Inventory analysis entails knowing the optimal number of products that a business should carry. It involves understanding the different variables that affect the production, sales, demand, and distribution of goods. By bringing all these elements together, decision-makers can paint a clearer picture of the warehouse’s operations and anticipate how much customers will want.
There are many techniques, methods, practices, and approaches for inventory optimization. The key is to orchestrate them around clearly defined goals and strategies and use the right data to complement their adoption.
Inventory analysis is more than just matching stocks with consumer demand. Transactions and inventories change hands between vendors, suppliers, manufacturers, packagers, distributors, warehouse workers, delivery drivers, and even multiple warehouses, to name a few. They influence the movement of merchandise, and they must be accounted for as they go to their final destination — the customers.
To track this movement, however, warehouse managers and their staff must know which type of inventory is going to where, what inventory should be prioritized, or when it’s expected to be delivered. Inventories are classified differently at various points in the supply chain and become data points that must be tracked to ensure their seamless transitions.
Inventories are commonly categorized into raw materials and components, work in progress (WIP), finished goods, and maintenance, repair and operations (MRO) goods.
Many companies might further itemize inventories depending on their use, the nature of their business, or the scope of their warehouse operations:
Raw materials: Resources used to create products. Raw materials become unrecognizable when they transform into finished goods.
Components: Similar to raw materials, but they remain recognizable from their original form when they become finished goods.
Work-in-progress (WIP): Also known as in-process or work-in-process inventory, which encompasses resources used in production (including raw materials or components, labor, and packing materials).
Finished goods: Products that have completed the manufacturing process and are available for sale and distribution.
MRO goods: Resources that support the production and manufacturing process or ensure business continuity.
Packaging and packing: Resources that separate and protect the product, further secure it, and provide labels and stock keeping unit (SKU) information. They also include materials that package SKUs in bulk and ready them for transportation.
Safety and anticipation stocks: Extra inventory meant to cover unforeseen situations or meet expected increases in demand. Safety stocks carry additional costs but ensure availability for the customer. Anticipation stocks are commonly based on trends in sales and production, or supply and demand in the case of raw materials and components.
Decoupling inventory: Additional resources or WIP inventory set aside at the production line to avoid disruption. Decoupling inventory mainly applies to manufacturing companies or businesses whose production lines work at varying speed.
Cycle stock: Products, raw materials, and components that are reserved to fulfill minimum production quotas or immediately satisfy sales orders.
Service inventory: The capacity or bandwidth of a service in a given period. It’s related to sales and revenue management. Examples include airline seats that expire once the flight takes off, hotel rooms that have a certain number of stays in a month, and table reservations in restaurants.
Transit inventory: Also known as pipeline or transportation inventory and refers to goods in transit between the manufacturer, warehouses, distribution or fulfillment centers, and buyers.
Theoretical inventory: Also called book inventory and refers to inventories reported on bookkeeping systems. This is mostly used to compare with actuals.
Excess or obsolete stock: Unsold, unused or nonproductive goods, raw materials, components, and other resources.
The principles behind inventory analysis are to decouple supply and demand, safeguard against outliers, and anticipate future trends while also keeping the operations running. Inventories go through intricate processes across the business and come in various forms, levels, and stages of completion. It’s important for warehouse managers to understand their complexities first.
These complexities are what makes inventory management multifaceted — one overlooked detail or outlying event can make or break the supply chain, which, in turn, has a domino effect throughout the company. There is no one-size-fits-all approach to analyzing and managing inventory: Each product from a single brand or manufacturer, for example, could have their own unique business model, and should be managed differently.
Mixing and matching these approaches should be based on priorities in the supply chain and overall business strategy. Here is a gist of the use cases and caveats of different approaches in inventory analysis and management:
| Inventory Analysis and Management Approach | How It Works | Use Cases and Caveats |
|---|---|---|
|
ABC analysis |
Divides items based on business value, with A as the most important and C as the least important Value and importance can be measured through different criteria, such as annual, quarterly, or monthly sales, profit margin, and consumption volume Enables companies to control and focus on items that generate the most business to the company, which helps reduce costs |
Gives a structured, easily digestible view on inventories and their value Might have a limited perspective on new product introductions or seasonality and novelty of products Requires standardization that might be too time-consuming and resource-intensive; needs some level of automation to achieve optimal results |
|
VED analysis |
Categorizes items based on their functional importance and value Divides items whether they are vital (a must), essential (a minimum amount is enough), or desirable (optional), and commonly measured through shortage costs |
Enables managers to ensure the availability of critical items
Most useful for companies that manufacture and stock parts and components or hospitals and suppliers of medical or pharmaceutical products |
|
HML analysis |
Classifies inventory based on a product’s unit price (high, medium, low)
Usually used together with ABC or VED analysis, or both |
Helps managers assess the security and storage requirements for high-priced items
Enables the company to control its purchase and consumption of materials Might have limited perspective on the ROI of products |
|
SDE analysis |
Categorizes items based on availability and supply (scarce, difficult, easy)
Scarce items have the longest lead time and are often imported; difficult materials have lead times of less than six months; easily available items are procured locally and sourced quickly |
Useful for planning the procurement of stocks and help managers focus on items that have problematic or longer lead times
