Developing KPIs For Projects

Here are some realistic KPIs that project managers can actually track : 1. Schedule Management 🔹 Average Delay Per Milestone – Instead of just tracking whether a project is on time or not, measure how many days/weeks each milestone is getting delayed. 🔹 Number of Change Requests Affecting the Schedule – Count how many changes impacted the original timeline. If the number is high, the planning phase needs improvement. 🔹 Planned vs. Actual Work Hours – Compare how many hours were planned per task vs. actual hours logged. 2. Cost Management 🔹 Budget Creep Per Phase – Instead of just tracking overall budget variance, break it down per phase to catch overruns early. 🔹 Cost to Complete Remaining Work – Forecast how much more is needed to finish the project, based on real-time spending trends. 🔹 % of Work Completed vs. % of Budget Spent – If 50% of the budget is spent but only 30% of work is completed, there's a financial risk. 3. Quality & Delivery 🔹 Number of Rework Cycles – How many times did a deliverable go back for corrections? High numbers indicate poor initial quality. 🔹 Number of Late Defect Reports – If defects are found late in the project (e.g., during UAT instead of development), it increases risk. 🔹 First Pass Acceptance Rate – Measures how often stakeholders approve deliverables on the first submission. 4. Resource & Team Management 🔹 Average Workload per Team Member – Tracks who is overloaded vs. underloaded to ensure fair distribution. 🔹 Unplanned Leaves Per Month – A rise in unplanned leaves might indicate burnout or dissatisfaction. 🔹 Number of Internal Conflicts Logged – Measures how often team members escalate conflicts affecting productivity. 5. Risk & Issue Management 🔹 % of Risks That Turned into Actual Issues – Helps evaluate how well risks are being identified and mitigated. 🔹 Resolution Time for High-Priority Issues – Tracks how quickly critical issues get fixed. 🔹 Escalation Rate to Senior Management – If too many issues are getting escalated, it means the PM or team lacks decision-making authority. 6. Stakeholder & Client Satisfaction 🔹 Number of Unanswered Client Queries – If clients are waiting too long for responses, it could lead to dissatisfaction. 🔹 Client Revisions Per Deliverable – High revision cycles mean expectations were not aligned from the start. 🔹 Frequency of Executive Status Updates – If stakeholders are always asking for updates, the communication process might be weak. 7. Agile Scrum-Specific KPIs 🔹 Story Points Completed vs. Committed – If a team commits to 50 points per sprint but completes only 30, they are overestimating capacity. 🔹 Sprint Goal Success Rate – Tracks how many sprints successfully met their goal without major spillovers. 🔹 Number of Bugs Found in Production – Helps measure the effectiveness of testing. PS: Forget CPI and SPI - I just check time, budget, and happiness. Simple and effective! 😊

If you're building a data career, mastering the art of measurement planning can be one of the most effective ways to differentiate yourself from your peers. Companies need people who are thinking about this every time they launch a new initiative. If you can develop strong skills here, it can be your ticket to getting involved earlier on, in more projects, and to becoming seen as a true strategic partner in your organization. Here's what you should focus on... 1. Think Business First -> Resist the urge to dive straight into the data. -> Understand how critical this project is to the business. -> Ask what the key goals for the initiative are. -> What are the most important questions you'll answer? 2. Know Your Audience -> Who is driving the project? Is this the primary audience? -> What are the goals and incentives of key stakeholders? -> What data can you provide that will help them? -> What types of info may inspire them to take action? 3. Define the Key Performance Indicators (KPIs) -> For the goals identified, translate them to metrics -> Prioritize metrics based on importance to stakeholders -> Go a layer deeper, and think about KPI driving levers -> How do you picture optimizing the businesses KPIs? 4. Identify the Data Sources You'll Need -> Where will you get each data point you need? -> Who owns or manages each existing data source? -> Are the data sources available real-time? -> Are there gaps in existing data? How do you fill them? -> How can you automate or streamline reporting? If you can follow this framework, you should be able to break down any project and build a measurement plan that will help your organization identify goals, understand outcomes, and optimize performance to drive the business to new heights. We've got a free guide that goes deeper on this, called 'How to Build a Measurement' plan. CHECK IT OUT: --> https://bit.ly/3eaXGmq @ Data Pros - what else would you add here? #data #analytics #businessintelligence #measurement #planningforsuccess

