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Better Warehouse And Inventory Analysis Is The Way For Unsurpassed Results, Reduced Wastage

To succeed, warehouse and inventory management operations need to have data. Indeed, no supply chain operation can have a competitive advantage unless they are data-driven. This is because accurate, complete, and timely data is critical for both warehouse staff and automation. Without high-quality data, operations cannot do effective inventory analysis. This article explores inventory analysis and what is needed to succeed. Specifically, we will review key metrics needed to drive inventory optimization and 6 key areas in regard to inventory analysis.

Key Metrics To Drive Warehouses And Inventory Optimization.

man in warehouse doing inventory analysis

Identifying the right key performance indicators (KPIs) is essential for driving warehouses and inventory optimization. By setting metrics levels and having a data-driven approach enables businesses to make informed decisions. Specifically, measurable metrics will lead to optimized efficiency, reduced costs, and enhanced customer satisfaction. Also, regular evaluation of these key metrics ensures that warehouse operations remain agile and adaptable to ever-changing market demands. To list, below is a short description of key warehouse and inventory optimization metrics.

  1. Profitability / Cost Metric – Gross Margin Return on Invested Inventory (GMROI). Here the focus of this metric is to see how well they are turning inventory into profits. Specifically, the formula is: GMROI = Gross profit margin / average cost of inventory on hand.
  2. Efficiency Metric – Inventory Turnover Rate. This metric shows how well you’re managing inventory. In particular, the formula also reveals how your products are selling. The formula is ITR = Cost of goods sold (COGS) during specified period / Average inventory during the period.
  3. Customer Satisfaction Metric – Stockout Rate. Here this KPI measures how often an item a customer orders is not available. The formula is SR = (Stockout order / total customer orders) x 100.

Now supply chain managers use many more warehouse and inventory metrics than listed above. These are just examples. Also, more metrics will be discussed further in this article. For a more detailed list of inventory management metrics, see Netsuite’s Inventory Analysis: Tips, Methods and KPIs.

How Warehouse And Inventory Analysis Enables Businesses Optimize Service Levels And Reduce Costs.

Warehouse and inventory metrics drive inventory analysis. Even though there are general principles to follow in inventory analysis, analysts need to be guided by the specific metrics for their supply chain operation. For example, some level of stock outs may be fine for some products, however not acceptable for other key products. Indeed, this is where inventory analysis comes in. To list, below are 6 key areas where inventory analysis is applied to optimize service levels and minimize costs based on key business drivers and operational metrics. 

1. Determine The Best Type Of Inventory Analysis To Use To Maximize Efficiency.

In an ideal world an order fulfillment center would have unlimited inventory so there would never be stock outs. Alas, this is not economically feasible. So what is the best way to analyze inventory to determine stock levels? Well that really depends on many factors. In particular, types of inventory analysis are dependent on the type of industry your business is in, the products you sell, your cash flow situation to name a few. To list, below is a short description of common ways a business can determine stock levels for its warehouse.

a. Inventory With Highest Revenue / Profit Margin – ABC Analysis.

This is the most popular inventory analysis method (especially for retail). Here, analysts rank inventory from the highest revenue and profit margins to the lowest using three buckets: A, B and C.

b. Inventory Most Vital – VED Analysis.

Manufacturing companies use this technique to assure they are focused on the most vital components in inventory. Again, there are three buckets: vital, essential, and desirable.

c. Inventory Categorized By Cost – HML Analysis.

Here manufacturers use this type of inventory analysis based on high, medium, and low cost. A twist on this is Last In, First Out (LIFO) and First in First Out (FIFO) that some companies use more for accounting purposes. Also, there is First Expire, First Out (FEFO) that for some companies is critical for sales and to avoid wastage.

d. Inventory Categorized By Scarcity – SDE Analysis.

For some products that are hard to get a hold of or have long lead times, this type of inventory analysis is favored. Here management categorizes products as follows: scarce, difficult, easy.

e. Sales Driven Inventory – Material Requirements Planning (MRP).

Here management orders inventory based on stock available and sales forecast. For example, seasonal inventory such as swimwear would be a good candidate for MRP.

f. Inventory Based On Sales And Total Cost – Economic Order Quantity (EOQ).

In this case, management assesses the sales rate of an item along with its ordering costs and storage costs.

g. Inventory Based On Inventory Turns – Fast, Slow and Non-moving (FSN).

Some products sell faster than others. So to avoid stock outages, these stocks need to be managed closely and re-ordered often. Here management categorizes products as fast-moving, slow-moving, and non-moving.

h. Set Custom Re-Order Level – Safety Stock Level.

Here management does more planning upfront setting inventory levels for each inventory item. This is to assure no stock outs by setting a safety stock level which when reached triggers a re-order.

