Tesi di Laurea Magistrale (sperimentale) - Supply Chain Risk Management: a case study on the most relevant disruptions during the Covid-19 pandemic

Università degli Studi di Verona

Scuola di Economia e Management

Corso di Laurea magistrale in Economics and Data Analysis

Supply chain risk management: a case study on the most relevant disruptions during the Covid-19 pandemic

Relatrice Laureando Prof.ssa Giulio Domenichini Barbara Gaudenzi Matricola VR461002

Anno Accademico 2021/22

Abstract

The already present difficulties of supply chain management, such as those related to globalization or to the increasing complexity and extension of supply chain networks, combined with the recent shocks caused first by the Covid-19 pandemic and then by the conflict between Russia and Ukraine, motivated the drafting of this work, which aims to answer the following research questions:

• “What connections exist between the effects of supply chain disruptions during the Covid-19 pandemic, business reactions to them, and business outcomes?”
• “How can one evaluate the impact of supply chain disruption on business’ performance during the pandemic, as well as the outcomes of any adopted mitigation strategies?”

To do this, it was decided to apply the Interpretive Structural Modelling (ISM), MICMAC analysis and the Bayesian Belief Networks (BBN) approach (applied on the GeNIe Modeler software) to the case study with a leading multinational company in the Fast-moving consumer goods sector (Alpha). The application of these methods led to the creation of an ISM model from interviews conducted with Alpha's Operations & Finance Director.

The processing of this information made it possible, in the first instance, to answer the first research question in that an ISM model was created on the basis of the SSIM and RE matrices, of the level partition process and of the MICMAC analysis, which relates the different variables and describes their interactions in terms of dependence power and driver power.

These results, combined with those obtained by transposing the model onto the GeNIe Modeler software and by applying the BBN approach, made it possible to answer the second research question. Indeed, the study allowed us to quantify the impacts of the individual variables on the model's target variables and to understand their cruciality in terms of sensitivity.

All this information and these results should enable risk managers to visualize their supply chain in a model and make more informed decisions thanks to the simulations performed on the model itself. 3

