Inventory management can be a complex business problem. Yet many modern inventory systems are underpinned by a deep technical infrastructure.
An inventory event, the receipt or the movement of stock, can comprise a spectrum of scanners, sensors, databases, API, business applications and reporting tools.
What may seem like a simple business event, a product going on or off the warehouse floor, is a deep technical implementation.
Modern inventory management systems deal simultaneously with an enormous variety of inventory events. There are product arrivals, movements and exits in various forms.
The key to inventory technology lies in being able to reflect the inventory information accurately in the face of these events.
Let’s Start with the Event
Perhaps the primary consideration in inventory is the event.
A warehouse receives 100 units of product X. There is presumably some sort of inventory event here. A database, an application, or even an API may need to be notified of said event.
So perhaps some information needs to be captured or stored.
This record might take the shape of various pieces of data:
Product ID:
Quantity:
Location:
Timestamp:
Transaction Type:
Source:
Now the event may update some inventory information:
Received: +100
Available Inventory: 500 → 600
Now imagine those 100 units of product X are being dispersed to various locations within the warehouse.
The inventory management system must appropriately reflect both the product, quantity, and location information.
Inventory management becomes a data architecture problem at this point.
Where Does the Data Come From?
There are several possible sources of information for an inventory system.
Barcode scanners
A barcode scanner can be used to pick up information about a product during receipt, picking, packing or shipping.
An application can learn what product has been scanned and apply the transaction to the inventory.
RFID
RFID is another way to identify an object through radio frequency technology.
Depending on the nature of the RFID infrastructure deployed, it can obviate the need for manual scanning in certain situations.
IoT devices
There are a variety of IoT devices that can be used to capture inventory information from the physical world.
A generalized IoT architecture could resemble the following:
Sensor
↓
Gateway
↓
Network
↓
Data Platform
↓
Inventory Application
↓
Dashboard / Business Process
The architecture will undoubtedly differ depending on the context and needs of the operation.
Humans
The human factor should not be discounted in an inventory system. There will undoubtedly be some situations where an employee needs to create or verify an inventory event.
There may be a web application, some sort of mobile interface, a warehouse management system or any number of other tools at the disposal of an employee.
Any effective inventory system should account for a variety of situations: automated and human-generated inventory events.
The Application Layer
Software is needed to take the inventory information and do something with it. A generalized architecture for an inventory application may resemble the following:
Physical Inventory
↓
Barcode / RFID /IoT
↓
Integration Layer
↓
Inventory Management System
↓
Database
↓
APIs / Business Applications
↓
Dashboards & Reports
The inventory management application, therefore, should encapsulate various business logic:
IF available_stock < reorder_threshold THEN
create_replenishment_signal
The actual realization will obviously differ depending on a company’s needs, but the basic idea is that the data about inventory should be valuable and usable information that can create meaningful decisions or actions.
APIs Become an Important Part of the Conversation
Modern businesses do not tend to use only one application. It is more likely that an organization uses an ecosystem of different business applications.
These applications might include an ERP system, a warehouse management system (WMS), a point of sale (POS) system, an e-commerce platform, transportation systems, inventory platforms, etc.
An effective technical architecture enables these various tools to communicate through API.
API enable these business applications to share information with each other.
An API-enabled architecture might resemble the following:
E-commerce Platform
↓
API
↓
Inventory System
↓
WMS
↓
Warehouse Operation
If proper inventory system integration does not occur, workers may need to perform the same actions in different applications.
This obviously opens the door to errors and duplication of efforts.
The Database Is only Part of the Puzzle
It is easy to assume that an inventory management application is simply a database about quantity on hand for various products.
The truth is, while the database does contain this valuable information, this is only a small piece of what an inventory application requires.
A functioning inventory application also requires: Transaction history, locations, product information, permissions, integration, data validation, data reporting, forecasting, and exceptions, among other things.
So in order to understand what 500 means in an inventory system: 500 what? 500 where? 500 as of when? 500 available or reserved? There are several crucial pieces of accompanying information that make up an inventory application beyond the raw quantity itself.
Real-Time Does Not Always Mean Right Now
It is also easy to believe that all inventory systems are fully integrated and are real-time.
The truth is, inventory systems do not always require real-time updating or adjustments. This depends on a company’s operational needs.
A retail business will have different inventory needs than a manufacturing facility. The former will require more emphasis on demand forecasting while the latter may focus more on supply chain management.
In any case, there are inventory applications that operate in real-time; however, this is not appropriate for all companies.
This is why architecture decisions should be based on operational needs as opposed to choosing an infrastructure based on a buzzword.
Where Does AI and Analytics Fit In?
Once a company has amassed a good amount of historical and inventory data, AI and analytics can become valuable parts of an inventory system.
Some operations that an inventory management system could use AI for:
Forecasting demand
Inventory optimization
Spotting patterns and outliers
Inventory planning and replenishment
General operational analysis
This is not to say that AI is a silver bullet. As with all data, the quality of AI models depends on the quality of the data inputted into it. Inventory systems with poor data management practices will not be able to rely on AI to help make their operations better.
One rule of thumb to remember is: Better models still depend on better data.
Security and Reliability Are Also a Concern
Inventory systems can house valuable pieces of information for an operation. As such, there may be a need for proper security, authentication, encryption, authorization, availability, auditing, and reliability. A company may have reliable operational data, but an application outage or breach can nevertheless inflict serious problems on an operation.
The Architecture Should Reflect the Workflow
A good inventory architecture is one that fits a business’s needs. There is no “one-size-fits-all” approach to choosing an inventory system.
It is always worthwhile to analyze where inventory events take place in an operation.
How are these inventory events currently captured? Where is the information currently captured or stored? Where does the information need to go? Where are bottlenecks or problem areas in the inventory process? Where might technology be useful in inventory processes?
Such a workflow-based approach will ensure that technology solves an inventory problem as opposed to technology being used simply for its own sake.
Companies that are looking to understand the kinds of components involved in a modern inventory system, inventory management software and technology solutions offer a useful insight as to how various technologies and processes combine to form a comprehensive system.
Final Thoughts
A modern inventory system is essentially an amalgamation of processes and technologies that work in tandem to create a digital representation of the physical world. Product X goes on and off the warehouse floor: sensors and scanners capture this event and software is needed to process this event and store this information in a database. There are various API tools that help different business applications communicate with each other. Historical information about inventory can be analyzed by analytics tools and AI to create more accurate demand forecasts and make other operational suggestions. A whole host of technologies come into play in modern inventory systems. The purpose of all of this technology, however, is a singular goal: creating a digital representation of physical inventory that is reliable and repeatable in order to create accurate analysis, inventory forecasts or automation in inventory processes, among other things.
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