Coverfoto van Pando
Pando

Pando

Softwareontwikkeling

Killing performance reviews with continuous performance calibration.

Over ons

Pando is an AI-powered performance platform that replaces annual reviews with continuous performance calibration. Managers get always-on insights about their team, plus specific coaching actions to take next. Built-in tools like levels, competency frameworks, feedback coach and AI-goal enhancement help employees and leaders write better feedback, set stronger goals, and keep expectations clear. Pando helps organizations move away from laborious, costly and ineffective annual performance reviews, to a just-in-time approach that saves time and gets the most employees are your organization performing their best.

Website
http://www.pando.com
Branche
Softwareontwikkeling
Bedrijfsgrootte
11 - 50 medewerkers
Hoofdkantoor
San Francisco
Type
Particuliere onderneming
Opgericht
2021
Specialismen
Consulting, Performance Managgement, Feedback, Continuous Calibration, Career Frameworks, Job Leveling, Career Progression, Equitable Performance Programs, Goals & OKRs, Real-time Performance Tracking en Employee Growth Velocity

Locaties

Medewerkers van Pando

Updates

  • Pando heeft dit gerepost

    We’ve been quiet on the product front, but I’m excited to share something new is will be here in the coming days… I founded Pando to help companies optimize the potential of all employees. Brining both my experience as a CMO and years of building community within and working with some of the best people operators on the planet (was lucky to spend time with…Beth Steinberg , Cara Brennan Allamano, Katie Burke Annie Trombatore , Lissa Minkin, Mike Joyner, 🏡 Kim Rohrer (she/her), Mark Frein, Luan Lam, Austin Sailors Melanie Oberman, Maia Josebachvili , Victoria Sevilla, Daniel M., Tony Truong Aisha Stephenson, Lorna Hagen, Roslyn F. Shelby Wolpa …and so many others!) There was a clear gap around connecting the dots for employees around their role, what’s expected of them and how performance is measured (tools were falling short—and still are). Pando’s thesis has always been: make performance continuous, just-in-time, and equitable—enable employees to level up when they’re ready, and decouple that from an annual event—leveraging real-time, always in performance calibration to compound outcomes. While that thesis remains unchanged, the environment in which it operates has evolved, rapidly. Organizations are now flatter, with fewer layers and even more responsibility for performance management has shifting to managers who are already stretched thin, also trying to adapt to a new world and pace of work. The problem we aimed to solve is still relevant, but like everything else, the solution must adapt. Performance management through forms, twice a year, combined with all the complexity and baggage of comp, and salaires reviews can’t continue to be our status quo. We now have a very unique opportunity to enable managers in a way we couldn’t before, and empower employees to iteratively improve and increase their impact, in the flow of work. Excited about the challenge of tackling the problem in a different way — eager to share and get your thoughts. Stay tuned 🚀

  • Pando heeft dit gerepost

    The team and I are building Nscale’s approach to how we enable, measure and assess high performance at work. This has become an endless debate in business. With numerous iterations. A few truths: 1. Trad. “performance management” was built for a world that no longer exists. Most work is collaborative, yet almost every process still optimises for individual outcomes. As Josh Bersin pointed out recently: the admin burden already made little sense; it makes even less sense in today’s world of AI. 2. Any system has to be clear about what it’s for. Reward results fairly, spot underperformance early, help people grow. Whatever. Pick your goals and build with this front of mind. 3. It’s not really about ratings vs no ratings. People simply want to know where they stand, how they improve, and whether the process is clear. The real question: is it helping people get work done, or getting in the way? 4. Context is Queen. What a v good approach looks like at 500 people is not what it looks like at 10,000 etc. And if we’re honest; most perf systems exist simply to feed the annual comp cycle, rather than create business value. Lucy Adams has written much about this. TLDR: Yes, agentic systems have the potential to completely strip all the unnecessary process here (AI supported calibration anyone?). What remains: we’ll still need some manager judgement, clear expectations and honest conversations about the work. Worth checking out: Thomas Forstner and Barbra Gago wrote solid pieces on this recently. Edie Goldberg also has well-researched ideas in her upcoming book.

