Unlocking Value Across the Supply Chain Through AI
Retail leaders have already begun infusing their supply chains with artificial intelligence (AI) engines and reaping the rewards of greater efficiency, speed, reliability and lower costs. Some have reported achieving return on investment (ROI) within six months due.
The reason why AI in the supply chain is a hot topic today is that the inventory management network is one the most complex systems in retail, a matrix of functions that range from sourcing to demand planning to last-mile delivery. It is a system in constant motion that encompasses physical items, transportation flows, hub-and-spoke nodes, and interconnected hardware and software technology.
In the recently posted special report, “The AI-Driven Supply Chain,” RIS explores how savvy retailers are turning to AI engines to help power the next-generation supply chain.
To take a deep dive into key recommendations that retailers can follow to unlock value in their supply chains, RIS sat down with Sanjeev Khanna of TCS for an exclusive interview.
RIS: Which supply chain management areas are good starting points for AI interventions?
Khanna: Supply chain processes, ranging from demand planning to last-mile delivery, generate and store an exorbitant amount of data across disparate systems. This situation presents an opportunity to create supply chain systems that deliver scientific decision-making and prediction capabilities.
Retailers will gain tremendous value from investing in intelligent, self-learning replenishment and forecasting capabilities that determine order quantities to achieve optimal product availability at the most economical cost. Other quick wins with AI are likely to be in demand fulfillment operations such as predicting capacity needs and customer promise breaches for dynamic resource allocation and proactive identification and remediation of potential delays.
At Tata Consultancy Services (TCS), we achieve the above through TCS Algo RetailTM – a paradigm shift in seamlessly integrating and orchestrating data across the retail value chain to unlock exponential value. Algo RetailTM helps retailers by integrating advanced digital technologies including AI into their business processes and applying algorithms for harnessing and channelizing the data for driving business success.
RIS: How can AI engines help supply chain managers improve control over omnichannel complexity?
Khanna: In an omnichannel environment, predicting demand by fulfillment options can be extremely challenging. Complexities in inventory management and capacity planning result in overhead costs and availability issues. During peak seasons, the supply chain flow can be completely disrupted and cause inventory to be clogged at distribution centers and stores, resulting in surplus inventory post season. These are typical situations where supply chain managers tend to lose control. AI-powered, self-learning solutions can help deliver near real-time computation by simultaneously considering multidimensional factors such as the most recent state of inventory, consumption rate, operational capacity, demand-shaping factors, and supply chain constraints. AI engines can provide a competitive advantage for supply chain planning and execution managers through three levels of algorithmic interventions — reactive, proactive, and pre-emptive — equipping them to handle the complexities of modern omnichannel retail.
RIS: Improving inventory management is a moving target for retailers. What role can AI play in mitigating over stocks and out-of-stock situations?
Khanna: Machine learning methods such as decision trees or neural networks can handle not only nonlinear relationships, but identify completely new patterns and relationships from humungous amounts of supply chain data. Accurate forecasts and ‘value chain aware’ order decisions cascade benefits across the entire supply chain, allowing for cost-saving and revenue-maximizing opportunities such as dynamic pricing and effective real-time inventory management.
Finally, AI-driven techniques are inherently scalable and thus can be used for holistic control of inventory throughout its lifecycle covering planning, allocation, and liquidation.
RIS: In the new fulfilment economy, ensuring a seamless customer experience is table stakes for retailers. How can AI improve decision making for delivering fulfillment promises?
Khanna: Being able to predict and anticipate customer needs and delivery options can be a game changer for omnichannel retail. Today, by leveraging AI-based tools, we can build advanced algorithms that help retailers predict exact inventory to be replenished and allocated based on fulfilment options. This not only reduces overall ‘click to deliver’ time and supply chain costs, but elevates customer satisfaction by several notches.
To ensure a seamless customer experience, the supply chain currently characterized by localized, siloed optimizations based on operational capacities is one of the areas where Algo RetailingTM delivers the most significant benefits. Algo RetailingTM transforms the supply chain through multi-dimensional, concurrent modeling, and optimization in near real-time across stores, distribution centers, transportation, and channels. This application of AI greatly improves availability and customer experience, delivers fulfillment promises while reducing cost to serve.
Tata Consultancy Services is an IT services, consulting and business solutions organization that has been partnering with many of the world’s largest businesses in their transformation journeys for the last fifty years. TCS offers a consulting-led, cognitive powered, integrated portfolio of business, technology and engineering services and solutions. A part of the Tata group, India's largest multinational business group, TCS has over 436,000 of the world’s best-trained consultants in 46 countries. For more information, visit us at www.tcs.com.