Supply Chain Management Strategies and Methodologies

Supply chain strategies (SCS) have been gaining increasing interest given the recent disruptive events associated with wars and pandemics, where traditional SCS have proven insufficient. This article presents a bibliometric review of SCSs, analyzing the main trends, authors, institutions, and countries in which they are found, which will allow new SCS scholars to establish direct contact with the literature. PRISMA methodology is used to identify 1430 documents published from 1993 to 2021, and then VOSviewer and Bibliometrix software are used to analyze the information. Findings indicate that the trend of SCS publications is increasing, that its main area of application is Business, Management and Accounting, and that the main authors are Christopher M., Saputra J. and Wang S., who are also the ones who initiated this term two decades ago. Additionally, the publications on the topic are articles, conference papers, and book chapters, indicating that they have undergone a review process. It is concluded that SCS will continue to grow in initiator countries such as the United States of America and the United Kingdom. However, countries such as China and India will start to increase their academic output significantly.

Demand analysis is one of the cornerstones of any supply chain management system, and most of the critical operational decisions in the supply chain rely on accurate demand predictions. Although a large body of academic literature proposes various forecasting methods, there are still important challenges when using them in practice. The common problem is that firms need to decide about thousands of products, and the demand patterns could be very different between them. In this setting, frequently, there is no single forecasting method that works well for all products. While some autoregressive models might work well in some cases, the demand for other products might require an ad-hoc identification of trend and seasonality components. In this chapter, we present a methodology based on meta-learning that automatically analyzes several features of the demand to identify the most suitable method to forecast the demand for each product. We apply the methodology to a large retailer in Latin America and show how the methodology can be successfully applied to thousands of products. Our analysis indicates that this approach significantly improves the firm's previous practices, leading to important efficiency gains in the supply chain.

The reorganization of the global supply process is giving shape to a new value creation paradigm, where clusters of local producers are becoming the pillars of global supply chains. This phenomenon, known as regionalization, demands the identification of regional productive sectors that exhibit the specialization and dynamism required to create high-value supply chains. Thus, regional development and high-value supply chains are related. In this chapter, we propose a methodological framework to identify the potentialities and opportunities of regional productive sectors to create industrial clusters and high-value supply chains. The State of Tamaulipas (in Mexico) and its municipalities functioned as the region and subregions of analysis, respectively. The results reveal that productive sectors with the more significant potential to create high-value supply chains are the agricultural and manufacturing sectors.

Currently, it is necessary to compete with other strategies, such as Mass Customization (MC), in modern and competitive environments characterized by market uncertainty. Industrial companies that work with engineering-to-order (ETO) production systems need appropriate “supply management” to achieve operational excellence, which allows for remarkable improvements in supply chain performance. The factors and practical improvements in the Supply Management function of ETO companies working in MC environments are identified in this study. These factors and practical improvements affect the raw margin of the operating account and the evolution of the purchase prices of repetitive parts. This paper presents the case of an ETO company shifting to MC strategies by applying the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology. The findings show that the introduction of component standardization programs has a direct and significant impact on account operations in a company. Thus, the cost of merchandise sold in total sales decreases by 1.34%, and the percentage of repetitive parts purchased increases by 10% if Early Purchasing Involvement (EPI) is used. This involvement employs a multidisciplinary team of design assessments (MTDA), improving more than 40% of the value of expenditures over sales, a direct improvement in the raw margin of the company’s operating account.

The World-Class Manufacturing Systems were tested for their adaptability and flexibility during the COVID-19 outbreak imposing restrictions and disrupting the supply chains. This chapter describes using Lean-Sigma for three case studies addressing the lessons and critical tools for overcoming uncertainty and challenges in a Latin American facility. Case 1 describes actions for expected sales increasing in a home-improvement product processing. The challenge, in this case, was addressed by using the eight wastes of Lean manufacturing. It is also supported with a layout redistribution and 5S, observing improvements in productivity levels and new technologies upgrading the process connectivity to elements of industry 4.0. Case 2 is a medical product; rapid demand and sales increment is the scenario to decide to adopt a dial-processing system with a robotic arm to automate four activities of the process. Adopted actions increase quality levels by 50% and a more significant efficiency in implementations, which reduces costs from 5.33 to 0.9 IEU/pc taking only two weeks for the ROI. Case 3 shows developments on a new health-related product, using DMADV of DFSS and reengineering as critical strategies for increasing the usability of equipment and resources available in the production area, resulting in a quick ROI and the newcomer successfully introduced to the market.

