skills in the highest demand." 🔎 Plan for multiple business scenarios. 👉 "By implementing a scenario-based approach, organizations create flexibility for rapidly changing industry conditions." 🔎 Take an innovative approach to filling talent gaps – by refocusing from hiring to reskilling and upskilling. 👉 "Hiring is cost intensive, since it takes time to onboard and ramp up an employee into a new role. While reskilling and upskilling also take time and resources, leaders can use these levers strategically, track their relative success, and shift gears as needed." 🔎 Embed SWP into business as usual: 👉 "Strategic workforce planning should become a business-as-usual process, not just a one-off exercise in the face of a single threat to an organization’s talent pipeline or business goals." 👉 If you enjoy curated resources like these, please check out the Data Driven HR Monthly. Every month I select and curate some of the best HR, future of work and people analytics resources of the month. You can read the June edition here: https://lnkd.in/exEqY-Hn - and the July edition will be published tomorrow 👈 #strategicworkforceplanning #humanresources #peopleanalytics #workforceplanning #futureofwork #chiefpeopleofficer #orgdesign #hrtech #employeeexperience #learning

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.

Introducing Insights in Chrome DevTools Performance panel! Many web developers know the power of the Chrome DevTools Performance panel, but navigating its wealth of data to pinpoint issues can be daunting. While tools like Lighthouse provide great summaries, they often lack the context of when and where issues occur within a full performance trace. On the Chrome team we're bridging this gap with the new "Insights sidebar" directly within the Performance panel. Read all about it: https://lnkd.in/gGd3bkPw This exciting feature integrates Lighthouse-style analysis right into your workflow. After recording a performance trace, the Insights sidebar appears, offering actionable recommendations. Crucially, it doesn't just list potential problems but highlights relevant events and overlays explanations directly on the performance timeline. Hover over an insight like "LCP by phase," "Render blocking requests" or "Layout shift culprits" to visually connect the suggestion to the specific moments in your trace. The sidebar covers key areas like Largest Contentful Paint (LCP) optimization (including phase breakdowns and request discovery), Interaction to Next Paint (INP) analysis (like DOM size impact and forced reflows), Cumulative Layout Shift (CLS) culprits, and general page load issues such as third-party impact and image optimization. It's designed to make performance debugging more intuitive by linking high-level insights to the granular data, helping you improve Core Web Vitals and overall user experience more effectively. Check out the Insights sidebar in the latest Chrome versions (it's been evolving since Chrome 131!). It’s a fantastic step towards making complex performance analysis more accessible. Give it a try on your next performance audit! #softwareengineering #programming #ai

Health care worker burnout remains high after the pandemic, and the U.S. Department of Veterans Affairs offers a national look at what we can do about it. I was pleased to join David C. Mohr, Maureen Marks, PhD, and colleagues in describing and quantifying burnout trends in health care workers across specialties over the last several years, taking particular note of the lingering effects of the pandemic on burnout. The VA has a robust, all-employee survey that asks every health care worker questions about burnout, with response rates now exceeding 70%. In many ways, VA offers the most up-to-date picture on health care worker burnout nationally, as the VA has health care workers serving Veterans in every US state and territory. With strategy and focus on this important issue, we were successful in reducing burnout in almost all fields within our clinical workforce over the past several years. And while times are now "calmer" than the height of the pandemic, burnout still persists at levels greater than pre-pandemic times. Part of that was likely the intense period of change our workforce experience as they implemented the PACT Act, which marked the largest expansion of Veterans health care and benefits in a generation. But part of it is also lingering sense that we just need to do more to support our workforce across different fields. As our discussion notes: "While previous research in the VHA and elsewhere mainly focused on physicians, our data suggest that this single scope of attention is insufficient. Looking across occupations, the high burnout rates among mental health professionals, including psychiatrists, psychologists, and social workers, underlies the need to direct more focus to these occupations and attend to occupation-specific causes of burnout and stress. Further, burnout rates among nurses were much higher than several of the physician specialties, highlighting the need for tailoring approaches to specific occupations. For example, offering alternative work schedules may be especially beneficial for nurses. There are notable differences along with underlying causes among health care professions on burnout that may influence the improvement change selected and its effectiveness." We hope that these insights can be useful for leaders in health care delivery across the country: https://lnkd.in/eYFHg-RH

Layoffs cost 10X to 100X more than they save, but HR’s data only covers compensation, so business leaders only see savings. I use data to talk at least one CEO out of layoffs every month. Here’s how to protect your team from the chopping block. Quantify the Loss: The most common mistake is making the case with the value the team has created and the projects it has delivered. CEOs think about future value, not past gains, when making layoff decisions. What projects won’t deliver and how much revenue will be lost? CEOs need growth now more than ever. Build the case with data that quantifies the forward-looking value on the team’s product roadmap. Emphasize This Year’s Losses: Your CEO is being told that after an initial cost in the next 1-2 quarters, the business will see higher margins. Quantify this year’s lost revenue in big, bold terms. Showcase how internal efficiency initiatives will save the company more than the team costs. What external teams will miss their goals? Everyone advocates for themselves, so you’ll stand out by getting other leaders to add their voices. Use external teams’ KPIs and connect them to top-level strategic goals. Reduce Costs Without Reducing Headcount: Take high-cost, low or uncertain returning projects off the roadmap. Optimize hardware and cloud utilization. Push out tool and infrastructure purchases. Consolidate and put pressure on vendors to offer discounts. I frame this as, “I can’t reduce the staffing budget, but here are other areas where I can provide similar savings this year.” Instead of saying “No,” give your CEO alternatives and new options. Focus on informing vs. convincing. Every company’s CEO and CFO are taking a hard look at the technology budget, and layoffs are being discussed quarterly. Be proactive. Assume it’s coming and prepare the case now. Your team and career will be better off if you do.

Hiring managers always want more candidates. "Just increase sourcing — we need more people at the top of the funnel," they say. But the number one thing you can do to push back on unrealistic hiring expectations? Leverage data. It’s your strongest ally— Not opinions, not gut feelings. When a leader hands down aggressive hiring targets, work backward: How many sourcers and recruiters do you *actually* need to hit those numbers? Even lightweight capacity planning gives you the power to advocate for the resources you need. Now, let’s talk about internal benchmarks— They tell a compelling story. When your recruiting manager asks you to hit specific targets, look at the last few years of data across your team. See tech recruiting consistently yielding 8 hires per quarter… …while business and sales recruiting hitting 12? That's not a performance gap. It's the reality of different talent markets. But it goes deeper than hire counts: - How many people do you need to reach out to make one offer? - How many phone screens to get to one hire? This conversion rate data tells the real story at every step of the funnel. And here's what's interesting: When we dig into the data, we often learn that the biggest problem isn't the top-of-funnel… …it's the drop-off rate in some other part of the funnel. That’s why you *must* fix that conversion rate first. It’s pointless to double your sourcing efforts if you're passing 100 candidates into a broken funnel. You’ve got a leaky bucket… …fix the leaks before adding more water.