supply chain management solutions

supply chain management solutions

Innovative Supply Chain Management Solutions: Enhancing Efficiency and Resilience

1. Introduction to Supply Chain Management

Intuitively, a large part of supply chain efficiency directly depends on distribution decisions concerning how, when, where, and by whom different materials and products are ultimately distributed or delivered. Recent studies suggest that more than 70% of the time and cost in manufacturing activities are directly related to transportation. The remaining 30% of manufacturing costs tied to non-transportation business processes hinge upon the delivery or distribution process. These costs depend on different concerns, such as the choice of modes and carriers of distribution; pickup and drop-off scheduling of carrier services; routing and location of supply-chain nodes; port-of-entry selections; cross-docking and multimodal transportation; demand, supply, and capacity interactions; congestion and other externalities; and risk and disruption tolerance, among others. As the emphasis of the traditional transportation-warehousing dichotomy continues to shift from cost to service and from activities to strategies, there is compelling evidence that contemporary commercial enterprise strategies can be traced to roots in historical logistics and SCM. This work is directed toward examining, analyzing, and providing operational tools related to some novel and innovative supply chain management strategies that have the dual goals of enhancing efficiency and resilience.

A supply chain begins with the acquisition of materials and resources, progresses through manufacturing, and ultimately culminates in the distribution of products to customers. Indeed, supply chain management (SCM), which encompasses the design and management of business systems and their capabilities to strategically coordinate the activities of procurement, production, inventory, financial, customer service, and logistics, is an imperative process in any manufacturing or service firm, whether global or local. Supply chain activities are typically threefold, beginning with planning, which is followed by sourcing, and then finally in the execution and control of operations. Specifically, these activities entail various inter-organizational business processes, such as supplier assessment and selection; supplier relationship management; logistics management, which includes shipping and receiving; inventory management and control; quality measurement; and order tracking, among others.

2. Challenges in Traditional Supply Chain Management

Before reviewing the supply chain management challenges, it should be clarified what is meant by supply chain management. Supply chain management is the integrated management of the interrelated activities, namely the material flow from supplier to manufacturer, the manufacturing process itself (including development and manufacturing of the product itself), and the distribution of the product from the manufacturer to the end customer. A particular sector or industry may encompass all necessary activities for different types of products, but a unique supply chain is always developed for a particular product family or a specific product. The supply chains within an industry compete with each other for available resources: markets, labor, finance, and material supply. These interrelated competitive activities generate the competition of one industry or country versus other industries or countries.

3. Emerging Technologies and Solutions in Supply Chain Management

Ogden et al., in the 2018 Annual Standards and Post-FSA Survey Report, observed that a majority of respondents identified the use of emerging technologies to manage supply chain and logistics service provider risk as the number one reason for companies investing in improved data and technology. These technologies, when applied together, could provide a streamlined process for organizing and simplifying a complex, global supply chain of components, metal, transport, and electromagnetic tests. Such collaborative applications of technology can also bring greater transparency, automated documentation, and data integrity. The development of artificial intelligence and machine learning, when applied to analyze data from the range of digital tools, can more quickly and accurately identify and reduce poor supplier performance and compliance issues.

In a bid to harness the opportunities offered by emerging digital technologies in enterprise operations, logistics, and supply chain practitioners are leveraging new business models, adopting smart technologies, and digital tools including big data, blockchain technology, internet-of-things systems, artificial intelligence, and robotics among others. These technologies have the potential to revolutionize enterprise operations, and indeed, many supply chain management executives and professionals are hopeful that the emergence and wider use of these new technologies offer solutions to many of the ongoing and emerging challenges in the industry. For example, industry analysts see blockchain technology as critical to enhancing global traceability of processes, which is essential to maintaining the stability and transparency of critical supply chains. Similarly, big data can provide more insights into activities across supply chains. Businesses around the world are applying big data in diverse ways, using data analytics as a basis for forecasting global trade and supply chain flows, identifying trade patterns, demand-supply mismatches, and other important information useful for decision making.

4. Case Studies and Best Practices in Implementing Supply Chain Solutions

In recent years, outsourcing has become one of the major strategies for manufacturing companies to achieve global competitiveness. Many studies have addressed and investigated various issues related to supply chain management. Second, modeling: that is, an innovative supply chain solution mechanism and practical application scenario. Third, evaluation: the proposed solution could generate sufficient market niches. At the process level, essential operations (design and implementation) for getting expected performance from the proposed supply chain system would involve implementation and supply chain management. Finally, reflection: the solution is beneficial for constructing a performance-driven supply chain and achieving a sustainable enterprise.

This section will showcase some best practices and outstanding cases of innovative supply chain solutions, and the problems solved by the solution in each exemplary case. The case study basically follows four key steps. First, problem identification: in order to reflect the important role of supply chain management in strategic decision-making, it is important to look at issues in supply chain management from a strategic perspective. Most of the problems in supply chain management are related to the strategic decisions and needs of the corporation. Such a fundamental function is the transformation function of markets and product development plans to practical operations and management. At the operational level, it provides a processing function of practical data for a business. It is the business system support of a business, and its support is subordinate to business activities.

5. The Future of Supply Chain Management: Trends and Opportunities

The real-time analytics of vast amounts of data generated by tracking products as they move through a supply chain or the connected devices that are part of sensor networks can provide valuable insights that can be used to make improvements in the way the organization sources, manufactures, distributes, and recovers products. The goal of supply chain intelligence is to enhance end-to-end visibility and decision-making across the extended supply chain, to drive breakthrough performance and sustainable competitive advantage. The way ahead is not just about automating existing processes, it is about adopting an analytical way of thinking, doing and being in every business system, process, and decision. After all, the ultimate purpose of all of this is not to create a smarter supply chain, it is to create a winning and sustainable business.

Currently, the main issues concerning the implementation of interactive and adaptive SCS (Smart Manufacturing Network Solutions), mainly targeting the manufacturing environment, encompass the lack of real-time data, information overload, and latency in the response of processes and systems to events and stimuli. Implications are far-reaching and include the need for a sophisticated autonomic control and initialization of the communication infrastructure. Such implications have drawn attention to new concepts particularly for real-time and embedded systems, such as Internet of Things (IoT) and its industrial version, known as Industrial IoT (IIoT).

In the near future, there will be several abilities involved in satisfying each of the elements, especially when regarding intelligent, connected supply chains. As the process and technology innovations getting stronger and better, digital connectivity will drive the next era of supply chain improvement towards the emergence of the smart supply chain. This implies new ways of working in a digital technology-driven ecosystem embracing platforms and supply network solutions. Supply chain management is being disrupted by advancements in data science and big data tools that are far beyond digitizing and automating traditional business processes. Goals of optimizing supply chain performance, smart supply chain management using algorithms, machine learning, and artificial intelligence are being adopted to make rapid predictions and better decisions.

The field of supply chain management will be significantly impacted by several emerging technologies and data analytics strategies in the future. Future technology trends towards more automation could lead to the complete replacement of humans from some sections of the process. Supply chain operations will minimize direct human intervention, and for higher levels of SCM activities like decision-making, operations, exceptions, human interaction and judgment will be the critical components. Thus, in higher categories of SCM services and functions, skilled managers will play a crucial role. Decision making will be more challenging when humans and machines operate together as part of the system. Successful collaboration between human decision-makers, and Artificial Intelligence (AIs), or machine decisions would be crucial for SCM operations. As a result, intelligent SCM solutions would not replace human workforce but assist or augment human labor involved in SCM processes.