5 Ways Business Intelligence Can Enhance Inventory Management

Originally published October 14, 2008

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. Implementing an inventory improvement solution driven by business intelligence (BI) can help retailers to improve their business in five key areas: assortments, replenishment, vendors, supply chain and markdowns. Detailed data related to physical and calculated inventories, inventory receipts and adjustments, supplier shipments and intra-enterprise item movements, sales, plans and forecasts, replenishment targets and safety stocks gathered in a centralized data repository serve as the foundation for the solution.

In this article, we discuss the importance of inventory management and how best-in-class retailers are utilizing business intelligence to analyze information from across the supply chain and internal operations to improve the efficiency of inventory throughout the enterprise in order to:

  • Conduct detailed, in-depth analysis of historical sales transactions, better anticipate demand, and relate their stocking positions to both short and long term trends;

  • Accurately track inventory throughout the entire supply chain from order through distribution centers to stores and to the sales floor; and

  • Develop and leverage fact-based analytical models of customer behavior to understand the factors that influence sales.

Targeted Assortments

Many retailers have begun to implement assortment planning tools which help them to create the most profitable mix of merchandise to carry within their stores. While assortment planning tools can help retailers create multiple iterations of their plans, integrating business intelligence is critical to providing insight as to what assumptions should be made to guide those plans. BI enables retailers to:

  • Analyze large amounts of detailed historical data. This analysis allows retailers to identify buying patterns for groups of products with similar attributes across groups of similar stores based on factors such as geography, demographics, size or volume ranking.

  • Refine their assortments. Business intelligence facilitates pre-season analysis to determine purchase quantities by size, allocation quantities by store for fashion items, and initial model stocks by size for new basic replenishment items as well as analysis of data from past seasons to determine the optimal mixture of sizes and styles for the product assortment.

  • Receive more accurate information on product profitability. Business intelligence provides the means by which retailers can assign and analyze financial costs by product and combine that information with sales to get a truer picture of product profitability allowing them to make more informed decisions on the items to be included or excluded from their assortments.

Business intelligence allows retailers to utilize metrics that may not be available in assortment planning tools to provide even greater insight into the assortment planning process.

Improved Replenishment

Many retailers carry an assortment of products that are replenished from a central distribution center based on pre-assigned target on-hand quantities. Best-in-class retailers are controlling and optimizing replenishment throughout their operations by applying BI to:

  • Improve the accuracy of operational forecasts. Business intelligence can bring model and safety stock data together with inventory and sales information to identify potential out-of-stock situations, highlighting where target stocks and/or safety stocks need to be increased to prevent lost sales. BI tools can be used to proactively generate alerts in these situations so that the problem can be addressed appropriately.

  • Determine over-stock situations. By combining sales data, forecast data and replenishment data, retailers can compute measurements such as target stock weeks of supply. Target and safety stocks that are too high relative to current sales trends can be reduced and the inventory repositioned in the supply chain as needed without risking stock-outs.

  • Identify slow-turning locations and products. Retailers can use BI to identify products with sluggish turnover ratios or products with stock on hand at the store but without sales, potentially indicating a failure to replenish shelves with available product; insufficient demand for the product at the location in question; noncompetitive pricing; ineffective marketing; or poor planogram layout.

  • Ensure the accuracy of inventory data in replenishment ordering systems. Retailers can use BI to automatically generate schedules for inventory verification via physical inventory counts. By focusing on small samples of products selected based on specific product attributes, historical sales trends, replenishment status, and prior count discrepancies, they can reduce the labor requirements, service delays, and significant process disruptions of an exhaustive inspection.

Business intelligence gives retailers the ability to closely monitor and analyze inventory levels within their enterprise, enabling them to more effectively stock merchandise based on the buying behavior of their customers. 

Vendor Collaboration

Inefficiencies in the supply chain affect not only the retailer, but also the vendors that supply the goods offered to consumers. Inaccurate or inaccessible data in the inventory management system can lead to retailers ordering unnecessary products because they don't know they have supply on hand or hinder a retailer from placing necessary orders when supplies are low. Leading retailers use business intelligence to collaborate with their vendors to:

  • Reduce or eliminate the "bullwhip effect." The bullwhip effect is the distortion of product demand signals generated by order batching, shortage planning and reactions to price variations across the supply chain. Although retailers may open access for vendors to monitor aggregated sales data on their products, vendors typically lack visibility into fine-grained transaction-level demand at retail stores. Providing vendors with insight into true demand reduces the necessary volume of safety stock kept on hand.

  • Leverage economies of scale. Demand for product lines with constant variability such as fashion items is inherently difficult to predict. By combining business intelligence-based sales analysis with postponement (also known as delayed differentiation), the vendor can stock undifferentiated product in bulk and delay specific labor to convert it into its final form until a dependable demand forecast is available.

