Defining Success Criteria

You hit every KPI. But did anything actually get better? Solving the wrong problem perfectly is still failure. So is solving the right one - without knowing how you’ll measure it. Let’s say a digital health platform launches: 🔹Sleek interface 🔹User numbers climbing 🔹Dashboards full of green ticks But two months later... 🔹Patients are still confused 🔹Clinicians are frustrated 🔹Data isn’t flowing across systems 🔹Helpdesk tickets pile up The dashboard says success... but the outcomes show otherwise. In digital health, success is often defined too narrowly: 🔸The platform went live 🔸KPIs were ticked 🔸Stakeholders celebrated But if patients still struggle, providers still burn out, and workflows remain broken - was it really a success? The truth is, different players define success differently: 🔹Patients want clarity and trust 🔹Clinicians want support in context 🔹IT wants performance 🔹Leadership wants results 🔹Funders want scale And that misalignment is where failure often begins. We don’t just need SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) goals. We need SMART goals for healthcare, ones that reflect complexity, context, and care. Because what gets measured, gets built. And if we define success in terms of speed and scale, we risk delivering fast but shallow. A better way would be to define success through multiple lenses Systems Thinking 🔸What ripple effects will this change create? 🔸Will it reinforce or undermine other parts of care delivery? Design Thinking 🔸Does this make life better for the people using it? 🔸Does it work in context, not just on paper? Interoperability Thinking 🔸Will it integrate across teams and platforms - or just add noise? How does SMART Goals for healthcare looks like? ✨S – Shared & Specific Is the goal clear and aligned across patients, providers, and implementers? ✨M – Meaningful & Measurable Does it tie to real improvement - not just activity? ✨A – Aligned & Achievable Is it grounded in actual clinical workflows and capacity? ✨R – Relevant & Responsible Is it equity-conscious, ethically sound, and system-aware? ✨T – Time-bound & Tracked Is it tracked across the care journey - with feedback loops, not just endpoints? What this looks like in action: 🔹30% reduction in medication errors across 3 facilities in 6 months 🔹15% improvement in post-discharge follow-up for elderly patients using an interoperable care platform 🔹Measurable reduction in care team workload without sacrificing continuity or quality Not: 🔸Number of logins 🔸Lines of code shipped 🔸How fast we deployed When goals are shared, meaningful, and grounded in real care, 🔸Teams stay focused 🔸Results are credible 🔸Patients feel the difference Define success. Measure what matters. That’s how we make digital health actually work. What’s one thing you believe we should start measuring - but rarely do in digital health today? #HumanCenteredDesign #SystemsThinking #Interoperability

Are you measuring what matters in your organization? A comprehensive measure of organizational effectiveness includes much more than profit margins and growth rates. The market and media often celebrate companies that show rapid financial growth or high profitability, leading to a cultural bias towards these metrics as signs of success BUT the tide is slowly turning- more businesses are recognizing the long-term value of a holistic approach to effectiveness and success. Many more businesses are embracing the concept of the "Triple Bottom Line," which measures success not just by financial profit ("Profit"), but also by the company's impact on people ("People") and the planet ("Planet"). HOWEVER 🚨 There is more work to be done! The prioritization of non-financial elements of organizational success can get pushed aside when financial pressures hit or quick results are valued. You have probably heard the phrase "What gets measured gets managed". This is generally true. Quantifying and measuring non-financial aspects of effectiveness, such as employee well-being, social impact, and workplace culture, is hugely important but remains challenging. 💡 Here's some straightforward steps to move you towards a more holistic approach to measuring success: 𝐒𝐭𝐚𝐫𝐭 𝐰𝐢𝐭𝐡 𝐜𝐥𝐞𝐚𝐫 𝐠𝐨𝐚𝐥𝐬: Define what holistic success means for your organization. This could include specific targets related to employee well-being, social impact, and environmental sustainability. 𝐄𝐧𝐠𝐚𝐠𝐞 𝐬𝐭𝐚𝐤𝐞𝐡𝐨𝐥𝐝𝐞𝐫𝐬: Talk to employees, customers, and community members to understand what aspects of your business matter most to them. Their insights can help shape your holistic success framework. 𝐂𝐡𝐨𝐨𝐬𝐞 𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 𝐦𝐞𝐭𝐫𝐢𝐜𝐬: Based on your goals and stakeholder feedback, pick metrics that are meaningful and manageable. For example, employee satisfaction can be measured through regular surveys, while environmental impact can be tracked through energy consumption or waste reduction metrics. 𝐔𝐬𝐞 𝐞𝐱𝐢𝐬𝐭𝐢𝐧𝐠 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬: Look into established frameworks (like GRI or B Corp standards for sustainability; Gallups Q12 Engagement Survey for employee engagement or the Denison Organizational Culture Model to measure workplace culture). There are existing frameworks for most known elements of organizational effectiveness so it's just a matter of looking into them. 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞 𝐢𝐧𝐭𝐨 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐦𝐚𝐤𝐢𝐧𝐠: Ensure that these holistic metrics are part of regular business reviews and decision-making processes, not just side projects. 𝐑𝐞𝐩𝐨𝐫𝐭 𝐭𝐫𝐚𝐧𝐬𝐩𝐚𝐫𝐞𝐧𝐭𝐥𝐲: Share your progress openly, including both successes and areas for improvement. Transparency builds trust and credibility. 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Be prepared to adapt and refine your approach as you learn what works and what doesn't. This is a journey, not a one-time task. #organizationaleffectiveness #measurewhatmatters #leaders

