How Business Intelligence Can Enhance Inventory Management
Effective inventory management translates to having the right amount of the right product at the right location delivered just in time to satisfy customer needs at minimum cost.
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Inventory management that is effective can ensure that the correct quantity of the appropriate product is available at the necessary location, and arrives just in time to meet the needs of customers while keeping costs to a minimum.
By utilizing a solution that is based on business intelligence, retailers can enhance their business in five major areas: assortments, replenishment, vendors, supply chain and markdowns.
Data such as physical and calculated inventories, inventory receipts and adjustments, supplier shipments, intra-enterprise item movements, sales, plans and forecasts, replenishment targets and safety stocks, all stored in a single centralized location, is the basis of the solution.
Retailers who are at the top of their field are using business intelligence to gather data from supply chain and internal operations to maximize inventory efficiency throughout the organization. This includes analyzing past sales transactions to anticipate demand, tracking inventory from order to distribution centers to stores and sales floor, and creating analytical models based on customer behavior to see which factors have an effect on sales.
By analyzing large amounts of historical data, retailers can identify buying patterns for groups of similar products and stores based on factors such as geography, demographics, size, or volume ranking. This allows them to adjust and refine their assortments to meet the needs of their customers.
Business intelligence allows for an analysis of past seasons to help determine the best mixture of sizes and styles for the product assortment, as well as informing pre-season purchase quantities by size and allocation quantities by store for fashion items, and initial model stocks by size for new basic replenishment items. This ensures a more accurate understanding of product profitability.
Retailers can use business intelligence to assign and analyze financial costs and combine them with sales data to get a clearer understanding of product profitability. This allows them to make more informed decisions on which items to include or remove from their products.
Business intelligence enables retailers to access metrics not available in assortment planning tools, thus giving them a deeper understanding of the assortment planning process.
Automate the replenishment process & Monitor store-level stock levels
Best-in-class retailers are utilizing Business Intelligence (BI) to improve their replenishment process and optimize their operations. BI is helping to increase the accuracy of operational forecasts, automate the replenishment process, and monitor store-level stock levels. As a result, retailers are able to maintain their pre-assigned target on-hand quantities from their central distribution centers.
Using Business Intelligence (BI) tools, data from models, inventory, sales and safety stock can be combined to detect potential out-of-stock conditions. These alerts are generated by BI to timely address the issue, and thus prevent lost sales. Moreover, the BI tools can also determine when target stocks and/or safety stocks must be increased.
Identify instances of excessive inventory
Retailers can use sales data, forecast data, and replenishment data to calculate measurements like target stock weeks of supply. If target and safety stocks are too high in comparison to sales trends, they can be decreased and the inventory can be moved around the supply chain without the worry of stock-outs.
Find places and items that have low sales turnover
Retailers can leverage the power of Business Intelligence to determine the cause of slow turnover of certain products, or the lack of sales despite existing stock in-store. Possible causes could include inadequate demand, uncompetitive pricing, ineffective marketing, or poor planogram layout. Additionally, BI can be used to create automated schedules for inventory verification, allowing the retailer to focus on smaller samples of products based on various criteria such as attributes, sales history, replenishment status, and discrepancies in prior counts. This reduces labor costs, delays in service, and process interruptions, as opposed to an exhaustive inspection.
Retailers can use business intelligence to carefully observe and evaluate their inventory levels, allowing them to restock merchandise in line with their customers' purchasing habits, thus increasing their efficiency.
The 'bullwhip effect' can lead to inefficiencies in the supply chain, impacting both retailers and vendors. To reduce or eliminate these inefficiencies, leading retailers are leveraging business intelligence to collaborate with their vendors. This collaboration helps them to better manage their inventory, allowing them to accurately access and update their data, which in turn helps them to order only the necessary products, while also avoiding overstocking and shortages.
