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Forecasting is hard. Finding analysts who do it well is even harder. Too often, I see forecasting either: 1. Overcomplicated: Applying complex ML models just to predict a moving average (?!), or 2. Oversimplified: Running regressions without understanding what the coefficients even mean. I personally use 4 forecasting methods to model a range of outcomes, from conservative to aggressive: 1. ARIMA - Smooths time series data, w/o seasonality adjustment. 2. SARIMAX -  Like ARIMA, but accounts for seasonality. Likely to be the safest and conservative forecast. 3. Prophet -  Captures non-linear trends and seasonality. Often the most accurate. My favorite model for growth forecasts. 4. Manual Projection – aka Olga's secret, overly complicated manual projection. I plot every available metric’s historical D/D, W/W, M/M, and Y/Y % change and analyze their: (a) correlations and relationships (b) seasonal thresholds. It takes ages to complete, but it delivers the most precise forecast. If done right. If I can account for everything the teams are doing. Which is rarely the case. 😬 When reporting, I typically present only Prophet alongside my Projection, keeping ARIMA and its variations for myself as checks. There are many time series models out there: MA, AR, ARMA, ARIMA, SARIMA, Exponential Smoothing, VAR, and more. Forecasts are fun.

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.

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.

Using Gem's dataset (140M+ applicants, 14.4M candidates, 1.3M hires), we looked at what actually moves candidates through the funnel. The single biggest finding: sourced applicants are 5x more likely to be hired than inbound (2.0% vs 0.4%). BACKGROUND: For years, recruiting advice has been pure superstition. Most teams guess at what works. We analyzed Gem's full dataset to see what actually moves candidates. Here's what we found: A 3-stage sequence should aim for 82%+ opens, 26%+ replies, and 14%+ interested. Sourced candidates are 5x more likely to be hired than inbound. THE 4-TOUCH SEQUENCE: Touch 1: Reason-first personalization Subject examples: - "Reaching out because of your Kubernetes migration post" - "Your talk on scaling Postgres caught my attention" - "Saw you just shipped v2 of the mobile app" Body: One line on why them, two sentences on value, soft ask. Why this works: Highly personalized messages see 73% engagement. Generic outreach gets ignored. Specific reasons signal you did the work. Touch 2: Concrete outcome Subject examples: - "Cut deployment time 40% - Staff SRE" - "Own data platform serving 50M users" - "Lead mobile eng for Series B fintech" Body: One outcome they'd own plus a 1-click scheduling link. Touch 3: Value with no ask Share a relevant resource like an open-source PR, launch note, or talk. Stay top of mind without pitching. Touch 4: Breakup email Subject examples: - "Should I close your file?" - "Last note - timing off?" - "Wrong time?" Body: Acknowledge silence, offer to close their file or reconnect later. Give them an easy out or a path back in. WHAT REASON-FIRST ACTUALLY MEANS: Bad: "We're hiring for a great role" Good: "Saw you scaled [system] to [metric] at [company] - that's exactly the challenge on our [project]" That's what Gem's #{{reason}} token operationalizes at scale. THE DIAGNOSTIC: If your opens are too low, your subject lines are generic. If your replies are too low, your value prop isn't clear or your ask is too big. If your interested rate is too low, you're targeting the wrong audience or timing. TAKEAWAY: Run this 4-touch sequence Monday. Measure your first 3 touches against 82/26/14. Want the full 2025 Recruiting Benchmarks report? Link in the comments. 👇

SmartRecruiters : the features that matter (and why teams adopt it fast) If you’re evaluating or implementing SmartRecruiters, here’s the feature map I use to align recruiters + hiring managers: ✅ ATS (end-to-end hiring workflow) Track applicants, standardize stages, keep everyone in one place (no “where is the latest resume?”). ✅ CRM (talent pools + nurture) Build pipelines for future roles and run outreach campaigns with measurable engagement. ✅ AI support (matching + assistant capabilities) Matching helps prioritize screening; AI-assistant concepts focus on removing repetitive work (screening/scheduling/engagement). ✅ Job Distribution Publish jobs broadly from one place (key for volume hiring and consistency). ✅ Dynamic Scheduling Reduce the back-and-forth for interviews (often one of the biggest time sinks). ✅ Messaging (SMS) Faster response loops with candidates—especially for high-volume roles. ✅ Integrations & Marketplace ecosystem Pre-built ecosystem to connect tools across sourcing, assessments, HRIS, etc. ✅ LinkedIn integrations (RSC + reporting) Sync candidate/app data with LinkedIn Recruiter and get ATS-enabled reporting (depending on your setup/contracts). My practical takeaway: SmartRecruiters is strongest when you design it as a hiring operating system (process + adoption), not just “an ATS implementation.” #SmartRecruiters #SAPSuccessFactors #ATS #Recruitment #TalentAcquisition #HRTech