  • Make vendors responsible for managing inventory. Web-based BI applications can allow selected external suppliers to access timely detailed demand information for their products across all locations and channels, allowing vendors to more accurately predict customer demand. Additionally, by providing aggregated information pertaining to their competitors' performance, retailers can foster competition between suppliers to proactively maintain shelf stock, virtually eliminating costly out-of-stock and overstock situations.

BI-based vendor managed inventory systems (VMI) co-opt vendors into taking responsibility for properly managing inventory levels at distribution centers and stores, resulting in exponential value for both the retailer and vendors alike.

Supply Chain Efficiency

Business intelligence gives retailers the ability to gain access to enterprise-wide information on the company's supply chain operations. This insight can help to improve the accuracy of demand forecasts and increase the efficiency of the supply chain, reducing lead times, carrying costs, and operating costs across the enterprise. Retailers can use BI to gain visibility within their supply chain by:

  • Scrutinizing detailed waypoint logs. Long order picking times may indicate equipment maintenance problems or suboptimal routing. High error rates in orders picked by a given operator can be symptomatic of insufficient training, excessive distraction or defective identification mechanisms. Lessening the amount of time spent locating specific items to fill orders can help to reduce operating costs, increase productivity and optimize service levels.

  • Analyzing vendor and distribution center lead time and lead time variability. Retailers can reduce the need for safety stock if they can identify bottlenecks in their delivery system and reduce lead times for movement to the sales floor.

  • Measuring forecast accuracy. Retailers that more quickly identify products with forecasts that vary significantly from actual demand can reduce the possibility that that product will experience an over-stock or out-of-stock position.

The aggregated effect of using business intelligence for supply chain optimization is a reduced need for safety stock to avoid service interruptions, increased asset liquidity, and easier access to available working capital.

Markdown Optimization

Business intelligence can be instrumental in both quickly identifying products that should be discontinued or marked down and determining the most profitable way to sell through poor performing merchandise. Combining item level plans with sales data allows retailers to quickly identify items to be promoted, marked down, or sent to outlet stores. The ability to react promptly to issues at item level enables retailers to avoid build-ups of non-productive merchandise.

In addition, business intelligence can be used to determine the most efficient ways to sell-through slow selling inventory. Retailers can use BI to identify the levels of discounts that have worked in the past to liquidate similar merchandise. Alternatively, BI can also be used to identify which locations have sold the product better or which sell markdown merchandise better so that broken assortments can be consolidated to the locations that have the best opportunity to sell the merchandise more quickly or at a higher price.

Retailers who take advantage of business intelligence to improve markdown optimization are able to spend less time determining merchandise to mark down and instead are focusing their efforts and investments on more productive inventory.

The Benefits of Business Intelligence for Inventory Improvement

World-class business intelligence environments allow retailers to increase their visibility into inventory management without hampering daily operations. By extracting information from disparate source systems into a centralized repository such as an enterprise data warehouse, retailers are concurrently reporting on metrics related to their supply chain, sales, production and internal operations to make better, fact-based business decisions. By utilizing a data warehouse that supports trending on both historical and future operational metrics such as weeks of supply, sell-through, inventory turnover, gross margin return on inventory and shrinkage, retailers can improve data quality and accuracy, manage inventory levels to avoid lost sales or oversupply, provide external vendors with increased visibility into product performance, and allow managers and executives to make more timely decisions using a common set of data trusted across the entire user community.

  • Rafael Algara
    Rafael is a Principal Subject Matter Expert at Claraview, a division of Teradata, a strategy and technology consultancy that helps leading retailers use business intelligence (BI) to achieve competitive advantage and operational excellence. Claraview offers retailers a total solution for leveraging business intelligence to improve their business, including full lifecycle BI services, retail-specific domain knowledge, and technology accelerators. Rafael has successful experience in designing, developing and deploying large business intelligence applications for a diverse set of retailers including big box, grocery, specialty and apparel retailers worldwide. He can be contacted at rafael.algara@claraview.com.
  • Sara Charen
    Sara is the Manager of Industry Solutions at Claraview, a division of Teradata, a strategy and technology consultancy that helps leading companies and government agencies use business intelligence to achieve competitive advantage and operational excellence. She is responsible for the development of implementation accelerators for retail analytics, including an enterprise Retail Data Warehouse, as well as focused offerings for Sales and Inventory, Store at a Glance, Assortment Planning and Market Basket Analysis. She may be contacted at sara.charen@claraview.com.

Recent articles by Rafael Algara, Sara Charen

 

Comments

Want to post a comment? Login or become a member today!

Be the first to comment!