Businesses today face major challenges in terms of greater competition and increased customer expectations from the global market. With advances in logistics and information technology, today’s customers are exposed to abundant products and services offered worldwide. Thus, businesses aim for competitive advantage and product/service differentiation to stay relevant and profitable. They strive to build robust supply chains that can help them deliver the right product/service more quickly and economically than their competitors. The focus of this book is to provide an overview on the current trends in supply chains as well as present advanced analytical models to optimize the design, planning and operation of supply chains. This chapter discusses the concept of supply chain management, various levels of supply chain decisions and their impacts, drivers and enablers of a supply chain, types of supply chain, and introduces the role of analytics in supply chain. Further, this chapter also presents relevant case studies to help readers better understand various aspects of supply chain management and their importance. Finally, this chapter links the various supply chain problems addressed in this book to the key decision levels and analytical methods, thereby setting the stage for the readers.

1 Overview of Supply Chain

A supply chain contains all stakeholders and activities involved in completing a customer’s order, be it a product or a service. Supply chains are not just restricted to the suppliers and manufacturers, but any stage directly or indirectly involved, including transporters, distributors, retailers, and even end-customers. Further, these stages may even be located in different countries across the world for a company with a global supply chain footprint. For example, the journey from coffee bean to a beverage at Starbucks involves such a global supply chain, where coffee beans and related items are brought from around the world and consigned to Starbucks’s 16,700 retail stores to serve over 50 million buyers across 51 different countries each week. A single cup of coffee at Starbucks, from the coffee bean, milk, sugar to the paper cup, can be dependent on as many as 19 countries, connecting some of the poorest countries in the world to the richest.

A formal definition of supply chain is given by Ravindran and Warsing (2016, p. 2) using two components:

  1. (i)

    “a series of stages (e.g., suppliers, manufacturers, distributors, retailers, and customers) that are physically distinct and geographically separated at which inventory is either stored or converted in form and/or in value.”

  2. (ii)

    “a coordinated set of activities concerned with the procurement of raw materials, production of intermediate and finished products, and the distribution.”

Supply chains tend to be highly dynamic; in addition to product movement, they also involve the flow of information and funds between different stages. For example, e-commerce websites, such as Amazon.com, adopt a series of interrelated activities, as shown in Fig. 1, to satisfy customer orders. The products from the third-party sellers are bought and shipped to one of the company’s fulfillment centers present worldwide, via air hubs, port facilities, and cross-docks. Cross-docks are places where goods from inbound transport are removed and then directly loaded onto an outbound carrier, to facilitate logistics efficiency. Usually, the fulfillment centers hold required inventory levels predicted by analytical algorithms to enable express deliveries. The fulfillment centers not only act as a warehouse but also host facilities to package products and prepare them for delivery when needed. Following customer orders, the products are usually moved from the fulfillment center to the nearest sortation center, where they are segregated based on ZIP codes. Consequently, they are transported to their appropriate delivery stations, where the products are prepared for their last-mile delivery.

Fig. 1
figure 1

Stages of E-Commerce Supply Chain

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As demonstrated in Fig. 1, real-world supply chains are usually not linear but complex convergent and divergent networks as a manufacturer may source from multiple vendors and then supply to numerous distributors. Further, the flow can happen in both directions and may be controlled by one or more intermediate stages. Finally, through the whole process, along with the product, both information and funds constantly flow to make the supply chain efficient. Thus, most supply chains tend to be complex networks or webs needing holistic management strategies to function effectively. The Association for Operations Management (APICS) defines supply chain management as “the design, planning, execution, control, and monitoring of supply chain activities with the objective of creating net value, building a competitive infrastructure, leveraging worldwide logistics, synchronizing supply with demand, and measuring performance globally” (Blackstone 2010, p. 148).

2 Supply Chain Decision Levels

While managing a supply chain, numerous decisions need to be taken regarding the flow of materials, information, and funds. The various decisions taken in a supply chain fall under one of the three levels, namely, strategic, tactical, and operational, based on how frequently that decision is taken and duration over which its impact is experienced.