Defining business-relevant KPIs for your dashboard can be a tricky task. Here is an example I encountered in my early career: 🎯 We were tasked with building a status dashboard for the warehouse management of a large e-commerce company. Together with the stakeholders, we identified the backlog in days as an important KPI that helps them decide on their capacity planning. The backlog should show a relationship between the unprocessed order pool and the next day's average daily processing capacity. We were happy to find an outbound backlog metric ready to be used in our BI system. After a quick review over several days, it looked like we had just found what we needed, so we included the metric in our dashboard. 🚨 Shortly after, our stakeholders complained that the numbers were extremely off compared to the business reality. We soon figured out that while the open order pool items were correct, the assumed average capacity was not. The BI system only contained the actual processed volumes instead of the planned future capacities. Due to the volatile nature of e-commerce, this definition difference of past vs. future values could lead to a completely opposite representation of the current backlog. With one definition, we showed a dramatic backlog of over 5 days, while the correct one would have been a healthy 0.5 days. 🔧 We were able to fix the metric by implementing a process to upload the planned capacities. 𝗟𝗲𝘀𝘀𝗼𝗻𝘀 𝗹𝗲𝗮𝗿𝗻𝗲𝗱: 1. Always check with the stakeholders to understand how they interpret the KPI.     2. Never assume that the number looks good. Check the definition, and if you are unsure, build your own metrics.     3. If you must choose between different definitions, choose the ones that best align with the stakeholder's decision. What challenges did you encounter when defining KPIs? Share your experience in the comments! ---------------- ♻️ 𝗦𝗵𝗮𝗿𝗲 if you find this post useful ➕ 𝗙𝗼𝗹𝗹𝗼𝘄 for more daily insights on how to grow your data analyst career #dataanalytics #datascience #kpis #stakeholdermanagement #dashboards

Curious about how top SaaS companies consistently hit their revenue targets? The answer lies in driver-based budgeting. 1. Identify Key Drivers First, find the measures that directly impact your ARR. These might include: ➡️Customer Acquisition Cost (CAC) ➡️Customer Lifetime Value (CLTV) ➡️Churn Rate ➡️Average Revenue Per User (ARPU) ➡️Sales Conversion Rates 2. Set Realistic Targets Set achievable goals for each driver: - New ARR: Lower CAC by optimizing marketing spend and improving lead quality. Boost sales conversion rates with better training and tools. - Expansion ARR: Increase CLTV by offering premium features and upselling. - Contraction ARR: Reduce contraction by addressing customer pain points. - Churn ARR: Lower churn by improving customer support and satisfaction. 3. Build a Driver-Based Model Create a budgeting model that integrates these drivers. Use different scenarios to see how changes in each driver impact your ARR. Validate and adjust your model with historical data. 4. Monitor, Adjust, and Align Track the performance of each driver against your targets. Use real-time data to spot trends and make adjustments. Ensure your teams are aligned with the budget and have clear KPIs tied to these drivers.