The maintenance area is a transcendental link within the supply chain since it is the unit in charge of maintaining the equipment destined to carry out various organizational tasks in perfect working order. The correct maintenance management through the supply chain allows one to fulfill a primary objective, to deliver the required quantity of goods on time at the minimum cost. Within the automotive industry, the supply chain aims to be as efficient as possible, so innovation and developing new technologies are opportunities for improvement. Among the various motors, the three-phase induction motor is the most used, and, like any industrial device, it requires diagnosis and maintenance to continue operating correctly. There are various methodologies to diagnose faults in electric motors; however, their capacity is limited since they can only analyze and detect one type of fault at a time. In the present work, the development of an expert system capable of recognizing three different fault patterns in electric motors is shown; the deterioration patterns involved in the study are severe damage or fatigue in the bearings and short circuits in the winding. The architecture of this system is composed of two artificial neural networks capable of classifying the types of faults in the electric motor, the first artificial neural network determines whether the motor is in good condition or not, and the second artificial neural network is activated when detecting an inconvenience in the motor to give rise to the fault diagnosis. The developed expert system was implemented in an industrial process and reached an average accuracy of 99%, which is why it is validated as a reliable method to diagnose the correct operation of electric motors and, therefore, improve the availability of said motors in addition to other teams with which they relate. The scientific contribution is based on the methodological proposal to achieve a correct diagnosis of the physical state of electric motors from artificial neural networks, which brings, consequently, an increase in manufacturing productivity and greater efficiency in the supply chain of organizations based on the accurate monitoring of the equipment.

This study examines the transactional and transformational leadership of manufacturing managers in Ciudad Juarez (Mexico) and its impact on supply chain flexibility and resilience, which contributes to quantifying the relationship between the variables to provide knowledge on the importance of leadership style in supply chain resilience. The dimensions and items of each latent variable were integrated into a questionnaire administered to Mexican Maquiladora. Two hundred thirty-one valid questionnaires were obtained and analyzed using a structural equation model (SEM) based on partial least squares (PLS) for validating the five hypotheses or relationships between variables. The results indicate that both leadership styles influence supply chain resilience; however, transformational leadership has a greater direct impact than transactional leadership. However, transactional leadership yielded better results when the mediating variable of flexibility was used. These results create a frame of reference to determine which leadership style can benefit the company, depending on the situation in which it finds itself.

In 2020, due to the COVID-19 pandemic, supermarkets took over as distributors of essential products. Due to this same situation, even the behavior of consumers changed radically since food, cleaning products, and personal hygiene products increased their presence at historical levels. This situation forced several commercial sectors to evaluate their data to respond immediately to the requirements of consumers. Therefore, the need arises for efficient and optimal planning of the products on the rack that are offered, focusing on those of greatest demand and sale to consumers. The present research study was carried out in an Ecuadorian supermarket, in which methodologies for the treatment of forecasts and inventories were applied through the historical sales data provided by the company for the years 2018, 2019, and 2020. Forecast models were applied to reduce uncertainty regarding planning the supply of the different products offered in the supermarket. The models were ARIMA, Holt, Holt-Winters, Seasonal Simple, and Winters Additive, while for the treatment and efficiency planning of the existing stock within the company; that is, having enough products to satisfy the demand, different inventory models and respective EOQs (economic order quantities) were applied according to the case. The information on sales management has been compiled and standardized in a Microsoft Excel template for the optimal flow of information and the recording of internal operations, achieving efficient product planning to avoid shortages in the supply chain.

Port operations experience high uncertainty in supply chains, and their importance in trade is significant since the sea carries out most global trade. Any disruptive event that strikes port facilities can affect local and national economies. This research studies a series of port disruptions with their respective failure modes based on a case study in the port of Barranquilla, Colombia. Then, the importance of these port disruptions is evaluated through a relational analysis of variables using the ISM methodology. Finally, we discuss real disruptive events that have occurred in Latin American ports. As a result, we find that hurricanes and terrorist acts are the events that have the greatest potential to affect port activities, and transportation failure is the most frequent failure type.

