Inventory is the lifeblood of product-based businesses. Too much of it ties up cash, and too little can lead to lost sales. That’s where using all inventory formulas strategically comes in — they help businesses maintain optimal stock levels, minimize costs, and meet customer demand efficiently.
Businesses use both common inventory formulas and advanced formulas. This depends completely on the size, needs, and processes of the organization.
Key Inventory Terms to Know
Inventory: The goods and materials a business holds for sale or production.
Cost of Goods Sold (COGS): The direct costs of producing or purchasing the goods that a company sells during a period.
Beginning Inventory: The value of a company’s inventory at the start of an accounting period.
Ending Inventory: The value of inventory on hand at the end of an accounting period.
Average Inventory: The average value or quantity of inventory during a period.
Demand: The quantity of a product that customers want in a given time frame.
Lead Time: The time between initiating an order for stock and receiving that stock.
Holding Cost: The total cost of storing and maintaining inventory over a period, usually expressed annually.
Ordering Cost: The expenses incurred each time you place an order for inventory.
Obsolete Inventory: Stock that a business can no longer sell or use because demand for it has dried up.
Shrinkage: Inventory losses that occur due to theft, damage, spoilage, or errors.
Backorder: A customer order that cannot be filled immediately because the item is out of stock but will be filled later once inventory is replenished.
Core Inventory Formulas With Examples
| SL | Formula Name | Formula |
|---|---|---|
| 1 | Inventory Turnover | COGS / Average Inventory |
| 2 | Days Sales of Inventory (DSI) | (Average Inventory / COGS) × 365 days |
| 3 | Average Inventory | (Beginning Inventory + Ending Inventory) / 2 |
| 4 | Economic Order Quantity (EOQ) | √(2 × D × S / H), where D = annual demand, S = ordering cost per order, H = annual holding cost per unit) |
| 5 | Reorder Point (ROP) | (Average Daily Usage × Lead Time) + Safety Stock |
| 6 | Safety Stock | (Max Daily Usage × Max Lead Time) - (Average Daily Usage × Average Lead Time) |
| 7 | Cost of Goods Sold (COGS) | Beginning Inventory + Purchases - Ending Inventory |
| 8 | Lead Time Demand | Daily Demand × Lead Time |
| 9 | Cycle Stock | Cycle Stock Order Quantity - Safety Stock |
Inventory Turnover Ratio
This formula measures how many times your inventory is sold and replaced in a given period. It indicates how efficiently a company manages its stock.
Formula:
Inventory Turnover = COGS / Average Inventory
Use Case:
- A high turnover ratio suggests strong sales or effective inventory management
- Low turnover ratio indicates weaker sales or possible overstocking
- Grocery stores have very high turnover (perishables sell fast), while luxury car dealers have lower turnover.
Example:
COGS = $100,000
Beginning Inventory = $20,000
Ending Inventory = $30,000
Average Inventory = (20,000 + 30,000) / 2 = $25,000
Inventory Turnover = 100,000 / 25,000 = 4 times
Days Sales of Inventory (DSI)
Days Sales of Inventory (DSI) is also known as Days Inventory Outstanding (DIO). It measures the average number of days it takes to sell through inventory on hand. It’s essentially the inverse of inventory turnover, converted to days.
Formula:
(Average Inventory / COGS) × 365 days
Use Case:
- DSI is used in financial analysis to assess liquidity of inventory.
Example:
Suppose a car dealership carries an average inventory of $5,000,000 (at cost) and has COGS of $20,000,000 annually.
DSI = (5,000,000 / 20,000,000) × 365
= 0.25 × 365
= 91 days
Average Inventory
Average Inventory is the typical amount of stock a company has over a period. It smooths out seasonal or irregular spikes by averaging beginning and ending inventory. This provides a more stable basis for analysis like turnover ratio.
Formula:
(Beginning Inventory + Ending Inventory) / 2
Use Case:
- It’s especially useful when inventory levels fluctuate.
- Businesses also track average inventory over longer periods to plan storage needs and capital requirements.
Example:
A toy manufacturer had $200k in inventory on January 1 and $300k on December 31.