One page. That's all I give teams to define a data product before we start building. If you can't explain the what, why, who, cost, and the expected revenue on a single page, you don't understand the project well enough to start it. I built this template after watching too many data products fail for the same reason. Bad clarity. A team would spend 6 months building something, then someone in leadership would ask "wait, what problem does this solve?" and nobody could give a clean answer. Or worse, everyone gave a different answer. So I created a one-page brief that every data product has to go through before it gets a single hour of time. I've used it at Fortune 500 companies and 10-person startups. Here's what's on the page. BUSINESS STREAM: Which part of the business does this support? If the answer is "everyone" then you haven't thought hard enough. A data product that serves everyone serves no one. PROJECT CONTEXT: What's happening in the business that makes this necessary right now? Not why it would be nice to have. Why it matters today. ROLES: Owner, Sponsor, Benefits Owner, Maintainer. If you can't fill in all 4, the project will stall. The one most people skip is Maintainer. Who keeps this thing running after it ships? If nobody owns that, you're building something that dies in 6 months. DEFINITION OF SUCCESS: Not "better insights" or "improved decision making." A number, revenue generated, cost reduced, time saved. If you can't put a number here, go back and figure out what problem you're actually solving. SCOPE: Two columns. In-scope and out-of-scope. The out-of-scope column is more important than the in-scope column. This is where you kill feature creep before it starts. I've seen data products go from "build a pricing model" to "build a pricing model with a dashboard and an alert system and an integration with Salesforce and a mobile app" because nobody wrote down what was out of scope. THE FINANCIALS: Cost vs. benefits over 3 years. Capital, expense, operating costs on one side. Sales, gross margin, etc... This is the section that separates real data products from science projects. If you can't project the financial impact, you're guessing. KEY PHASES AND MILESTONES: Broken down by quarter. Not a 47-page project plan. Just the big milestones that tell you if the project is on track or not. HELP NEEDED: What's blocking you right now? What do you need from leadership? This section forces honesty. Most project briefs are designed to make things look good. This section is designed to surface problems early. Every data product I've shipped started with some version of this page. When teams push back and say it's too simple, I tell them that's exactly the point. Complexity is where bad projects hide. If your team is working on a data or AI product right now, could you fill this out today? If not, that tells you something important about how well the project is actually defined. #AIStrategy #DataLeadership #GenAI

People ask me how I measure success in my law firm. Financial metrics are important. Case outcomes matter. Revenue matters. But that's just one piece of the puzzle. Here's what else I track: • Existing client referrals • Past client referrals • Customer satisfaction scores • Staff engagement scores These tell me what's really happening. What is our reputation in the marketplace?  What are other people saying about us when we're not in the room? That matters just as much as the numbers on our P&L. High CSAT means referrals are coming.  High staff engagement means your A-players aren't leaving. High client satisfaction means fewer malpractice concerns and more repeat business. Revenue, case outcomes, etc. is a lagging indicator.  It tells you what already happened. These other metrics tell you what's about to happen. If your revenue is growing but your client satisfaction is dropping, your staff is disengaged, and your referrals are declining, that's smoke. And where there is smoke, there is fire. Track the right numbers and you'll build a firm that lasts. Track only revenue and you'll burn out chasing a number that doesn't mean what you think it means.

