Understanding the Link Between Metrics and Project Success

"You can’t manage what you don’t measure." Yet, when it comes to change management, most leaders focus on what was implemented rather than what actually changed. Early in my career, I rolled out a company-wide process improvement initiative. On paper, everything looked great - we met deadlines, trained employees, and ticked every box. But six months later, nothing had actually changed. The old ways crept back, employees reverted to previous habits, and leadership questioned why results didn’t match expectations. The problem? We measured completion, not adoption. 𝗖𝗼𝗻𝗰𝗲𝗿𝗻: Many organizations struggle to gauge whether change efforts truly make an impact because they rely on surface-level indicators: → Completion rates instead of adoption rates → Project timelines instead of performance improvements → Implementation checklists instead of employee sentiment This approach creates a dangerous illusion of progress while real behaviors remain unchanged. 𝗖𝗮𝘂𝘀𝗲: Why does this happen? Because leaders focus on execution instead of outcomes. Common pitfalls include: → Lack of accountability – No one tracks whether new processes are being followed. → Insufficient feedback loops – Employees don’t have a voice in measuring what works. → Over-reliance on compliance – Just because something is mandatory doesn’t mean it’s effective. If we want real, measurable change, we need to rethink what success looks like. 𝗖𝗼𝘂𝗻𝘁𝗲𝗿𝗺𝗲𝗮𝘀𝘂𝗿𝗲: The solution? Focus on three key change management success metrics: → 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻 𝗥𝗮𝘁𝗲 – How many employees are actively using the new system or process? → 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗜𝗺𝗽𝗮𝗰𝘁 – How has efficiency, quality, or productivity changed? → 𝗨𝘀𝗲𝗿 𝗦𝗮𝘁𝗶𝘀𝗳𝗮𝗰𝘁𝗶𝗼𝗻 – Do employees feel the change has made their work easier or harder? By shifting from "Did we implement the change?" to "Is the change delivering results?", we turn short-term projects into long-term transformation. 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀: Organizations that measure change effectively see: → Higher engagement – Employees feel heard, leading to stronger buy-in. → Stronger accountability – Leaders track impact, not just completion. → Sustained improvement – Change becomes embedded in the culture, not just a temporary initiative. "Change isn’t a box to check—it’s a shift to sustain. Measure adoption, not just action, and you’ll see the impact last." How does your organization measure the success of change initiatives? If you’ve used adoption rate, performance impact, or user satisfaction, which one made the biggest difference for you? Wishing you a productive, insightful, and rewarding Tuesday! Chris Clevenger #ChangeManagement #Leadership #ContinuousImprovement #Innovation #Accountability

Your CFO wants to know the return on your software development budget? Here are 5 metrics that actually matter in the boardroom - and they're not story points. As a CTO, I've found these key metrics create a meaningful fitness function for your development organization: 1. Business Value per Feature: Don't just ship features - measure their impact. That new checkout process? Track how it changes conversion rates and order values. 2. Lead Time from Idea to Impact: Understand your value stream. Sometimes a 30-minute deployment is stuck behind weeks of stakeholder meetings. 3. Throughput and its composition: Monitor the balance between new features, maintenance, and bug fixes. When maintenance exceeds 25%, it's time to invest. 4. Quality Signals: Track customer experience, operational efficiency, and technical health. These are your early warning system. 5. Team Health: Happy teams deliver better results. Regular pulse checks predict delivery performance weeks before metrics show issues. But never compare teams through these metrics. Each team operates in a unique context with different challenges. Instead, help each team understand and improve their own trends. Metrics should drive improvement, not punishment. Use them as a compass, not a hammer. What metrics do you use to measure development success?

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

Measuring and showcasing the business impact of UX research can be challenging, but it’s crucial for demonstrating the value we bring. To make this more tangible, I’ve built a dashboard that tracks key metrics and insights to help communicate our contribution to the company’s success. Here’s how I’m breaking it down to show impact for the business: 1. Research impact: We categorize each research project by its level of impact: ➔ Low: Provides valuable insights but doesn’t lead to immediate action. ➔ Medium: Validates or refines existing ideas. ➔ High: Directly influences the product roadmap or business strategy. By tracking these metrics, we can demonstrate how many projects directly contribute to strategic decisions and influence the company’s goals. 2. Tied to business KPIs: We tag each research project with the business goals it aligns with, like CSAT, conversion rates, or task completion rates. This allows us to highlight how research contributes to improving key business metrics. By linking research findings to KPIs, we’re able to quantify the value we’re adding. 3. Project complexity and external costs: We categorize projects by complexity (simple, moderate, complex). This helps us see how often we’ve needed external resources because of a lack of internal capacity. Tracking this allows us to highlight the extra costs of outsourcing, helping make the case for expanding the internal research team to reduce expenses. 4. Denied Projects: We track the number of projects we’ve had to deny due to capacity constraints. This is crucial for showing unmet demand for research, which in turn shows the business the need for more resources. Denied projects highlight how much additional impact we could be making if the research team had more capacity. 5. National vs. International: By tagging whether research projects are national or international, we gain insights into where the company is focusing its efforts. This helps ensure that we’re aligning our research efforts with market priorities and identifying gaps where more international or cross-market research could drive business growth. By creating these dashboards, we’re able to quantify and visualize the impact UX research makes for the business, whether it’s driving decisions, contributing to KPIs, or highlighting the need for more capacity to meet growing demand. How are you showing the business value of UX research in your company?

