Operations & Process
AI Prompt Templates

The analysis · 83% of an order’s time is spent waiting, most of it for one collection

A SIPOC lists the suppliers, inputs, process steps, outputs and customers of a process on one page. A value stream map adds the time each step takes and the time spent waiting before it, so the delay can be located.

• 9 hours of work, 52 hours elapsed: value-added time is 17% of lead time. The other 43 hours are queues between steps, and that is where the delivery promise is lost.
• 19 hours at the dock: the old courier collected at 11:00 and 16:00; the new one collects once, at 16:00. Orders packed after the cut-off, 38% of them, now wait overnight.
• 11 handoffs: the order passes between customer service, the warehouse, quality and the courier eleven times, and address changes are keyed in twice.

Takeaway: measure the waiting time between steps, not only the work, and start with the 19-hour wait for the single courier collection.

The analysis · Four people handling returns four ways put $180K of invoices into dispute

A standard operating procedure (SOP) is the written, approved way a task is done, with numbered steps, owners and checks. A work instruction is the short version of the critical steps, used at the workstation.

• 9 days to a credit: with no procedure, returns waited for whoever had time. Clinics waited an average of 9 working days for a credit and withheld payment in the meantime.
• 1 credit in 5 was wrong: each person priced returns differently, and clinics disputed $180K of invoices in two quarters.
• One exception with a safety cost: temperature-controlled items had been restocked after return. The procedure now quarantines them at receipt, with no exception.

Takeaway: write every step with one owner and a measurable standard, and give every exception a rule rather than leaving it to judgement.

The analysis · One station at 124% of capacity decides whether orders make the collection

The Theory of Constraints holds that the output of a process is set by its bottleneck, the step with the least capacity against demand. First-pass yield is the share of units completed correctly the first time, without rework.

• 250 lines an hour short: verification handles 1,050 lines an hour; demand between 10:00 and 14:00 is 1,300. Four hours of shortfall leaves about 1,000 lines waiting each day.
• More people everywhere would not help: picking runs at 71% and packing at 62% of capacity at the peak. Extra pickers would only lengthen the queue at verification.
• 93.8% first-pass yield: 6.2% of 26,000 orders a month, about 1,600, leave with the wrong item or quantity. Most pass through verification during the peak.

Takeaway: add capacity only at the verification bottleneck, and only during the 10:00-to-14:00 peak.

The analysis · Three process causes, not new starters, explain three quarters of the errors

A Pareto analysis ranks causes by frequency to find the few that account for most failures. A fishbone diagram groups possible causes by category, and the 5 Whys asks why repeatedly until the answer is a cause in the process.

• 76% from three types: wrong item 41%, wrong quantity 22% and missed line 13% of the 1,612 errors logged in September.
• The override is the process cause: verification lets a picker skip a failed scan with a manual confirm. At the peak it is used on 18% of lines, and error rates are the same for new and experienced staff.
• $103K a month: each error costs about $64 in reshipping, credit processing and labour. 1,612 errors in September cost $103K, about $1.24M a year.

Takeaway: remove the manual override at verification and separate look-alike products before spending anything on training.

The analysis · The two highest risks were both preventable by a rule and a scan

Failure mode and effects analysis (FMEA) lists the ways each process step can fail and scores each on severity, occurrence and detection. Multiplied together, they give the risk priority number, used to decide which failures to prevent first.

• 31 parcels, $43K: each lost temperature-controlled parcel costs about $1,400 in product, reshipping and credit. 31 in a quarter is $43K, before any cost to patient care.
• 315 from a calendar: a 48-hour cold pack cannot survive a weekend. Sending cold-chain parcels only until Wednesday 16:00 removes the failure mode rather than inspecting for it.
• 240 from a missing check: nothing stopped a parcel leaving without its cold pack. Scanning the pack before the label prints makes the error visible at the point it happens.