Annual average inventory:
= (200k + 300k) / 2
= $250,000
Economic Order Quantity (EOQ)
It is the optimal order size that minimizes total inventory costs. EOQ balances two opposing costs: ordering costs (which decrease per unit as you order more at once) and holding costs (which increase as you hold more inventory).
Formula:
EOQ = √((2 × Demand × Ordering Cost) / Holding Cost)
Or,
EOQ = √(2 * D * S / H)
- D = annual demand (units per year),
- S = ordering cost per order (fixed cost each time you order),
- H = annual holding cost per unit (often the unit cost * carrying cost %, or a given cost per unit).
Use Case:
- EOQ tells you how much to order each time to be most cost-effective.
- Companies use EOQ mostly for stable products with steady demand. It’s less useful if demand is erratic or if there are quantity discounts
Example:
A retail shop sells about 2,400 units of a product per year (200 per month). Placing an order costs $30 in admin and shipping. Holding a unit for a year costs $5 (storage, insurance).
EOQ:
= √(2 * 2400 * 30 / 5)
= √(2 * 2400 * 6)
= √(28,800)
= 170 units
Reorder Point (ROP)
The Reorder Point is the inventory level at which you should trigger a replenishment order to avoid running out. It answers when to order more. The ROP accounts for the demand expected during the lead time plus a safety buffer.
Formula:
(Average Daily Usage × Lead Time) + Safety Stock
Use Case:
- Businesses calculate a ROP for each item so that when inventory falls to that threshold, they know it’s time to reorder.
Example:
A pet food store sells an average of 5 bags of dog food per day. Delivery from the supplier takes about 7 days after placing an order. The manager keeps 10 bags as safety stock to handle any demand spikes or delays.
Here, Lead Time Demand
= 5 * 7 = 35 bags.
Adding safety stock of 10 bags,
Reorder Point = 35 + 10
= 45 bags.
Safety Stock
It shows the buffer inventory kept to protect against uncertainties, such as higher-than-forecast demand or supplier delays. It’s “just-in-case” inventory.
Formula:
(Max Daily Usage × Max Lead Time) – (Average Daily Usage × Average Lead Time)
Use Case:
- Companies use it to prevent backorders or lost sales without grossly overstocking.
Example:
A pharmacy dispenses on average 20 bottles of a certain medication weekly, and resupply lead time averages 2 weeks. However, occasionally demand can spike to 30 bottles in a week and supplier delays up to 3 weeks have occurred.
Max weekly usage (30) * max lead time (3 weeks)
= 90;
Average weekly usage (20) * avg lead time (2 weeks)
= 40;
Safety Stock = 90 – 40
= 50 bottles
Cost of Goods Sold (COGS)
COGS represents the cost attributable to the goods that were sold during a period. It links beginning inventory, purchases, and ending inventory.
Formula:
COGS = Beginning Inventory + Purchases – Ending Inventory
Use Case:
- COGS is fundamental in accounting to determine the cost of sales on the income statement and the value of ending inventory on the balance sheet.
- From an inventory management perspective, knowing COGS helps in calculating turnover ratios and in evaluating gross profit.
Example:
A bookstore began the quarter with $80,000 worth of books in stock. It purchased $50,000 more during the quarter. At quarter’s end, the inventory count values to $70,000.
COGS:
= 80,000 + 50,000 – 70,000
= $60,000.
Lead Time Demand
Lead Time Demand is the quantity of a product that is expected to be sold (or used) during its lead time. Essentially, it’s how much demand accumulates while waiting for an order to arrive.
Formula:
Lead Time × Average Daily (or weekly) Demand
Use Case:
- Tells you the baseline stock you need on hand when you place a new order.
- Businesses also use it for scheduling production in manufacturing (how much of component X will be used in the next two weeks of production runs?).
Example:
A hardware supplier sells 100 units of a power drill per week on average. The lead time from the manufacturer is 3 weeks.
Average weekly demand (100) × 3 weeks
= 300 drills
Cycle Stock
Represents the portion of inventory that is expected to be sold based on normal demand cycles, as opposed to safety stock which is extra. Cycle stock is the regular inventory that you cycle through to meet customer orders. It rises and falls as you receive and sell units in routine ordering cycles.