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  • Pando heeft dit gerepost

    Most orgs bundle three completely different questions into one annual event. Is this person ready for a promotion? Have they progressed in their current role? Are we paying them fairly relative to market? These are separate questions with separate timelines and separate data sources. But we cram them all into the same calibration meeting, the same review cycle, the same conversation. No wonder the process feels broken. It is. Promotion readiness should be evaluated when someone demonstrates sustained next-level performance. Not once a year. Role progression should be continuous. Competency-based, tied to clear expectations at each level. Market adjustments should be administrative. Data-driven. Disconnected from individual performance conversations entirely. At Pando, we separate these into two distinct motions. Pay-for-progression runs on the individual's timeline. Salary reviews run on the company's market cycle. Two separate processes. Two separate conversations. Two separate outcomes. Full breakdown of the framework and the five system failures it addresses: https://lnkd.in/ewgQcE-Q

  • What are you doing to mitigate "brain fry" from AI usage? How do we build programs with intention to reduce the impending burnout?

    Profiel weergeven voor Barbra Gago

    One of the biggest risks in an AI-native era is not being talked about enough: Is AI increasing burnout faster than it increases productivity? On Lenny Rachitsky podcast this week, Simon Willison said something every People leader should pay attention to: “I can fire up four agents in parallel and have them work on four different problems. And by 11 a.m., I am wiped out for the day.” Imagine, by 11 am being done for the day, and not because you feel accomplished and can take the rest of the day off, but because your brain is literally toast. This is a blind spot we should all pay close attention to. Mandating AI adoption, encouraging experimentation, and celebrating speed gains…without consideration or intention around the human cost of sustaining that pace. Harvard Business Review recently called this “AI brain fry”—mental fatigue caused by excessive use or oversight of AI tools beyond a person’s cognitive capacity. The research warns it can increase errors, decision fatigue, and even intent to quit. It drew on a study of 1,488 U.S. workers across large companies. 🚨That should be a flashing red light for HR and People leaders because the risk isn’t just “Will AI replace jobs?” It’s also: What happens when people are expected to produce 10x…and stay at that pace indefinitely? AI can absolutely remove low-value work: accelerate drafting, synthesis, analysis, and execution. But if organizations simply use that gain to pile on more output, more responsiveness, and more context-switching, then we haven’t improved work. We’ve just industrialized burnout. This is where modern performance strategy matters. In an AI-native workplace, high performance cannot mean: • always on • infinitely scalable • constantly available • producing at machine speed WE are not models. And “more capacity” is not the same as “sustainable capacity.” The companies that get this right will not be the ones with the most aggressive AI mandates but rather, those that redesign work itself with: CLEARER priorities, better calibration, healthier expectations, and performance systems that reward impact—not just volume. HR leaders need to start measuring the hidden cost of AI adoption, not just the visible productivity gains. Are you seeing this in your organization yet—more output on paper, but more cognitive overload underneath it? Credit to Simon Willison 🙏 for articulating what many knowledge workers are already feeling, even if they don’t have language for it yet. #FutureOfWork #AIatWork #PeopleStrategy HBR research: https://lnkd.in/eFud4CGT AI State of the Union (Lenny's Pod): https://lnkd.in/eJpx2gkk

  • What if compensation increases didn't all happen at once? Most companies run one or two massive comp events per year—a spike in payroll, an enormous coordination effort, lots of time spent in "calibration", and a process that produces questionable insight at enormous cost. What if instead, increases happened in real-time as individuals level up? This isn't just a cleaner philosophy. It's better financial management: → Cash flow smooths out. No more payroll spikes. Budgeting becomes predictable and plannable. → Fast growers get recognized faster. The person who's clearly operating at the next level shouldn't have to wait six months for a window to open. That gap is exactly when high performers start looking elsewhere. → Trust goes up. A lot of employee cynicism about performance management comes from systems that feel delayed, opaque, and disconnected from reality. A continuous model makes an honest promise — and keeps it. → Process overhead collapses. No giant annual ritual. No managers manufacturing meaning at review time. No employees waiting for the cycle to catch up with their growth. This is the "just-in-time progression" model Barbra Gago makes the case for in her latest article—two separate motions, taken entirely off the annual clock. The link is in the comments.