Many FP&A teams forecast compensation using top-down assumptions like "salaries grow 3% year-over-year and benefits are 25% of pay." But this usually fails. Bottoms-up cost builds allow FP&A professionals to build accurate compensation models like this one. Instead of starting with high-level assumptions and averages, it begins with inputs that can then drive the averages used in the financial model. This is an example I sometimes use to illustrate how FP&A teams can build more accurate payroll forecasts: • Separate senior professionals from junior professionals • Build salary growth rates at the category level • Add fringe and statutory costs line by line • Calculate each cost as a % or salaries or per person • Include benefits % of salary to capture non-cash comp The result of this technique is you get a transparent, auditable model with inputs that can be easily flexed. You get immediate sensitivities that you can run on headcount, pay mix, or changes to benefits. And you can easily integrate these assumptions with workforce planning. You can also break down leadership, management, and staff by job category and assign salary bands. If the CFO asks why personnel costs went up 8%, you can show exactly where that increase is coming from. A bottoms-up cost build like this doesn't just make your forecast more detailed. It makes it more defensible for FP&A business partners serving human resources.

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

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.

Employees with 3 or more different managers in a year are up to 75% more likely to leave your company Yesterday, we saw that only ~50% of employees in Pave’s dataset have kept the same manager for a full year. Today, let’s go one step deeper and look at the impact of “manager thrash” on employee attrition. _____________ As a quick caveat, the reported turnover rates include both voluntary and involuntary (as well as regrettable and non-regrettable) attrition. And yes, this includes layoffs too. _____________ 𝗧𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁𝘀 𝗮𝗰𝗿𝗼𝘀𝘀 𝗣𝗮𝘃𝗲’𝘀 𝗱𝗮𝘁𝗮𝘀𝗲𝘁? • 𝗢𝗻𝗲 consistent manager over the past 12 months => Attrition rates between 𝟭𝟲% 𝗮𝗻𝗱 𝟮𝟬% depending on company stage. • 𝗧𝘄𝗼 managers over the past 12 months => Attrition rates between 𝟮𝟭% 𝗮𝗻𝗱 𝟮𝟳%. • 𝗧𝗵𝗿𝗲𝗲 𝗼𝗿 𝗺𝗼𝗿𝗲 managers over the past 12 months => Attrition rates between 𝟮𝟱% 𝗮𝗻𝗱 𝟯𝟰%. _____________ 𝗧𝘄𝗼 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀 𝘁𝗼 𝗰𝗮𝗹𝗹 𝗼𝘂𝘁: 1️⃣ In general, the more managers an employee has, the more likely they are to leave the company. 2️⃣ Attrition rates are usually highest at early stage startups and gradually decrease as companies mature. ________________ 𝗔𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆 𝗳𝗼𝗿 𝗧𝗼𝘁𝗮𝗹 𝗥𝗲𝘄𝗮𝗿𝗱𝘀 𝗮𝗻𝗱 𝗛𝗥 𝗟𝗲𝗮𝗱𝗲𝗿𝘀: ✅ Re-orgs, performance management, and layoffs are somewhat inevitable in the world of company building. However, be cognizant of the tangible impact that “manager thrash” has on employee attrition. In particular, I encourage you to run a cohort analysis around how much manager thrash your top performers have undergone over the past 12 months as a way to proactively predict attrition risk org-by-org. I’d also call out that it’s important to consider whether or not attrition spikes caused by “manager thrash” are due to causation or correlation with other forces. Think critically here. Is it the disruption, inconsistent expectations, or something else? #pave #orgchart #benchmarks

We all want to hire the best people - but a mistake so many founders make is ignoring step 1: Build a talent magnet 🧲 Psychometric testing, blind referencing, task-based assignments and culture-fit interviews - all great tools for selecting talent... But if your top of funnel is only 50 candidates per role - you're better off investing time in building the top of funnel rather than selection. At my first company we built a talent magnet that attracted 2,000 candidates per role (pre AI applications). Here are the core steps to building top of funnel in hiring: 1. Define your culture - ensure it is authentic and 'controversial' 2. Craft your employer brand - the reasons people enjoy working at your company (beyond your culture) - eg at sequel those might be working with the world's best athletes on a daily basis, funding pioneering founders, a 'dope' office with a roof terrace & plenty of socialising space, an experienced team with multiple exits 3. Pick your benefits carefully - you are what you attract - at sequel we offer a learning budget, free gym membership, private healthcare, a generous parental policy and proactive wellness screenings - therefore we have healthy team members with a hunger to learn and who want to have families one day 4. Talk about the above publicly - post on LinkedIn, attend events, talk to the press, apply for awards 5. Craft job descriptions optimising for top-of-funnel - remove barriers like requirements for certain levels of education, include wide salary ranges (and pick the range carefully), offer equity if you can, link to other resources to help people learn about your brand (eg we have a team video on our website) 6. Use an ATS & post widely to job boards - we use Workable and post to 20+ job boards for every role 7. Host events - hackathons are a great way to build relationships with engineering and product talent and spend extended period of time seeing how they work 8. Outbound - do not just rely on inbound - create an ideal candidate profile with a detailed dream job history - and start pro-actively reaching out to people who fit the profile Focus on attraction before you invest time in selection. It's a bit like dating... Any other tips for building a magnet for talent?