Index

• Abstract .............................................................................................................................. 3
• Introduction .................................................................................................................... 9
• Chapter 1 Supply chain risk management: process and effects on performance .................................................................................................................. 13 .................................................. 13
• 1.1. Background concepts and definitions .......................................... 14
• 1.2. Risk classification and ISO 3100 guidelines .......... 15
• 1.3. ISO 31000: principles and framework of risk management ........................................................................ 15
• 1.3.1. Principles for an effective Risk Management ................................................................................................ 17
• 1.3.2. Risk Management framework ............................................................................. 19
• 1.4. Risk management process .......................................................................................................... 20
• 1.4.1. Scope, context and criteria .................................................................................................. 21
• 1.5. Risk assessment .................................................................................................................. 21
• 1.5.1. Risk identification .......................................................................................................................... 24
• 1.5.2. Risk analysis ...................................................................................................................... 29
• 1.5.3. Risk evaluation ................................................................................................... 31
• 1.6. Risk treatment ........................................................................................................................... 33
• 1.6.1. Risk control ........................................................................................................................ 34
• 1.6.2. Risk financing ........................................................................ 35
• 1.7. Implementation and review ........................................................................................... 35
• 1.7.1. Implementation of risk strategies .......................................................................................................... 35
• 1.7.2. Monitoring and review
• Chapter 2 SC risk management: building a resilient supply chain ................... 37 .................................................. 37
• 2.1. Background concepts and definitions ....................................................................... 38
• 2.2. Structure of a supply chain ........................... 39
• 2.3. Why supply chain risk management is so crucial ............................... 41
• 2.4. SC risks classification: sources and outcomes .............................................................. 43
• 2.5. Building a resilient supply chain ............................................................................................................. 43
• 2.5.1. Redesign the supply chain ............................................................................................................ 45
• 2.5.2. Supply chain collaboration ....................................................................................................... 47
• 2.5.3. Agility: visibility and velocity .................................................................. 49
• 2.5.4. Creating awareness on supply chain risk management ......................................................... 50
• 2.5.5. Supply chain continuity management: a boost for resilience
• 2.6. Rising SC risk and the impact of Covid-19 on global supply ...................................................................................................................... 51 Chains 5
• Chapter 3 Analysing the correlation among risks in complex networks 55
• 3.1. Why it is important to analyse correlation among variables ........................................................ 55 In complex supply chain networks ............................................................................................ 55
• 3.2. The Delphi method
• 3.3. Analytic Hierarchy Process (AHP) and Fuzzy-Analytic ............................................................................ 59 Hierarchy Process (F-AHP) ..................... 62
• 3.4. Interpretive Structural Modelling approach (ISM) ................................................................................................. 66
• 3.5. MICMAC analysis .................................. 66
• 3.6. Construction of the model in GeNIe Modeler ......................................................................................... 67
• 3.6.1. Discrete and continuous variables ............................................................................................................................. 67
• 3.6.2. Probability ......................................... 69
• 3.7. Sensitivity analysis in Bayesian networks
• Chapter 4 Case study: an ISM approach to the study of supply chain disruptions and mitigation strategies ........................................................ 71 ............................................................................... 71
• 4.1. Case study introduction .............................................................................. 71
• 4.2. Variables identification ...................................................... 73
• 4.3. Analysing variables relationships ........................................................................................... 73
• 4.3.1. Structural self-interaction matrix ..................................................................................................... 75
• 4.3.2. Initial Reachability Matrix ...................................................................................................... 75
• 4.3.3. Final Reachability Matrix ............................. 78
• 4.4. MICMAC analysis: driver and dependence power ..................................................................................................... 80
• 4.5. ISM map design ........................................................................................................................ 80
• 4.5.1. Level partition ........................................................................................................................ 83
• 4.5.2. ISM diagraphs ........................................................................................................................ 85
• 4.5.3. The ISM Map ..................................................................... 86
• 4.6. Model development on GeNIe ........................................................................... 86
• 4.6.1. Definition of variable states and frequency ..................................................................................... 86
• 4.6.2. Identification of strong relationships .............................................................................. 87
• 4.6.3. Qualitative conditional probability tables ......................................................................... 90
• 4.6.4. From words to numbers (quantitative CPTs) ............................................................... 91
• 4.6.5. Considerations about variables D11, D12 and D13 ................................................................................................................. 92
• 4.6.6. ISM Map on GeNIe ...................................... 95
• 4.7. Sensitivity analysis and tornado diagrams
• 4.8. A reformulation of the ISM map: sensitivity analysis and .......................................................................................... 112 Tornado diagrams
• Key results and conclusions ............................................................................ 1276
• List of tables ............................................................................................................... 131
• List of figures ............................................................................................................. 132
• References ..................................................................................................................... 13478

Introduction

All business activities are nowadays embedded in a specific socio-economic environment which, due to its uncertainty and dynamism, entails risks of various kinds for the companies themselves. In addition, the progressive process of globalization, which has significantly contributed to the intensification of competitiveness in various sectors, is pushing companies to give more and more importance to objectives such as improving efficiency and effectiveness from an organizational and operational point of view, as well as improving the quality of the products and services offered.

In an attempt to follow this path, risk management activities are taking on an increasingly crucial role within companies that aim to be competitive and at the same time hedged against certain risks, especially those that could have a significant impact on business continuity, i.e. on the company's ability to continue operating its business even following a disruption.

In particular, this work focuses on Supply Chain Risk Management, which is nothing more than an application of the discipline of Risk Management to issues specifically related to the Supply Chain.

The reason why this business area is so crucial in guaranteeing objectives such as efficiency, product quality and business continuity is inherent in the very definition of the Supply Chain: "It is a network between a company and its suppliers to produce and distribute a specific product to the final buyer.” This network includes different activities, people, entities, information, and resources. The supply chain also represents the steps it takes to get the product or service from its original state to the customer (Kenton, 2021).

