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Inventory Management · 8 min read · Updated Sep 9, 2026

What Are the Most Common Inventory Control Models?

Name: TranZact
Brand: TranZact

Worker standing beside sheet-metal cutting equipment in a small Indian manufacturing workshop

Inventory control models are systematic methods, like EOQ, ABC analysis, and Min-Max, that tell you how much stock to order and when. The right model depends on demand stability and SKU count, not on which one sounds most sophisticated.

Most Indian manufacturers actually run two or three of these models side by side, a coarse ABC split to decide what deserves attention, then a specific reorder model for each category. This guide covers the models that get used on real shop floors, and how to pick between them.

What Is an Inventory Control Model?

An inventory control model is a rule-based method for deciding order quantity and order timing for a stock item. Instead of reordering by gut feel, the model sets a trigger, a quantity, or both, based on demand rate, lead time, and the cost of holding stock versus running out of it.

Get the model wrong for an item and you either tie up cash in slow-moving stock or run stockouts on fast-moving parts. Get it right and the same warehouse holds less total inventory while service levels go up.

There is no single correct model. A fastener used across twenty products behaves nothing like a semi-finished casting made to a specific customer’s forecast, and Indian SME manufacturers usually need two or three models running side by side across their SKU base.

Inventory Control Models Compared

Which Inventory Control Model Fits Your Factory?

Catches overload before it happens. A work center running past capacity shows up in the plan, not on the shop floor three days before a ship date.
Grounded in real data. CRP pulls from the bill of materials, routing, and master production schedule instead of a supervisor’s gut feel.
Points to the actual bottleneck. When capacity falls short, CRP identifies which work center and by how much, not just that something is wrong.
Supports realistic promise dates. Sales can commit to delivery dates the shop floor can actually hit.
Needs current data to work. CRP is only as accurate as the routing, BOM, and capacity data feeding it.

Model

Best Fit For

Complexity

EOQ (Economic Order Quantity)

Stable demand, single-SKU reordering

Low

ABC Analysis

Large SKU counts needing value-based prioritization

Medium

Min-Max (Fixed Reorder Point)

Simple manual reordering with a safety buffer

Low

Fixed Reorder Period

Periodic supplier visits or scheduled ordering cycles

Low

JIT (Just-in-Time)

Lean, high-turnover production with reliable suppliers

High

Two-Bin System

Small parts and fasteners needing a visual reorder cue

Low

How Each Model Actually Works

Here is what each of the most-used models means in practice for an Indian manufacturer:

EOQ balances ordering and holding costs. EOQ = the square root of (2DS/H), where D is annual demand, S is cost per order, and H is holding cost per unit per year. It assumes stable demand and fixed costs, so it fits standard, single-SKU items more than volatile ones.
ABC Analysis ranks stock by revenue contribution. Roughly the top 10-20 percent of SKUs by value get grouped as A (tight control, frequent counts), the next tier as B, and the high-volume, low-value tail as C (loose control, infrequent review).
Min-Max sets a floor and a ceiling. Reorder triggers the moment stock falls to the minimum, and the order brings it back up to the maximum, a simple rule that works well without dedicated software.
Two-Bin uses a physical trigger instead of a number. The second bin is opened only when the first runs out, and that becomes the reorder signal, useful for small parts and fasteners tracked on the shop floor rather than in a system.

Sawtooth chart showing stock level dropping to a reorder point, an order being placed, and stock rising again after lead time

Common Mistakes When Choosing a Model

Most inventory control failures are not about picking the wrong formula, they are about applying one model to every SKU regardless of fit:

Running EOQ on volatile-demand items. The formula assumes stable demand; feeding it seasonal or lumpy demand data produces an order quantity that is wrong in both directions.
Skipping the ABC split entirely. Reviewing every SKU at the same frequency wastes time on low-value C items and under-reviews the A items that actually move revenue.
Setting Min-Max levels once and never revisiting them. Demand shifts, lead times change with new suppliers, and a Min-Max band set a year ago quietly becomes wrong.
Ignoring lead time variability. A supplier that used to deliver in 5 days and now takes 12 will blow through a reorder point sized for the old lead time.
Managing multi-location stock with a single-location model. Every model above assumes one stocking point; with multiple warehouses, the reorder trigger needs to account for where the stock actually sits.

Still deciding your reorder point on a spreadsheet, one week behind the shop floor?

TranZact gives you real-time stock levels and automatic reorder alerts, so whichever model you pick actually triggers on time instead of after someone remembers to check.

See automatic reorder alerts in action →

Where TranZact Fits for Inventory Control

TranZact does not auto-select an inventory control model for you, what it gives you is real-time stock levels across every warehouse, plus automatic reorder alerts and stock ageing history so whichever model you choose actually gets triggered on time.

That is not the same as a dedicated forecasting or ABC-classification module, and we would rather say that plainly than have you assume otherwise. For most Indian SME manufacturers, accurate real-time stock data plus a disciplined manual model, ABC first, then EOQ or Min-Max per category, covers the gap well.

FAQs

What is the most commonly used inventory control model?

EOQ and ABC Analysis are the two most widely used. ABC Analysis is often applied first to prioritize SKUs, and EOQ or a reorder-point model is then applied within each category to decide order size and timing.

What is a probabilistic model of inventory control?

A probabilistic model uses probability distributions, rather than a single fixed number, to plan for demand that varies unpredictably. It adds a safety stock buffer sized to the level of demand uncertainty, instead of assuming demand is constant.

Can small manufacturers run these models without dedicated software?

Yes, for a limited SKU count. ABC Analysis and Min-Max both work on a spreadsheet. The model breaks down once SKU count, multiple warehouses, or supplier lead-time variability make manual tracking too slow to catch a reorder point in time.

How does EOQ differ from Min-Max?

EOQ calculates one fixed order quantity meant to minimize total ordering and holding cost, assuming stable demand. Min-Max instead sets a reorder trigger (minimum) and a target level (maximum), and the actual order quantity varies each time based on how far stock has fallen.

Can a manufacturer use more than one inventory control model at once?

Yes, and most Indian manufacturers do. A common setup runs ABC Analysis across the full SKU base, then applies EOQ to stable A-category items, Min-Max to B-category items, and a Two-Bin visual system to low-value C-category fasteners and hardware.