  • Pando heeft dit gerepost

    7 PERFORMANCE MANAGEMENT TOOLS YOU NEED TO KNOW 👇 Most people think their performance management processes and tools are pretty much 💩 But now we have access to much better tooling that it really changes how we can approach it. + make it way more enjoyable and useful for everyone The flexibility and the data we can now work with is amazing. So if you’re doing it the old way… Check out these: 1. Taito.ai 2. Culture Amp 3. Opre 4. Pando 5. Crewmojo 6. Topicflow 7. TeamMaven I personally don't recommend vibe coding performance tooling. There is so much to get wrong in this space. And there really are so many cool tools for this now. Check them out and 400+ more on stakkd.tech HR tech database! Am I missing some hot tech from this list? 🔥 Tag them in the comments! _________ Hi I'm Jess 👋 I am a bootstrap founder of Stakkd and Linnx Building useful and accessible products is my mission 🚀

  • Six experts debated whether pay for performance works. 62% of the audience voted in favor. And yet the most important question went unanswered: If not pay for performance—then what, exactly? The "for" side was right: if you don't differentiate for performance, you get adverse selection. Your best people leave. The people most comfortable in a flat structure stay. The "against" side was also right: knowledge work is collaborative and emergent. You can't OKR your way to innovations like Gmail, the iPhone, etc. Single ratings compress nuance into a number that's mostly useful for filling in a spreadsheet. The realty is that both sides were debating variations of the same broken system. A point-in-time annual cycle trying to simultaneously give feedback, assess performance, make promotion decisions, and determine comp—with undertrained managers and too much else going on to make this process valuable for anyone. The debate will never be settled if we stay inside that system. Our founder, Barbra Gago has the third position and the structural argument for why it's operationally better for the whole business, not just philosophically cleaner. Full article here 👇 https://lnkd.in/ehAM6H2d And thanks for Jessica Z., Mark Frein, Matt McFarlane, Kim Minnick, 🏡 Kim Rohrer (she/her), James A Seechurn for the lively discussion and well thought out arguements.

  • Reframing performance reviews to focus on impact and value can significantly enhance employee feedback. Instead of generic questions, starting with "What are the 2 most significant achievements you made during this period?" and "How did these achievements create value for the organization?" encourages more honest self-assessment and clearer connections to business outcomes. This approach not only helps employees articulate their contributions but also reinforces the link between individual work and organizational success, fostering a more engaged and results-oriented culture. Check out the full conversation here: https://lnkd.in/epvxHVzh

  • Pando heeft dit gerepost

    Before you figure out how to measure AI token usage as a performance indicator—do your employees know what level they're at and how to grow? No joke! Just this morning, I saw multiple posts about teams racing to develop token-usage tracking dashboards, AI competency frameworks, and output metrics for a new era of work. We absolutely need to get there. But a lot of organizations are still operating without the basics (a solid leveling foundation) and that gap will cause major chaos downstream. This is your gentle reminder to get back to basics first. Without a well-designed leveling framework, you get: 🔴 Political performance reviews—when there's no clear structure defining what "good" looks like at each level, promotion decisions become subjective, inconsistent, and frankly, political. The loudest voices win, not the best performers. 🔴 Inequitable comp—different leveling frameworks for different teams (Engineering gets 10 levels, Marketing gets 4) widens pay gaps, often along gender and demographic lines. The structure itself becomes the bias. 🔴 The Peter Principle at scale—when management is the only path to growth, you keep promoting great individual contributors into roles they didn't sign up for and aren't set up to succeed in. You lose your best ICs and gain your worst managers. 🔴 Retention problems hiding in plain sight—if employees can't see a path forward (career advancement in their role), they find one somewhere else. The good news? These are all solvable before they become expensive. Here are some slides from a leveling workshop I run covering why job leveling matters, the most common pitfalls we see—like stacked IC/Manager tracks, too few levels, and leveling frameworks built backwards from comp data—and how to evolve your structure to give people real mobility and growth. If your team is still operating with a handful of vague levels and a title change at each rung, this is where to start. Get the foundation right first. Everything else: performance, comp, culture, and yes, eventually your AI productivity metrics, will be better for it. What's the leveling mistake you've seen cause the most downstream damage? Drop it in the comments 👇 #PeopleOps #JobLeveling #CareerDevelopment

  • Organisatiepagina weergeven voor Pando.

    3.166 volgers

    Establishing a feedback culture requires building the habit of giving feedback regularly. Implementing 'Feedback Fridays' offers a simple yet effective structure. Employees answer three upward feedback questions, while managers provide downward feedback through three corresponding questions. Utilizing a shared document initially helps streamline the process when formal systems are absent. Consistent feedback loops are crucial for development and performance. Check out the full convo with Hebba Youssef here: https://lnkd.in/epvxHVzh

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Financiering

Pando 2 rondes in totaal

Laatste ronde

Basis

US$ 5.000.000,00

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