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市場調查報告書

供應鏈用巨量資料分析的全球市場 - 成長性,趨勢,及未來預測

Supply Chain Big Data Analytics Market - Growth, Trends, COVID-19 Impact, and Forecasts (2021 - 2026)

出版商 Mordor Intelligence Pvt Ltd 商品編碼 393915
出版日期 內容資訊 英文 80 Pages
商品交期: 2-3個工作天內
價格
供應鏈用巨量資料分析的全球市場 - 成長性,趨勢,及未來預測 Supply Chain Big Data Analytics Market - Growth, Trends, COVID-19 Impact, and Forecasts (2021 - 2026)
出版日期: 2021年01月01日內容資訊: 英文 80 Pages
簡介

本報告涵括供應鏈用巨量資料分析的全球市場,基於市場成長促進因素,阻礙因素,產業魅力度,以及市場競爭情形的廣泛調查,來進行現行市場分析與未來預測。同時更提供該市場各類型,不同引進形態,各終端用戶產業,及各地區別之各部門詳細的分析與預測。

第1章 序論

  • 本調查的成果
  • 調查上的估計條件
  • 調查範圍

第2章 調查手法

第3章 摘要整理

第4章 市場動態

  • 市場概要
  • 市場成長促進因素及阻礙因素序論
  • 市場成長促進因素
  • 市場成長阻礙因素
  • 產業魅力度 - 波特的五力分析
    • 新加入企業帶來的威脅
    • 買主/消費者談判力
    • 賣主談判力
    • 替代品帶來的威脅
    • 企業間的競爭度

第5章 市場分類

  • 各類型
    • 各解決方案
    • 各類服務
  • 不同引進形態
    • 內部部署
    • 雲端
  • 各終端用戶產業
    • 零售
    • 交通運輸及物流
    • 製造
    • 醫療
    • 其他終端用戶產業
  • 各地區市場
    • 北美
    • 歐洲
    • 亞太地區
    • 南美
    • 中東·非洲

第6章 市場競爭情形

  • 企業簡介
    • SAP SE (SAP)
    • IBM Corporation
    • Oracle Corporation
    • MicroStrategy Incorporated
    • Genpact Limited
    • SAS Institute Inc.
    • Sage Clarity Systems
    • Tableau
    • Birst Inc.
    • Capgemini Group
    • Kinaxis Inc.

第7章 投資分析

第8章 市場機會及未來趨勢

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目錄
Product Code: 53713

The Supply Chain Big Data Analytics Market was valued at USD 3.55 billion in 2020 and is expected to reach USD 9.28 billion by 2026, at a CAGR of 17.31% over the forecast period 2021 - 2026. With advancements in information technology, firms are now able to access, store, and process a massive amount of data. Organizations are analyzing data sets and identifying key insights to apply to their operations, making it evident that Big Data has an important role to play in any industry. From food and beverage distribution to high tech, companies are incorporating analytics.

  • The widespread use of digital technologies has led to the emergence of Big Data Analytics (BDA) as a critical business capability to provide companies with better opportunities to obtain value from an increasingly huge amount of data and gain a commanding competitive advantage.
  • BDA in logistics and supply chain management (LSCM) has garnered increasing attention due to its complexity and the prominent role of LSCM in enhancing the overall business performance. According to a survey conducted by Accenture in 2014, more than one-third of the respondents reported being engaged in serious conversations to deploy analytics in LSCM, while three out of ten already have taken an initiative to implement analytics.
  • LSCM faces the most significant challenges that can potentially result in inefficiencies and wastage in supply chains, such as delayed shipments, rising fuel costs, inconsistent suppliers, and ever-increasing customer expectations, among others.
  • The power of data is becoming evident to businesses of all shapes and sizes, from financial service to automobile manufacturing, healthcare, NGO, and more. It is increasingly becoming essential to make the best use of Big Data analytics in a supply chain to generate more profound insights. The retail sector streams a massive amount of data across its supply chains, at diverse customer touch points in many omnichannel operations.
  • According to a survey by Softweb Solutions, retailers who use predictive analytics have achieved a 73% increase in sales, as compared to those who did not use it. Therefore, retailers are utilizing Big Data solutions via customer analytics to multiply profitability and outperform competitors by personalizing their in-store offerings and online product. However, there are few stumbling blocks for supply chain management while executing real-time analytics.

Key Market Trends

Retail is Expected to Register a Significant Growth

  • The retail industry currently holds a significant share of the supply chain big data analytics market, and is expected to present vast opportunities of growth, owing to the growing number of data sources being generated, with the adoption of IoT solutions, beacons, and RFID technologies across the supply chain.
  • Moreover, retailers adopt IoT solutions and devices to analyze customer data, track stock levels, and strengthen customer relationships. All these technological improvisations not only enable better tracking of the products across the supply chain, but also help in gaining a clear understanding of customer behavior.
  • For instance, retailers have also put in a network of RFID readers into the roof space of their sales floors, allowing them to read all of the stock on display and providing more accurate inventory visibility. Augmenting this trend, the American Apparel is leveraging RFID tags and data analytics tools to improve inventory management, while Walmart employed Big Data analytics to enhance its in-store and supply chain management.
  • However, massive amounts of this useful information are left to rot, resulting in the overall conversion rates of only 2-3%. Thus, the supply chain big data analytics market has been gaining traction in the retail segment to leverage the data, with its ability to understand, analyze, and generate valuable insights.

