Eilfracht- und Überstundenzuschläge durch JIT-Engpässe
Definition
Kanban/JIT systems aim to cut warehousing and carrying costs by triggering replenishment only when bins reach a defined level, often via scanning and simple bin signals.[2][5][8] When this process is manual or poorly integrated with supplier lead times, parts run out unexpectedly. To avoid line stoppages, planners resort to same‑day couriers, airfreight, or weekend production with overtime rates. Industry guidance on JIT notes that businesses trade lower holding costs against higher vulnerability to disruption.[4][8] Typical Australian emergency freight for industrial components can cost AUD 500–2,000 per shipment domestically and more for international air. If a mid‑size auto‑parts plant faces 3–5 such incidents per month due to Kanban/JIT shortages, that alone is AUD 18,000–120,000 per year in freight. Adding overtime (e.g. 10–20 overtime hours per month across key workcentres at 1.5x pay) gives a further AUD 30,000–80,000 per year. Combined, a logic‑based estimate is around AUD 100,000–300,000 in avoidable annual cost overruns linked directly to poorly controlled Kanban/JIT replenishment.
Key Findings
- Financial Impact: Logic-based estimate: AUD 18,000–120,000/year in expedited freight plus AUD 30,000–80,000/year in overtime to catch up after JIT shortages = ~AUD 100,000–300,000 per plant per year.
- Frequency: Ongoing: several emergency shipments and catch‑up shifts per month in plants with manual Kanban monitoring or unstable supplier performance.
- Root Cause: Manual scanning or paper cards, lack of integrated reorder points with real lead times, inadequate safety stock for high‑variability demand, and poor supplier performance visibility.
Why This Matters
The Pitch: Australian 🇦🇺 automotive parts manufacturers waste AUD 100,000–300,000 annually on expedited freight and overtime created by Kanban/JIT stockouts. Automating inventory thresholds, demand forecasting and supplier alerts cuts these emergency costs.
Affected Stakeholders
Supply Chain Manager, Production Planner, Warehouse Manager, Finance Manager, Procurement Manager
Deep Analysis (Premium)
Financial Impact
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Current Workarounds
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Methodology & Sources
Data collected via OSINT from regulatory filings, industry audits, and verified case studies.
Related Business Risks
Umsatzverluste durch Fehlmengen und nicht erfüllte OEM-Abrufe
Fehlentscheidungen durch fehlende Transparenz in Kanban-/JIT-Beständen
Cost of Poor Quality from Chargeback Disputes
Supplier Indemnification Delays under ACL
Rush Order Costs from ECO Delays
Idle Equipment from ECO Bottlenecks
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