Supply chain management is the heart of retail management and has the ability to inform the overall health of a business. As a result, businesses looking to gain a competitive advantage in the global marketplace are investing more heavily in supply chain management. Investment in the proper technologies needed to build a strong supply chain not only enables prompt replenishment of products in inventory, but also optimizes planning capabilities in rapidly evolving business ecosystems while minimizing duplication, errors and inefficiencies.
The supply chain challenges of the past few years have underscored the importance of proper and efficient supply chain management. Failure to meet customers’ expectation of timely, cost-effective and ethical delivery of goods can profoundly impact a company’s ability to retain consumers. Agile companies know that prioritization of the existing customer base is key to revenue growth, since more resources are needed to attract new ones.
Customer loyalty is paramount to building a scalable business model, and the availability of inventory coupled with the guarantee of delivery will ultimately allow a business to meet and exceed its KPIs. To address these challenges, teams looking to drive sales conversions and customer loyalty are adopting a new concept of inventory pacing in order to keep up with rapidly changing ecosystems largely driven by evolving customer expectations.
Using Inventory Pacing to Spot Improvement Areas Throughout the Supply Chain
Inventory pacing begins with sales-to-inventory forecasting, or the prediction of sales revenue during a given period of time. Seems simple enough, right? The process can actually be a bit more complex than retailers anticipate.
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Sales-to-inventory forecasting requires consideration of several variables, including conversion rates, average deal rates, average renewal rates and the average length of time to close a deal, among other factors. Retailers also need to figure in historical data and pipeline forecasting, as well as changes in policy, the economy and products that could potentially impact sales.
Finally, sales forecasting reports need to leave room for unforeseeable disruptions to the supply chain. With the help of AI and automation, retailers can more precisely estimate the amount of inventory to keep in stock at any given time while minimizing production waste and the dreaded “out-of-stock” status.
Given the current state of the global supply chain and increased dependence on online retailers, businesses looking to ensure optimal ROI on internal processes cannot afford to skimp on machine learning algorithms, AI-enabled predictive analytics and Big Data, which can identify areas of improvement across the full length of an organization’s supply chain. Sales-to-inventory forecasting not only determines sales numbers but also informs other business decisions, ranging from hiring and resource management to marketing decisions and inventory and shipping procedures.
Navigating the Dynamic and Evolving Shipping Industry
When it comes to retaining customers, late deliveries can be the ultimate deal breaker, and labor shortages across the shipping industry have created even more obstacles for retailers. Companies looking to better navigate unforeseeable and external factors should lean into newer technologies and machine learning to ensure expedited and timely delivery. AI and automation can better estimate the arrival time of containers into ports as well as use predictive data to flag risks. By using Big Data, ecommerce retailers can better predict weather conditions and identify the best shipping routes to minimize delays of container shipments.
AI algorithms and analytics are also able to provide unprecedented deep insight into goods while significantly reducing human error. Retailers can better ensure quality control and minimize the loss of goods with AI-enabled systems that can account for the number of container shipments and quality of goods while en route. Through Big Data and automation, damaged goods are more accurately reported through the matching of product size, color and shape to previously stored data. Perishable goods and containers with guaranteed one- or two-day delivery are better prioritized with the help of machine learning and trackers. Finally, real-time tracking of goods that are en route allows brands to budget more effectively as well as cut down on damaged, lost and stolen goods.
The Future of Ecommerce is Automated and Digitized
Companies that don’t have access to sales-to-inventory forecasting and tracking capabilities would do well to invest in newer technologies that can streamline operations, from inventory management to product delivery through the deployment of machine learning and AI. Proper application of inventory pacing is crucial to the successful reduction of human error, increased efficiency of inventory management, minimization of waste and accurate risk assessment. Ultimately, inventory pacing will better position retailers for success in an increasingly competitive retail landscape.
Joe Wu is the General Manager at Oceanwing, a full-service provider of ecommerce solutions and market analytics for retail brands and a subsidiary of Anker Innovations, where he oversees the company’s dynamic ecommerce ecosystem. He is a seasoned expert in international business and product development, stemming from a stint as Senior Director of Global Online Sales at Anker, where he drove record growth in the launch and distribution of the company’s audio products.
