digital supply chain

Business and Technology Insights

Realizing the Promise of Autonomous Supply Chain: The Four Key Building Blocks

 
January 23, 2019

Business 4.0 technologies are upending traditional ways of doing business. For organizations, intelligent, agile, automated and cloud   technologies present an opportunity to make their supply chain connected, smart, and autonomous, enabling stakeholders to make decisions on the fly. This is critical to building agile and responsive operations that help speed up time to market and meet soaring customer expectations. Little wonder brands such as Walmart and Gap have already automated their supply chain for greater efficiency. According to some estimates, by 2023, at least 50% of large global companies will be using AI, advanced analytics, and IoT in their supply chain operations. This means end-to-end automation of supply chain operations with minimal human intervention is critical for competitive success. How can companies achieve this?  

Building a digital supply chain can help leaders gain real-time visibility into the entire supply chain operations such as transportation, inventory, and warehousing of goods by enabling autonomous operations. The result: enhanced decision-making and reduced effort and costs. 

Laying the Foundation for a Digital Supply Chain

Apart from visibility, a digital supply chain helps set in motion initiatives that enable organizations to realize an end-to-end autonomous operation, leading to exponential benefits. Setting up a digital supply chain requires businesses to focus on four foundational building blocks. These include: a connected environment comprising key stakeholders; an internet of things (IoT) ecosystem for harvesting data from stakeholders and functions; an analytics layer (powered by machine learning) to provide guidance on business scenarios; and finally a decision engine that acts on the intelligence.    

Let’s take a look at how these four building blocks work in tandem to create an end-to-end autonomous supply chain: 

Enabling global traceability with IoT

  o The first step in building an autonomous supply chain is to connect various systems such as ERP, CRM, and warehouses through an IoT platform. Doing so enables businesses to track real-time information on material or product movement across each process and function. Leading companies such as DHL and Cargotec are using IoT in logistics to increase visibility and streamline operations. In addition, companies can achieve complete reverse traceability – tracking of goods from customers to vendors - leveraging IoT. The result: efficient recall and accurate inventory predictions and quality improvement recommendations. 

Creating a connected ecosystem for business impact

  o Companies are increasingly using RFID, GPS, and drones for gathering real-time updates on a product’s location while in transit, assessing the condition of perishable goods, and calculating pending inventory. For instance, yard management solution company PINC, utilizes drones to identify the location of trailers and shipping container, enhancing inventory accuracy. However, effectively managing the high volume of data generated by a connected ecosystem is crucial to generating efficient insights. One way to do this is by segmentation of suppliers and stakeholders to enable focus on high priority and high ROI initiatives, enabling change management, and partnering with technology providers to drive innovation and superior service. 

Building supply chain digital twins 

o Building a digital twin of the supply chain lays the foundation for autonomous operations. This involves integrating various platforms such as ERP, MES, CRM and creating functional twins of key stages. For example, a digital plant can create a digital twin of the manufacturing process. Through connected logistics, companies can build digital twins of different scenarios for integration and simulation. When coupled with digital twins, a connected ecosystem enables end-to-end visibility of the supply chain. This, in turn, helps build what-if scenarios for an autonomous selection of the right fulfillment patterns, increasing sales and customer retention.

Analytical models

  o Leveraging analytics, heuristics, conditional planning, and other cognitive decision models can help customers drive key business decisions such as logistics rerouting, on-demand manufacturing, and effective supply chain synchronization. By 2023, it is estimated that over 30% of operational warehouse workers will be supplemented with collaborative robots. This will result in a seamless autonomous function, paving the way for high agility, nimbleness, reduced cost of operations, and increased customer fulfillment and retention. 

The path to an end-to-end autonomous supply chain

The path to end-to-end autonomous operations starts with  putting the  foundational blocks in place, then aligning milestones with active business challenges, and finally, establishing a technical and architectural roadmap. Setting up the foundational blocks itself  can lead to increased revenue through higher customer retention and reduced operational costs due to optimized inventory management.

 

Anandakumaran Ponnuswamy is the Global Head of the Connected Supply Chain Solutions at TCS. He brings more than 16 years of experience working across various industries, for more than 100 customers. He specializes in supply chain solutions across sourcing, planning, scheduling, order management, logistics, inventory management, and aftermarkets. He has delivered significant business value for customers through disruptive technologies such as IoT, automation, deep learning, and digitization.