MRP Lot Sizing Methods: LFL, EOQ, POQ & More Compared

MRP lot sizing methods determine how much material to order when your MRP system identifies a net requirement. Choosing the right lot sizing approach for each item in your inventory directly impacts ordering costs, holding costs, cash flow, and warehouse space. In this guide, we compare the major lot sizing methods, show the math behind each, and help you determine which method fits each category of item in your operation.

For context on how lot sizing fits into the broader MRP process, see our complete MRP guide and MRP inputs and outputs.

Why Lot Sizing Matters

When MRP calculates net requirements, it determines that you need a certain quantity of a material by a certain date. But how much should you order? Exactly the net requirement? A larger batch to get a discount? Enough to cover several weeks?

The answer involves balancing two competing costs:

• Ordering costs: Setup charges, purchase order processing, shipping, receiving inspection
• Holding costs: Storage space, insurance, obsolescence risk, opportunity cost of tied-up capital

Order too frequently in small quantities, and ordering costs dominate. Order infrequently in large batches, and holding costs pile up. Lot sizing methods provide systematic approaches to finding the balance.

The Six Main Lot Sizing Methods

1. Lot-for-Lot (LFL)

The simplest method: order exactly the net requirement for each period.

How it works:

Advantages:

• Minimizes holding costs (no excess inventory)
• Simple to understand and implement
• Best for expensive items where holding costs are high
• Matches production precisely to demand

Disadvantages:

• Maximizes the number of orders placed
• Higher ordering and setup costs
• No buffer for demand variability

Best for: High-value items (A items), custom manufacturing components, perishable materials, items with unpredictable (lumpy) demand.

2. Economic Order Quantity (EOQ)

EOQ calculates the mathematically optimal order quantity that minimizes total annual cost (ordering + holding). See our full EOQ guide for detailed formulas and examples.

The EOQ Formula:

EOQ = sqrt((2 x D x S) / H)

Where:

• D = Annual demand (units)
• S = Ordering cost per order ($)
• H = Annual holding cost per unit ($)

Example:

• Annual demand: 10,000 units
• Ordering cost: $50 per order
• Holding cost: $2 per unit per year

EOQ = sqrt((2 x 10,000 x 50) / 2) = sqrt(500,000) = 707 units

Advantages:

• Mathematically optimal for stable demand
• Balances ordering and holding costs
• Well-understood, widely implemented

Disadvantages:

• Assumes constant demand (rarely true in manufacturing)
• Does not account for price breaks
• May result in partial period coverage
• Requires accurate cost data

Best for: Commodity items with stable demand, C items with high ordering costs, standard raw materials.

3. Fixed Order Quantity (FOQ)

Order a predetermined fixed quantity whenever MRP generates a requirement, regardless of the actual need.

How it works:

The FOQ is often set to match supplier minimums, package quantities, or container loads.

Advantages:

• Aligns with supplier quantity constraints
• Predictable order sizes simplify receiving
• Easy to implement

Disadvantages:

• May not optimize cost
• Creates varying levels of excess inventory
• Does not adapt to demand changes

Best for: Items with supplier minimum order quantities, items sold in standard packs, items requiring full container loads for shipping.

4. Period Order Quantity (POQ)

POQ orders enough to cover a fixed number of periods of demand. The number of periods is often derived from EOQ.

Calculating POQ periods:

POQ Periods = EOQ / Average Period Demand

If EOQ = 707 units and weekly demand averages 192 units:

POQ Periods = 707 / 192 = 3.7, rounded to 4 weeks

How it works:

Advantages:

• Reduces ordering frequency while limiting excess inventory
• Adapts to variable demand better than FOQ
• Inventory drops to zero at the end of each coverage period

Disadvantages:

• Requires calculating the optimal period coverage
• May create large orders if demand spikes in certain periods

Best for: Items with moderate value and variable demand, where you want to consolidate orders but not carry excessive inventory.

5. Part Period Balancing (PPB)

PPB is a dynamic method that looks ahead at future requirements and groups them together until the cumulative holding cost approximately equals the ordering cost.

The Logic:

Keep adding future periods' demand to the order until: Cumulative Holding Cost >= Ordering Cost

Example (ordering cost = $50, holding cost = $0.50/unit/week):

PPB would order 100 units (Week 1 only) because adding Week 3 demand pushes holding cost well above ordering cost. In practice, PPB looks for the balance point.

Advantages:

• Dynamically optimizes each order decision
• Adapts to demand patterns better than static methods
• Generally produces lower total cost than FOQ or basic POQ

Disadvantages:

• More complex to understand and explain
• Requires accurate cost data
• Results can be counterintuitive

Best for: B items with irregular demand, situations where demand varies significantly period to period.

6. Least Unit Cost (LUC)

LUC calculates the per-unit cost for different lot sizes and selects the quantity with the lowest unit cost (including both ordering and holding costs).

For each candidate lot size:

Unit Cost = (Ordering Cost + Holding Cost) / Order Quantity

The lot size with the lowest per-unit cost wins.

Best for: Similar scenarios to PPB, particularly when unit cost visibility is important for purchasing decisions.

Lot Sizing Method Comparison

Choosing the Right Method: ABC Framework

A practical approach is to align lot sizing methods with your ABC inventory classification:

This framework ensures you minimize inventory investment on your most expensive items while reducing ordering workload on your cheapest items. Pair this with appropriate safety stock levels for each class.

Lot Sizing Modifiers

Most MRP systems, including RMDB, support modifiers that override or adjust the base lot sizing calculation:

• Minimum order quantity: Never order less than this amount (e.g., supplier minimum)
• Maximum order quantity: Never order more than this (e.g., storage constraint)
• Order multiple: Round up to the nearest multiple (e.g., items sold in packs of 12)
• Scrap factor: Increase order quantity to account for expected scrap

Frequently Asked Questions

Optimize Your Lot Sizing with the Right Tool

Getting lot sizing right can save thousands in inventory carrying costs while preventing stockouts. RMDB from User Solutions supports all major lot sizing methods with per-item configuration, so you can apply the optimal strategy across your entire inventory.

Schedule a free demo to see how intelligent lot sizing reduces your material costs.