Let’s imagine we have an inventory system. Two of its customers decide to order the last remaining unit of a given product at roughly the same time. Does our application allow both of these orders to go through?
This is just one example of a complex series of constraints and rules which go into making an inventory system.
Spreadsheets can be useful, but businesses that want centralized visibility, automation, and protection from mistakes need something more powerful.
Let’s look at some fundamentals of the inventory application development process and consider how engineers can build more robust, reliable tools.
1. Build Inventory Records With Audit Trails
Begin by creating or identifying the data model which our application will use. At the simplest possible level, this might consist of a product ID, product name, SKU, and stock quantity.
In practice, however, it will likely be necessary to track more information. Perhaps we will need to track where inventory is stored, or what products have been reserved for specific customers. Auditing and debugging issues later on will become significantly easier if we leave behind a paper trail of what events occurred and when.
Some examples of this information might include:
• What inventory adjustments have occurred? Has inventory been received from a supplier, sold to a customer, or returned? Has it been transferred from one warehouse to another?
• How did the application reach the state that it is currently in?
• What is the reason for this adjustment? Does it involve an order or reservation?
• What quantity of the given product has been physically affected by this transaction?
• What time did this occur, and what other contextual information might be relevant?
We may also want to associate inventory records with other values, such as an order ID or a customer reserving this product. In a multi-warehouse environment, a given inventory record might also have a location field.
Depending on specific business logic, the data model will take shape. It is important to track all of the relevant adjustments as transactions and build an auditable paper trail.
2. Avoid Overselling With Transactional Integrity
Let’s return to the example of two customers attempting to place an order for the last remaining unit of a product. We want to sell one unit of this product to one customer and prevent the other customer from getting the same item, but it is very difficult to do so if both processes read and write information concurrently.
Using a relational or NoSQL database engine, it might be possible to prevent this sort of issue through transactions and concurrency controls.
The above SQL statement, for instance, will reduce a product’s inventory by 1 if the quantity of this product is at least 1 and prevent any such changes from occurring otherwise.
An application making this request should then be able to determine whether one row was affected (in which case the update was successful) or zero rows (in which case the requested update has failed). This is useful, but there are also additional nuances and edge cases which need to be considered. This includes whether this is the right approach in the context of a reserve-inventory system, what happens if a similar request comes in again later, what occurs when transactions need to be applied concurrently, inventory location and availability, or how this will impact order cancellations.
The point is to ensure that the application itself prevents overselling rather than relying solely on application-layer controls.
3. Automate Inventory Updates With Caution
Inventory automation systems can be immensely helpful. By ensuring that inventory changes occur automatically when certain processes are followed, there is less of a need for manual records or adjustments to go wrong. An automated inventory application might automatically update quantity fields when a purchase is made or an order is processed.
There is a good reason to be cautious, however. The same automation that helps can also hurt if there is no appropriate protection in place. For instance, if the application tries to update inventory again after it has already done so successfully, it will lead to double-counting errors.
We can avoid such issues by including appropriate transaction constraints, such as idempotency keys. Inventory record validation is also important, particularly since we will be working with other systems such as payment processors, order management tools, and warehouses.
4. Barcode Reader And RFID Inventory System Software Requirements
Barcode scanners and RFID (radio-frequency identification) readers offer similar advantages. They allow products to be uniquely identified without requiring human intervention. They are valuable tools in warehouses, as they can help ensure that physical inventory changes are reflected in digital inventory records. They can work in tandem with inventory applications or be incorporated as part of an integrated system.
RFID readers operate differently than barcode scanners and can be further categorized into active and passive variants, depending on whether RFID tags are powered by their own batteries.
An RFID reader will generally operate within a working range (a distance of several centimeters to a few meters) and scan for RFID tags within this area. If RFID tags are affixed to products within this range, it will be possible to obtain unique RFID identifiers for these products.
As with barcode scanners, the specific details will vary depending on the specific use case. Some examples might involve scanning barcodes or QR codes, scanning multiple products at once, determining quantity, or performing inventory verification.
From a software standpoint, such systems should be able to translate a barcode or RFID tag into a given product. The application will also want to verify that the request is legitimate and actually allowed and perform the relevant inventory adjustments for the given RFID or barcode.
It is necessary to choose a method based on the specifics of the inventory environment. RFID systems tend to be more valuable at certain points and less valuable at others. They are generally much more expensive than traditional barcode scanners, for instance, but do not always need to be applied to individual products and can be read without being seen.
5. Inventory Application API: Exposing Product Catalog And Inventory
Inventory applications tend to integrate with a variety of other tools, ranging from e-commerce platforms to enterprise resource planning systems. An API will generally want to expose how inventory information is structured, how requests should be processed, and what error conditions can occur. There are also broader architectural decisions which need to be made as well.
Some important considerations include authorization, authentication, validating incoming requests (particularly IDs), rate limiting, transaction retries, error reporting, and product categorization.
Larger applications, in particular, should consider implementing an event-driven or asynchronous architecture, rather than making direct requests and receiving responses. In practice, asynchronous systems can be even more challenging to develop and are often more error-prone, unless there is a very compelling reason to adopt them. A database and transaction engine will likely suffice for the needs of most applications.
6. Build Inventory Management Reports And Insights To Support Decision Making
Inventory records can be analyzed to produce insights on inventory performance. The application can detect patterns and trends relating to inventory records, such as the most popular products, inventory turnover, or inventory shrinkage.
Historical sales and purchase records, when combined with current inventory records, can help in building forecasts and detecting demand fluctuations.
Reports produced by an inventory application should be focused on answering specific questions. What products are approaching their minimum threshold? What records need to be adjusted? Which products are consistently low-selling or high-selling? Where are the main bottlenecks and delays in operation?
Consistent metrics allow managers and executives to analyze the performance of this application and the state of the business in general, but only if the underlying records are accurate and trustworthy.
7. Test Edge Cases And Failure Scenarios In Inventory Applications
Applications should be tested not only against normal operations, but also against abnormal operations. It is important to have processes in place to manage unexpected problems, such as orders going through which should not have, inventory adjustments canceling each other, or inventory records becoming completely unusable. In the context of inventory applications, a few sample test scenarios might include the following:
• Attempt to reserve the same inventory item for two orders simultaneously.
• Submit the same request several times to an API endpoint.
• Cancel an order that had previously reserved some inventory.
• Return a product and increase its inventory.
• Cancel a warehouse transfer.
• Submit a request to an external API that times out.
• Adjust inventory quantity through an unauthorized or unexpected method.
• Ensure that failed transactions do not leave the system in an inconsistent state.
• Ensure that a few important inventory transactions are properly traceable in case of an incident.
It is important to test the integrity of the system under conditions simulating some of these problems. In practice, inventory errors tend to occur not during normal operation but at the interfaces between systems.
8. Inventory Platforms: Selecting The Best Option For Your Business
Inventory control and management systems vary widely in terms of scale, scope, and capabilities. The choice of one option over another will be informed by the specific needs of the business and its suppliers. Businesses considering this decision should examine its existing procedures and plan accordingly.
The Inventory Master web page offers a number of resources for engineers and managers interested in building or selecting an appropriate toolset. Businesses can use this resource to learn more about the available approaches and select a viable option. Documentation and requirements analysis can help set expectations and ensure that a given selection fits the needs of the business rather than the other way around.
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