How will we know we've been successful? Too often, in organizational transformation efforts, the answer to that question is in the eye of the beholder. Rather than arguing about who's perspective is "right", however, it can be useful to think about organizational change success as multi-dimensional. Change is complex, after all. Our measures of it should reflect that reality, without being overly complicated. For me, the three buckets of achievement, completion, and acceptability fit that bill. These come directly from the work of Susan Miller on implementing strategic decisions - please see the comments for a link. ➡ Achievement: Gauge how close you've come to creating meaningful results from the change you are implementing. This helps to ensure you don't mistake activity for outcomes. That said, Rome wasn't built in a day, so it's wise to look for signs of learning first before evaluating performance. ➡ Acceptability: Get feedback on stakeholder satisfaction regarding the change solution and process. People's current experience with change can shape their view of future changes. So, getting better here can bring both short and long-term dividends. ➡ Completion: Assess how well you execute. Bringing about change in organizations can be an intensive and expensive undertaking. Managing schedule, scope, and budget effectively is a critical. Additionally, some research indicates that people's perspectives of a given change are influenced by their belief in the organization's ability to manage it competently. Using defined success dimensions such as these can build shared understanding of different perspectives and enable more robust conversations about the definition of success for any given change. Importantly, developing relevant measures and tracking progress on multiple dimensions can also support more nuanced learning about what aspects of change you are doing well and the best areas to target if you want to improve your organization's approach to change. If change is truly the only constant in organizations today, surely that's something worth knowing. #changemanagement #transformation #transformationalchange #organizationalchange #changeleadership

As Project leaders, we don’t always get to choose our projects. But we do get to choose how we evaluate them, how we advocate for what they need, and where we push back. That choice makes a bigger difference than most people realise. When a new project lands on my desk, these are the three questions I assess early, not to reject the work, but to understand what I’m walking into. 1️⃣ Does this project have executive support and adequate resources? If the answer is no, the gap needs to be documented and escalated early. Starting a project knowing it’s under-resourced doesn’t make anyone committed or resilient. It usually leads to burnout, quiet frustration, and avoidable failure. →What this looks like in practice: Asking questions like: * Who actually owns this? * Who is accountable when priorities shift? * What’s the real budget and not the hopeful one? Clarity here protects both delivery and the people doing the work. 2️⃣ Can success be defined in clear, measurable terms? If success can’t be articulated early, it’s worth pushing for clarity even when it feels uncomfortable. Ambiguous goals almost always turn into scope creep later. And when outcomes aren’t clear, accountability becomes personal instead of objective. →What this looks like in practice: Getting stakeholders to align on two or three concrete outcomes and not vague statements like “improve efficiency” or “make it better.” Clear success criteria reduce conflict long before it shows up. 3️⃣ Will this project teach something or support where I’m heading? Not every project needs to be a growth opportunity. But it helps to be honest about what role the work plays. Some projects are about learning. Some are about visibility. Some are simply about keeping things running. →What this looks like in practice: Recognising when a project is “keep-the-lights-on” work versus growth work and adjusting expectations, energy, and boundaries accordingly. Both are valid. They just need to be approached differently. We can’t always say no to work. But asking these questions early helps us understand: * where support is needed, * where boundaries should be set, * and where to ask for help before pressure builds. That awareness changes how the project is led and how sustainable the work becomes. What do you look for when a new project lands on your desk? N.B. This can be applied outside work too. Follow Benjamina for practical perspectives on #projectexecution, #leadership judgment, and #delivery under real constraints.

