Managing the Supply Chain with a Retail Data Warehouse

Explore how a Retail Data Warehouse transforms Supply Chain Management in the retail sector. 🛒 Dive into success stories like GWA Group and Michael Hill, and learn from Zara's excellence. 📈

Managing the Supply Chain with a Retail Data Warehouse
Managing the Supply Chain with a Retail Data Warehouse

The effectiveness of a data warehouse is crucial for the successful management of inventory and supply chains. It enables retailers to gather essential data which can be utilized to optimize strategies and maximize competitive advantages. Inadequate control over the supply chain can result in disastrous consequences, turning success into failure, profits into losses, and allowing market share to slip away to rival companies. If desired products are unavailable due to inadequate supply strategies, customers will not hesitate to switch their loyalty. Additionally, stocking shelves with unsold products signifies wastage of valuable resources. A prosperous supply chain management strategy relies on advanced data analysis to forecast demand accurately while anticipating any potential changes that might impact it.[1][2]

A crucial aspect of gaining a competitive advantage is the consolidation of relevant data into a centralized location, known as a data warehouse. This undertaking necessitates resources and dedication to ensure the high quality of captured data. Despite this, many retailers have not made investments in attaining all the necessary customer-centric data for their warehouses. However, those retailers willing to commit themselves can benefit greatly from this opportunity. When determining which main areas and sub-areas should be encompassed by the data warehouse, it is essential to consider what analytic subject areas are integral to its inclusion.[3][4]

Digital Transformation in Retail Supply Chain

Managing the Supply Chain with a Retail Data Warehouse has become an imperative to stay competitive and responsive to rapidly changing market conditions. Here's a deeper dive into how data warehouses in retail can bring about transformative changes, backed by real-world success stories and findings:

Digital Transformation with Microsoft Dynamics 365

GWA Group Limited: Faced with the pandemic's challenges, GWA Group accelerated its digital transformation by deploying Microsoft Dynamics 365, an end-to-end solution for data and actionable insights, to manage various aspects of its business, including supply chain, warehouse management, finance, and operations. This transformation enhanced their business flexibility and agility, proving the importance of data-driven decision-making in retail.[5][6]

Michael Hill: This international jeweler used Microsoft Dynamics 365 to overcome logistic complications during the pandemic by gaining better visibility into inventory availability across its supply chain. The platform allowed Michael Hill to treat each of its stores as a warehouse location, enhancing customer service and responding adeptly to changing business needs.[7][8]

Optimizing Retail Supply Chain

According to McKinsey, optimizing the retail supply chain through a sustained effort can increase sales by 3.0 to 7.0 percent, improve margins by 1.5 to 2.5 percent. Achieving this requires a holistic view of challenges and managing disruptions efficiently across different timelines, showcasing the critical role of data analytics in retail supply chain management.[9]

AI and Automation in Retail Supply Chain

A study by the IBM Institute for Business Value revealed that top-performing Chief Supply Chain Officers are leveraging digitization and AI automation 95% more than their peers, breaking down siloes that hinder data access and extraction from various systems, thus underscoring the role of a data warehouse in enabling AI-driven supply chain optimizations.[10]

Zara's Supply Chain Mastery

Zara's cross-functional operations strategy and vertically integrated supply chain have been crucial to its success. Through well-managed inventories and a push control system enabled by a robust data analytics framework, Zara has achieved lower markdowns, higher profitability, and value creation for shareholders, showcasing how data-driven supply chain management can significantly impact retail success.[11]

These examples underscore the pivotal role of a retail data warehouse in enhancing supply chain management, leading to improved operational efficiencies, customer satisfaction, and ultimately, higher profitability. Through intelligent data analytics and automation, retail businesses can gain better insights, make informed decisions, and stay agile in the face of market changes.

