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全球供應鏈大數據分析市場：市場規模、份額、趨勢分析、機會、預測——按解決方案、按服務、按最終用戶、按地區 (2019-2029)
市場調查報告書
商品編碼
1227594

全球供應鏈大數據分析市場：市場規模、份額、趨勢分析、機會、預測——按解決方案、按服務、按最終用戶、按地區 (2019-2029)

Supply Chain Big Data Analytics Market - Global Size, Share, Trend Analysis, Opportunity and Forecast Report, 2019-2029, Segmented By Solution ; By Service ; By End User ; By Region
出版日期: | 出版商: Blueweave Consulting | 英文 200 Pages | 商品交期: 2-3個工作天內

價格
簡介目錄

全球供應鏈大數據分析市場規模將在 2022 年達到 47.8 億美元，到 2029 年達到 150.3 億美元，2023-2029 年的複合年增長率預計為 17.98%。

由於越來越多地採用物聯網 (IoT) 解決方案以及對高級分析解決方案的需求激增，全球市場正在蓬勃發展。

本報告研究全球供應鏈大數據分析市場，提供市場洞察、市場概況、區域市場分析、競爭格局、公司概況等。

內容

第一章研究框架

第 2 章執行摘要

第 3 章全球供應鏈大數據分析市場洞察

  • 工業價值鏈分析
    • DROC 分析
    • 增長動力
      • 擴大物聯網解決方案的引入
      • 對高級分析解決方案的需求
    • 約束因素
      • 庫存成本高
    • 機會
      • 技術進步
    • 任務
      • 安全和隱私問題
  • 技術進步/最新發展
  • 監管框架
  • 波特的五力分析
    • 供應商的議價能力
    • 買家的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭激烈程度

第 4 章全球供應鏈大數據分析市場概述

  • 2019-2029 年市場規模和預測
    • 按金額（百萬美元）
  • 市場份額/預測
    • 按解決方案
      • 物流分析
      • 製造分析
      • 規劃和採購
      • 銷售和運營分析
      • 可視化和報告
    • 按服務
      • 專業的
      • 支持和維護
    • 最終用戶
      • 零售
      • 運輸和物流
      • 製造業
      • 醫療
      • 其他
    • 按地區
      • 北美
      • 歐洲
      • 亞太地區
      • 拉丁美洲
      • 中東和非洲

第五章：北美供應鏈大數據分析市場

  • 2019-2029 年市場規模和預測
    • 按金額（百萬美元）
  • 市場份額/預測
    • 按解決方案
    • 按服務
    • 最終用戶
    • 按國家
      • 美國
      • 加拿大

第 6 章歐洲供應鏈大數據分析市場

  • 2019-2029 年市場規模和預測
    • 按金額（百萬美元）
  • 市場份額/預測
    • 通過解決方案
    • 按服務
    • 最終用戶
    • 按國家
      • 德國
      • 英國
      • 意大利
      • 法國
      • 西班牙
      • 荷蘭
      • 其他歐洲

第7章亞太供應鏈大數據分析市場

  • 2019-2029 年市場規模和預測
    • 按金額（百萬美元）
  • 市場份額/預測
    • 按解決方案
    • 按服務
    • 最終用戶
    • 按國家
      • 中國
      • 印度
      • 日本
      • 韓國
      • 澳大利亞和新西蘭
      • 印度尼西亞
      • 馬來西亞
      • 新加坡
      • 菲律賓
      • 越南
      • 亞太其他地區

第 8 章。拉丁美洲供應鏈大數據分析市場

  • 2019-2029 年市場規模和預測
    • 按金額（百萬美元）
  • 市場份額/預測
    • 通過解決方案
    • 按服務
    • 最終用戶
    • 按國家
      • 巴西
      • 墨西哥
      • 阿根廷
      • 秘魯
      • 其他拉丁美洲

第 9 章中東和非洲供應鏈大數據分析市場

  • 2019-2029 年市場規模和預測
    • 按金額（百萬美元）
  • 市場份額/預測
    • 通過解決方案
    • 按服務
    • 最終用戶
    • 按國家
      • 沙特阿拉伯
      • 阿拉伯聯合酋長國
      • 卡塔爾
      • 科威特
      • 南非
      • 尼日利亞
      • 阿爾及利亞
      • 其他中東和非洲地區