This, in fact, being an interconnected network with all company activities and resources, has repercussions on the entire business activity. It is therefore evident how a correct and up-to-date Supply Chain Management strategy can not only contribute to the minimization of the costs related to disruptions but can act as a real competitive advantage in an increasingly saturated global market, where process efficiency and agility in responding to disruptions will increasingly make a difference (Suhong et Al, 2004).

In addition to this, evidence and recent literature says that the recent Covid-19 pandemic has put global supply chains in serious trouble, exposing them to new disruptions that have proved difficult to manage (Chowdhury et Al., 2021; Meier and Pinto, 2020; Pujawan and Bah, 2021).

In the light of these new disruptions, which are getting more and more unpredictable and have catastrophic consequences, it is of paramount importance for companies to invest in improving the resilience of their supply chains, thereby increasing their chances of preserving business continuity even in the face of risk events. However, given that there are various enablers and strategies that can be implemented to improve supply chain resilience, research is needed to investigate the relationships and correlations between risk sources, strategies and performance indices in order to understand which variables are most sensitive, which impact the others the most and where it is therefore most efficient to invest time and money if the goal is to make the supply chain resilient and robust.

In order to pursue these objectives and in view of the premises made, two research questions were formulated to guide this work of analysis and research. The former asks “What connections exist between the effects of SC disruptions during the pandemic outbreak, business reactions to them, and business outcomes?” while the latter asks “How can one evaluate the impact of SC disruption on business’ performance during the pandemic, as well as the outcomes of any adopted mitigation strategies?”

To try to answer these questions, the choice of method fell on the ISM approach and MICMAC analysis in order to construct a graphical and conceptual model on which to then analyze the relationships between the variables, perform sensitivity analyses and perform tornado diagrams.

In this way, it was possible to classify the variables belonging to the model, subdivide them according to their hierarchical level, obtain information on the impact they have on the other variables and in particular on performance, as well as information on the ancestor variables that influence the various nodes of the model. Through sensitivity analyses and tornado diagrams, we were also able to understand which variables are the most sensitive and in what range the conditional probabilities of the model's target variables vary when the input variables vary.

Specifically, the paper consists of an introduction followed by four chapters and conclusions.

In the first chapter, the focus is on risk management activities and definitions of terms and concepts useful for understanding this chapter as well as this paper are first proposed. Next, the various risk categories according to the ISO 31000:2018 guidelines are presented and then it is explained, again taking ISO 31000:2018 as a reference, which principles to follow and the framework to adopt in order to achieve effective risk management are explained. Then, Chapter 1 continues with a presentation of the risk management process, described in all its phases. Finally, the chapter closes with a section devoted to the implementation of the strategies chosen through the risk management process and to the review of these strategies once implemented.

Chapter 2, on the other hand, narrows the focus on the supply chain and thus describes the peculiarities of the risk management process applied precisely to this business area. Since the objective here is to highlight the crucial importance of resilience in achieving a robust supply chain that withstands disruptions and does not jeopardize the company's activities, preserving its business continuity, the focus is placed on the motivations that justify the focus on SC risk management (2.3). This is after having explained, as in Chapter 1, the definitions of the technical terms used in this chapter. Section 2.2., on the other hand, illustrates the structure of a typical supply chain, while section 2.4. refers to the classification of supply chain risks: in particular, attention is drawn to the sources of risk and the possible effects and impacts on the company performance. Some of the strategies and best practices proposed in the literature on the subject are then investigated in order to increase the resilience and robustness of the supply chain. The chapter ends with a section dedicated to emerging risks, particularly those that affected global supply chains during the pandemic period due to the spread of Covid-19.

The third chapter is instead dedicated to explaining the methodology used in the case study proposed in the fourth chapter and the alternative or complementary methodologies that can be used to complement the chosen method or to implement other types of analysis. Specifically, it is explained why it is so important, especially nowadays, to analyze complex networks such as supply chains. The chapter continues with the presentation of the Delphi method, the Analytic Hierarchy Process (AHP) (with a hint also to Fuzzy-AHP) and the Interpretative Structural Modelling approach (ISM), which is the method chosen and used for our analysis. A useful method for classifying variables according to their dependence power and driver power, such as that of MICMAC analysis, is also presented in section 3.5. In the conclusion