Anyone who has overseen a supply chain for any length of time knows that much more goes into proper supply chain logistics, organization, and management than simply determining an optimal economic order quantity.
While maintaining a balance between the costs of ordering and housing inventory is a critical component of any supply chain system, there are many other factors that can and should be taken into account. Just-in-time manufacturing, products that are temporarily available versus long-term offerings, the amount of cash typically on hand that can be used for reordering ” the number of such considerations can seem endless.
And that only addresses the issue of inventory management. True supply chain optimization also involves things like customer service expectations, costs of manufacturing, fulfillment, and transportation.
How Inventory Data Analytics Can Help
The numerous factors that go into properly addressing any supply chain management system are precisely why every company should consider applying inventory data analytics to their approach. With so many moving parts, waste and inefficient processes are strong possibilities that can quickly eat into a company’s bottom line.
Using the power of big data to track things like inventory turnover, life cycles on warehouse and transportation equipment, and even utilizing the ever-increasing capabilities of modern AI, and machine learning can have a dramatic effect on minimizing waste and maximizing profits.
With modern supply chain management systems already so complex, it’s important that inventory data analytics are understood and applied in ways that are truly beneficial. A company cannot simply gather data and expect it to be a panacea for all supply chain management woes.
Further, inventory data analytics can be used in conjunction with analytics from marketing efforts to adequately evolve product lines, anticipate trends, and prevent shortages. As noted by marketing expert Rob Timmermann:
When you provide additional marketing, specifically digital marketing, to your products, you add on top of the marketing already being done by those companies who are carrying your product. You also gain insight into your customer base and, as a result, can continue to innovate and build upon existing products or invent new ones ¦ You evolve your inventory, sell more product and, by no coincidence, keep your business afloat in these evolving times.
As is the case with all big data, it takes knowledge and forethought to properly organize and understand both the information being gathered as well as how to use the data to create actionable solutions that provide genuine results. Here are a few ways that inventory analytics can be applied in order to help track data and optimize a typical supply chain:
Chart and Diagrams
An effective way to utilize inventory analytics is through the creation of business analysis models. From organizational charts to process flow diagrams, activity diagrams, and so on, there are many classic ways to help represent data in a format that allows a team to understand everything from inventory quantities to shipping methods, manufacturing processes, and so on.
Creating KPIs
Creating and monitoring key performance indicators (KPIs) is an essential part of inventory management data tracking. KPIs are a critical component of keeping an inventory system running smoothly. Some typical KPIs include customer satisfaction, order cycle time, and inventory turnover.
Inventory Organization and Cost
Of course, another obvious use of proper inventory analytics is the ability to organize your inventory. Understanding the cost of carrying inventory, as well as detailed information on how much of each product is actively on the shelves, can enable a manager to create parameters for when each product should be reordered ” a critical reason for supply chain managers to use predictive analytics.
If you have an inefficient, unorganized inventory system, consider seeking out an overhaul. A cleaner, more efficient system can save a ton of money and time.
Defining Management Roles
A less obvious benefit of properly applied inventory analytics is the ability to clearly delegate management team responsibilities. If a system is in place that properly tracks and reports data, it gives a company the ability to assign specific, actionable roles to their employees.
Having real-time knowledge of inventory and a data-driven system in place allows the process of restocking inventory to require a minimal workforce with simple, clear KPIs dictating when actions should be taken. Applying inventory analytics allows for the simplification of management roles and responsibilities.
Extended Life Cycles
Another way that tracking data can help improve a company’s supply chain is by using AI and machine learning in order to track the extended equipment life cycle of warehouse vehicles, machinery, and other equipment. This allows for both extended use (e.g. getting the most out of a company’s equipment) as well as proactively preparing to replace assets. With machine learning becoming more accessible, the ability to have AI play a substantial role in managing inventory has become a major consideration for many businesses.
Transparency
Inventory analytics also allows for increased transparency throughout a company’s supply chain efforts. Properly tracking inventory and having KPIs in place allows senior management to remain aware of even the most granular information regarding how a company’s supply chain is being managed.
In addition, the continued development of things like cloud technology has allowed larger quantities of big data to be easily accessed and analyzed in order to identify risks and offer potential improvements to supply chain management.
The Impact of Inventory Analytics on the Supply Chain
There’s no doubt that inventory analytics continues to play an ever-growing role in supply chain management. From its predictive ability to the organization and deeper knowledge that it provides, the inventory analytics is allowing businesses to operate in a more efficient manner. This development is a godsend in a modern world, where things like e-commerce, combined with brick-and-mortar operations, have continued to complicate nearly every level of the supply chain.
