🚨 SAP IBP Worst Practices… continuing on to Supply Planning and IO

⚠️ WP #4: One lead time. Every product. Every location. What could go wrong?

We keep seeing this in SAP IBP Inventory Optimization implementations — and it could quietly kill the usability and the credibility of the tool even before go-live. 💀

🛠️ The integration consultant loads the master data. The lead time field is messy.

📂 Some plants have it. Some don’t.

🤔 The values look suspect. ⏰ Deadline pressure mounts. So the consultant uses a simple input file that has just one value for all…

👉 Pick an “average” — say 30 days — and apply it across the board.

🏭 Domestic distributors, 🚛 regional suppliers, 🚢 overseas manufacturers.
✏️ Same number. Move on. ✅

🙃 Contrary to LinkedIn posts here preaching people to ignore lead time, what could go wrong in this situation?

📊 Look at what real lead times actually look like in a typical multi-tier network:

🇺🇸 → Cleveland fasteners: 3 to 7 days
🇺🇸 → Atlanta sensors: 10 to 18 days
🇺🇸 → Houston resin drums: 18 to 32 days
🇲🇽 → Monterrey castings: 25 to 45 days
🇨🇳 → Shenzhen electronics: 55 to 85 days
🇮🇳 → Mumbai pharma API: 65 to 95 days

🤷‍♂️ What do you think? All locations created equal?! 🌍⚖️
💬 Drop your thoughts in the comments 👇

Struggling with lead time master data in your SAP IBP rollout? Contact Valtitude — we’ve helped Fortune 500 supply chains fix exactly this before go-live. → https://valuechainplanning.com/usability-consulting/SAP-IBP

Read: SAP IBP Worst Practices WP2 — A “Best Fit” Model Pool with No Design Thinking