Scoping a Mis-Shipment Project at a Regional Distribution Center
You are a newly certified Green Belt at a regional distribution center that ships roughly 48,000 orders a month. After a key-account escalation, the site director asks you to "fix the mis-shipment problem." Last quarter, mis-shipments - wrong item, wrong quantity, wrong address - ran at 1.8% of orders against a contractual limit of 0.5%. The director wants the charter to cover all three error types, all six pick zones, all three shifts, and to add late shipments and damaged cartons "while we're at it." You have 20% of your time, no capital budget, and a team of one supervisor, two pickers, an IT analyst and a customer service rep. Pareto of last quarter: wrong item 52%, wrong quantity 31%, wrong address 17%. Zone 3, the high-velocity split-case zone, produced 46% of wrong-item errors while shipping 21% of orders. Zones 1 and 2 are pallet-only and have run near zero errors for six months. The director has already told the account manager that mis-shipments will be "under 1% by Q3."
1. Draft a problem statement and critique the director's proposed scope. What do you include, what do you exclude, and on what evidence?
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Problem statement (draft) "Between July and September, mis-shipments in the distribution center averaged 1.8% of shipped orders (approximately 860 per month) against a customer requirement of 0.5%. The gap costs an estimated $X per month in returns, expedites and chargebacks. The team will reduce total mis-shipments to 0.5% or below by the end of Q2, without capital expenditure."
Why the director's scope fails the arithmetic test Starting at 1.8% and targeting 0.5% requires a 72% reduction. Wrong-item errors are 52% of the total (0.94 points). Even perfect elimination of every wrong-item error leaves you at 0.86% - still above target. So a wrong-item-only project cannot deliver the goal; you must also attack wrong quantity (0.56 points). Wrong address is only 0.31 points and may originate upstream in order entry, outside your control.
Keep: wrong item and wrong quantity, weighted by their contribution to the gap, with Zone 3 as the initial focus since it generates 46% of wrong-item errors on 21% of volume. Zones 1 and 2 are pallet-only with near-zero errors - exclude them and say so explicitly, with data.
Park: late shipments and damaged cartons. Different defect families, different root causes, different process owners. Adding them dilutes the team and destroys the ability to attribute improvement.
Flag: the "under 1% by Q3" commitment was made before any data was analyzed and before the scope was agreed. Restate it as conditional on scope sign-off.
2. Write an operational definition for "wrong item" and specify how the team will collect baseline data for the in-scope zones.
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Operational definition - wrong item A shipped order line counts as a wrong-item defect when the item number on the carton and on the pack slip does not match the item number on the released order line, as verified by either (a) the customer's claim, or (b) the post-ship audit, whichever is discovered first. Excluded: authorized substitutions documented on the pick ticket; cancelled lines; items short-shipped (that is wrong quantity, counted separately); carrier damage. Who records: the audit clerk for audit-detected defects, customer service for claim-detected defects. When: within 24 hours of discovery. Where: one log keyed on order number, date, zone, shift, picker ID and order type.
Why this matters Without a written definition, the two pickers on your team will disagree about substitutions and short-ships, and the baseline will be unusable.
Baseline data plan
- 4–5 weeks, all orders from Zone 3 plus Zone 4 as a comparison cell.
- Stratify by shift, picker, order type (each-pick vs case), day of week.
- Sample size: to estimate a 1.8% rate within ±0.3 percentage points at 95% confidence you need n ≈ 1.96² × 0.018 × 0.982 / 0.003² ≈ 7,500 orders. Zone 3 at ~10,000 orders/month gives you that inside one month; use five weeks to capture a full shift cycle.
- Run an attribute agreement check first: 50 orders independently classified by both auditors, report kappa. If kappa is below 0.7, fix the definition before collecting baseline.
3. The director wants to know whether the team composition is adequate. What gaps do you raise, and how do you handle the 20% time constraint?
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Gaps in the team
- No order-entry or configuration owner. Wrong address is 17% of defects and wrong-item is partly a pick-instruction problem. If the root cause sits in the item master or the WMS pick logic, your IT analyst can query data but cannot change configuration. Add whoever owns WMS configuration, even at 2 hours a week.
- No upstream representation. If order entry keying drives wrong address, the DC cannot fix it alone; you need a customer-service lead with authority over the order-entry process, not just a rep who reports symptoms.
- No finance or accounting partner. The charter needs a cost-of-poor-quality figure for prioritization and for the close-out. A rough number from finance is enough; without it the project competes poorly for attention.
- Two pickers is right, but they must be from Zone 3 and ideally different shifts. Otherwise the team designs a fix that only works on day shift.
Handling 20% time 20% of a week is one day. Plan the project around a small number of high-value activities: one week of charter and baseline design, one month of data collection that runs without you via the audit clerk, then analysis and pilot. Delegate data pulls to the IT analyst and daily data integrity to the supervisor. Pre-schedule weekly 45-minute team reviews and cancel them only when there is genuinely nothing to decide. If the analysis phase needs more than a day a week, ask for a temporary increase - in writing, tied to a specific milestone - rather than quietly letting the project stall.