Developing a Project Closure Checklist

𝗧𝗼𝗱𝗮𝘆, 𝗣𝗠𝗜 𝗿𝗲𝗹𝗲𝗮𝘀𝗲𝘀 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝗿𝗲𝘀𝘂𝗹𝘁𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗹𝗮𝗿𝗴𝗲𝘀𝘁 𝘀𝘁𝘂𝗱𝘆 𝘄𝗲’𝘃𝗲 𝗲𝘃𝗲𝗿 𝗰𝗼𝗻𝗱𝘂𝗰𝘁𝗲𝗱 - 𝗼𝗻 𝗮 𝘁𝗼𝗽𝗶𝗰 𝘁𝗵𝗮𝘁 𝗶𝘀 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝘁𝗼 𝗼𝘂𝗿 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻: 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗦𝘂𝗰𝗰𝗲𝘀𝘀. 📚 Read the report: https://lnkd.in/ekRmSj_h With this report, we are introducing a simple and scalable way to measure project success. A successful project is one that 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘀 𝘃𝗮𝗹𝘂𝗲 𝘄𝗼𝗿𝘁𝗵 𝘁𝗵𝗲 𝗲𝗳𝗳𝗼𝗿𝘁 𝗮𝗻𝗱 𝗲𝘅𝗽𝗲𝗻𝘀𝗲, as perceived by key stakeholders. This clearly represents a shift for our profession, where beyond execution excellence we also feel accountable for doing anything in our power to improve the impact of our work and the value it generates at large. The implications for project professionals can be summarized in a framework for delivering 𝗠𝗢𝗥𝗘 success: 📚𝗠anage Perceptions For a project to be considered successful, the key stakeholders - customers, executives, or others - must perceive that the project’s outcomes provide sufficient value relative to the perceived investment of resources. 📚𝗢wn Project Success beyond Project Management Success Project professionals need to take any opportunity to move beyond literal mandates and feel accountable for improving outcomes while minimizing waste. 📚𝗥elentlessly Reassess Project Parameters Project professionals need to recognize the reality of inevitable and ongoing change, and continuously, in collaboration with stakeholders, reassess the perception of value and adjust plans. 📚𝗘xpand Perspective All projects have impacts beyond just the scope of the project itself. Even if we do not control all parameters, we must consider the broader picture and how the project fits within the larger business, goals, or objectives of the enterprise, and ultimately, our world. I believe executives will be excited about this work. It highlights the value project professionals can bring to their organizations and clarifies the vital role they play in driving transformation, delivering business results, and positively impacting the world. The shift in mindset will encourage project professionals to consider the perceptions of all stakeholders- not just the c-suite, but also customers and communities. To deliver more successful projects, business leaders must create environments that empower project professionals. They need to involve them in defining - and continuously reassessing and challenging - project value. Leverage their expertise. Invest in their work. And hold them accountable for contributing to maximize the perception of project value at all phases of the project - beyond excellence in execution. 📚 Please read the report, reflect on its findings, and share it broadly. And comment! Project Management Institute #ProjectSuccess #PMI #Leadership #ProjectManagementToday

