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PDCA Experiment & Results Tracker

A compact, interactive PDCA (Plan–Do–Check–Act) experiment form for quick shop-floor tests. Collect hypothesis, primary metric baseline and after values, success criteria, lessons learned, and clear next steps so short experiments produce measurable, sustainable improvements and can be reviewed in weekly huddles.

Interactive Tool

PDCA Experiment & Results Tracker

Run quick, measurable shop-floor experiments

Use this compact PDCA (Plan–Do–Check–Act) tracker to turn small hypotheses into measurable improvements. Before you start, name a single primary metric you will use to judge success and record a clear baseline. Keep experiments short, collect the smallest useful sample, and capture practical lessons so good changes stick. Flag experiments you want to discuss in your weekly huddle so teams can adopt or iterate quickly.

Quick tips: choose one primary outcome (e.g., ticket time, remakes per 100 tickets, food cost %), state who owns data collection, plan a short sample window (days or shifts), and include how you will control for known confounders.

Short descriptive name (e.g., 'Faster expo during dinner rush').
Who is responsible for running the test and collecting results.
Choose the area this experiment most directly affects. Helps tag and group experiments for later sharing and scaling.
Brief context: the problem, where it occurs, and why it matters.
A clear, testable statement of what you expect to happen and why.
Name the main metric you'll measure (e.g., ticket time, food cost %, remakes per 100 tickets).
Units for the metric (e.g., minutes, %, $ per week, count).
Clarifies how to interpret change (required for consistent reporting).
Record the metric value before the experiment. Note units above.
Record the metric value after the experiment (same units).
Optional: compute (After - Baseline) / Baseline * 100. Enter negative for reductions. Useful for quick comparison across experiments.
Describe success thresholds and any secondary metrics to watch.
How long the test will run. Use short durations for rapid learning.
If applicable, how many tickets, guests, or shifts you'll use to collect data.
YYYY-MM-DD
YYYY-MM-DD or expected end date
Who collects data, which systems or manual counts, and any calculation notes. Include where raw data or spreadsheets are stored.
Known risks, possible confounders, and how you'll control for them.
Optional: simple estimate of upfront cost to adopt the change (materials, training). Use same currency for comparisons.
Was the test successful?
Calculate impact (e.g., minutes saved per ticket, $ per week). Include assumptions and simple math.
Helps prioritize follow-up: if yes, note barriers and required adaptations.
List what would stop this being adopted elsewhere and what additional resources or changes would be needed.
What worked, what didn't, and why. Note details that will help repeat or scale.
Adopt, adapt, scale, or run another experiment? Who will do the follow-up and by when.
Quick flag to surface this experiment during the team's weekly huddle.
Name of person who reviewed results in huddle (optional).
YYYY-MM-DD (optional).
Describe any attached photos, spreadsheets, or location of raw data.
Optional: comma-separated tags for searching (e.g., 'expo, dinner, remakes').
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