United States is Expected to Hold Major Share

  • The United States is rigorously looking to strengthen its manufacturing industry, by enhancing its productivity by laying emphasis on improving activities across the supply chain, within the industrial sector in the country. The e-commerce industry in the United States is proliferating, owing to which the requirement for efficient supply chain management is on the rise. According to the US Commerce Department, the e-commerce industry in the country rose by over 40% in 2017. As a result, Big Data is expected to rise significantly, thereby, having a positive impact on the supply chain analytics in the country.
  • The e-retailers in the North American retail market are rigorously trying to enhance the customer experience, by incorporating same-day delivery, which can effectively be achieved through effective supply chain management. Notably, according to Auburn University's Harbert College of Business, in early 2018, the retailers in the United States were expected to foster their investment in the supply chain management, especially in technology upgrade, owing to expansion and rapid growth in the e-commerce industry.
  • Additionally, startups are trying to venture into the retail space in the region that are raising funds to boost their operational efficiency through Big Data analytics and other emerging technologies. For instance, A.S. Watson group (ASW) announced a partnership with Rubikloud, a Toronto-based startup, primarily to invest in developing Big Data capabilities. The former company invested about USD 70 million to enhance the operational efficiency and customer experience through the integration of visualization and machine learning capabilities. As a result, it is projected to propel the supply chain big data analytics market growth in the country.

Competitive Landscape

The supply chain big data analytics market is highly competitive and consists of several major players. In terms of market share, few of the major players currently dominate the market. These major players with prominent shares in the market are focusing on expanding their customer base across foreign countries. These companies are leveraging on strategic collaborative initiatives to increase their market shares and profitability. The companies operating in the market are also acquiring start-ups working on supply chain big data analytics technologies to strengthen their product capabilities. In July 2018, Deloitte and SAS entered into an agreement to address the complex risk and regulatory calculations at scale, and turn compliance into an opportunity.

Reasons to Purchase this report:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Increasing Need of Business Data to Improve Efficiency
  • 4.3 Market Restraints
    • 4.3.1 Operational Complexity Coupled with High Maintenance Costs
  • 4.4 Value Chain / Supply Chain Analysis
  • 4.5 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.5.1 Threat of New Entrants
    • 4.5.2 Bargaining Power of Buyers/Consumers
    • 4.5.3 Bargaining Power of Suppliers
    • 4.5.4 Threat of Substitute Products
    • 4.5.5 Intensity of Competitive Rivalry

5 MARKET SEGMENTATION

  • 5.1 By Type
    • 5.1.1 Solution
      • 5.1.1.1 Supply Chain Procurement and Planning Tool
      • 5.1.1.2 Sales and Operations Planning
      • 5.1.1.3 Manufacturing Analytics
      • 5.1.1.4 Transportation and Logistics Analytics
      • 5.1.1.5 Other Solutions (Inventory Planning and Optimization Analytics and Scheduling and Reporting Tools)
    • 5.1.2 Service
      • 5.1.2.1 Professional Service
      • 5.1.2.2 Support and Maintenance Service
  • 5.2 End User
    • 5.2.1 Retail
    • 5.2.2 Transportation and Logistics
    • 5.2.3 Manufacturing
    • 5.2.4 Healthcare
    • 5.2.5 Other End Users
  • 5.3 Geography
    • 5.3.1 North America
      • 5.3.1.1 United States
      • 5.3.1.2 Canada
    • 5.3.2 Europe
      • 5.3.2.1 United Kingdom
      • 5.3.2.2 Germany
      • 5.3.2.3 France
      • 5.3.2.4 Italy
      • 5.3.2.5 Rest of Europe
    • 5.3.3 Asia-Pacific
      • 5.3.3.1 China
      • 5.3.3.2 Japan
      • 5.3.3.3 South Korea
      • 5.3.3.4 India
      • 5.3.3.5 Rest of Asia-Pacific
    • 5.3.4 Latin America
      • 5.3.4.1 Mexico
      • 5.3.4.2 Brazil
      • 5.3.4.3 Argentina
      • 5.3.4.4 Rest of Latin America
    • 5.3.5 Middle-East & Africa
      • 5.3.5.1 United Arab Emirates
      • 5.3.5.2 Saudi Arabia
      • 5.3.5.3 South Africa
      • 5.3.5.4 Rest of Middle-East & Africa

6 COMPETITIVE LANDSCAPE

  • 6.1 Company Profiles
    • 6.1.1 SAP SE (SAP)
    • 6.1.2 IBM Corporation
    • 6.1.3 Oracle Corporation
    • 6.1.4 MicroStrategy Incorporated
    • 6.1.5 Genpact Limited
    • 6.1.6 SAS Institute Inc.
    • 6.1.7 Sage Clarity Systems
    • 6.1.8 Salesforce.com Inc (Tableau Software Inc.)
    • 6.1.9 Birst Inc.
    • 6.1.10 Capgemini Group
    • 6.1.11 Kinaxis Inc.

7 INVESTMENT ANALYSIS

8 MARKET OPPORTUNITIES AND FUTURE TRENDS