Formula:
Cycle Stock = Average Inventory – Safety Stock
Use Case:
- By distinguishing cycle stock from safety stock, companies can better analyze their inventory.
Example:
A retailer carries 300 units on average of a certain phone model and keeps 50 units of those as safety stock.
Cycle Stock:
= 300 – 50
= 250 units
Advanced Inventory Formulas With Examples
Beyond the basics, there are advanced inventory formulas and metrics that help analyze profitability, customer service, and operational efficiency.
Gross Margin Return on Investment (GMROI)
GMROI (Gross Margin Return on Inventory Investment) measures how much gross profit you earn for each dollar of inventory you invest in. It’s a profitability ratio for inventory
Formula:
GMROI = Gross Margin / Average Inventory Cost
Use Case:
- Retailers and wholesalers use GMROI to evaluate inventory productivity
Example:
A clothing boutique has an average inventory cost of $50,000 and generated $120,000 in sales last quarter with a COGS of $60,000.
The gross margin = 120,000 – 60,000
= $60,000.
GMROI = 60,000 / 50,000
= 1.2, or 120%
Sell-Through Rate
Sell-Through Rate (STR) is the percentage of inventory sold during a period relative to the amount of inventory received or available in that period. Typically measured monthly, it shows how quickly stock is selling.
Formula:
Sell-Through Rate (%) = (Units Sold in Period / Units Received or On Hand in Period) × 100
Use Case:
- A popular metric in merchandising and retail planning.
- It helps identify winners and losers in the product assortment.
Example:
An electronics store received 500 units of a new smartphone model in a quarter. By the quarter’s end, 450 units were sold.
Sell-Through Rate:
= (450/500) × 100
= 0.9 × 100
= 90%
Backorder Rate
This metric indicates the proportion of orders you couldn’t fulfill immediately because items were out of stock. It reflects how often customers face backorders.
Formula:
Backorder Rate (%) = (Number of Orders Backordered / Total Orders) × 100
Use Case:
- Companies monitor backorder rate as a service level KPI. A low backorder rate is generally a sign of good inventory availability.
Example:
An online hobby shop received 500 orders last month. Due to some stockouts, 20 orders couldn’t be completely fulfilled (those customers either waited or got partial shipments).
Backorder Rate:
= (20/500) × 100
= 4%
Shrinkage Rate
Shrinkage rate is the percentage of inventory lost to theft, damage, spoilage, or record-keeping errors. It quantifies inventory shrinkage as a fraction of what should have been there.
Formula:
Shrinkage (%) = ((Book Inventory – Actual Inventory) / Book Inventory) × 100
Use Case:
- This metric is crucial in retail and manufacturing.
- Companies strive to minimize shrinkage through security, training, and process improvements.
Example:
A convenience store’s inventory system shows $50,000 of products should be in stock, but after a physical count, only $48,500 worth is actually on shelves/storage.
Shrinkage:
= (50,000 – 48,500) / 50,000 × 100
= 1,500 / 50,000 × 100
= 0.03 × 100
= 3%.
Fill Rate
This is the percentage of customer orders (or order lines) that you can fill completely from stock without backordering or missing items.
Formula:
Fill Rate = (Orders Fulfilled in Full / Total Orders) × 100%
Use Case:
- Fill rate is a key customer service metric.
- Can be tracked by channel, product, or warehouse to pinpoint issues.
Example:
A wholesale distributor received 500 orders today. Out of these, 485 orders shipped complete, while 15 had at least one item short (backordered).
The order fill rate:
= 485/500 × 100
= 97%
Inventory Accuracy
Inventory Accuracy is the degree to which the inventory records (in an ERP or inventory system) match the actual physical inventory. High accuracy means your books reflect reality, which is essential for trustable data.
Formula:
Inventory Accuracy (%) = (Counted Quantity / Recorded Quantity) × 100
Use Case:
- Inventory accuracy is critical for financial reporting (the inventory asset value) and for automated reordering
Example:
A warehouse performs cycle counts every week on a sample of SKUs. This week, they counted 200 units across various items, but the system said there should be 210.
