Third Party Logistics – Development of a selection model to enhance supply chain visibility

Table of Contents

1. Introduction

1.1. Objectives and Problem Definition

1.2. Structure of the Thesis

1.3. Scope and Delimitations of the Thesis

2. Literature Review

2.1. Introduction to Supply Chain Management

2.1.1. The Supply Chain as a Competitive Advantage

2.1.2. Supply Chain Challenges

2.1.3. Major Supply Chain Drivers

2.1.3.1. Production

2.1.3.2. Inventory

2.1.3.3. Location

2.1.3.4. Transportation

2.1.3.5. Information

2.2. Supply Chain Visibility

2.2.1. Benefits of Supply Chain Visibility

2.2.1.1. Bullwhip-Effect

2.2.1.2. Demand Uncertainty

2.2.1.3. Safety Stock

2.2.2. Obstacles in Achieving Supply Chain Visibility

2.2.3. Technology Landscape

2.3. Key Performance Indicators (KPIs)

2.3.1. The Fundamentals of KPIs

2.3.2. KPIs for Supply Chains

2.4. Introduction to Outsourcing

2.4.1. Outsourcing Benefits and Risks

2.4.2. Outsourcing in the Logistics/Supply Chain Industry

2.4.3. Third Party Logistics (3PL)

2.4.4. A Framework for Make/Buy Decisions

2.5. Customer Segmentation

3. Company Overview

3.1. Company Profile

3.2. Visibility System of COMPANY

4. AS-IS Analysis

4.1. Methodology

4.1.1. Research Methods

4.1.2. Strategy and Data Analysis

4.1.3. Assessment of Method Alternatives

4.1.4. Wrap-up of the Methods

4.2. Elicitation and Analysis

4.2.1. Demand Aggregation and Analysis

4.2.1.1. Stock Turnover

4.2.1.2. Stock Availability

4.2.1.3. Forecast Accuracy

4.2.1.4. Inventory Obsolescence

4.2.1.5. Finished Goods Inventory

4.2.1.6. Stock Outs

4.2.1.7. Ratio: Safety Stock/Demand

4.2.1.8. Safety Stock/Inventory

4.2.2. Inventory Costs Analysis

4.2.2.1. Best Case/Worst Case Scenario

4.2.2.2. Safety Stock Cost Calculation

4.2.2.3. Opportunity Costs

4.2.3. IT Resources Decision Matrix

4.2.3.1. Core Competence Questionnaire

4.2.3.2. Capacity/Knowledge Matrix

4.2.3.3. Make/Buy Decision

4.2.4. Customer Segmentation

4.2.4.1. New Customer

4.2.4.2. Short-Term Service

4.2.4.3. Permanent Service

4.2.4.4. Entire SCM

4.2.5. Vulnerability Analysis

5. TO-BE Concept

5.1. Selection Model Concept

5.1.1. General Information

5.1.2. Reduction of Complexity

5.1.3. Structure and Development of the Selection Model

5.1.4. Sample Case: Metal Stamp Manufacturer

5.2. Pre-requisites for the Selection Model

5.3. Selection Model Sub-Modules

5.3.1. Identifying the Supply Chain Visibility Gap

5.3.2. Inventory Costs

5.3.3. Opportunity Costs Calculator

5.3.4. Make/Buy Decision for the Visibility System

5.3.5. Value-based Customer Segmentation

5.4. Sensitivity Analysis of the Customer Segmentation

5.5. Summary of the Sample Case Company

5.6. General Application of the Selection Model

5.7. Recommendation for Implementation

6. Conclusion and Future Aspects

Objectives & Core Themes

The primary objective of this thesis is the design and development of a selection model prototype to identify and segment client and non-client companies based on their need for enhanced supply chain visibility (SCV). By analyzing demand and inventory data, the model determines whether companies face an SCV gap and recommends appropriate service tiers to improve their supply chain performance.

• Development of a prototype selection model to identify SCV gaps.
• Analysis of demand and inventory data to evaluate performance.
• IT resource determination to inform make/buy decisions for visibility systems.
• Customer segmentation into four distinct categories for tailored service offerings.
• Practical application of the model to a specific sample case manufacturer.

Excerpt from the Book

Summary of Chapters

1. Introduction: Defines the thesis objectives, focusing on the development of a selection model for supply chain visibility (SCV) to help companies improve their performance through better information sharing.

2. Literature Review: Provides a theoretical foundation covering supply chain management, SCV, key performance indicators (KPIs), outsourcing strategies, and customer segmentation.

3. Company Overview: Outlines the profile of the supporting company and its proprietary web-based visibility system designed to provide real-time end-to-end supply chain data.

4. AS-IS Analysis: Details the empirical-inductive methodology used for data elicitation and analysis, including the statistical methods for evaluating demand and inventory data to identify SCV needs.

5. TO-BE Concept: Describes the design and application of the selection model prototype, including its sub-modules for cost calculation, IT resource evaluation, and the segmentation of a sample metal stamp manufacturer.

6. Conclusion and Future Aspects: Summarizes the thesis findings, confirming the prototype's effectiveness in identifying SCV gaps and proposing future expansions for the model.

Keywords

Supply Chain Management, SCM, Supply Chain Visibility, SCV, Selection Model, KPIs, Inventory Management, Outsourcing, Make/Buy Decision, Customer Segmentation, Demand Variability, Safety Stock, Logistics, Information Sharing, Business Intelligence

Frequently Asked Questions

What is the core purpose of this thesis?

The thesis aims to develop a structured selection model prototype that helps companies identify gaps in their supply chain visibility and provides a basis for offering targeted logistics services.

What are the primary fields of study involved?

The research primarily covers Supply Chain Management (SCM), Supply Chain Visibility (SCV), IT resource management, and various performance measurement techniques like KPIs.

What is the main research question or goal?

The goal is to design a model that uses empirical demand and inventory data to segment companies and determine the necessity for implementing a supply chain visibility system.

Which scientific methodology is applied?

The work employs an empirical-inductive research method, utilizing data provided by a third-party logistics provider and applying statistical benchmarks to analyze company performance.

What topics are covered in the main body?

The main body examines SCM basics, the importance of SCV, the role of KPIs, outsourcing strategies, and detailed methods for aggregating and analyzing inventory and demand data.

Which keywords define this work?

Core keywords include Supply Chain Visibility, SCV, Selection Model, Key Performance Indicators, and Customer Segmentation.

How is the sample company analyzed within the model?

The sample company—a metal stamp manufacturer—is analyzed using historical demand and inventory data, which is then benchmarked against "Best-in-Class," "Median," and "Laggard" performance categories to quantify the potential for improvement.

What role does the IT Resource Decision Matrix play?

This matrix determines if a company possesses the internal capacity and knowledge to develop its own visibility solution or if it should outsource this function to a logistics provider.