If I had to fill 100+ roles across multiple teams without burning out my recruiters… This is the unbreakable system I’d build to filter and prioritize the right candidates before your team spends hours in interviews that go nowhere. Here's what happens when you get the top of the funnel wrong: your team spends most of their time in final rounds with candidates who were never going to work out. The goal is embarrassingly simple: disqualify candidates who don't meet must-have requirements, then optimize and rank the ones that do. This sounds basic, but it's astonishing how many processes completely fail at this fundamental step. Alignment: 1/ Define the role mission Why does this role exist and what value does it create? Force every hiring manager to articulate the positive impact, not just fill a gap on the org chart. 2/ Map tangible 90-day outcomes What does success actually look like? Translate vague job descriptions into specific deliverables someone can point to and say "that's what good looks like." 3/ Apply the "Best Doctor For" approach When you need heart surgery, you find the best cardiologist for your condition. Same logic here - define the exact specialist based on mission and outcomes. 4/ Set binary must-haves (yes, I'm almost embarrassed to bring this up) Missing any single one = immediate no. If you wouldn't actually reject someone for lacking it, stop calling it a requirement. It's shocking how many "requirements" lists have 15+ items where half aren't actually required. 5/ Define nice-haves (duh) This should be used as scoring/optimization for candidates that met must-haves. 6/ Top-of-Funnel Screening Basics: Validate signs of excellence Has this person been a top performer before? Look for patterns of achievement, not just participation in impressive-sounding projects. 7/ Check relevant accomplishment patterns Have they delivered similar outcomes? Focus on what they've actually accomplished that maps to your role's success criteria. 8/ Assess environment relevance Have they done it in relevant contexts? Company stage, industry complexity, team size, growth phase - environment shapes everything. 9/ Train for interview efficiency Ask permission to interrupt and explain why you're asking specific questions. Acknowledge it might feel robotic, but surgical precision beats small talk when candidates aren't yet sold. Fix your top-of-funnel alignment and screening, and you stop wasting weeks on candidates who were never going to work out. P.S. At Mokka, we've automated this entire top-of-funnel process - from role mission clarity to evidence-based candidate ranking. Because when you're scaling fast, the system needs to be stronger than individual execution.

𝗔𝗜 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻𝘀: 𝗧𝗵𝗲 𝗕𝗿𝗶𝗱𝗴𝗲 𝗳𝗿𝗼𝗺 𝗣𝗼𝗖 → 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗣𝗼𝗖𝘀 𝘄𝗼𝘄. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗽𝗮𝘆𝘀. The gap from PoC → production is real. Your demo dazzles in a controlled pre-production setup, but by day two in the real world, cracks appear. The root cause? Many builds skip a continuous, iterative evaluation framework anchored to rigorous acceptance criteria. Acceptance criteria differ from success criteria—and grasping this is crucial for reliable scaling. 𝗤𝘂𝗶𝗰𝗸 𝗲𝘅𝗮𝗺𝗽𝗹𝗲: Almond grading with 25 defect classes. We spent ~6 months building a golden set (~2,000 images per class) and only green‑lit when two bars were hit: 90% F1 on a blind holdout (success) and the production line met the business bar — low false rejects (≤2%), line‑rate throughput, and a unit‑cost ceiling (acceptance). 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗰𝗿𝗶𝘁𝗲𝗿𝗶𝗮 𝘃𝘀. 𝗔𝗰𝗰𝗲𝗽𝘁𝗮𝗻𝗰𝗲 𝗰𝗿𝗶𝘁𝗲𝗿𝗶𝗮 (𝗻𝗼𝘁 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲) • 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗰𝗿𝗶𝘁𝗲𝗿𝗶𝗮 (𝗯𝘂𝗶𝗹𝗱‑𝘁𝗶𝗺𝗲): fast signals for iteration—task win‑rate, RAG groundedness, tool‑call accuracy, unit tests. • 𝗔𝗰𝗰𝗲𝗽𝘁𝗮𝗻𝗰𝗲 𝗰𝗿𝗶𝘁𝗲𝗿𝗶𝗮 (𝗴𝗼‑𝗹𝗶𝘃𝗲 & 𝘀𝗰𝗮𝗹𝗲): the business bar—success rate, time‑to‑task, cost per task, risk/safety, and operability (observability, canary, rollback). If this isn’t met offline, don’t ship. If it slips in production, auto‑rollback. 𝗔𝗰𝗰𝗲𝗽𝘁𝗮𝗻𝗰𝗲 𝗳𝗼𝗿𝗺𝘂𝗹𝗮 (𝗲𝘅𝗮𝗺𝗽𝗹𝗲) Ship only if Success rate ≥ X%, Time‑to‑task ≤ Y minutes, Cost per task ≤ $Z. 𝗧𝗵𝗿𝗲𝗲 𝗺𝗼𝘃𝗲𝘀 𝘁𝗵𝗮𝘁 𝘄𝗼𝗿𝗸 𝗳𝗼𝗿 𝗶𝘁𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗲𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻𝘀:  𝗚𝗼𝗹𝗱𝗲𝗻 𝘀𝗲𝘁 + 𝘀𝗰𝗼𝗿𝗶𝗻𝗴 𝗴𝘂𝗶𝗱𝗲. Curate 50–100 real tasks. Define a simple scoring guide (what “good” looks like), align reviewers, and version the dataset and the guide. Keep a blind holdout and track how often reviewers agree. Gate with thresholds (e.g., ≥80% first‑pass resolution in <2 minutes, ≤2% escalations). 𝗟𝗟𝗠‑𝗮𝘀‑𝗷𝘂𝗱𝗴𝗲—𝘄𝗶𝘁𝗵 𝘀𝗮𝗳𝗲𝗴𝘂𝗮𝗿𝗱𝘀. Use pairwise comparisons, 2+ judge models, and human spot‑checks. Monitor judge disagreement/drift in CI and block merges on preference win‑rate drops. Log evaluation cost and latency so tests don’t balloon spend. 𝗦𝗰𝗼𝗿𝗲 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝘁𝗲𝘅𝘁. • Agents: goal completion, steps‑to‑success, tool‑call success and preconditions, safe‑action %, rollback/undo rate. 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲: 𝗔 𝘀𝘁𝗲𝗽 𝗺𝗼𝘀𝘁𝗹𝘆 𝗺𝗶𝘀𝘀𝗲𝗱 Name an Evaluation Owner with approve authority. Run weekly evaluations and publish the scoreboard. Tie every score to success rate, time‑to‑task, and cost per task. 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀 • Make evaluations your ship/no‑ship gate tied to KPIs. • Start with a 100‑task golden set and a guardrailed LLM‑judge in CI. • Always score execution and keep a visible, weekly scoreboard. Treat evaluation like a product—owned, versioned, and tied to outcomes—and you’ll ship AI that sticks and scales. #AgenticAI, #AIEvaluation, #EnterpriseAI, #RAG, #MLOps