Day 24: QA Metrics That Truly Matter in Projects: In every software project, Quality Assurance (QA) metrics serve as critical indicators, they help teams understand progress, identify risks, and continuously improve. But here’s the key insight: not every metric is valuable. We need to focus on the metrics that provide actionable insights those that help the team, stakeholders, and business make smarter decisions. 🎯 Why Do QA Metrics Matter? Effective metrics help teams: ✅ Spot Bottlenecks → Where are we stuck? Where do we slow down? ✅ Measure True Progress → Are we on track with testing efforts, or just busy? ✅ Contribute to Quality → While testing cannot “ensure” or guarantee quality, it plays a vital role by identifying issues early and improving feedback loops. ✅ Support Stakeholder Communication → Well-presented metrics keep everyone aligned, from developers to business leaders. Without meaningful metrics, teams risk flying blind, focusing on surface-level numbers or vanity statistics that don’t help the product or process. 📊 Essential QA Metrics That Matter Here’s what to monitor closely: 1️⃣ Test Coverage → % of code or requirements covered by tests. High coverage helps reduce the risk of missing defects. 2️⃣ Defect Density → Number of defects per unit (e.g., per 1,000 lines of code). It reflects code quality and testing thoroughness. 3️⃣ Defect Leakage → Number of defects discovered after release, which shows how effective pre-release testing really was. 4️⃣ Test Execution Rate → How many planned tests have been executed in a defined timeframe, tracking testing progress. 5️⃣ Defect Resolution Time → Average time the team takes to fix reported defects, highlighting team efficiency. 6️⃣ Test Case Effectiveness → % of executed test cases that actually catch defects, showing how well-designed the tests are. 7️⃣ Automation Coverage → % of tests executed through automation tools or scripts (not a testing type, but an execution method), increasing speed, repeatability, and consistency. 8️⃣ Requirements Coverage → % of project requirements with linked test cases, ensuring that critical business needs are being verified. 🛠 Best Practices for Using Metrics: Align With Project Goals → Choose metrics based on what the team or business needs to know. Review Trends, Not Just Snapshots → Patterns over time matter more than isolated numbers. Be Honest About What Metrics Can (and Can’t) Do → Remember, metrics and testing contribute to quality — they cannot magically ensure it. Communicate Clearly → Use visual reports, dashboards, or summaries that stakeholders (technical and non-technical) can understand and act on. ✅ Final Thought: QA metrics, when chosen and used thoughtfully, help teams improve continuously, deliver stronger products, and maintain trust with stakeholders. Focus on the few that matter — not the many that look impressive but tell you nothing.

I used to measure my success as a project manager by hitting deadlines If the project finished on time, I called it a win. Hit the scope, check. Stayed on budget, check. Delivered by the date, double check. And done. But then rework creeped in. Customers weren't totally happy with the deliverable. Or the new tool that was supposed to change the game went unused. I realized, projects can be on time and STILL fail. Because success shouldn't be measured on delivery alone. Value is a major part. Here's what I changed to measure success in my projects: 👉 Ask "so what?" after every milestone Not all milestones are created equal. Did your deliverable actually move the business forward? Did it continue to help solve the problem you set out to fix? If not, then it wasn't success. 👉 Tie metrics to impact over activity This is why goals should be outlined early in a project and tied to something measurable. Task completion is not a good indicator of success. Start tracking outcomes like efficiency gained, revenue generated, or customer experience improved. Find ways to gamify your impact so that your teams are motivated to do the work better (and faster). 👉 Make project reflection a constant habit Lessons learned are done at the end of the project. Many don't even do them. If you're doing them once or not at all, you're missing out on the most valuable information. What's working? What's not? What's actually driving value/change for the organization? By consistently evaluating, you can double-down on what's driving progress and cut what isn't. Projects that are delivered on time are good. But those that make a difference, whether they're delivered on time or not, are the ones that truly have value. 🤙

