Supply intelligence / Prototype 01

Import planning, made clear.

Know what to reorder, when to reorder, and what delays could cost.

● Interactive research prototype — all product and sales data are fictional. Recommendations are rules-based and require human approval.

Products monitored

Across three suppliers

At-risk SKUs

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Coverage below effective lead time

Suggested purchase value

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Using illustrative unit costs

Inventory days at risk

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Combined gap across critical SKUs

Replenishment priority

Transparent rules, not opaque AI predictions

Base scenario

Product	On hand	Sales / day	Coverage	Effective LT	Signal	Buy units

Why these recommendations?

Logic audit

Scenario lab

What if?

Supplier delay +0 days

0 days30 days60 days

Target coverage after arrival Demand multiplier

Projected cash needed

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Adjust assumptions to inspect purchasing exposure.

Stock coverage

Days / SKU

Coverage at selected demand scenario. Orange indicates coverage below lead time.

How it works

1Estimate daily demand from the example sales rate and your demand scenario.

2Compare available stock coverage with each supplier's lead time plus your chosen delay.

3Suggest enough units to cover lead time and post-arrival target, net of stock on hand and inbound orders.

MODEL NOTE — Days of cover = on hand ÷ adjusted daily sales. Recommended quantity = max(0, ceil(adjusted daily sales × (effective lead time + target coverage) − on hand − inbound)). Quantities round to order multiples. This planning heuristic does not model uncertain lead-time distributions, service-level safety stock, backorders, cash constraints, SKU substitution or shelf life. Real implementation needs testing and customer-specific rules.