𝗛𝗼𝘄 𝗱𝗼𝗲𝘀 𝘆𝗼𝘂𝗿 𝗳𝗮𝗰𝘁𝗼𝗿𝘆 (𝗼𝗿 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀) 𝗺𝗲𝗮𝘀𝘂𝗿𝗲 𝗘𝗔’𝘀 𝗶𝗺𝗽𝗮𝗰𝘁? Great discussions this week on posts measuring Enterprise Architecture (EA) success! Two insightful comments on posts caught my attention and are worth expanding on: Mark Gale brought up important nuances: 🔹 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐚𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐢𝐨𝐧 (KPI #1) isn't often considered but can be powerful. Measuring the "leadership cycle from strategy to execution" can be simplified as tracking the time from when an idea is first proposed to its actual Go-Live day. 🔹 𝐂𝐨𝐬𝐭 𝐫𝐞𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐬𝐭𝐚𝐧𝐝𝐚𝐫𝐝𝐢𝐳𝐚𝐭𝐢𝐨𝐧 (KPI #2) can face significant business resistance when rationalizing applications, whereas infrastructure and vendor consolidation might be simpler to execute internally. 🔹 𝐀𝐥𝐢𝐠𝐧𝐦𝐞𝐧𝐭 𝐰𝐢𝐭𝐡 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐲 (KPI #3) is the ultimate EA goal but challenging to quantify. Clear, tangible measurement approaches remain elusive, ongoing challenge for all architects. Aligning on and baselining key business value metrics are first steps. Taskin Kilincat offered a practical, stakeholder-driven perspective from a manufacturing lens: 🔹 How does your factory specifically measure EA’s financial impact? 🔹 Do your EA KPIs align clearly with what resonates most with your shareholders? Taskin's comment underscores a key point: Effective KPIs must be relevant to your stakeholders—whether shareholders or operational teams. Here’s my weekend reflection for you: 🔸 Are your EA KPIs stakeholder-aligned? 🔸 How do you practically measure EA impact, especially in complex environments? --- ➕ Follow Kevin Donovan 🔔    👍 Like | ♻️ Repost | 💬 Comment 🚀 Join 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐬’ 𝐇𝐮𝐛 https://lnkd.in/dgmQqfu2

I've spent over 4,000 hours in stakeholder requirement-gathering meetings! Save hours of your life by asking these questions: 1. What do they plan to use the data for? 1. What initiative are they working on? 2. How will this initiative impact the business? 3. Is this for reporting or optimizing existing workflows? Understanding the purpose of the data helps you define its impact. 2. How do they plan to use the data? Will they access it via SQL, BI tools, APIs, or another method? 1. Do they have a workflow to pull data from your dataset? 2. Do they just do a `SELECT *` from your dataset? 3. Do they perform further computations on your dataset? This determines the schema, partitions, and data accessibility needs. 3. Is this data already present in another report/UI? 1. Is this data already available in another location? 2. Do they have parts of this data (e.g., a few required columns) elsewhere? Ensuring you're not recreating work saves time and avoids redundancy. 4. How frequently do they need this data? 1. How frequently does the data actually need to be refreshed? 2. Can it be monthly, weekly, daily, or hourly? 3. Is the upstream data changing fast enough to justify the required latency? Understanding frequency helps you determine the pipeline schedule. 5. What are the key metrics they monitor in this dataset? 1. Define variance checks for these metrics. 2. Do these metrics need to be 100% accurate (e.g., revenue) or directionally correct (e.g., impressions)? 3. How do these metrics tie into company-level KPIs? Memorize average values for these metrics; they’re invaluable during debugging and discussions. 6. What will each row in the dataset represent? 1. What should each row represent in the dataset? 2. Ensure one consistent grain per dataset, as applicable. 7. How much historical data will they need? 1. Does the stakeholder need data for the last few years? 2. Is the historical data available somewhere? Ask these questions upfront, and you'll save countless hours while delivering exactly what stakeholders need. - Like this post? Let me know your thoughts in the comments, and follow me for more actionable insights on data engineering and system design. #data #dataengineering #datastakeholder