𝗪𝗵𝗮𝘁 𝗱𝗼 𝘆𝗼𝘂 𝘁𝗿𝗮𝗰𝗸 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗢𝗞𝗥𝘀? 𝗖𝗵𝗮𝗻𝗰𝗲𝘀 𝗮𝗿𝗲, 𝗺𝗼𝘀𝘁 𝗼𝗳 𝗶𝘁 𝗱𝗼𝗲𝘀𝗻'𝘁 𝗺𝗮𝘁𝘁𝗲𝗿. Most teams think: More metrics = more ways to show progress. More dashboards = more "data-driven" decisions. More KRs = higher chance of hitting something. They keep adding more because it feels safer. Teams confuse outputs with outcomes. We're tracking so many things, optimizing so many metrics, running so many experiments... when in reality we're missing the main point. We're optimizing for 𝗰𝗲𝗿𝘁𝗮𝗶𝗻𝘁𝘆 𝗼𝗳 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆 instead of 𝗽𝗿𝗼𝗯𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗼𝗳 𝗶𝗺𝗽𝗮𝗰𝘁. "We spent six weeks tagging every onboarding project in Jira. Our OKR slide was immaculate…go-live times? Unchanged." Sound familiar? You end up with 12 dashboards showing green arrows while your core business metric stays flat. You were measuring everything except what actually mattered. Take this real example: Instead of "Outbound experiments live and buzzing," one company tracked "Outbound-sourced pipeline ≥ $20k/week with ≥60% conversion." Same team. Same effort. Completely different focus. Another company switched from tracking "knowledge base migration completed" to "% of ticket replies that include KB links from 22% → 60%." Result? Resolution time dropped from 26 hours to 6 hours. Reality: One well-chosen metric explains 80% of your success. Most teams lock in their Key Results before they even understand what drives the outcome. They're solving for what they can measure, not what they should measure. Your test: Can you hit your Key Result without changing how your business actually operates? If yes, you're tracking theater, not transformation. I've built the complete diagnostic framework, including the exact audit questions that reveal if your OKRs will actually drive results, in my latest post >> https://lnkd.in/eVM3NVZz For the love of the game 🏴☠️ ⚡️

🎯 Myth #9: Project Success = On Time, On Budget (From the series: Project Management Myths That Need to Die) Let’s talk about one of the most dangerous lies in project management: 🗣️ If it’s on time and on budget—it’s a success! Sounds logical, right? But here’s the brutal truth: 📉 A project can hit every milestone and stay within budget— and still fail miserably in delivering business value. Think about it… ✅ You delivered the system—but no one adopted it. ✅ You finished the product—but it didn’t solve the customer’s problem. ✅ You built the solution—but it’s already obsolete. That’s not success. That’s a well-executed waste of resources. 🚫 The triple constraint (time, cost, scope) is a delivery metric. It is not a value metric. It tells you how efficient the process was—not how effective the outcome is. Here’s what modern project success actually looks like: 💡 Value delivered—not just work completed. 💡 Stakeholder satisfaction—not just box-checking. 💡 Strategic alignment—not just task execution. 💡 Long-term adoption—not short-term delivery. 💡 Outcomes over outputs. Impact over activity. In my 40+ years in the field, I’ve seen projects “celebrated” at go-live… only to quietly be retired six months later because they never created meaningful impact. 🧠 Myth to Kill: If we delivered on time and budget, we succeeded. ✅ New Truth: If we delivered measurable value and impact, we succeeded. 🔍 Food for Thought: What’s your definition of success? How does your organization measure the value of a project—beyond the schedule? Let’s redefine the scoreboard. 📣 Share below: What’s one project you’ve seen that met the plan—but missed the point? #ProjectLeadership #ProjectSuccess #BeyondTheTripleConstraint #ValueDrivenPM #Drtonyprensa767 #StrategicExecution #PMOMetrics #ProjectManagement #FoodForThoughtPM

Ever got blank stares from your stakeholders when presenting your model's MAPE? Choosing relevant model metrics is not always straightforward. While MSE, precision, and F1 score are crucial, they often don't resonate with non-technical stakeholders focused on business metrics. They sometimes lack context and fail to showcase the tangible impact on the business. Opt for metrics that translate to the stakeholders' language. For instance, explain, “We can predict product costs within +/- $5, 90% of the time. This enables precise budgeting with a $X buffer.” This simplifies the model's performance, making it relevant and understandable for non-technical audiences. It also prevents unnecessary model refinement when further error reduction isn't needed. Before optimizing your models, engage with stakeholders to understand their priorities, convey your model's real-world utility, and align your efforts. This fosters impactful, successful data science projects. Which metrics have you found effective in linking data science with business outcomes?