Takeaway: score every failure mode before it happens, and fix the top risks with rules and scans that make the error impossible, not with reminders.

The analysis · $100K a year of changes removes about $0.9M a year of error costs

Lean process redesign removes the eight wastes from a process: transport, inventory, motion, waiting, overproduction, over-processing, defects and unused skills. The future-state map shows the process after the changes.

• Waiting is the largest waste: a second daily collection removes the 19-hour overnight wait for 38% of orders, and brings lead time from 52 to 22 hours.
• Defects are the most expensive waste: errors cost about $1.24M a year. Removing the override and re-slotting 120 look-alike products targets an error rate of 1.5%, saving about $0.94M a year.
• The bottleneck gets capacity only at the peak: a second verification lane from 10:00 to 14:00 costs $38K a year, instead of adding people across the warehouse.

Takeaway: fund the four changes as one redesign, and pilot it on one shift before rolling it out.

The analysis · The 9% saving cost Brennock $1.8M a year

Total cost of ownership (TCO) adds to a supplier’s price every other cost of using it: failures, rework, switching and management time. A weighted scorecard fixes the selection criteria and their weights before any bid is opened.

• $414K saved, $2.2M lost: the switch cut the $4.6M delivery bill by 9%, $414K a year. Credits alone ran at $1.1M in two quarters, $2.2M a year: a net loss of about $1.8M.
• Weights fixed first: on-time performance 30, cold-chain capability 25, cost 25, service and claims 10, systems 10. The March decision had used price only.
• Bid C at $4.8M: dearer than today’s price by $0.2M, cheaper by $1.6M on total cost, and the only bid with dedicated cold-chain vehicles.

Takeaway: fix the criteria and weights before opening bids, and compare suppliers on total cost of ownership, not on price.

The analysis · $1.1M of failures with no service level meant $0 recovered

A service level agreement (SLA) defines the service a supplier must deliver as measured targets. A service credit is the reduction in the supplier’s charge when a target is missed.

• $0 of $1.1M recovered: the March contract promised “best efforts”. Brennock paid clinics $1.1M in credits and could claim none of it from the courier.
• A credit sized to matter: Bid C’s monthly charge is about $367K. Each point below 97% costs the courier about $7.3K a month, up to a cap of $55K.
• A way out: three consecutive months below 94% gives Brennock the right to terminate, with a 90-day handover the supplier must support.

Takeaway: measure every service level from shared data, attach a credit that matters to the supplier, and write the exit terms before signing.

The analysis · A 1.2-point miss is $8.8K a month and a pattern worth fixing

A supplier performance review compares a supplier’s results with its contract, calculates what is owed for misses and agrees corrective actions. A quarterly business review (QBR) is the meeting where this is done.

• $8.8K in January: on-time delivery was 1.2 points below the 97% target. At 2% of the $367K monthly charge per point, the credit is $8.8K, and it is claimed.
• The miss has one location: 8% of clinics are on rural routes, and those routes account for 61% of late deliveries, most of them on Tuesdays.
• An action with a date: the courier adds a second van on rural Tuesday routes from 15 February, and the February scorecard shows whether it worked.

Takeaway: claim every credit the contract allows, and tie each corrective action to the data pattern behind the miss.

The analysis · A control chart would have shown the March failure within a week

A control plan lists the measures that keep a process on standard, their limits and the response when a limit is breached. Statistical process control uses control charts to separate normal variation from a real change.

• Six days against eleven weeks: on-time delivery fell below 95% six days after the courier switch. Without a limit or an owner, it was noticed after eleven weeks and $1.1M of credits.
• 2.1% is calculated, not chosen: the upper control limit comes from eight weeks of daily error rates since the redesign. Above it, the warehouse manager starts a review the same day.
• Six measures, six owners: each measure on the dashboard has one owner and a written response. Nine other measures the teams used to report were dropped.

Takeaway: give every measure an owner, control limits calculated from data, and a written response for when a limit is breached.