Inventory Management of Products

In retail, the data regarding inventory can be categorized based on various metrics using inventory management. This systematic approach enables retailers to effectively track the supply chain process from purchase order to store placement. By analyzing these metrics, adjustments can be made to optimize inventory levels and meet customer demands. Key performance indicators such as stock turnover for different products, the overall investment in inventory over time, the distribution of inventory at each stage of the supply chain (including orders, shipping, en route to stores and on shelves), frequently returned items along with reasons behind returns, and product availability in each store can all be evaluated to assess supply chain efficiency.[12]

Inventory management strategies vary depending on the retailer's brand image, product offerings, and market segment. For instance, a mid-priced grocery store that focuses on essential items such as bread and milk may have a more limited range of available products and rely on replenishing stock in full quantities. This involves closely monitoring sales rates and inventory levels to automatically initiate re-ordering processes. To effectively manage their inventory, retailers must also have access to information about competitor pricing so they can competitively price staple items.[13]

In contrast to the previous illustration, a fashion retailer specializing in seasonal apparel faces more intricate decision-making challenges. While the per-item profit may be greater, it is crucial to analyze SKUs within specific styles or categories when determining whether price reductions or product promotion are necessary. Because of the relatively short duration of each season, there may be a need for acquiring an entire season's worth of merchandise in just a few purchases in order to avoid substantial discounts at the end of the season.[14][15]

Managing Vendors

Retailer-supplier connection analysis, known as vendor management, encompasses the evaluation of each supplier's value to the retailer based on quantitative insights. This assessment considers factors such as sales and return predictions accuracy, punctuality and flexibility of vendors, frequency of product returns, promptness in payment by retailers, and shared sales and stock data. By leveraging this data effectively, retailers can enhance their relationship with vendors.[16][17]

The significance of a vendor business intelligence extranet has been highlighted in previous articles. Such BI applications enable vendors to gain insight into how their performance is perceived by retailers. This helps bridge any communication gaps that may arise between suppliers and retailers. A comprehensive vendor scorecard comprising key metrics along with access to detailed order and shipment information enables productive collaboration between the two parties and facilitates better decision-making for both the retailer and the vendor.[18][19]

Analysis of Product Costs

Product cost analysis offers greater precision in understanding costs by examining markups, discounts, and other costs such as shipping, storage, and stocking. Additionally, it can provide answers to key business questions, such as: How can product costs be lowered while still improving both product and customer profitability? What effect do changes in sale prices and product mixes have on profit and revenue? Cost of goods sold is often the most indistinct metric in the retail industry, as it is universally understood from an accounting perspective, yet many retailers interpret it differently. To combat this, creating a unified database of the components of cost and using it as the foundation for calculating derived costs can minimize variations between databases.[20][21]

Merchandise and Collection Organization

Merchandise and assortment planning assesses the efficacy of assortments, stores, and departments. It can optimize store clusters and assortment plans based on real results by examining data such as the open-to-buy position in comparison to the previous year, profiles of store clusters, and the performance of clusters in different locations.[22][23]

Merchandise and assortment planning, while not typically seen as part of the supply chain, still trigger actions in the supply chain, such as orders for goods production and delivery to distribution centers and stores. These two processes are increasingly important in the retail industry and rely heavily on data and analytical tools for effective functioning. While some retailers may choose to purchase specialized tools for these functions, the inputs (e.g. SKU sales history) and outputs (assortments, financial targets) should be stored in a data warehouse and analyzed over time. Distribution center operations is also important, as it allows retailers to monitor distribution center performance, analyze employee costs, shipments and receipts, shrinkage, and weeks of supply, and investigate ways to reduce costs through retraining or reassignment, alternative shipping methods, and changes in handling methods.[24][25]

A retailer should source the following types of data into their data warehouse to track the data subject areas: Merchandise and Assortment Plans (objectives related to inventory and sales), Financial Plans and Targets, Open-to-Buy Data, Assortment Plans by Store and Vendor-Centric Data (Contracts, Deals, Purchase Orders, Incentives for Bulk Purchases and Baseline Inventory Costs). This data should be compared with actual results to create better strategies for minimizing direct costs of re-supply.[26][27]

Segment-specific product information can be used to optimize shelf space allocation for fashion, food, and other product segments in each store, according to their respective sales volumes. Physical and calculated inventories, inventory receipts and adjustments, supplier shipments, and intra-enterprise item movements are essential to maintaining optimal inventory levels. Additionally, data on transfers between distribution centers and stores can help to detect excessive handling issues.[28][29]

The Whole Picture

By leveraging their retail data warehouses, many retailers can gain a comprehensive understanding of their supply chain by combining detailed supply chain data and analysis with sales and customer data. This will enable them to gain a complete picture of both demand and supply side factors in their retail business. Data warehousing plays a crucial role in the retail industry as it allows retailers to track and analyze various types of data, including sales history, financial plans and targets, assortment plans, and distribution center operations.

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