Hey everyone! It's been a few weeks, so thanks for sticking around and welcome to the newcomers. You'll notice PlotStack looks a little different this week. You told me the think pieces are what you actually read, so I've given them more room in a section called “Today’s Topic”, and rounded up the links and tools into one shorter section called “Worth Your Time”. Structurally everything else is the same.
Now the point behind this issue. A while back my team shipped a report we were proud of. It was clean, fast, and did exactly what was expected. About a month or so later a stakeholder asked a simple question: is anyone actually using it?
And I didn't have a ready answer. I knew it had been delivered and I knew it worked. What I didn't have was any record of who opened it, how often, or whether usage held up after the first week. We built it but never set it up to be measured.
If you've shipped a dashboard/product/(or really anything), you've probably had a version of this conversation.
TRIVIA
Before it meant a screen full of charts, the word "dashboard" referred to something else. What was it?
A. A panel of gauges on early steam locomotives
B. A board on horse carriages that blocked mud kicked up by the horses
C. A chalkboard in telegraph offices used to post incoming messages
D. A navigation board on sailing ships used to plot a course
Answer at the bottom of this issue
TODAY’S TOPIC
Measure Before Anyone Asks
Every launch comes with a question, and that question almost always shows up after it's too late to collect the data (this is completely natural, and should be expected). A dashboard goes live and a month later someone asks if anyone uses it. A campaign runs and the VP wants to know if it moved anything. A process change rolls out and finance wants a before and after.
You can clean data after the fact. You can reshape it and model it. But you can't go back and record clicks, views, or baselines from the past. Most platforms also only keep usage history for a limited window, so the evidence often disappears before anyone thinks to look for it.
So what can we do?
What we can do before shipping anything:
Write down the question you'll be asked in 30 days. Usually "is anyone using this?" or "did it work?" Write it down before launch, not after.
Decide what you need to count, and how precisely. An estimate is often good enough to answer "is this being used?" Just label it clearly so nobody treats a rough number like an audited one.
Capture the baseline now. A "before" number that exists today is worth more than a precise "after" number with nothing to compare it to.
Save your usage data somewhere that doesn't expire. If the only record lives in a tool that keeps 30 or 90 days of history, schedule an export before it rolls off.
Track the long tail. Launch week tells you very little. Whether people are still opening the report in week six is the real message.
WORTH YOUR TIME
ARTICLE
Measuring the Success of Data and Analytics: A Quick Start Guide
A short read on deciding what success looks like before you build. It also warns that user counts and visit frequency are an easy place to start but can mislead, since high usage doesn't always mean people are getting value from the dashboard. Read more →
ARTICLE
How to Measure BI Adoption and Prove ROI
The key idea here is that most adoption tracking stops at the first stage, so someone who logs in once and never returns still counts as "activated" even though the dashboard had no real impact. It's a vendor blog, so read the benchmarks with some skepticism, but the framework holds up. Read more →
TOOL
DuckDB
An in-process analytical database you can run from a notebook or the command line with zero setup. Worth including because it's the kind of tool that rewards understanding why columnar analytics is fast rather than just memorizing syntax. Free and open source. Discover more →
QUICK STUDY
▶️ Data Storytelling Basics (in 3 Steps): How to Communicate Data and Numbers
Anita challenges the old statement “the data speaks for itself” (it does not!). And she explains why and what we, as data professionals, can do to set up a great story using data. Learn more →
COMMUNITY BOARD
FROM THE EDITOR
Summarize and understand anything on the web.
Turn any screen into instant insight, VizBuddy captures your browser and hands you a structured analyst-grade summary in seconds (Chrome only).
FROM THE EDITOR
Free Notion Templates build for data professionals
Trusted by 1,000+ users, download the templates designed to keep your goals, projects, and ideas in perfect sync.
TRIVIA ANSWER
Before it meant a screen full of charts, the word "dashboard" referred to something else. What was it?
A. A panel of gauges on early steam locomotives
B. A board on horse carriages that blocked mud kicked up by the horses ✅
C. A chalkboard in telegraph offices used to post incoming messages
D. A navigation board on sailing ships used to plot a course
The "dash" was the mud and debris splashing up from the road. The name carried over to the panel in front of the driver in early cars, and eventually to the thing we build. Read more about it 📖
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