2.1 Strategic

Strategic decisions primarily determine how a supply chain is designed and who will be the partners for the upcoming years. Unlike other decisions, strategic decisions have a significant long-term impact, and making sudden changes is generally both expensive and not feasible. However, both the customer demands and market are ever-changing, making it crucial for the companies to carefully account for the uncertainties tied with the future before making any strategic decisions. These decisions majorly decide the structure of the supply chain, method for material procurement, strategy for allocating resources, and processes undertaken at each stage. Broadly all the strategic decisions taken in a supply chain fall under one of the three categories—network design, production and sourcing, and information technology.

First, in network design, decisions regarding the number and type of facilities needed, their geographic locations, and their production and storage capacities are made. Other strategic decisions regarding the mode of transport between these facilities also fall into this category. Second, in production and sourcing, decisions on making or buying (whether to outsource or conduct the activity in-house) at each stage of a supply chain are taken. Moreover, decisions on the selection of vendors, sub-contractors, and other alliances also belong to this category. Finally, strategic decisions can also be related to managing information technology infrastructure. Decisions like what type of information systems are needed, and whether to develop them internally, buy the related commercially available version or employ the freely available open-source alternatives are taken here.

An American multinational food and beverage corporation, PepsiCo, is an apt example of how effective strategic decisions can better satisfy customers. While PepsiCo’s best-known products were carbonated drinks packaged in metal cans or plastic bottles, the change in customer’s preferences towards nutritious food and environmentally friendly products created a challenge. To satisfy this new set of customer preferences, PepsiCo took the strategic decision to empower alternatives like Naked Juice and O.N.E Coconut Water (Forbes 2016). The company sourced ingredients from across the world, including certified non-GMO, fresh, and organic alternatives. Further, to enable the production of these products, global supply chains were set-up with refrigeration capabilities throughout the chain. Finally, to satisfy environmentally conscious customers, Naked Juice products were packaged in recyclable bottles. Furthermore, these bottles were explicitly designed in cuboidal shapes to improve packing efficiency during transportation, and the modes of transportation employed were also changed to reduce the overall carbon footprint.

Chapters “Product Life Cycle Optimization Model for Closed Loop Supply Chain Network Design”, “Supply Chain Risk Management in Indian Manufacturing Industries: An Empirical Study and a Fuzzy Approach”, “Improving Service Supply Chain of Internet Services by Analyzing Online Customer Reviews”, and “An Integrated Problem of Production Scheduling and Transportation in a Two-Stage Supply Chain with Carbon Emission Consideration” address some of the key strategic issues in a supply chain.

2.2 Tactical

Tactical decisions, unlike strategic choices, have a relatively moderate impact. Typically, these decisions are related to supply chain planning activities and are made every month or quarter. Due to the shorter time frame, these decisions face lesser uncertainties, though not insignificant. However, companies can leverage better prediction tools to mitigate these medium-term uncertainties and even alter their decisions with relatively more ease. Specifically, strategic decisions taken during the design stage can be capitalized to optimize the supply chain and meet the changing customer demands and market conditions. The tactical decisions required for planning the supply chain activities can be grouped into a few broad categories such as

  • Purchasing: Decisions on the quantity of materials (supplies) to procure as well as the time to order.

  • Production planning: Decisions related to the quantities needed to be produced over different time periods to meet varying demands are made.

  • Transportation: Decisions related to scheduling shipments of raw materials, intermediates, and final products

  • Inventory Management: Decisions on how much supplies should be stored to mitigate shortage risks while keeping inventory costs minimal.

  • Distribution: Decisions that aim to coordinate the distributor replenishment schedule with the production capacity to make the product or service available for the customer at the right time

IKEA, a multinational furniture retail company, is a success story on how effective tactical decisions can revolutionize a business. IKEA is well-known for providing a wide variety of home furniture at very affordable prices. This is particularly made possible through innovative and optimized decisions in inventory management. For example, IKEA stores observe a “cost-per-touch inventory” principle, where the company seeks to reduce the cost-incurred by cutting down on the number of times it handles (touches) a product (TradeGecko 2018). First, IKEA stores are equipped with showroom inventories from where the customers on selecting their products can retrieve their packages and take them home by themselves. Second, apart from showroom inventory, the store also features reserve inventories of two types—high-flow and low-flow inventories. The high-flow inventories are filled with reserve stocks of fast-moving products where more frequent handling takes place. However, by equipping these high-flow facilities with automated storage and retrieval systems, IKEA could further cut-down handling costs efficiently. All the cost-cutting made through the tactical decisions mentioned here is reflected in the low price of the products available for IKEA customers.