The connection among various places in the world is thanks to transport, which generates advantages in areas like economic development, international support in the face of catastrophes, and cultural and knowledge exchange, to mention some. The need to move people and goods locally and internationally determines the control of transportation systems; however, there are uncontrollable external factors. Corona Virus Disease (COVID-19) is a disease that arose in China, and due to its characteristics and the lack of information about the virus, it was difficult to prevent its spread around the world, causing a global pandemic. A fundamental activity for controlling the spread of the virus and medical assistance is the adequate distribution of medicines and medical equipment to hospitals. Mechanisms are currently being sought in Mexico to efficiently carry out this public sector activity. Therefore, this work offers to the decision-makers in the health sector a proposal for the distribution of medicines and medical equipment to the different hospitals in Mexico. The proposal presented applies quantitative methods, specifically allocation methods and the Clarke and Wright heuristic, to support the results. The proposal offered a viable, effortless, and helpful alternative to personnel involved in distribution activities and recommendations to the practitioners in the health sector and logistic areas.

The management of the supply chain faces increased challenges for its optimization. The poultry industry, which has a large share of global food, is no exception. A particular challenge is more critical than others due to the product’s short perishability and the reduced times of the merchandise in the warehouse. Thus, the importance of having an optimal distribution process increase. This study will conduct a qualitative analysis to determine the leading causes that prevent us from achieving optimal distribution performance. Based on the critical success factors, improvement actions can be proposed. Finally, the improvement actions will be evaluated through an AHP process, and the evaluation criteria will be based on the most relevant performance indicators in the industry. Thus, the best viable option can be determined quantitatively according to the weighting in the most important criteria. The investigation will determine that implementing an integrated data warehouse will be the most optimal solution for a distribution process in the poultry industry.

Given their size, Mass consumption companies constantly resolve a large number of claims. Sometimes, these claims are not attended to with the necessary speed owing to non-optimized prioritization. The following article proposes using georeferencing, routing, and forecasting to improve this process. To achieve the above, the case of a leading company in the dairy industry will be analyzed internally and externally, as well as the application of quality tools.

The main objective of this work is to diagnose and improve the proposal for a Distribution Center (DC) of a productive Chilean company. This implies recognizing the current state of the DC, analyzing its processes and bottlenecks, and obtaining time measurements. The research problem is associated with the current main problems: operation using overtime costs, dispatch delays, and storehouse collapse. The diagnosis stage considers the parameters to be measured, such as time, number of purchase orders, packing, dispatches, and receptions. This diagnosis allows us to understand that aisle operators (pickers) are a critical resource and that the first work processes to improve concern picking and dispatching. Thus, it is possible to improve the operation of the DC to enhance critical resources and processes. It is proposed to use two pickers and invest them in two tablets. It is estimated that this proposal could significantly reduce external storage costs because it implies an increase in the capacity to process orders by 42.5%, equivalent to 145 releases, which is 43 more than today.

Disruptions in supply chains can lead to a market breakdown, and the products have different disruption sensitivities to processed food and fresh food. This work analyzes the disruptions caused in fresh food supply chains of Cochabamba’s vulnerable downtown population, Bolivia. Based on the data collected, a new food kit delivery policy is proposed based on mobile market distribution. The data collected considered vulnerable areas in a region, communities’ social characteristics as a typical diet, and food nutritional contribution, among others, for a week. Finally, this study identified the selected region’s products, networks, and delivery routes.

Growing environmental concerns regarding pollution have led to legislation toughening worldwide to achieve mitigation. For example, in Chile, the extended producer responsibility (EPR) law makes producers responsible for waste management of the goods they market within the country. One of these goods is end-of-life tires (ELT) because of their high pollution potential. The EPR law establishes the goal of collecting 50% of common tires and a valorization of 25% by 2023, gradually increasing over the years. Thus, there is an opportunity to implement an ELT supply chain with valorization technologies to explore new energy alternatives and value-added products. This would contribute to a circular economy and national energy matrix decarbonization. Therefore, through a comprehensive literature review, this study aimed to identify the principal supply chain design challenges for ELT treatment through a sustainable approach. Twenty-five articles were reviewed and analyzed considering the sustainability dimensions addressed, the decision-making levels assessed, the type of ELT treatment, the network structure, the country of study, the inclusion of uncertainty, the optimization model proposed objective functions number, the solution method used, and authors’ analysis. The conclusions highlight the current research contributions and shortcomings and suggest possible directions for future work.