Over the last year, I’ve seen many people fall into the same trap: They launch an AI-powered agent (chatbot, assistant, support tool, etc.)… But only track surface-level KPIs — like response time or number of users. That’s not enough. To create AI systems that actually deliver value, we need 𝗵𝗼𝗹𝗶𝘀𝘁𝗶𝗰, 𝗵𝘂𝗺𝗮𝗻-𝗰𝗲𝗻𝘁𝗿𝗶𝗰 𝗺𝗲𝘁𝗿𝗶𝗰𝘀 that reflect: • User trust • Task success • Business impact • Experience quality    This infographic highlights 15 𝘦𝘴𝘴𝘦𝘯𝘵𝘪𝘢𝘭 dimensions to consider: ↳ 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆 — Are your AI answers actually useful and correct? ↳ 𝗧𝗮𝘀𝗸 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗶𝗼𝗻 𝗥𝗮𝘁𝗲 — Can the agent complete full workflows, not just answer trivia? ↳ 𝗟𝗮𝘁𝗲𝗻𝗰𝘆 — Response speed still matters, especially in production. ↳ 𝗨𝘀𝗲𝗿 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 — How often are users returning or interacting meaningfully? ↳ 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗥𝗮𝘁𝗲 — Did the user achieve their goal? This is your north star. ↳ 𝗘𝗿𝗿𝗼𝗿 𝗥𝗮𝘁𝗲 — Irrelevant or wrong responses? That’s friction. ↳ 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗗𝘂𝗿𝗮𝘁𝗶𝗼𝗻 — Longer isn’t always better — it depends on the goal. ↳ 𝗨𝘀𝗲𝗿 𝗥𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻 — Are users coming back 𝘢𝘧𝘵𝘦𝘳 the first experience? ↳ 𝗖𝗼𝘀𝘁 𝗽𝗲𝗿 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻 — Especially critical at scale. Budget-wise agents win. ↳ 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 𝗗𝗲𝗽𝘁𝗵 — Can the agent handle follow-ups and multi-turn dialogue? ↳ 𝗨𝘀𝗲𝗿 𝗦𝗮𝘁𝗶𝘀𝗳𝗮𝗰𝘁𝗶𝗼𝗻 𝗦𝗰𝗼𝗿𝗲 — Feedback from actual users is gold. ↳ 𝗖𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 — Can your AI 𝘳𝘦𝘮𝘦𝘮𝘣𝘦𝘳 𝘢𝘯𝘥 𝘳𝘦𝘧𝘦𝘳 to earlier inputs? ↳ 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆 — Can it handle volume 𝘸𝘪𝘵𝘩𝘰𝘶𝘵 degrading performance? ↳ 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 — This is key for RAG-based agents. ↳ 𝗔𝗱𝗮𝗽𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗦𝗰𝗼𝗿𝗲 — Is your AI learning and improving over time? If you're building or managing AI agents — bookmark this. Whether it's a support bot, GenAI assistant, or a multi-agent system — these are the metrics that will shape real-world success. 𝗗𝗶𝗱 𝗜 𝗺𝗶𝘀𝘀 𝗮𝗻𝘆 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗼𝗻𝗲𝘀 𝘆𝗼𝘂 𝘂𝘀𝗲 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀? Let’s make this list even stronger — drop your thoughts 👇

Every PM wants to measure the success of their product. But most struggle to do it correctly. As a product management hiring manager, leader, and coach, I've seen that many product managers struggle with defining the right success metrics They focus on generic metrics like acquisition, engagement,  retention These are insufficient. My recommendation is to ask concrete questions when thinking of metrics Here's a list of questions I ask: 𝗧𝗵𝗶𝗻𝗸 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝘂𝘀𝗲𝗿 𝗳𝗶𝗿𝘀𝘁 1. What is the user’s goal? 2. What human need do they want to fulfill? 3. What action signifies that their need is met? 4. Is that action enough to know user’s job is done? 5. How can I measure that action? 𝗧𝗵𝗶𝗻𝗸 𝗮𝗯𝗼𝘂𝘁 𝘂𝘀𝗮𝗴𝗲 𝗮𝗻𝗱 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻 1. How many users are using the product? 2. How many users should be using it? 3. Which users aren't using it but should be using it? 𝗧𝗵𝗶𝗻𝗸 𝗮𝗯𝗼𝘂𝘁 𝗵𝗼𝘄 𝗺𝘂𝗰𝗵 𝘂𝘀𝗲𝗿𝘀 𝗲𝗻𝗷𝗼𝘆 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 1. How many users like the product? 2. How much do they like it? 3. What action(s) show they “like” it? 4. How can I measure those actions 5. Do they like it enough to keep coming back? 6. If yes, how often should they come back? 𝗧𝗵𝗶𝗻𝗸 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝗼𝗳 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘁𝗵𝗲𝘆 𝗮𝗿𝗲 𝗴𝗲𝘁𝘁𝗶𝗻𝗴 𝘄𝗵𝗶𝗹𝗲 𝘂𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 1. Are users finding it hard to complete certain actions? 2. Are there things that users dislike? 3. Are there enough options for users to choose from? 4. Are there things that users want to do, but the product doesn’t allow them to? 5. Can we measure all the above? 𝗧𝗵𝗶𝗻𝗸 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝗼𝗳 𝗺𝗲𝘁𝗿𝗶𝗰𝘀 1. Can I cheat on any of the above metrics? 2. Do above metrics give the most accurate answer? 3. Are all metrics simple enough for everyone to understand? 𝗧𝗵𝗶𝗻𝗸 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗻𝗲𝘁 𝗶𝗺𝗽𝗮𝗰𝘁 𝗼𝗻 𝘁𝗵𝗲 𝗼𝘃𝗲𝗿𝗮𝗹𝗹 𝗽𝗿𝗼𝗱𝘂𝗰𝘁/𝗰𝗼𝗺𝗽𝗮𝗻𝘆 1. Are  above metrics a true representation of success? 2. Any other parts of user journey I should measure? 3. Will a positive impact on above metrics lead to a negative impact on other critical metrics? 4. Is the tradeoff acceptable? -- How easy or tough do you find creating success metrics? What is your process?