Chapters “An Integrated Problem of Production Scheduling and Transportation in a Two-Stage Supply Chain with Carbon Emission Consideration” and “A Simulation-Based Evaluation of Drone Integrated Delivery Strategies for Improving Pharmaceutical Service” prescribe the best course of action for tactical decision-making.

2.3 Operational

Operational decisions are short-term choices (such as day-to-day operations) characterized by low uncertainty and expenditures. A supply chain is pre-determined by the strategic and tactical decisions, and the operational decisions do not impact its configuration nor planning policies. However, operational decisions can optimize performance at an individual order level within the constraints fixed by the previous decision levels. The focus is to deliver to the inbound customer orders in the most effective manner. Operational decisions are related to activities, including allocating production or inventory in response to customer order, selecting a date for delivering the product or service, updating the pick-up task list used at the warehouse, assigning appropriate shipment methods, and finally, placing replenishment order to maintain inventory.

The importance of operational decisions can be emphasized using the case of Target Corporation, one of the largest retailers in the United States. However, the company could not successfully penetrate into the Canadian market. While there are many reasons attributed to the Canadian stores’ failure, ineffective operational decisions played a significant role. These stores ran out of stocks within the initial days of their opening as enough replenishment orders were not being placed. The empty shelves were very disappointing for the eager customers expecting an abundance, as found in the US stores (Fortune 2015). Even during the latter days, the store faced inconsistent supplies at the distribution centers and the retail stores. The flow of individual products was not appropriately tracked, entries were miss-understood, and even the demand forecasts were not accurate. These lead to inefficient operational decisions that were expensive both in terms of storage cost and customer satisfaction. Finally, all the customer resentments cumulated and reached a stage from where recovery seemed far-fetched. Within 2 years, the company shut down all of its 133 Canadian stores and incurred $2.5 billion in losses.

Chapters “Pro-Active Strategies in Online Routing” and “Prescriptive Analytics for Dynamic Real Time Scheduling of Diffusion Furnaces” provide strategies to make effective real-time operational decisions.

3 Supply Chain Enablers and Drivers

Enablers can be understood as things that are needed to achieve a goal. Marien (2000) reports four enablers that are needed for the effective functioning of a supply chain, namely

  • Organizational infrastructure: It is crucial for an effective supply chain as it determines how the different stages coordinate together to accomplish its goals. The key concern here is organizing supply chain activities, both within the firm and across firms, for vertical orientation or more decentralization.

  • Technology: Two types of technologies, manufacturing technology, and information technology, are necessary to enable superior supply chains.

  • Strategic alliances: Establishing long-term partners is a key enabler for a supply chain. Alliances specifically play a vital role in a decentralized supply chain where great power and responsibility are present with the suppliers.

  • Human resources: Includes technical and managerial employees with a holistic understanding of supply chain management concepts and tools. These employees are needed to design and operate an effective supply chain.

While enablers support the smooth functioning of a supply chain, the drivers are areas of crucial decision making. The four major drivers of a supply chain, as described by Ravindran and Warsing (2016, pp. 7–9) and Chopra and Meindl (2013, pp. 41–42), include inventory, transportation, facilities (plants and distribution centers) and suppliers. These drivers do not function independently but interact with each other to establish the overall performance of a supply chain. For example, setting up facilities in remote places away from major cities may reduce rental costs, but will increase transportation costs and affect delivery time. Similarly, procuring and storing supplies in large quantities can reduce cost in terms of raw material and transportation and even improve customer satisfaction levels, but will drastically increase inventory storage costs. Hence understanding how these drivers interact and making efficient trade-offs between them is crucial to achieving superior supply chain performance.

