Supplier Lead Time Tracker — Chibuike Dialaekwe

// reliability ranking

Supplier Lead Time Reliability Leaderboard

// portfolio metrics

Lead Time KPI Summary

// analytics

Lead Time Performance Charts

Promised vs Actual Lead Time by Supplier (Avg Days)

Side-by-side comparison — bars above the promised line indicate chronic over-delivery; the gap is the hidden safety stock cost

Lead Time Variance Distribution (%)

How often each supplier delivers early, on-time, or late — shows reliability pattern not visible from averages alone

Reliability Score Ranking

Composite reliability score (0–100) — weighted on consistency, variance, and on-time rate. Flagged at <70

Avg Lead Time Variance by Category (days)

Which procurement categories suffer the most lead time slippage — helps prioritise supplier development effort

Monthly On-Time Delivery Rate — Last 12 Months

Portfolio-wide OTD% trend — target 95%. Declining trend signals systemic supplier performance degradation

// raw data

📊 Raw Dataset

PO-level lead time records from ERP — 50 rows shown. Red rows = review flagged (variance >20%). Download full dataset below.

PO Number	Supplier	Category	Item Code	PO Date	Promised Delivery	Actual Delivery	Promised LT (d)	Actual LT (d)	Variance (d)	Variance %	Reliability	Review Flag

// methodology

Problem → Solution → Findings

🔴▶ PROBLEM

Lead time data lived only in individual PO line items inside the ERP — no aggregated view existed showing whether a supplier's historical performance matched their contracted commitment
Safety stock calculations used contracted lead times rather than actual lead times, systematically under-calculating buffer stock for unreliable suppliers and causing avoidable stockouts
Supplier review meetings relied on anecdotal delay examples rather than statistical performance data — suppliers could dispute individual cases, and without a dataset, procurement had no rebuttal
No early-warning mechanism existed — a supplier could be drifting 8 days late on average for 3 months before anyone noticed, because the deterioration was gradual and invisible in individual PO reviews

🔵▶ SOLUTION

SQL pipeline joining ERP purchase order headers with goods receipt records to build a supplier_lead_time_fact table with one row per PO line, capturing promised and actual lead times with full date arithmetic
Reliability score formula: weighted average of on-time rate (50%), inverse of variance coefficient (30%), and trend direction (20%) — giving a single 0–100 score per supplier that updates monthly
Automated review flag triggered at >20% variance on a rolling 90-day basis, with a supplier performance brief auto-generated in Power BI for insertion into the quarterly review pack
Lead time actuals fed back into the inventory planning model to replace contracted lead times — immediately improving safety stock accuracy for 14 suppliers with chronic overruns

🟢▶ FINDINGS

Average actual lead time across the supplier base was 4.8 days longer than contracted — effectively doubling the required safety stock for those suppliers when the actuals replaced contract figures in the planning model
Electronics category showed the worst performance: avg variance of +6.2 days (31% above contract), driven primarily by two suppliers using contracted lead times from 2022 that no longer reflected their post-COVID capacity
Switching safety stock calculations to actual lead times for flagged suppliers reduced both stockout events (down 31%) and overstock instances (down 18%) simultaneously — because some suppliers were actually faster than their contracts stated
Supplier review meetings became data-driven within one cycle: suppliers presented with rolling 90-day variance data accepted responsibility for corrections in 7 of 8 cases where previously they had disputed delay claims
OTD rate improved from 76% to 94% within two quarters as suppliers became aware their lead time performance was being tracked and scored monthly

// outlook

📈 Forecast & Projections

6-Month Lead Time Trend Projection by Supplier

Historical actual lead time (solid) vs projected trend (dashed) — declining = improving performance; rising = deteriorating reliability

SUPPLIER:

// strategic guidance

💡 Advice for Companies with Similar Challenges

Supplier Lead Time Management — Key Recommendations

Embed lead time reliability scores into your supplier KPI review process. A supplier consistently 5+ days late on a 14-day lead time is effectively doubling your safety stock requirement. Quantify this cost and present it in contract renegotiations — it makes the business case for penalty clauses or dual-sourcing undeniable.
Replace contracted lead times with rolling actuals in your planning system. This single change, requiring nothing more than a SQL query on your ERP goods receipt data, can immediately improve safety stock accuracy by 20–40% for suppliers with chronic lead time variance.
Build a supplier lead time trend monitor, not just a snapshot. A supplier with a 15% variance today but a worsening trend over 3 months is a bigger risk than one with 20% variance on a stable or improving trajectory. Direction matters as much as current position.
Make the data visible to suppliers, not just internal teams. When suppliers know their lead time reliability is being measured and scored monthly — and that the score feeds into sourcing decisions — behaviour changes. Transparency is the cheapest performance improvement tool in procurement.

// KEY TAKEAWAY

Supplier lead time reliability is one of the most undertracked metrics in supply chain. Every day of untracked variance is a day your safety stock model is working with wrong inputs — either over-buffering (wasting working capital) or under-buffering (risking stockouts). Building the SQL tracker costs one sprint. The compounding benefit to planning accuracy, working capital, and supplier accountability continues indefinitely.

Supplier Lead TimeTracker

Supplier Lead Time
Tracker