Supply Chain 4.0: An Overview
How Digital and Analytical Technology Could Power Supply Chains
This article provides a quick overview of Industry 4.0 systems and how they could enhance capabilities in a supply chain. (in another article I give examples of specific capabilities that these systems could build)
The current trend in supply chains across the globe and industries is toward becoming more agile and responsive while simultaneously maintaining cost-efficiency. This is a result of general momentum toward globalization and competition, customers becoming more connected and aware (thanks to internet, smartphones and social media), and digital technologies offering new opportunities for organizations to be more customer responsive and thereby differentiate themselves in new ways. Two years of Covid-19 pandemic have accelerated the progress of digitalization, making the CXOs and managers more anxious about charting a transition to digitalization and analytics in a manner that adds value to their business and mission (this is valid not only for profit-making businesses but also for non-profits with social mission).
State of Digitalization and Analytics in Supply Chains
The current use of digitalization and analytics in most organizations remains patchy. The data gathered from various points of execution in a supply chain’s operations are largely semi-automated, periodic, and confined within a facility or a region (e.g. sales area). The IT systems are not fully integrated. As a result, use of automated processes and analytics to support execution and planning of supply chains is partial. Automation of operations remains confined to individual machines and that of data capture to sensors at certain clusters of operations (e.g. GPS in vehicles and IoT sensors on machines) (see Figure 1). There are, of course, some organizations that are much advanced in terms of adoption of digitalization and analytics — for instance, GE, P&G, Walmart, Maersk, Tetra Pak, and the new-age e-commerce firms such as Amazon, Uber, Airbnb, Flipkart, Ola, Swiggy, Bigbasket — but they are exceptions to the general scenario. Most of the firms that didn’t start as e-commerce are trying to play ‘catch up’.
The Promise of Industry 4.0 Technologies
Industry 4.0 is about distributed, intelligent and interconnected systems of production, logistics, supply chain partners (including suppliers and customers) and resources (both workers and machines), based on a range of technologies. This is unlike Industry 3.0 which was primarily about robotic manufacture and other automated production systems with electronics and computerized control (for reference, Industry 2.0 saw the rise of electrification and mass production and assembly lines in industry, and Industry 1.0 began with the advent of mechanization of production and logistics powered by steam and water).
The Industry 4.0 technologies and their uses for supply chains could be classified into three categories.
1. Distributed and interconnected systems to collect, store, share and trace information in a quick and secure way. By ‘interconnected systems’ we imply systems of organizations (own, suppliers, customers), humans (workers, teams of workers, customers), machines, facilities, and products. This is possible with technologies such as mobile devices, IoT/sensors, cloud, blockchain, augmented reality (AR), collaborative platforms, data and data exchange related standards and protocols. These technologies connect and combine the physical and cyber worlds. They have the potential to create value across a supply chain by facilitating collaboration and autonomous, near-real time exchange of information while guaranteeing security and traceability.
2. Analytical systems to use information intelligently. The intelligent use of data/information is possible through analytical tools of big data, cloud computing, artificial intelligence (including machine learning and deep learning), statistics, optimization (including OR), and simulation. These tools help in assessing the past and current status of a set of operations or supply chain (e.g. costs incurred, time taken, customer service levels achieved), predict relevant future parameters (e.g. forecast of sales, likely delivery of customer order, chance of machine failure, chance of customer returns), and prescribe desirable actions and cognitive decisions (e.g. predictive maintenance of machines, procurement/production/distribution/inventory stocking plan based on forecasts, sales targets, promotions, design of new products, marketing strategies).
3. Flexible, collaborative and automated systems of production and logistics to enable agile, custom and efficient operations in the supply chain. These systems are made possible through technologies such as additive manufacturing (3D printing), cobots (collaborative robots), intelligent automated guided vehicles (AGVs), drones, and AR. These technologies have developed more or less independent of the data capture and analytical systems described in the previous categories. However, they create a synergistic effect together with those categories by automating complex tasks, enhancing human-machine interfaces, and permitting JIT, small-lot, make-to-order manufacturing and deliveries that are also efficient.
With digitalization and analytical technologies of Industry 4.0 it is possible to achieve automated, real-time (or near real-time) data capture and tracking throughout the supply chain. Combined with analytical tools, they can permit collaborative and efficient execution of operations. With flexible and automated systems, these operations could become not only efficient but customer-responsive. With predictive, prescriptive and cognitive analytics, it would be possible to enhance the quality and speed of improvement actions in the short and long term, such as diagnosing and preventing defects, reducing excess stocks, resource downtime, delays and other waste, identifying and removing bottlenecks, and strategically adding capacities, locations, partners and products (see Figure 2).
Our experience of serving customers at IGSA Labs shows that the execution processes could be automated to a great extent. The planning and strategy making processes depend crucially on the vision and creativity of humans. However, they could be directly assisted with automated cognitive analytics and the quality of human decisions could be enhanced drastically.
However, most Industry 4.0 technologies are expensive and their implementation could disrupt existing technology systems, processes, work practices and skills. Therefore, utmost care is required in deciding the kind of capabilities that an organization wishes to build, in selecting the right technologies that would help build those capabilities, and making changes in skills, processes and organization in order to ensure effective implementation. We can draw lessons from the organizations that have taken lead and are making relatively successful transitions. Those are the topics for another day!
(In another article I discuss examples of specific supply chain capabilities that Industry 4.0 technologies could build)
