Retail Supply Chain: Its Evolution and Where We’re Headed

As customer demands have shifted due to the popularity of mobile commerce and omnichannel retailing, retail brands’ supply chain operations have had to evolve to match. Retailers are acutely aware of the role data plays in business success, and supply chain operations are grappling with making the most of the data collected. This article will outline the retail supply chain evolution and make the case for prescriptive analytics, detailing why it is needed today and in the future.

Supply Chain Evolution

Twenty years ago, retailers and brands were focused on how to reduce costs per unit. Supply chain management was a complex process that supported this priority through the linear function of moving products from one place to another in the cheapest way possible in different silos. However, at this point, little attention was paid to analyzing the actual product demand and how to appropriately align supply better with demand to increase inventory turns and return on assets.

As retailers adopted a demand-driven approach, the supply chain paradigm shifted. Instead of focusing primarily on reducing the cost of the unit supply of products, enterprises tuned into planning actual detailed demand of each SKU (in what locations and how many of the SKU are needed for each day/week). This radical change caused the supply chain to find ways to optimize each step of the process, bringing the importance of logistics and management to the forefront of analysts’ minds and added new Key Performance Indicators (KPIs) to be optimized.

With the introduction of the Internet of Things (IoT) and smart machines interpreting data, new types of advanced optimization can be found throughout the supply chain across all industries. Enterprises have welcomed this modernization because it offers new types of sensing ability, visibility, and collaboration between all department partners. This modernization was most evident within the Integrated Business Planning (IBP) process, where the coordination and movement of products and risk mitigation became much more streamlined.

Simultaneously, retailers and brands introduced, and mastered, technologies like computers and mobile – resulting in mobile-shopping and omnichannel operations. For supply chain, this meant yet another evolution in the process. These technologies had a positive impact on optimizing the end-to-end chain from production to consumption. Armed with these technologies, enterprises embraced innovation and opened collaboration within departments and outside suppliers.

Next-Gen Innovation in Supply Chain

In an effort to improve user experience and optimize processes, retailers look to technology for the clearest insight and recommendations. Even just a few years back in the early stages of mobile adoption, supply chain managers were needed in order to pull and interpret this data, then offer recommendations on how to improve KPIs based on sensing ability as close to real-time as possible. This process was not scalable and flawed because data is understandably difficult to interpret and can result in any number of conclusions based on different personal and political biases of the analytical power user.

The next generation of innovation in supply chain analytics involves cutting out the risk of human error and enable scale with advanced technologies, like prescriptive analytics solutions. These offerings help ease the responsibilities of the supply chain manager as well as the people in the field (often called “at the edge”), by offering the most strategic approach to a very complicated supply chain process.

Unprecedented Analytical Capabilities

With the advent of prescriptive analytics, supply chain managers have a solution that has helped improve efficiency by providing simple, actionable tasks across all organizations, from the distribution center, to the store, and even to headquarters. This level of insight into the channels has helped analysts eliminate negative impact behaviors or encourage positive ones. By leading supply chain analysts to specific behaviors that need to be addressed early, prescriptive analytics cuts down the time spent pulling and sorting data from the identified patterns, and instead, empowers teams to focus their attention on other moving pieces of the supply chain. But most importantly, it provides analysts with a source of unbiased prescriptive tasks that anyone can follow at the edge in near real-time, the DC, or at headquarters.

Another benefit is traceability. Prescriptive insights help analysts track the current and future performance of the supply chain. For example, prescriptive analytics empowers analysts to identify hold-ups before they occur, then call out how they can be resolved, ultimately optimizing the outcome every time, everywhere. In today’s fast paced world, being able to predict or notify the appropriate handler of supply chain disruptions and having contingency plans in place is critical to success. But this is only possible if these companies know where a given product is located at any point in the supply chain. The insight and visibility that prescriptive analytics provides has been shown to increase profitability, optimize resource planning, and improve the customer experience.

Prescriptive Analytics are Here to Stay

Leading the way into this next generation of supply chain, retailers and CPG companies have quickly recognized the benefits and are already starting to reap the rewards of additional data insights. Prescriptive analytics have evolved the human role in the supply chain by empowering employees at all levels from the less technology savvy, to executives. With prescriptive analytics, the path is clear – retailers can better understand their data, make more informed decisions close to real-time, cut costs, and improve their sales and margins.


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