I’ve spoken to enough founders, designers, and devs to notice a pattern. They track hours like proof of value. 10 hours designing. 8 hours coding. 3 hours stuck on client calls. And they wonder why clients still push back. But clients don’t care about your hours. They care about outcomes. Not once will your client say, "Wow, this looks like 40 hours of work." But what they will say, "Does this do what we need it to do?" That’s what clicks for them. People don’t pay for effort. They pay for outcomes. They care about: • Did the landing page convert? • Did the site load fast? • Did the product work the way they imagined? That’s what gets judged. Not the late nights or "how long it took." And when expectations aren’t clear, that’s when resentment creeps in. One person’s "minor tweak" is another’s full rebuild. That’s why I always tell service providers: • Put it in the contract. • Make it measurable. • Define success upfront. Don’t leave room for assumption. And start defining success before the project starts. It protects your time. It protects your energy. And most importantly, it protects your client relationship. Let effort fuel the outcome - not define it. And if you want to make outcomes measurable in contracts, here's what I suggest 1) Set clear, quantifiable deliverables Don’t just say "design a landing page." Be specific instead: "Design a landing page with three sections, mobile responsive, integrated with XYZ form, delivered in Figma and HTML." 2) Define success metrics For example:  "The landing page must achieve a minimum conversion rate of 8% within 30 days of launch (measured via Google Analytics)." Or: "Website load time under 2 seconds on 4G, tested with PageSpeed Insights." You can measure these. 3) Use acceptance criteria List what needs to be true for the project to be considered complete. For e.g.,  "All buttons and forms function as intended; site passes accessibility checks; all content matches approved copy." 4) Be clear on revision limits and feedback cycles Such as,  "Includes two rounds of revisions. Further changes billed at $X/hour." Or "Client feedback must be provided within 3 business days to keep the timeline on track." 5) Tie payments to outcomes, not hours Break payments into milestones based on deliverables: "40% on design approval, 30% on development completion, 30% on final handover and live launch." And when you make outcomes measurable, you: • Eliminate ambiguity • Reduce scope creep • Build trust (and repeat business) So, before your next project, ask: Is your contract tracking hours, or is it defining results? Because in the end, clients remember outcomes - not overtime. --- ✍ Tell me below: Do you define "done" in your projects?