The Inventory Accuracy:
= (200/210) × 100
= 95.2%
Holding Cost Percentage
Holding Cost Percentage is the annual cost to hold inventory expressed as a percentage of the inventory value. It encapsulates all carrying costs (storage, capital, insurance, obsolescence, etc.) relative to the inventory’s worth
Formula:
Holding Cost % = (Annual Total Carrying Costs / Average Inventory Value) × 100%
Use Case:
- Knowing your holding cost % is important for decisions like how much inventory to keep and for calculating EOQ.
Example:
A distributor calculates its inventory carrying cost components: storage and handling $100k, cost of capital $50k (opportunity cost of money tied in inventory), insurance $10k, and depreciation/spoilage $40k, totaling $200k per year. Their average inventory is $800k.
Holding Cost Percentage:
= (100k+50k+10k+40k)/800k
= (200k/800k) × 100%
= 25%.
Carrying Cost Per Unit
Carrying Cost per Unit is the dollar amount it costs to hold one unit of an item in inventory for a year. It’s basically the holding cost % applied to the unit’s cost or derived from total costs divided by total units.
Formula:
Carrying Cost per Unit = Total Annual Carrying Costs / Average Units in Inventory
Use Case:
- Carrying cost per unit is useful for calculating EOQ.
- Companies might factor carrying cost into the pricing of slow-moving items.
Example:
A furniture company determines its holding cost is $2 million per year, and on average they have 10,000 pieces of furniture in inventory (ranging from chairs to sofas).
The average carrying cost per unit
= 2,000,000 / 10,000
= $200 per unit per year
Total Inventory Cost
Total Inventory Cost, in this context, usually means the sum of all relevant costs associated with inventory. This often includes Purchase costs, Ordering costs, Holding costs, and Stockout/Shortage costs.
Formula:
Total Inventory Cost = Purchase Cost + Ordering Cost + Holding Cost + Shortage Cost
Use Case:
- Businesses calculate total inventory cost to evaluate their inventory policies.
Example:
Let’s say a parts supplier has annual demand for a part of 10,000 units. Unit purchase cost is $5 (so $50k if they meet all demand). If they order in batches of 1,000, that’s 10 orders/year. Ordering cost per order is $100, so annual ordering = $1,000. Holding: average inventory = 500 units (half of 1,000) and holding cost per unit $1/year, so annual holding = $500. If occasionally they run short, they estimate a shortage cost of $200 per year (expedited shipping fees and some lost sales).
So, total inventory cost:
= $50,000 (purchase) + $1,000 (ordering) + $500 (holding) + $200 (shortage)
= $51,700 for the year.
Obsolete Inventory Percentage
This indicates the % share of your inventory that is obsolete (unsellable or extremely slow-moving) among the total inventory.
Formula:
Obsolete Inventory % = (Value of Obsolete Inventory / Total Inventory Value) × 100%
Use Case:
- Firms track this to keep inventory lean.
Example:
A company selling phone accessories finds that older model cases and chargers have built up in the warehouse. They audit and identify $20,000 of inventory that hasn’t sold in over 2 years (for outdated phone models). Their total inventory is $200,000 at cost.
Obsolete Inventory Percentage:
= (20k/200k) × 100
= 10%.
Choosing the Right Inventory Formulas for Your Business
Not every formula is equally important for every business. The right set of inventory metrics and formulas depends on your industry, inventory type, business model, and goals. Consider the following factors:
- Inventory Type & Characteristics: The nature of your products can guide your focus. For perishable or time-sensitive goods (food, fashion), DSI and sell-through rate are critical. You need to sell before expiry or season’s end. For high-value items (e.g., jewelry, machinery), inventory turnover might naturally be lower, but accuracy and shrinkage control are paramount to avoid costly losses.
- Business Model (Retail vs. Manufacturing vs. eCommerce): Retailers mainly focus on sell-through, GMROI, and turnover to ensure shelf space is used effectively and to plan promotions. Manufacturers are very concerned with EOQ, reorder points, and safety stock for raw materials, ensuring production lines never stop while minimizing holding costs.
Tools and Software to Automate Inventory Formulas
Calculating and monitoring these formulas manually can be time-consuming, especially as your business grows. Many modern tools and software can automate the heavy lifting, providing real-time calculations and insights.
