HML Analysis In Inventory Management: How Unit Price Helps Control Stock Decisions

HML analysis is an inventory classification method that groups items based on unit price. HML stands for High, Medium, and Low.

It is simple, but useful. A manufacturing business may carry thousands of items: raw materials, spares, consumables, packaging material, bought-out components, tools, and finished goods. Not every item needs the same purchase control. Some items are cheap but used in large quantities. Some are expensive but used rarely. Some are medium-value items that still need planned attention.

HML analysis helps managers identify items where unit cost itself deserves control.

AICAN Optiwise helps manufacturers classify, track, and review inventory so purchase and stores teams can make better decisions instead of treating every item equally.

What Is HML Analysis?

HML analysis classifies inventory items into three groups based on unit price:

• H items: High unit price
• M items: Medium unit price
• L items: Low unit price

The business decides thresholds based on its own material profile. For one company, an item above Rs. 5,000 per unit may be high-value. For another, the threshold may be Rs. 50,000.

The classification should reflect business reality, not a copied rule.

Why HML Analysis Matters

HML analysis matters because high-unit-price items can create financial risk even in small quantities.

A factory may not buy expensive spares often, but one wrong purchase can block money. A high-value raw material may need stricter approval. A low-value consumable may need a simple reorder process to avoid wasting management time.

HML helps decide where to apply control.

HML Vs ABC Analysis

ABC analysis classifies inventory by annual consumption value. It considers both quantity consumed and value.

HML analysis classifies inventory by unit price only.

For example, a bearing may have high unit price but low annual consumption. It may be H in HML but not A in ABC. A low-cost packaging item may be L in HML but A in ABC if annual consumption is huge.

Both methods are useful. They answer different questions:

• ABC asks: where is most inventory value consumed annually?
• HML asks: which items are expensive per unit?

Together, they give a more complete view.

How To Perform HML Analysis

A practical process looks like this:

1. Export item master with unit price.
2. Clean duplicate item codes and inconsistent units.
3. Decide H, M, and L thresholds.
4. Classify each item based on unit price.
5. Review exceptions with purchase and stores teams.
6. Apply controls for each category.
7. Review periodically as prices change.

The quality of classification depends on clean item master data.

Example

Suppose a manufacturer defines:

• H: Items above Rs. 10,000 per unit
• M: Items from Rs. 1,000 to Rs. 10,000 per unit
• L: Items below Rs. 1,000 per unit

A specialized motor costing Rs. 42,000 becomes H. A cutting tool costing Rs. 4,500 becomes M. A packing label costing Rs. 2 becomes L.

The motor may require purchase approval, supplier comparison, and minimum stock review. The cutting tool may need planned reorder. The label may need bulk reorder and simple availability control.

Controls For H, M, And L Items

H items may need:

• Senior approval before purchase
• Strict stock review
• Vendor negotiation
• Avoidance of excess stock
• Physical security
• Usage tracking

M items may need:

• Planned reorder levels
• Periodic price review
• Purchase monitoring
• Consumption tracking

L items may need:

• Simple reorder rules
• Bulk purchase where economical
• Easy issue process
• Stock-out prevention

The point is not to make inventory complicated. The point is to match control with risk.

How ERP Helps HML Analysis

ERP helps because HML requires clean item and price data.

A connected ERP can support:

• Item master unit price
• Purchase price history
• Supplier comparison
• Stock quantity
• Stock value
• Consumption data
• Approval rules
• Reorder levels
• Category-wise reports

Optiwise by AICAN can help manufacturers use item data for practical inventory control instead of manual spreadsheet reviews.

Where AICAN Optiwise Fits

AICAN helps manufacturing teams improve operational visibility. AICAN Optiwise connects purchase, inventory, production, and reporting so businesses can classify items and act on the classification.

Founder’s Note

Inventory control is not about watching every item with the same intensity. That wastes time and still misses risk.

At AICAN, we like simple methods that help teams decide where attention matters. HML analysis is one of those methods: easy to understand, useful when connected to real data, and powerful when combined with ERP discipline.

FAQs

What is HML analysis?

HML analysis classifies inventory into High, Medium, and Low categories based on unit price.

How is HML different from ABC analysis?

ABC looks at annual consumption value. HML looks at unit price only.

Why is HML useful?

It helps businesses apply stricter controls to expensive-per-unit items and simpler controls to low-value items.

How often should HML analysis be updated?

It should be reviewed periodically, especially when purchase prices change significantly.

How can Optiwise help?

Optiwise by AICAN helps maintain item, price, purchase, stock, and reporting data needed for better HML analysis.