4 Types of Supply Chain

Each company has a competitive strategy that involves satisfying the needs of the customer belonging to a particular segment. The overall supply chain and its individual stages need to align with this strategy. For example, customers of a supermarket prioritize availability and variety over the price of the products. These customers are willing to pay higher prices, provided they can buy everything from vegetables to pastries at the same place. Hence, these stores have robust supply chains that provide a vast range of 15,000 to 60,000 SKUs. While on the other hand, customers of limited-assortment stores want lower prices and are ready to compromise on variety. These stores tend to have cost-effective supply chains that offer a limited range of items (fewer than 2000), with many stores not offering any perishables. The requirements of the customers prioritized by the competitive strategy must match with the capabilities of the supply chain, and this consistency is referred to as strategic fit by Chopra and Meindl (2013, p. 21). In case of a lack of strategic fit, the company must alter the supply chain to meet its competitive strategy or modify its competitive strategy based on what its supply chain is designed to do well. Depending on these supply chain capabilities, supply chains can be understood as one or a mix of the following types:

  • Responsive

  • Efficient

  • Resilient

  • Humanitarian

  • Green

  • Sustainable

Figure 2 illustrates the key capabilities of the different supply chain types with respect to seven different criteria, namely, profitability, cost reduction, speed, flexibility, social responsibility, environmental concern, and ethical practice.

Fig. 2
figure 2

Capabilities based on supply chain type with respect to different criteria

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4.1 Responsive Supply Chain

Ravindran and Warsing (2016, p. 12) describe responsiveness as “the extent to which customer needs and expectations are met, and also the extent to which the supply chain can flexibly accommodate changes in these needs and expectations”. Therefore, responsive supply chains seek to prioritize service levels over operating costs. Further, the responsive supply chains tend to follow a push framework where the supply chain is initiated in anticipation of a customer order instead of a response to an actual customer order (pull strategy). The push strategy helps companies serve their customers quickly but at the cost of higher inventory costs, including wastages. The characteristics of responsive supply chains include:

  • Short delivery time

  • Wide product varieties

  • Provision for customized orders

  • High reliability

  • Superior service quality

One of the industries that heavily depend on the responsiveness of their supply chains is the fashion industry. To catch up with changing seasonal trends, the companies rely on quick and flexible supply chains. These companies prioritize flexibility, reduced lead time, and timely distribution over cutting costs. For this reason, these companies prefer to have an in-house manufacturing facility despite low-cost manufacturing options in other countries, which might compromise on-time performance or flexibility.

4.2 Efficient Supply Chain

Not every competitive strategy prioritizes responsiveness. In the case of stationery manufacturers, where both the product variety and its demand are mostly standard, responsiveness may not be the key. For instance, adopting a flexible supply chain that manufactures custom stationery in small batches and then ships them using an express transporter only makes the stationery unnecessarily expensive, leaving the customers dissatisfied. In such scenarios, a cost-efficient supply chain is vital. Efficiency is the output obtained per unit input, and in the case of a supply chain, it is the ratio of the revenue generated to the cost incurred. Thus, the sole goal of an efficient supply chain is to minimize the costs. The stages where supply chains focus to cut-costs include:

  • Raw materials procurement

  • Inventory holding

  • Manufacturing

  • Transportation and distribution

  • Facility operations

Efficient supply chains tend to follow a pull strategy that is practiced in environments where the demand is known. Here the supply chain is only reactive to the actual customer order. Such efficient supply chains tend to hold fewer inventories and carry a level load in warehouses to minimize costs associated with picking and packing. Efficient supply chains have their drawbacks as well. For instance, to reduce costs, product offerings need to be standardized. This affects variety and personalization capabilities, which decreases responsiveness. In fact, for every strategic decision to increase efficiency, there is usually a compromise on responsiveness. This relationship can be observed in the responsiveness-efficiency tradeoff frontier described by Ravindran and Warsing (2016, p. 9–10) and Fisher (1997, pp. 105–117), as shown in Fig. 3.

Fig. 3
figure 3

Responsiveness-efficiency trade-off frontier

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4.3 Resilient Supply Chain

In recent years, a supply chain’s capability to anticipate and handle disruptions (i.e., resilience) has taken importance. This change is primarily due to two reasons. First, today’s world has grown into a highly interconnected global village where a small disruption at a particular place is transmitted to the entire world. For example, earlier, an epidemic was usually contained within a region. However, today, owing to high connectivity, epidemics quickly spread and become a global pandemic like the novel coronavirus disease 2019 (also referred to as COVID-19), causing a worldwide disruption. Secondly, today’s supply chains have become truly global, with each stage located in a different country altogether. Hence a small workers’ strike at one of the countries can stop the entire global supply chain. Thus, in a world of globalization where disruptions are felt everywhere, it is essential to design supply chains by keeping resilience as a priority.