Batteries are products of many devices, especially electronic ones. The rapid development of electronic devices has reduced the effective life span of these products. As a result, these products end up in landfills and cannot be valorized or used again, causing environmental pollution by the hazardous substances they contain. Currently, it is possible to find different policies and initiatives to increase the percentage of recovered batteries. However, this is a complex process because of its different formats and components. In addition, recovery systems must be developed from a sustainability perspective, which increases their complexity from the perspective of evaluation and implementation. This study presents a literature review to map how the design and implementation of battery recovery supply chains have been addressed in the literature. Fourteen journal articles were selected and analyzed considering the type of problem addressed, the variety of batteries and sustainability dimensions considered, the supply chain studied, the optimization model approach, and the geographical location of the case studies. The main findings are the lack of consideration of social, political, and technological aspects in the sustainability assessment and the lack of consideration of domestic-use batteries.

The last two decades have witnessed significant growth in Latin American cities, with 81% of the region's inhabitants living in urban areas. This tendency affects the quality of citizens’ lives and produces greater demand for resources and services. This study aims to provide alternative solutions to improve the problems of vehicular congestion and logistics processes in one of the most congested sectors of Popayán. First, logistics operations were characterized in the city center using the last mile/km²-MIT methodology. This methodology allowed us to identify areas with the greater vehicular flow and a higher density of economic activities. Subsequently, two scenarios were evaluated with discrete simulations to determine the loading and unloading zones and schedules for loading and unloading times to suggest improvements in vehicular flow. The results showed an 8% improvement in loading and unloading zones, a 12% increase in the pedestrian/vehicle ratio, an 18% improvement in pedestrian trips, and a 16% reduction in vehicle flow disruptions. Finally, the chapter provides a proactive tool for decision-makers to guide public policies aimed at improving urban-to-last-mile freight distribution in Popayán.

Due to the constant growth in our need for energy and the search through international agreements to reduce the use of fossil fuels to reduce carbon emissions, the promotion and use of renewable energy sources have increased. The increased use of renewable energies, mainly wind and solar, has also increased the interest in energy carriers such as hydrogen, mainly the so-called green hydrogen, because, in addition to storing energy, it also offers the possibility of using hydrogen as a fuel with low environmental impact, giving a possibility to indirectly electrify some industries that are difficult to electrify. That is why the correct planning and design of the hydrogen supply chain (HSC) are necessary. This study seeks to identify and describe the actors involved in the operation of the HSC, the decisions each actor must make and the relationships that may exist with other actors in the supply chain. Next, the strengths and weaknesses concerning the aspects identified are analyzed in Colombia. Subsequently, the problem types, modeling techniques and solution methods applied in the design of the HSC are identified and analyzed, with greater emphasis on optimization techniques. Finally, some challenges and proposals for future research in HSC design are presented.

Maritime supply chains are a highly dynamic environment in which multiple public and private stakeholders interact by exchanging digital data through various systems and technologies in cyberspace. The maritime industry is immersed in a digital transformation process that is evolving to be highly dependent on cyber-physical systems composed of information and operational technologies. In the Latin American and Caribbean region, there are multiple challenges in cybersecurity of the maritime industry in general, as countries present different maturity levels in their cybersecurity capabilities, particularly in protecting critical infrastructures, including ports, terminals and intermodal connections. This chapter describes cyberthreats, vulnerabilities, risks and recent cyberattacks in maritime supply chain operations in Latin America and the Caribbean (LAC), discusses ongoing supranational initiatives towards the development of cybersecurity capabilities for maritime supply chains in the region, analyzes advances of LAC countries in developing cybersecurity capabilities and adopting best practices for maritime supply chain operations, discusses the region's prospects for development of cybersecurity policy and strategy, and provides recommendations for decision-makers and technical staff in charge of maritime supply chain operations.

This chapter shows the effort made by higher education institutions, governments, and companies to jointly build the strategy to define the supply chain in two logistics ecosystems as a cooperation response in Megaregion Sonora-Arizona. The areas considered were: social, gastronomic, tourism, and business and logistics development, whose objective was to build—based on projects—ecosystems in each workshop, as well as the search for funds. The method shows the procedure in five stages: (1) sensitization, (2) business and logistics conceptualization workshop, (3) development project proposal, (4) present ecosystems, and (5) search for funding sources for implementation. The main results are the constitution of two ecosystems: (1) agro-food and tourism logistic ecosystems and; (2) Health and Tourism. The main conclusions established that the two logistics ecosystems, the agro-food and tourism sector and the second in the health and tourism sectors, have the flexibility and development potential in the short and medium-term to respond to post-pandemic related to their logistics and commercialization between two states.