Stakeholder-Informed KPI Development

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

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

Many stakeholders think of a KPI in their mind 💭 and hand it over to analysts to calculate — without clearly defining: 𝗖𝗮𝗻 𝘆𝗼𝘂 𝗽𝘂𝗹𝗹 𝘁𝗵𝗶𝘀 𝗞𝗣𝗜 𝗳𝗿𝗼𝗺 𝗵𝗶𝘀𝘁𝗼𝗿𝗶𝗰 𝗱𝗮𝘁𝗮? Sounds simple — but here’s where things go wrong… ---> What it actually means at the transaction level ---> What filters or exclusions apply ---> What the base timeline is ---> Whether the data even exists in the current system 👉 And what happens next? A new analyst, often struggling with i𝗺𝗽𝗼𝘀𝘁𝗲𝗿 𝘀𝘆𝗻𝗱𝗿𝗼𝗺𝗲, doesn’t ask follow-up questions. They spend hours trying to reverse-engineer the KPI, make a bunch of assumptions, and deliver something that’s almost right… but not quite. Eventually, the stakeholder replies: “That’s not what I meant.” 💡 𝗛𝗲𝗿𝗲’𝘀 𝗮 𝗯𝗲𝘁𝘁𝗲𝗿 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 (𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝗜 𝘁𝗲𝗮𝗰𝗵 𝗷𝘂𝗻𝗶𝗼𝗿 𝗮𝗻𝗮𝗹𝘆𝘀𝘁𝘀): ---> Set up a 15-minute call before you start ---> 𝗗𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝗞𝗣𝗜 𝗰𝗹𝗲𝗮𝗿𝗹𝘆 𝗮𝘁 𝘁𝗵𝗲 𝗿𝗼𝘄/𝘁𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻 𝗹𝗲𝘃𝗲𝗹 ---> Agree on: ---> Filters (e.g. exclude canceled or RTM orders?) ---> Base event (order date? ship date? delivery date?) ---> Data availability (do we even have this field?) ---> 𝗪𝗮𝗹𝗸 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 3–5 𝘀𝗮𝗺𝗽𝗹𝗲 𝗿𝗼𝘄𝘀 𝗶𝗻 𝗘𝘅𝗰𝗲𝗹 𝗮𝗻𝗱 𝗰𝗮𝗹𝗰𝘂𝗹𝗮𝘁𝗲 𝗶𝘁 𝗺𝗮𝗻𝘂𝗮𝗹𝗹𝘆 ✅ Final Takeaways ---> To analysts: It’s not a weakness to ask for clarity — it’s your superpower ---> To stakeholders: 10 minutes of upfront alignment can save hours of wasted effort ---> Define KPIs together at the row level ---> Walk through sample data before you automate anything Let’s build a culture where 𝗱𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻𝘀 𝗮𝗿𝗲 𝗮𝗴𝗿𝗲𝗲𝗱 𝗳𝗶𝗿𝘀𝘁, not assumed later. Because a KPI without definition is just... guesswork. 🎯

Why 73% of Projects Fail and How I Stopped Losing Stakeholder Support Let me tell you a quick story. Years ago, I was leading an ops overhaul that was supposed to streamline internal reporting. Everything looked good on paper, timelines, budget, resource allocation. I checked every box… Except one: I didn’t fully engage the stakeholders who would actually use the system every day. 🚨Big mistake. Within 3 weeks of launch, adoption lagged, teams worked around it, and leadership questioned the ROI. That’s when it hit me—involvement doesn’t equal alignment. Just because stakeholders are informed doesn’t mean they’re invested. So I changed my approach. Here’s what I did: • Identified key influencers across departments, not just top execs, but daily users and frontline managers. • Used long-form discovery sessions to understand their actual pain points (not just the ones listed on a dashboard). • Built a feedback loop into every sprint cycle. Small changes. Real-time validation. • Created internal linkages between project goals and departmental KPIs (this one’s huge). The result? 🎯 41% faster implementation. ✅ 3X higher adoption in the first 30 days. 💬 Consistent stakeholder engagement from kickoff to post-launch. Why does this matter for you? If you’re a project manager, ops lead, or department head, especially in finance, tech, or healthcare, here’s your reality: 📌 You’re juggling timelines, compliance, and team bandwidth. 📌 You’re expected to “drive transformation” and still “not disrupt the day-to-day.” 📌 You’re measured by results but those results start with buy-in. So ask yourself: Are you just updating stakeholders or are you empowering them to shape outcomes? That’s the difference between a delivered project and a sustained solution. If you’re tired of rework, delays, or lukewarm adoption, start by rethinking how you engage your stakeholders. Involve early. Involve meaningfully. Involve often. ✅ Start with a 30-minute alignment session before you build your next project charter. ✅ Don’t just collect feedback—co-create the solution with the people who live it. You’ll thank yourself later. Let’s stop managing projects and start leading with people who matter. #ProjectManagement #StakeholderEngagement #LeadershipInAction