In recent times, the COVID-19 global pandemic highlighted the importance of a resilient supply chain. Deloitte (2020) reported that the companies that could perform well during the pandemic were the ones that invested in supply chain risk management. These companies diversified their supply chain from a geographic perspective to avoid risks from disruptions caused in any one country. Further, they multi-sourced vital components to reduce dependency on any one vendor. Finally, they also considered inventory plans that allowed for buffers needed to manage unprecedented disruptions. On the contrary, the companies that scrambled were highly dependent on a specific geography or a particular supplier for vital commodities. A singular focus on cost-cutting caused negligence towards resilience, making these supply chains brittle and vulnerable during disruptions.

4.4 Humanitarian Supply Chain

Barve and Yadav (2014) describe the humanitarian supply chain as the “flow of relief aid and the related information between the beneficiaries affected by disaster and the donors so as to minimize human suffering and death”. In a humanitarian supply chain, the customers include the affected people and the intermediate storage facilities, while the supplies include relief aids like materials, logistics, and even volunteers. Since humanitarian supply chains face a lot of unknowns, uncertainties and need coordination among numerous stakeholders (like donors, volunteers, government, NGOs, and military), along with relief aids, the effective flow of information is vital. This type of supply chain is complex as they tend to have limited infrastructure and other resources, making them dependent on donors and volunteers.

Humanitarian supply chains need to be highly responsive to the disaster type and its changing phases. While they may be newly established during a particular crisis, humanitarian works during the COVID-19 pandemic showed the importance of leveraging existing supply chains’ flexibility. Highly responsive fashion companies like Prada, Armani, Gucci, and Giorgio could customize their manufacturing facilities to produce medical overalls. Moreover, within 72 h from the France government’s request, Louis Vuitton, a French luxury conglomerate, converted its perfume factories to manufacture sanitizers and provided pandemic support (Vogue Business 2020).

4.5 Green Supply Chain

With increasing customers showing concern for the environment, companies seek to identify and incorporate environmentally friendly practices in their supply chain to gain competitive advantage. Further, the government imposed environmental regulations that have made it imperative for companies to build greener supply chains, especially in countries like France, Spain, Morocco, and Kenya. Building a green supply chain requires a unified effort from all the stakeholders and stages. Manufacturers must work alongside both the suppliers and customers to enable their environmental goals. These environmental goals usually include reducing solid waste, effluent waste, air emissions, and usage of toxic materials.

While employing a green supply chain can give a competitive advantage, there still are concerns about whether they will translate into substantial improvement in profits or market share. However, employing environmentally harmful practices have impacted businesses negatively. For example, Nestle, a global food processing company, had to face a myriad of issues when Greenpeace International held the production of Nestle’s confectionery product, KitKat, responsible for deforestation (Purkayastha and Chaudhari 2012). The company was accused of destroying precious rainforests to increase palm plantations and palm oil produce needed to manufacture their confectionary. Further, by facilitating high impact social media campaigns, Green peace could pressurize Nestle to stop sourcing palm oil from Sinar Mars, an organization accused of illegally clearing rainforests, and source its palm oil responsibly. Similarly, Unilever too had to stop purchasing palm oil from controversial vendors.

4.6 Sustainable Supply Chain

With dwindling resources, today’s supply chains need to focus on social and environmental facets along with common economic goals to achieve sustained growth. These three dimensions of sustainability are together referred to as the “triple bottom line (3BL)”. The goals of a sustainable supply chain can be understood as the following:

  • Economic dimension—This is primarily concerned with generating higher profits and achieving growth.

  • Social dimension—The focus here is on improving employment opportunities, workplace safety, charity, and overall community wellbeing.

  • Environmental dimension—This deals with aspects involving global warming, ozone layer depletion, climate change, different types of pollution, and ecological preservation.

