Warehouse Workflow Lab

Plan your starting measurements

Published by Voodoo Robotics · workflows.voodoorobotics.com

Person responsible for this worksheetDateVersion

Decision to support

What to do: State the decision the data must resolve.

Decision / hypothesisWrite the decision this information will help you make.Example: Should Zone A change from one-order picking to eight-order carts?Current-state boundaryState exactly which work, area, shift, or cases are inside and outside the worksheet.Example: Zone A day shift; oversize orders excludedCandidate future stateBriefly describe the proposed method that will be compared with today’s method.Example: Pick eight orders per cart with one labeled tote per orderPrimary KPIName the main result the change should improve.Example: Completed order lines per direct labor-hourGuardrail KPIName a result that must not get worse while the main result improves.Example: Order accuracy must remain at least 99.8%

Metric definitions

What to do: Make each measure reproducible.

This section is a list.Use one row for each task, observation, test, person, field, or requirement. Add more rows when needed.

Sampling plan

What to do: Protect against a convenient but biased sample.

Dates and shiftsList the calendar dates and shifts that must be included in the sample.Example: July 20–24, 2026 · day and night shiftsOrder / SKU strataList order and product groups that must be represented separately.Example: 1-line, 2–5-line, and 6+-line ordersPeak periodsList the busy hours, days, or seasons that the sample must include.Example: Weekdays 2–4 p.m. and the final five shipping days of each monthWorkers / experience levelsName the role or person and shift when it matters.Example: Day-shift picker; 6 months experienceMinimum transactionsEnter a measured count and the period or group it covers.Example: 1,200 order lines during the day shiftKnown confoundersList other changes that could make the result look better or worse.Example: Three new workers started during week 2

Data quality

What to do: Name the validation and owner.

Missing-data ruleState what happens when a required record or value is missing; do not silently treat it as zero.Example: Exclude the row, count it as missing, and investigate if more than 2% are missingOutlier handlingState when an unusual result stays in the data, is reported separately, or is removed with a reason.Example: Keep ordinary shortages; report network outages separately and never delete them silentlyManual cross-checkDescribe the small manual count used to confirm the system data is trustworthy.Example: Compare 50 WMS completions with video timestamps and supervisor tallyData ownerName the person responsible for this decision, task, or approval.Example: A. Rivera — Operations ManagerApproval dateEnter the exact date, due date, or review frequency.Example: July 22, 2026