Nailed the deadline, Stayed under budget And still got called a Failure. Imagine You’ve worked so hard on a project. → Your team stayed up late → You handled every problem → And somehow, you finished everything → On time and under budget. You feel proud and can’t wait to show it to the client. But then, the client looks at it. → They don’t smile. → They don’t look excited. → Instead, they ask, "Why doesn’t this feel right?" Your heart sinks. → The deadlines were met. → The costs were managed. → You followed the plan perfectly. But the client’s disappointment is crystal clear. You feel the weight of failure pressing down, even though you did everything right. This is the moment when you realize: → Success isn’t just about delivering what’s promised. → It’s about delivering what matters. What went wrong? → The goals weren’t clearly defined. → Stakeholders weren’t aligned. → Everyone worked hard, but without a shared vision → Lack of alignment in communication → gap in project goals & priorities → Poor communication created confusion about project goals & priorities. → Inconsistent touchpoints led to misaligned expectations and frustration. This is why defining success isn’t just a step: it’s the foundation. Before the next project, imagine how things could feel different: → If you and the client agreed on measurable goals upfront. → If your team knew exactly what the client valued most. → If adjustments were made along the way to stay aligned. That’s the power of clarity. It keeps you from reliving the fear of sitting in that room, watching a proud moment turn into disappointment. So ask yourself: Are you defining success in a way that truly delivers value? Or are you leaving it to chance?

Why are startup success metrics designed for the 1% who raise from VCs? "My goal isn't a billion-dollar exit. It's a sustainable business that supports my life,” a founder told me when we were discussing her vision for success for her business. The startup world has one definition of success: - Exponential user growth - Massive fundraising rounds - Growth at all costs - Unicorn valuation - Eventual IPO But what if you’re amongst the 99% who do not raise from VCs? What if your definition of success is different? Founders I work with are building multi-million dollar businesses. Yet, they tell me up front that they are not interested in these things. They want to create life-changing wealth. But they're doing it intentionally, on their terms, with metrics that matter to THEM. We rally around success metrics like: - Take-home per founder - Time for fun / family - Team wellbeing and satisfaction - Mission impact measurements - Founder joy and fulfillment These smart founders are not following someone else's definition of success. For my own business this year my defition of success is: same revenue or higher than last year while spending 1/4th the time on the business. This isn’t because I’m lazy lol I need the extra time to build my second business. We’re building businesses aligned with our personal values, goals, and definitions. ➡️ What non-traditional metrics do you use to measure success in your business?