One of the pioneers in sustainability, Ben & Jerry’s, could successfully incorporate all the three dimensions in its mission (Performance Magazine 2020). As early as 1989, the organization opposed the use of recombinant growth hormones to prevent harsh financial impact on family farming. The company introduced the “Caring Dairy” program and established Fair Trade prices to support its farmers in conducting sustainable farming practices. The organization also established Ben & Jerry’s Foundation to motivate its employees to give back to their societies. Further, the company also invested in sustainable packaging solutions. With all its sustainability endeavors, Ben & Jerry’s is considered as an example of how prioritizing sustainability helps businesses build a well-liked brand.

5 Impact of Industry 4.0 on Supply Chain

The current industrial revolution, Industry 4.0, is about integrating physical and digital systems to enable effective decisions that require minimal human supervision. It focuses on inter-connectivity using technologies such as the internet of things (IoT), cloud computing, artificial intelligence (AI), and advanced robotics. While these intelligent technologies have transformed numerous areas, they specifically have a profound impact on supply chains. Industry 4.0 has led to major improvements in different supply chain stages, including procurement, inventory management, logistics, production, and retailing, by facilitating process integration, automation, digitization, and analytical power. The ability to exchange data and make decisions is particularly useful in supply chain as they have a dynamic network consisting of multiple stakeholders and stages needing collaborative decisions at every level.

Despite numerous benefits, a majority of companies are yet to adopt Industry 4.0 technologies into their supply chain due to doubts on return on investments, struggle to find qualified talent to implement and maintain these systems, shortage of financial resources, concerns over data security, lack of information technology infrastructure or even due to the sheer lack of knowledge about its benefits (Horváth and Szabó 2019). However, there have indeed been numerous success stories. One of the best examples is the widespread adoption of intelligent tools that can accurately predict consumer behavior and guide demand planners. Demand planning is a manually intensive week-long task repeated at the beginning of every month (SAS 2018). Demand planners spend 40% of their time cleaning and managing inventory and sales data, an additional 30-40% of time reviewing forecasting models and fine-tuning them, and 10% of time reporting their findings (SAS 2018). This further becomes cumbersome when a supply chain deals with numerous products across different categories. Nevertheless, with developments in analytical technologies, supply chains leverage AI tools to effectively handle most of these manual and repetitive tasks, leaving time for demand planners to focus on other value-adding work.

Apart from demand planning and then sourcing from reputed suppliers, ensuring the quality of a product/service is a vital aspect of supply chain management (Romano and Vinelli 2001). With improvements in capturing and analyzing sensory data, companies continuously monitor their product/service to ensure consistent quality. For example, manufacturing industries capitalize on image processing and machine learning developments to automate visual inspections, which would otherwise be time-consuming, labor-intensive, and prone to human error. Like few modern call centers, other service providers also leverage voice recognition and natural language processing tools to ensure their agents’ quality and drive customer satisfaction. Further, with developments in IoT technologies, not only quality is monitored but also controlled. For example, many plastic goods manufacturing companies continuously monitor their manufacturing process at all stages. When any temperature deviation or product abnormality is identified, the production process enabled using IoT is automatically modified to produce ideal results. Thus, Industry 4.0 also supports supply chains by enabling consistent quality, cutting-down costs, improving resource utilization, and driving process efficiency.

Due to the developments in Industry 4.0 technologies, specifically IoT and sensor technology, both manufacturing and service organizations generate massive amounts of industrial data. To a large extent, the success of a supply chain lies in its ability to effectively capitalize on this data by leveraging advanced analytical tools to gain intelligence. Supply chain analytics deals with the use of quantitative models for data-driven management of all the decision levels—from helping in supply network design and vendor selection at the strategic level to managing procurement, inventory, demand planning, and logistics at tactical and operational levels.

The traditional sources of data for supply chain analytics include radio frequency identification (RFID) systems that automatically track items attached with RFID tags, global positioning systems (GPS) that provide the locations of shipments in transit, and barcode enabled systems that capture transactions. Further, supply chain analytics also heavily depends on data visualization techniques to report its findings in a human interpretable manner. Depending on the complexity and value addition, supply chain analytics can be classified into three types—descriptive, predictive, and prescriptive.