As a BA, the clarity of our user stories and acceptance criteria can make or break a project. Here are some real-life examples of common mistakes and how to avoid them: ✅ 𝐓𝐨𝐨 𝐁𝐫𝐨𝐚𝐝: A user story like "As a user, I want a dashboard so that I can see information" is too vague. Instead, try "As a marketing manager, I want to view real-time user engagement statistics on a dashboard to adjust campaigns quickly." ✅ 𝐓𝐞𝐜𝐡-𝐒𝐩𝐞𝐚𝐤: A user story stating "As a user, I need a SQL database to store customer data" might confuse non-technical stakeholders. Better: "As a customer service rep, I need a way to retrieve customer histories quickly to improve service times." ✅ 𝐅𝐞𝐚𝐭𝐮𝐫𝐞-𝐂𝐞𝐧𝐭𝐫𝐢𝐜: Writing "As a user, I want a four-step checkout process" focuses on system design rather than user needs. Flip it to: "As a shopper, I want a quick and easy checkout process so that I can complete my purchase in minutes." ✅ 𝐌𝐢𝐬𝐬𝐢𝐧𝐠 𝐀𝐜𝐜𝐞𝐩𝐭𝐚𝐧𝐜𝐞 𝐂𝐫𝐢𝐭𝐞𝐫𝐢𝐚: Don't just say, "The system should load fast." Specify, "The home page shall load within 3 seconds on 80% of occasions as measured by [specific tool]." ✅ 𝐒𝐭𝐚𝐭𝐢𝐜 𝐒𝐭𝐨𝐫𝐢𝐞𝐬: If initial feedback suggests users are confused by a feature, update the user story. Original: "As a user, I want tooltips on each dashboard element." Improved: "As a new user, I want clearly labeled tooltips on each dashboard element, appearing as I hover over them, to help understand the data presented." 🔄 𝐏𝐫𝐨 𝐓𝐢𝐩: Regularly revisit and revise your user stories and acceptance criteria based on ongoing feedback from all stakeholders. BA Helpline

How I write Acceptance Criteria (without them becoming vague or useless) One of the biggest causes of rework in delivery is acceptance criteria that are too vague. You’ll see AC like: → “Works as expected” → “User friendly” → “Loads quickly” → “Shows available times” The issue is simple: none of that is testable. So devs interpret it one way, testers interpret it another way, and sign-off turns into opinion. Here’s how I approach it 👇 1️⃣ Start with the user story AC are always linked to a story. If the story isn’t clear, the AC won’t be either. 2️⃣ Ask a small set of prompt questions (only use what’s relevant) → What does success look like? → What inputs does the user provide? → What rules/validations apply? → What can go wrong / no result scenarios? → What must be saved/retained/updated? 3️⃣ Write the AC in Given / When / Then → Given (setup) → When (action) → Then (observable outcome) The outcome? → Clear, testable AC the whole team can align on → Less guesswork in build + test → Cleaner sign-off If you found this useful, consider giving me a follow Matthew Thomas Holliday and reshare to your network ♻️ Want to build confidence in your BA career? Feeling stuck? Wanting extra guidance? Wanting to learn simple, repetable steps that will make you stand out?? That's exactly what our BA mentoring community helps you with (link in bio). #businessanalyst #acceptancecriteria

✅ #BAConceptsSimplified — Acceptance Criteria When I first heard the term Acceptance Criteria, it sounded like something only QA teams cared about. But as I started learning, I realized — it’s actually one of the most powerful tools for a Business Analyst to ensure clarity and alignment. 💡 💬 So, What Are Acceptance Criteria? They’re the conditions or requirements that must be met for a feature or user story to be accepted as complete by stakeholders. In simple words — Acceptance Criteria tell everyone, “This is how we’ll know the work is done right.” Example: 📝 User Story: “As a customer, I want to reset my password so that I can regain access to my account.” ✅ Acceptance Criteria: The user receives a password reset link via email. The link expires after 30 minutes. The new password must meet security standards. A confirmation message appears after successful reset. These criteria turn a simple story into something measurable and testable. 🎯 Why Acceptance Criteria Matter 1️⃣ Clarity: Removes ambiguity for developers, testers, and stakeholders. 2️⃣ Validation: Helps ensure every feature meets the user’s expectations. 3️⃣ Quality Assurance: Acts as a checklist for testing and review. 4️⃣ Alignment: Keeps everyone on the same page about “done.” 💡 My Takeaway as a Fresher Good acceptance criteria make a huge difference — they bridge the gap between intent and execution. It’s where the user’s needs, business goals, and system behavior all meet perfectly. As a BA, it’s not just about documenting what to build — it’s about defining what success looks like. 🌱 What’s one best practice you follow while writing acceptance criteria? I’d love to learn from your experience! 👇 #BAConceptsSimplified #BusinessAnalyst #AcceptanceCriteria #UserStories #BABasics #BusinessAnalysis #AgileBA #BACommunity #LearningInPublic #FreshersPerspective #ProductManagement #RequirementsEngineering #ProjectManagement #QualityAssurance