Might have a limited perspective on items with the same availability but different procurement characteristics |
|
Consignment stock/inventory |
Inventory is owned by one party but held by another
Payment terms are favorable, since payment is only due after the product’s use Commonly adopted for retail and pharmaceutical products where there’s an opportunity to showcase products in front of a bigger customer base |
More useful for managing fast-moving items that will be used or consumed in a very short term More suitable as part of a vendor-managed inventory (VMI) agreement where the stock profiles of different items have already been defined Can be risky for suppliers because they don’t receive payment until the inventory is sold |
|
Cycle counting or perpetual inventory counting |
Involves regular, repeated checking of preselected sections in inventory
Can be done by starting in one area of the warehouse then proceeding with the rest on a rotating basis |
A good alternative to annual stock counts by spreading the effort throughout the year
Useful for counting items that have more value or are fast movers |
|
Maister’s rule (aka the square root rule of inventory) |
Expressed as a formula for estimating the size and cost of inventory and calculating the required safety stocks based on the number of warehouses |
Can be valuable when making strategic decisions on operations where the costs of infrastructure, labor, equipment, and transport are taken into account |
|
Demand variability |
Quantifies predictability (or unpredictability) in customer demand Can be used when looking at trends, customer forecasts, and historical product demand data |
Useful for setting safety stocks based on the finished product’s level of availability
Needs reliable and accurate historical and point-of-sale data to be better forecast demand |
|
Periodic review system |
Inventories are reviewed at fixed, regular intervals and checked if they need replenishment
Used in conjunction with digital inventory management systems where safety stocks, cycle stocks, and delivery lead times are automatically computed |
Needs some level of automation, digitization, and digitalization
Can be useful for reviewing a vast number of items spread across different warehouses Can be used in retail and self-service stores where stock levels are reviewed at the end of each afternoon and orders are sent to distribution centers for delivery |
|
Reorder point system (ROP) |
Measures the minimum level of inventory within the warehouse for specific items where replenishment orders are triggered
Reorder points are calculated based on the item’s sales velocity and lead time |
More suitable for products that aren’t significantly affected by demand
Might not be the most efficient approach for minimizing costs in transportation and logistics as different orders (depending on the reorder point) can be made to different suppliers |
|
Replenishment order quantities |
Similar to ROP but is based on quantity; both approaches can be used to determine the exact orders needed
Calculated through average daily usage or consumption and average lead time |
Only used to understand the practicable and optimal quantity of items to be ordered
Can be used to control inventory when vendors or suppliers insists on a minimum order quantity or value |
|
Economic order quantity |
Identifies the ideal amount of inventory that should be ordered while minimizing costs
Measures costs based on warehouse ownership or tenancy, the staff needed to operate the warehouse, and lost revenues from obsolete or unavailable stock, among others |
Needs assessment if the warehouse can hold additional or higher inventory
Can be used if the company has enough resources to manage larger batches of items and shoulder the risk of obsolete stocks Can be used if the incentives of ordering larger items outweigh the risks |
|
Safety stock calculation (aka buffer or security stock) |
An insurance policy that calculates additional stock needed to account for unforeseen delays or disruptions, customer-driven variations, or changes in demand |
Required when demand is higher than average and if the replenishment and delivery lead times are unpredictable
Can be used to compensate in failures in delivery lead times |
|
Stock/inventory turn |
Estimates the average number of times that a raw material, component, or product goes in and out of the warehouse over a certain period
Calculated for individual items |
Required for measuring inventory performance on a daily, weekly, or monthly basis; manufacturing warehouses or distribution centers can measure stock turns monthly or every half-year
Useful for determining if specific items are fast or slow movers |
In inventory optimization and management, less is more — as long as you can replenish the product and deliver it on time. Having “less,” however, means having more data. After all, you can’t manage or improve the warehouse’s operations without measuring it.
That’s where warehouse analytics figure into inventory analysis. By analyzing key data points on the warehouse and the inventories it produces, holds, sells, or distribute, managers and decision-makers can proactively strike a balance between efficiency and profitability.
Many organizations already recognize the significance of data and analytics in their supply chains. In fact, 91% of surveyed chief supply chain officers said they are actively investing on advanced analytics to bridge the operational and strategic divide. This means transforming their data into actionable sales, supply, and demand forecasts, assessing risks, avoiding disruptions, automating business processes, and delivering an omnichannel experience. Through 2024, 50% of organizations will have AI, machine learning, and advanced analytics embedded in their supply chains. Over half of surveyed supply chain leaders also increased their investment last year in digital technologies and predictive analytics capabilities to optimize inventory management.
Data is foundational to inventory optimization and warehouse management. You need data to know which items you need — at the right time and in the right quantities — where and how you should store them, and when you should buy or sell them. You also need data to see if your team is meeting your KPIs. You need data to get to know your customers, retailers, and distributors better and anticipate their needs and demands. More importantly, you need a platform that can aggregate and visualize these data points into actionable information that can be used to enrich the business’s value and supply chains.
Lingaro Group’s supply chain analytics practice provides data engineering and advanced analytics services for logistics, warehousing, and transportation that enable enterprises to drive cost efficiencies and enhance service levels and operational efficiency. Lingaro helps organizations use data to gain end-to-end visibility in their supply chain that, in turn, enables them to accurately forecast demand, enhance resilience and responsiveness, maximize inventories, optimize resource allocation, streamline routes, minimize waste, and generate savings.