  • Descriptive analytics uses aggregation, visualization, and mining of historical data to provide insights on prior trends and patterns. It helps supply chain practitioners to learn from the past and also uncover relationships between variables, thus empowering them to make better decisions in the future. Apart from past data, descriptive analytics also uses current data to provide valuable real-time information and visibility needed to effectively manage the supply chain. For example, information on the current locations and quantities of different products in a supply chain can help managers optimize several decisions such as delivery schedule, transportation modes, and replenishment orders. Tools such as dashboards, scorecards, and sales reports are key enablers of descriptive analytics.

  • Predictive analytics enables an organization to estimate the likelihood of future outcomes using historical data. It relies on forecasting and machine learning algorithms to achieve its purpose. In a supply chain, predictive analytics is majorly used to predict demand, customer purchasing patterns and behaviors, inventory records, and performances of various supply chain stages. The complexity of the models deployed as well as the value-addition from predictive analytics is higher as opposed to descriptive analytics.

  • Prescriptive analytics aims to provide the best course of action, given a particular situation, and also report on the consequence of undertaking such an action. While descriptive and predictive analytics provide decision support, prescriptive analytics ventures one-step further with decision automation. For example, predictive analytics can forecast the demand given historical data, whereas prescriptive analytics will be able to capitalize on such predictions to provide the optimal replenishment policy along with its impact on the inventory costs. Thus, prescriptive analytics provides the highest degree of intelligence, but is also the most complicated among the three types of analytics. The key tools for prescriptive analytics are mathematical optimization models, simulations, and heuristics. Though many companies have employed prescriptive analytics to automatically optimize production, inventory, and logistics, the use of prescriptive analytics is still at its early stages (Lepenioti et al. 2020)

This book focuses on introducing the recent trends in supply chain management as well as the applications of advanced analytical models that impact different decision levels. While adoption of Industry technologies in supply chains has numerous facets, improving visibility is one of them. Visibility provides the ability to track orders and products as they move through the manufactures’ value chain to the final customer. Chapter “Intelligent Digital Supply Chains” provides a detailed discussion on visibility in supply chains. Long-term decisions need to include future uncertainties, and Chaps. “Product Life Cycle Optimization Model for Closed Loop Supply Chain Network Design” and “Supply Chain Risk Management in Indian Manufacturing Industries: An Empirical Study and a Fuzzy Approach” strive to optimize these strategic decisions in the manufacturing sector by proposing a mixed-integer linear programming model and multi-criteria decision-making methods, respectively. Particularly, Chap. “Product Life Cycle Optimization Model for Closed Loop Supply Chain Network Design” is concerned with strategic decisions needed to optimize the product life cycle in a specialized supply chain, while Chap. “Supply Chain Risk Management in Indian Manufacturing Industries: An Empirical Study and a Fuzzy Approach” aims to address strategic decisions that aid in foreseeing exigency and mitigating risks. Chapter “Improving Service Supply Chain of Internet Services by Analyzing Online Customer Reviews” focuses on the service supply chain, specifically that of internet services. It aims to discover strategic insights from online customer reviews by employing text analytics and root cause analysis techniques for this purpose. To address the need of the hour, environment-friendly practices, Chap. “An Integrated Problem of Production Scheduling and Transportation in a Two-Stage Supply Chain with Carbon Emission Consideration” proposes a mathematical model for integrated optimization of strategic and tactical decisions that also accounts for carbon emissions. Chapter “A Simulation-Based Evaluation of Drone Integrated Delivery Strategies for Improving Pharmaceutical Service” addresses tactical decisions in service delivery using simulation modeling. It tries to evaluate the integration of futuristic drones for delivering vital pharmaceutical products. Finally, Chaps. “Pro-active Strategies in Online Routing” and “Prescriptive Analytics for Dynamic Real Time Scheduling of Diffusion Furnaces” propose optimization models and heuristics to deal with operational decisions proactively. While Chap. “Pro-active Strategies in Online Routing” aims to control urgent logistics in real-time, Chap. “Prescriptive Analytics for Dynamic Real Time Scheduling of Diffusion Furnaces” focuses on prescriptive analytics for controlling scheduling in a manufacturing process in real-time.