📊 KPIs for Planning Engineers — How Do You Measure Performance? Planning isn’t just about creating schedules — it’s about controlling time, cost, and progress. To evaluate performance properly, every Planning Engineer should track Key Performance Indicators (KPIs). 🔹 1. Schedule Performance Index (SPI) 📌 Measures schedule efficiency ✔ SPI = 1 → On schedule ✔ SPI < 1 → Delay ✔ SPI > 1 → Ahead 🔹 2. Schedule Variance (SV) 📌 Shows delay or ahead status in time/value ✔ Negative → Delay ✔ Positive → Ahead 🔹 3. Cost Performance Index (CPI) 📌 Measures cost efficiency ✔ CPI < 1 → Over budget ✔ CPI > 1 → Under budget 🔹 4. Critical Path Stability 📌 Tracks how often the critical path changes ✔ Frequent changes = unstable planning ✔ Stable path = better control 🔹 5. Baseline vs Actual Variance 📌 Measures deviation from plan ✔ Planned vs Actual dates ✔ Delay in key milestones 🔹 6. Look-Ahead Reliability 📌 Measures short-term planning accuracy ✔ % of planned tasks completed in 2–4 week plan ✔ Helps site coordination 🔹 7. Schedule Quality Index 📌 Measures schedule health ✔ Logic completeness ✔ No open ends ✔ Limited constraints 👉 Often checked inside Primavera P6 🔹 8. Resource Utilization 📌 Measures efficiency of manpower & equipment ✔ Planned vs actual usage ✔ Over/under allocation 🔹 9. Progress Accuracy 📌 Measures reliability of updates ✔ Site vs reported progress match ✔ Reduces false reporting 🔹 10. Delay Response Time 📌 Measures how quickly planner reacts ✔ Time taken to identify and respond to delays ✔ Faster response = better control 🔍 Key Insight 📌 “A planner’s value is not in making schedules — it’s in controlling performance.” 🔥 Pro Tip 👉 Don’t track too many KPIs 👉 Focus on 4–5 strong indicators that actually drive decisions #PlanningEngineer #PrimaveraP6 #ProjectControls #KPI #Construction #Scheduling #ProjectManagement

𝗞𝗥𝗔 & 𝗞𝗣𝗜 𝗳𝗼𝗿 𝗦𝘂𝗰𝗰𝗲𝘀𝘀𝗳𝘂𝗹 𝗡𝗲𝘄 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 (𝗡𝗣𝗜) Launching a new product isn’t just about getting it out on time—it’s about making sure every step is controlled, validated, and sustainable. Here’s a structured framework that connects Key Result Areas (KRA) with Key Performance Indicators (KPI) to drive excellence in NPI: ✅ Launch Readiness – SOP on time, tooling readiness, process capability ✅ Manufacturing & Process Validation – FPY ≥95%, rework ≤1%, takt time adherence ✅ Supplier Readiness – On-time PPAPs, PPM ≤500, 100% APQP completion ✅ Quality & Compliance – Customer audit ≥90%, ≤2 complaints/1000 units, rejection ≤1.5% ✅ Project Execution & Control – Gate reviews ≥95%, milestone slippage ≤5% ✅ Cost Control – Within 100% of budget, ≤5% deviation due to late changes ✅ Cross-Functional Team Performance – ≥98% closure of actions, ≥95% CFT effectiveness ✅ Training & Documentation – 100% operator training & work instruction readiness 🔑 The takeaway: A disciplined NPI process ensures products hit the market on time, at the right cost, and with zero compromise on quality. 💡 Which KPI do you find most challenging to achieve in your NPI journey? Happy Learning 😊 -------- 🔔 Join our 𝙌𝙐𝘼𝙇𝙂𝙍𝘼𝙈 community for more Insightful information - Link in the comment section If you like this content & if it was useful for you, 🟢 Save it in your archive 🟡 Share it with your connections 🔴 Comment it and let us know your thoughts Follow me for more Balaji L R

