AI Prompts for Inventory Optimization

Inventory optimization is not 'less inventory'. It is the right inventory: enough of the items that move to protect service, less of the items that do not, and none of the items that will never move. Most inventory problems are policy problems — reorder points set years ago, min/max levels copied across items with different behavior, and nobody owning the slow movers.

These prompts run a health diagnostic, derive replenishment policies by segment, and build an action plan for excess and obsolete stock. They complement the safety stock and ABC analysis pages, which go deeper on their specific calculations; this page is the overall review.

Before you use these

Have these ready to replace the highlighted [variables]:

• Inventory by item: on-hand quantity and value, last 12 months usage, lead time, current policy parameters
• Item attributes: ABC class, lifecycle status, shelf life
• Service level targets by segment
• Carrying cost rate

The prompts

• 1. Run the inventory health diagnostic
• 2. Set replenishment policies by segment
• 3. Build the excess and obsolete action plan

1. Run the inventory health diagnostic

Act as an inventory analyst running a health check on [site / category].

Data: [item, on-hand qty, unit cost, 12-month usage, lead time, reorder point / min / max, ABC class, lifecycle status, last movement date]
Targets: [service level by class, weeks of cover target by class]
Carrying cost rate: [% per year]

1. Compute for each item and segment: inventory value, annual turns, weeks of cover, and classification as healthy / excess (cover above target by more than [x] weeks) / slow-moving (no usage in [n] months) / obsolete (discontinued or no usage in [m] months).
2. Summarize value by classification and by ABC class. Identify the 20 items holding the most excess value.
3. Policy diagnosis: items where the reorder point or max is inconsistent with usage and lead time (too high → excess; too low → stockout risk). Show the comparison for the worst cases.
4. Stockout exposure: items with cover below lead time.
5. Annual carrying cost of excess and the cash release if excess were reduced to target.
6. Top five opportunities ranked by value, each with the action type (policy change, one-off reduction, disposition, stock transfer).

Show the classification thresholds used. Do not treat low turns as a problem for items with legitimate reasons (spares, seasonal builds) — flag them for review instead.

2. Set replenishment policies by segment

You are designing replenishment policies for [site / category] by inventory segment.

Segments: [e.g. ABC × XYZ, plus lifecycle: new / mature / end-of-life]
Segment characteristics: [demand level and variability, lead time and variability, unit value, shelf life, supplier MOQ]
Service level targets by segment: [%]
Constraints: [system capabilities, order frequency limits, storage]

For each segment:
1. Policy type: continuous review (reorder point / order quantity), periodic review (order-up-to level), min/max, kanban, or make/buy-to-order. Justify by demand pattern, value and lead time.
2. Parameter logic: how reorder point or order-up-to level is derived (expected demand over lead time + safety stock), how order quantity or review period is set (EOQ, MOQ, pack size, supplier schedule), and the safety stock method.
3. Review frequency for the parameters themselves.
4. Exceptions: items in the segment that should not follow the policy (new items without history, seasonal, promotional, end-of-life) and how to handle them.
5. Expected effect on inventory and service versus current, with the assumptions.

Present as a policy matrix. Flag any segment where the target service level is unrealistic given lead-time variability, and state what would need to change.

3. Build the excess and obsolete action plan

Act as an inventory manager building an excess and obsolete (E&O) action plan.

E&O list: [item, qty, value, months since last movement, lifecycle status, reason if known]
Disposition options and typical recovery: [use in production / substitute, return to supplier (terms), sell via alternate channel (%), rework, transfer to another site, scrap/recycle]
Root cause clues: [forecast error, MOQ, engineering change, customer cancellation, over-ordering, policy]

1. Group the items by likely root cause and by best disposition. Show value per group.
2. For each group: recommended disposition, expected recovery value and cost, timeline, owner, and any approval needed (write-down authority).
3. Prioritize by value recoverable and speed, and by storage or shelf-life pressure.
4. Financial view: expected write-down, cash recovered, carrying cost avoided.
5. Prevention: for each root cause group, the process change that stops it recurring (e.g. MOQ review, engineering change notice linked to inventory check, end-of-life run-out planning), with owner.
6. A monthly E&O review format: new entrants, aged items, actions closed, provision movement.

Be realistic about recovery rates — do not assume resale value without a channel. Distinguish items that need a decision from items that need a process.

Before you act on the excess list

The diagnostic produces a ranked list of excess and slow-moving stock. Run this before anyone starts disposing of it.

• Usage is true demand, not constrained shipments — stockout periods understate usage and inflate 'excess'
• Items with legitimate low turns are excluded or flagged: spares, seasonal pre-builds, regulatory minimums, strategic buffers
• Lead time used in the policy check is actual receipt performance, not the system parameter
• Open purchase orders and in-transit stock are included in projected cover
• Engineering change notices and end-of-life dates have been checked against every item on the list
• The value basis is consistent (standard cost vs last purchase price) across items
• Someone owns each disposition line and has the write-down authority it needs

Related prompts

• Safety Stock Calculation
• ABC and ABC-XYZ Inventory Analysis
• Working Capital Analysis
• Demand Forecasting
• Service Level Analysis
• Warehouse Operations Improvement

Logical next step

After this, most operations teams move on to Safety Stock Calculation.

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