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The Spare Parts Paradox: Why You’re Always Out of What You Need

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Friday Afternoon, 3:47 PM

Critical pump fails. Technician checks Maximo: Replacement seal – Stock: 0.

Last ordered 9 months ago. Lead time: 3 weeks.

Production line down. Cost: $8,400 per day.

Meanwhile, same storeroom:

  • 47 V-belts for equipment retired in 2021
  • 23 control panels for a machine never purchased
  • 180 gaskets for models no longer in operation

Obsolete stock value: $340,000

The part you need: $120

The parts you have: $340,000 worth you’ll never use

This is the spare parts paradox.

The ABC Analysis Failure

Hospital in Egypt, 2024:

Surgical light bulb: $15 (C item, minimal stock) Generator relay: $8,500 (A item, always stocked)

What happened:

Light failed during procedure. Bulb out of stock. Surgery delayed 45 minutes.

Generator relay? Sitting in storeroom for 6 years. Never used. Likely never will be (dual redundancy).

ABC analysis optimized for cost.

Should have optimized for consequence.

The Criticality-Based Classification

Manufacturing plant in GCC, 2025:

Reclassified 3,400 spare parts:

Critical (12%): Stops production OR safety risk. Stock regardless of cost.

Important (31%): Reduces capacity. Stock based on lead time × failure frequency.

Standard (44%): Inconvenience. Order when needed.

Obsolete (13%): Equipment retired. Liquidate within 90 days.

Result after 12 months:

  • Critical part availability: 67% → 96%
  • Inventory value: $2.1M → $1.4M (33% reduction)
  • Stockouts causing downtime: 89% reduction

The MIN/MAX Calculation

Most companies guess: “Let’s keep 5 to 10 bearings.”

Better: calculate from data.

MIN = (Average usage × Lead time) + Safety stock

Example:

  • Average: 3 bearings/month
  • Max usage: 7 bearings
  • Lead time: 1.5 months

MIN = (3 × 1.5) + [(7-3) × 1.5] = 4.5 + 6 = 11 bearings

MAX = MIN + Order quantity = 11 + 8 = 19 bearings

Reorder at 11, order 8 more.

The Failure History Gap

Common problem:

Bearing fails → replaced → work order closed.

Missing: link between part and failure cause.

Better workflow:

  1. WO created: Failure code BEARING_OVERTEMP, Asset PUMP-P-225
  2. Part issued: BEARING-B-4409, linked to WO
  3. WO closed: Root cause: Misalignment
  4. Data visible: Query shows bearing consumed 12 times, 9 failures from overtemp on same pump

Action: Fix misalignment on PUMP-P-225 → bearing consumption drops 75%.

The Lead Time Reality

Vendor says: 4 weeks

Reality includes:

  1. Recognition: 3-5 days
  2. Approval: 2-7 days
  3. Vendor processing: 2-3 days
  4. Manufacturing: 15-20 days
  5. Shipping: 5-10 days
  6. Receiving: 1-3 days

Total: 28-48 days (4-7 weeks)

Water treatment plant, Egypt, 2024:

Chemical pump diaphragm. Vendor lead time: 3 weeks.

Actual average: 37 days (5.3 weeks)

Reorder point set for 3 weeks → stockouts 6 of 8 times.

Reset for 6 weeks + 1 week safety → zero stockouts in 14 months.

The Consignment Strategy

Traditional: Buy $45,000 part. Sits 3-5 years. Ties up capital.

Consignment: Vendor owns part. Sits in your storeroom. Pay only when used.

Hospital, Saudi Arabia, 2024:

47 high-value items ($15K-$85K each), total $2.1M

New model: Vendor owns stock, hospital pays when installed.

Result:

  • Capital freed: $2.1M
  • Part availability: Same (100%)
  • Cost per part: 8% higher
  • Net: $2.1M freed vs $18K annual cost increase

The Quarterly Audit

University, Saudi Arabia:

Q2 2024:

  • 23 items stocked out 2+ times → MIN too low
  • 67 items unused 18+ months → MAX too high
  • 12 items for retired equipment → liquidate

Actions: Increased MIN on 23, reduced MAX on 67, liquidated 12 ($31K recovered)

Q3 2024: 8 stockouts (down from 23)

Q4 2024: 3 stockouts

Continuous improvement.

What to Do This Week

Sunday: Run obsolete stock report (unused 12+ months)

Monday: Verify top 20 results

Tuesday: Get liquidation quotes

Wednesday: Run stockout report

Thursday: Review MIN/MAX for top 10 stockout items

The Real Numbers

Manufacturing plant, 680 SKUs, 2024-2025:

2024:

  • Inventory: $1.8M
  • Stockouts: 67 incidents
  • Downtime cost: $420K
  • Obsolete stock: $340K

2025 (after optimization):

  • Inventory: $1.2M (33% reduction)
  • Stockouts: 12 incidents (82% reduction)
  • Downtime cost: $75K
  • Obsolete liquidated: $280K recovered

Total benefit: $945K

Project cost: $35K

Payback: 14 days

Final Thought

Your storeroom isn’t there to store parts.

It’s there to prevent downtime.

If you have $2M in parts but stock out on a $120 seal that stops production, your inventory strategy is backwards.

Stock what breaks, not what costs.


Need a spare parts analysis? Contact Innexa for an inventory optimization review.

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About Innexa IT Solutions

 Innexa works exclusively with IBM Maximo and Maximo Application Suite for asset-intensive organizations across Egypt and the GCC. We support clients in building asset performance capabilities through disciplined data practices, integration clarity, and practical execution roadmaps grounded in real operational environments.

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