Your project is not the goal. 𝗜𝘁 𝗶𝘀 𝗮 𝘁𝗼𝗼𝗹 𝘁𝗼 𝗳𝗶𝘅 𝗮 𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗽𝗼𝗹𝗶𝗰𝘆 𝗴𝗮𝗽. If you cannot prove exactly which gap you fix, evaluators don't see an investment. They see a hobby. The #1 reason for low Impact scores is 𝗰𝗼𝗻𝗳𝘂𝘀𝗶𝗻𝗴 𝗢𝘂𝘁𝗽𝘂𝘁𝘀 𝘄𝗶𝘁𝗵 𝗢𝘂𝘁𝗰𝗼𝗺𝗲𝘀. OLD THINKING ❌ 𝗧𝗵𝗲 𝗢𝘂𝘁𝗽𝘂𝘁 𝗧𝗿𝗮𝗽 (What 90% people write in theri KPI table): • 50 teachers trained. • 1 platform launched. Evaluator reaction: "So what? 𝗬𝗼𝘂 𝗷𝘂𝘀𝘁 𝗽𝗿𝗼𝘃𝗲𝗱 𝘆𝗼𝘂 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗯𝘂𝘀𝘆." NEW THINKING ✅ The Outcome Shift (𝗪𝗵𝗮𝘁 𝗲𝘃𝗮𝗹𝘂𝗮𝘁𝗼𝗿𝘀 𝗻𝗲𝗲𝗱 𝘁𝗼 𝗵𝗲𝗮𝗿): • ≥ 20 % increase in novice teachers’ digital-teaching confidence after pilot (supporting Digital Education Action Plan). • ≥ 25 % improvement in mentors’ ability to use AI-supported mentoring dashboards (serving DEAP Obj 1) • ≥ 30 % reduction in perceived professional isolation among rural teachers (E+ Horizontal priority - Inclusivity) • 2 Ministries adopt the framework (serving Council Resolution 2022). Evaluator reaction: "𝗧𝗵𝗶𝘀 𝘀𝗼𝗹𝘃𝗲𝘀 𝗮𝗻 𝗘𝗨 𝗽𝗿𝗼𝗯𝗹𝗲𝗺." Please take a look at the matrix below. Most proposals stop at the middle column. 𝗪𝗶𝗻𝗻𝗶𝗻𝗴 𝗽𝗿𝗼𝗽𝗼𝘀𝗮𝗹𝘀 𝗮𝗱𝗱 𝗧𝗪𝗢 𝗰𝗼𝗹𝘂𝗺𝗻𝘀 𝗼𝗻 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁. The Rule: If you can't name the specific policy document your KPI serves, you don't have a result. You have a to-do list. -- PS: My name is Igor Razbornik, and I translate policies into actionable steps in my training on proposal writing. 600 people in the last two years went through 4-days in-person training to achieve 𝟯𝟬% 𝗯𝗲𝘁𝘁𝗲𝗿 𝘀𝘂𝗰𝗰𝗲𝘀𝘀 𝗿𝗮𝘁𝗲 in 30% less time

Most projects fail for the same reason. Leaders track outputs, but ignore the signals that show if the project is healthy. The truth is, you cannot manage what you do not measure. Here are 15 KPIs that separate successful project managers from the rest: → Project Timeline Adherence: % of tasks completed on time. → Budget Variance: difference between planned vs. actual spend. → Resource Utilisation: how effectively resources are used. → Task Completion Rate: % of tasks finished compared to total. → Project Velocity: speed of task completion over time. → Customer Satisfaction: client feedback and survey results. → Risk Management Effectiveness: how well risks are identified and mitigated. → Quality of Deliverables: accuracy and alignment with standards. → Stakeholder Engagement: level of involvement and communication. → Change Request Rate: frequency of changes during execution. → Team Morale: overall satisfaction of the project team. → Issue Resolution Time: how fast blockers are removed. → Scope Creep: changes compared to the original plan. → Return on Investment (ROI): financial returns vs. project cost. → Communication Effectiveness: clarity and efficiency within the team. Strong leaders do not wait for the project to collapse before they look at the data. They watch these metrics closely, fix issues early, and deliver results with confidence.