Want better sprints? Start with better metrics. Agile success isn’t about guessing it’s about tracking the right data. ✓ Sprint Velocity & Story Points Gauge your team’s delivery capacity and fine-tune sprint planning with historical data. ✓ Sprint Progress Visualization Visual cues like burndown charts help monitor scope creep and pacing in real time. ✓ Cycle Time vs. Lead Time Understand time efficiency Cycle Time reflects execution, Lead Time reveals delivery performance. ✓ Task Management Efficiency Too many WIP (Work in Progress) items? That’s a signal to reduce multitasking and improve focus. ✓ Team Happiness Index Morale impacts productivity. Regular pulse checks lead to better engagement and retention. ✓ Defect Density Track bugs early. Low defect density means higher product quality and team effectiveness. ✓ Sprint Goal Success Rate Did the team meet the sprint goal? This shows alignment between planning and execution. ✓ Release Frequency Frequent releases mean faster feedback loops and better adaptability to change. ✓ Technical Debt Tracking Identify patterns in rushed work or rework. Addressing this early saves future costs. ✓ Team Collaboration Health Better collaboration leads to shared ownership and faster problem-solving. Common Myths Agile doesn’t believe in metrics. → Agile isn't anti-data it’s anti-waste. Good metrics inform, not control. Velocity is the only metric that matters. → Velocity without quality or context can be misleading. Focus on outcomes, not just speed. Metrics are for managers, not teams. → The best teams track their own metrics to inspect, adapt, and grow. All metrics should be quantitative. Why does this matter? ✓ These KPIs help teams improve sprint over sprint. ✓ Scrum Masters use them to remove blockers and coach teams. ✓ Stakeholders gain visibility into team performance and product health. What’s the toughest KPI to measure in your team? #BusinessAnalyst #ProjectManager #AgileLeadership #ScrumMaster #AgileMetrics

For over two decades, I've been writing acceptance criteria and helping teams write them. But it was a particular insight that sent the quality of my user stories and my automation through the roof. Acceptance Criteria fall into one of two categories. Understanding which type you are writing, and which type you SHOULD write, is the key to writing acceptance criteria that really deliver. Acceptance Criteria fall into two categories: Business Rules and Journey Scenarios. Knowing which type to write is essential for effectiveness. The two types of acceptance criteria are: 📜 Business Rules: Business Rules focus on specific rules or logic, allowing for quick execution and integration. They offer a detailed way to verify individual aspects. 🗺️ Journey Scenarios describe end-to-end user journeys, involving multiple components. They take longer to write and execute but are vital for understanding the big picture. A balance between these two types is key. Business Rules should be 90% or more of your criteria, with Journey Scenarios filling the rest. Avoid the trap of solution-centric criteria, which can lead to misinterpreting business needs. By employing these two types strategically, you can ensure that your software meets its functional requirements and aligns with broader objectives. You can learn more about this and other ways to write more effective BDD scenarios in the free eBook: "The 7 Qualities Of Highly Effective BDD Scenarios (and How AI Can Help)". Let me know if you'd like to know more.

Everyone says “change is happening” But how do you know it’s actually working? Change initiatives are easy to start. Harder to measure. Without clear indicators, leaders guess if progress is real And guesswork rarely works Top change leaders track these metrics to stay ahead: 1/ Achievement → How close did we get to our change goals → Focus on learning first, then performance Example: % of project milestones met vs. planned 2/ Completion → How well did we execute on schedule, scope, and budget → Example: Tasks finished on time and within budget 3/ Acceptability → Stakeholder satisfaction with the process and solution → Example: Survey scores, qualitative feedback 4/ Engagement → How involved are teams and stakeholders in the change → Example: Attendance in workshops, participation in feedback sessions 5/ Adoption → Are people actually using new systems, behaviors, or processes → Example: % of employees actively using a new tool or workflow 6/ Sustainability → Are changes sticking over time or fading → Example: Reassess behaviors 3–6 months post-change 7/ Impact → The measurable difference on business outcomes → Example: Efficiency gains, revenue growth, or error reduction Stop hoping for progress. Start proving it. P.S. Which of these metrics do you track most closely in your change initiatives? -- Follow me, Daniel Lock, for practical tips for leading change, consulting & thought leadership