Financfy
Financy a comprehensive small-business accounting software that offers robust inventory management features. It’s designed to monitor stock levels in real-time and automate important calculations. It can use your sales history to suggest reorder points or safety stock levels. The system generates inventory reports (e.g., stock levels by item, valuation reports) that let you quickly derive metrics like turnover or DSI. Because it’s integrated with accounting, when you make a sale or purchase, your inventory and COGS are updated instantly.
Key features of Financfy’s inventory module include:
- Tracking products across multiple warehouses
- Setting reorder levels with alerts when stock hits the threshold
- Providing real-time inventory valuations using FIFO methodology
- Automatically compute things like current inventory value and COGS
QuickBooks
QuickBooks is a widely-used accounting software. In its Online Plus and Advanced versions it includes inventory tracking capabilities. QuickBooks allows you to set up each product with details like reorder point and preferred vendor. It then tracks inventory in real time. The tool also low stock alerts. With these features, the software effectively automates the ROP formula by telling you when to reorder.
While QuickBooks might not explicitly show formulas like EOQ or safety stock, it gives you the data (average sales, on-hand, on order, etc.) to compute them.
NetSuite
NetSuite is an ERP (Enterprise Resource Planning) system suited for medium to large businesses. It offers a very powerful Inventory Management module. Being an end-to-end solution, NetSuite can automate and optimize advanced formulas. For example, NetSuite has built-in demand planning and can automatically calculate reorder points and safety stock using historical data, seasonality, and even sales forecasts.
It supports multi-location inventory, tracking stock across warehouses and retail stores in one unified view. NetSuite can automatically trigger transfer orders or purchase orders when inventory at a location hits its reorder point.
Zoho Inventory
This software caters to small and mid-sized businesses, especially those doing multi-channel sales. It automates several inventory management tasks: order management, barcode scanning, multi-warehouse tracking, and integrations with e-commerce platforms.
With Zoho Inventory, you can set reorder points for each item and it will send automatic alerts when stock falls below those levels. This is essentially automating the ROP formula notification. It also helps with batch and serial number tracking (useful for tracking expiry and shrinkage causes).
Additionally, it supports automation workflows. For instance, automatically creating a purchase order when an item hits its reorder point, effectively automating the reorder process end-to-end.
Excel / Google Sheets Templates
For businesses not ready to invest in dedicated software, spreadsheets remain a powerful tool. Excel or Google Sheets templates can automate formulas on a smaller scale.
There are many pre-built inventory management templates available that include formula calculations. For example, an Excel template might allow you to input daily sales and current stock, and then automatically calculate projected run-out dates, turnover, DSI, and even signal reorder needs (using conditional formatting).
Many small businesses start with these templates. However, as inventory data grows, manual entry into Excel can become cumbersome and error-prone.
Real-World Example or Case Study
FlexiTog, a company specializing in cold-weather workwear, faced challenges with stockouts and excess stock. FlexiTog’s management decided to revamp their inventory strategy using the formulas we discussed.
They started by analyzing demand patterns and lead times for each product, calculating accurate Reorder Points and Safety Stock. They implemented EOQ for ordering from their overseas supplier, balancing the shipping cost (ordering cost) with holding cost.
FlexiTog reportedly decreased stockouts by 98% and achieved a 99.98% availability rate for customer orders. Almost every customer order could be filled immediately from stock, a huge leap in service performance. Additionally, by clearing obsolete stock and tightening ordering, they reduced total inventory by about 20% in value without compromising sales.
Key Takeaways From Applying Formulas
- By applying EOQ and safety stock formulas, FlexiTog balanced costs and service
- Computing and monitoring metrics like turnover, fill rate, and obsolete percentage helped pinpoint where to act
- FlexiTog sets up monthly reviews of inventory KPIs, making them a continuous process
Conclusion
For accounting and business professionals, the inventory formulas enable you to optimize inventory levels (cutting excess stock while avoiding shortages), improve financial metrics (like freeing up cash and increasing gross margin return), and enhance customer satisfaction (through high fill rates and low backorders).
The key is to pick the formulas that align with your business model and goals, monitor them regularly, and make the best use of modern tools to automate and support your analysis.