So you can see there is not one standard way to manage inventory. Management will need to decide which type of inventory analysis to use. In some cases, they may even use several different types of inventory analysis types depending on such things as product characteristics, warehouse location, or service levels needed to be competitive. For a more detailed list of inventory analysis types, see Netsuite’s Inventory Analysis: Tips, Methods and KPIs.

2. Analysts Are Most Effective In A Data-Driven Warehouse And Inventory Management Operation.

Embracing a data-driven mindset can significantly improve warehouse and inventory operations. By utilizing data analytics tools, organizations can gain valuable insights into patterns and trends that might otherwise remain hidden. In particular, this information can reveal areas for operational improvements, streamline processes, and help eliminate bottlenecks. Furthermore, data-driven analysis enables companies to forecast future demand more accurately, enabling them to plan for peak periods and minimize downtime during slower seasons. To more explore data-driven analysis and decision-making, see SC Tech Insights’ Data-Driven Decision-Making: its Enormous Impact And The Truth On Limitations.

3. Minimize Stock Outs And Increase Inventory Accuracy Through Real-Time Automation Of Inventory Analysis.

To minimize stock outs it is best to leverage an inventory management system. Here analysts configure inventory management systems based on their inventory analysis technique. For example, this can be based on an ABC analysis or other type of inventory control. Besides an inventory management system, inventory managers can also leverage Internet Of Things (IoT) devices such as Radio Frequency (RF) ID tags to minimize data entry and human error. Also, robotics such as drones can be used to automate manual inventories to assure system accuracy.

So by implementing automated systems that track inventory levels in real-time, analysts and management can make rapid adjustments to replenish stock as needed. This level of control results in fewer stockouts, ensuring that customers receive their orders on time and with the correct items. Additionally, real-time automation reduces the likelihood of human error, leading to higher overall inventory accuracy.

4. Streamline Warehouse Operating Costs Through Inventory Analysis.

man in warehouse doing inventory analysis

Proper inventory analysis plays a significant role in optimizing warehouse operating costs. By regularly analyzing inventory levels, businesses can identify slow-moving items to clear out excess or obsolete stock. For instance, these insights enable organizations to implement just-in-time (JIT) inventory management strategies that lower carrying costs and free up valuable warehouse space. Effective inventory analysis also highlights potential cost-saving opportunities by identifying inefficiencies in the supply chain, such as supplier delays or high freight costs. To list, below are the types of costs that can be minimized through inventory analysis.

a. Logistics and Warehousing Costs.

This includes rent, labor, utilities, inventory management fees, and the cost of shipping goods to customers. For example, analysts can analyze labor productivity resulting in optimizing the schedules for warehouse employees.

b. Materials Handling Costs.

This includes buying or leasing equipment to labor for operating several heavy machines.

c. Total Capital / Cost Of Purchasing Inventory.

This includes the actual cost of inventory, financing fees, loan maintenance fees, and interest. For example, analysts can identify slow-moving and obsolete items. Thus, management then can decide to remove these items from inventory.

d. Risk-Holding Costs.

This includes inventory depreciation, obsolete stock, shrinkage, and the impact of stockouts.

e. Insurance Costs.

This includes any insurance costs associated with running a warehouse.

f. Space Utilization Optimization.

This type of inventory analysis helps to identify optimal product placement in the warehouse. Also, different types of storage systems, both manual and robotic, can result in significant space savings. Click here for details on different types of logistics robotics.

See Nsktglobal’s How Data Analytics Can Help In Inventory Management for more discussion on streamlining warehousing costs.

5. Minimize Warehouse Stock Shrinkage, Overstocks, and Product Expirations Through Inventory Analysis.

Properly analyzing your inventory data allows you to mitigate the risks associated with shrinkage (loss of items), overstocks (excess inventory), and product expirations. For instance, product expirations can be minimized by setting up an inventory strategy of First Expire, First Out (FEFO). Also, monitoring real-time inventory levels, tracking incoming shipments, and carefully managing outgoing orders, warehouse operators can decrease these risks and improve overall efficiency. Further, analysts can do a root cause analysis to identify ways to minimize stockage shrinkage due to theft, inaccurate product counts, and damage. This proactive approach helps businesses maintain their inventory control while reducing costs and waste.

6.  Optimize Returns Processing Through Inventory Analysis.

Returns processing is a critical aspect of warehouse operations that can significantly impact the bottom line. Inventory analysis can help businesses identify trends in product returns and find ways to address potential issues before they escalate further. By monitoring data related to product quality, shipping accuracy, or packaging standards, businesses can identify reasons for returns and implement appropriate corrective actions. Ultimately, this optimization results in reduced return rates and improved overall customer satisfaction.

For more ideas and discussion on inventory analysis, see Netsuite’s Inventory Analysis: Tips, Methods and KPIs and ShipBob’s Inventory Analytics Guide

For more information from Supply Chain Tech Insights, see articles on Supply ChaineCommerce, and Data Analytics.

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