The bullwhip effect is caused by order batching, shortage planning, and sensitivity to price changes throughout the supply chain. Retailers can allow vendors to view aggregated sales data for their products, but vendors usually can't see the detail of individual transactions at stores. Having better knowledge of actual demand can help reduce the amount of safety stock kept in reserve.
Take advantage of cost savings that come from producing goods or services in large quantities
By using a combination of business intelligence-based sales analysis and postponement (also known as delayed differentiation), vendors can stock undifferentiated products and delay converting them into their final form until a reliable demand forecast can be established. This is especially helpful when predicting demand for product lines with varying levels of variability, such as fashion items.
Vendors should be held accountable for overseeing inventory
By employing web-based BI applications, retailers can provide their external suppliers with detailed, up-to-date data regarding demand for their products in all locations and sales channels. This will enable vendors to more accurately anticipate customer needs. Additionally, by making available information concerning the performance of their competitors, retailers can spur competition among suppliers, thus reducing the likelihood of out-of-stock and overstock scenarios. Moreover, VMI systems that leverage BI technology can be beneficial to both retailers and vendors by forming a collaboration in which vendors take responsibility for effectively managing inventory at distribution centers and stores.
Improving the effectiveness of the supply chain
Retailers can utilize business intelligence to gain visibility into their company's supply chain operations. This can lead to more precise demand forecasts, and make the supply chain more efficient, reducing lead times, carrying costs, and other operational costs at the enterprise level.
Retailers can use Business Intelligence to gain insight into the workings of their supply chain by closely examining waypoint logs. If an order takes a long time to be picked, it could be a sign of malfunctioning equipment or inefficient routing. Moreover, if a single operator is making more errors than usual, this could be an indication of inadequate training, external distractions, or faulty recognition systems.
Can also help to lessen the amount of time spent locating items to fill orders, which will reduce operating costs, increase productivity and optimize service levels. If retailers can pinpoint the parts of their delivery system that are causing delays and shorten the amount of time it takes for items to reach the sales floor, they can reduce the amount of safety stock that needs to be kept on hand.
Assessing the precision of predictions
Retailers who utilize business intelligence to identify products that have a large discrepancy between forecasts and actual demand can limit the chances of over-stocking or running out of stock. This kind of supply chain optimization leads to a decreased need for safety stock, increased liquidity of assets, and a greater ability to access working capital.
Business intelligence can be extremely useful in determining which products should be discontinued or discounted, as well as the most profitable way to move slow-selling merchandise.
By combining item level plans with sales data, retailers can quickly determine which items should be promoted, marked down, or sent to outlet stores. This allows them to take swift action to prevent the accumulation of unproductive merchandise. Additionally, business intelligence can be leveraged to discover the most efficient methods to sell slow-moving inventory. For example, retailers can utilize BI to determine the discounts that have been successful in clearing out similar items in the past.
By using Business Intelligence to identify which locations have sold the product better or which sell markdown merchandise better, retailers can consolidate broken assortments to those locations with the greatest potential for higher sales or better pricing. This way, businesses can focus their time and money on more profitable inventory, instead of determining which items to markdown.
Business intelligence can be used to improve inventory management in numerous ways. It provides a comprehensive view of inventory levels and trends, enabling retailers to make informed decisions about product procurement and stocking levels. It also allows retailers to monitor warehouse operations and gain insights into the performance of their supply chain partners. Additionally, business intelligence can help retailers identify and reduce inventory shrinkage, and optimize inventory levels for seasonal or promotional opportunities. By leveraging business intelligence to its fullest potential, retailers can ensure that their inventory management practices are working to improve their bottom line.
Retailers can use a data warehouse that tracks both past and upcoming operational metrics such as weeks of supply, sell-through, inventory turnover, gross margin return on inventory, and shrinkage to improve data quality and accuracy, manage inventory levels and prevent lost sales or oversupply, give external vendors more insight into product performance, and enable managers and executives to make decisions faster with a shared set of data that everyone trusts.