第10章競爭格局

  • 主要公司和產品列表
  • 2022 年全球供應鏈大數據分析公司的市場份額分析
  • 競爭基準：按運營參數
  • 重大戰略發展（合併、收購、合作等）

第 11 章 COVID-19 對全球供應鏈大數據分析市場的影響

第12章公司概況（公司概況、財務矩陣、競爭格局、關鍵人才、主要競爭對手、聯繫人、戰略展望、SWOT分析）

  • SAP SE（SAP）
  • IBM Corporation
  • Oracle Corporation
  • MicroStrategy Incorporated
  • Genpact Limited
  • SAS Institute Inc.
  • Sage Clarity Systems
  • Salesforce.com Inc（Tableau Software Inc.）
  • Birst Inc.
  • Capgemini Group
  • Kinaxis Inc.
  • Accenture PLC
  • Aera Technology
  • JDA Software Group, Inc.
  • Lockheed Martin Corporation
  • Maersk Group.
  • 其他有影響力的公司

第 13 章關鍵戰略建議

第 14 章研究方法論

簡介目錄
Product Code: BWC23125

Global Supply Chain Big Data Analytics Market Size More Than Trebles to Cross USD 15 Billion by 2029.

Global supply chain big data analytics market is flourishing because of an increasing adoption of internet of things (IoT) solutions and a surging demand for advanced analytics solutions.

BlueWeave Consulting, a leading strategic consulting and market research firm, in its recent study, estimated global supply chain big data analytics market size at USD 4.78 billion in 2022. During the forecast period between 2023 and 2029, BlueWeave expects global supply chain big data analytics market size to grow at a significant CAGR of 17.98% reaching a value of USD 15.03 billion by 2029. Major growth factors of global supply chain big data analytics market include increasing adoption of IoT solutions and surging demand for advanced analytics solutions. The retail industry presently occupies a significant share of the supply chain big data analytics market, owing to the adoption of IoT solutions, beacons, and RFID technologies across the supply chain, and it is expected to present vast growth opportunities due to the growing number of data sources being generated. Retailers employ IoT devices and solutions to analyze customer data, track stock levels, and engage with customers. All of these technology improvements not only make it easier to track products along the supply chain, but they also help to gain a better insight of customer behavior. Increased awareness of the benefits of supply chain analytics (SCA) solutions, such as forecasting accuracy, supply chain optimization, waste minimization, and meaningful synthesis of business data, is expected to boost the expansion of overall market during the period in analysis. However, high inventory cost is anticipated to restrain the growth of global supply chain big data analytics market.

Global Supply Chain Big Data Analytics Market - Overview:

Supply chain analytics (SCA) refers to the processes that businesses use to gain insight and extract value from large amounts of data associated with the procurement, processing, and delivery of commodities. SCA is an important component of supply chain management (SCM). Big Data is the term used to describe the huge volumes of structured and unstructured data that corporations utilize to find trends and patterns in human behavior and interactions. Because of improvements in information technology, businesses can now access, store, and process massive volumes of data. Organizations are analyzing data sets and gaining valuable insights to apply to their operations, highlighting the value of Big Data in any industry. Analytics is utilized in a wide range of industries, from food and beverage distribution to high technology. Big Data Analytics (BDA) has emerged as a critical business capability for organizations trying to extract value from an ever-increasing volume of data and gain a competitive edge as a result of the widespread adoption of digital technology.

Impact of COVID-19 on Global Supply Chain Big Data Analytics Market

The COVID-19 pandemic had a negative short-term impact on global supply chain big data analytics market. The pandemic has forced numerous manufacturers to temporarily suspend production in order to comply with new government requirements. The epidemic has directly impacted revenue sources, as supply chain and trade interruptions have harmed overall operations. The crisis, on the other hand, is likely to present a huge opportunity for supply chain management system suppliers to enhance their revenue shares by offering advanced technology-based supply chain solutions. Customers around the world must determine how supply chain analytics solutions may better prepare businesses for demand variations, difficult conditions, and macroeconomic volatility following the crisis. However, improved business outcomes and cost-effectiveness of supply chain management as a result of supply chain analytics adoption are predicted to stimulate the adoption of supply chain analytics solutions in a variety of end-use applications. Demand in the retail and consumer products, healthcare, and manufacturing industries is projected to continue strong. Furthermore, the market's ability to provide effective and efficient administration of end-to-end corporate operations is expected to boost its growth over the forecast period.

Global Supply Chain Big Data Analytics Market - By End User:

Based on end user, global supply chain big data analytics market is divided into Retail, Transportation and Logistics, Manufacturing, and Healthcare segments. The retail segment holds the highest market share. The increasing number of data sources generated by the adoption of IoT solutions, beacons, and RFID technologies throughout the supply chain. Merchants also use IoT solutions and devices to analyze customer data, track stock levels, and improve customer interactions. All of these technology advancements not only allow for improved tracking of products across the supply chain, but also aid in acquiring a clear insight of client behavior.

Competitive Landscape:

Major players operating in global supply chain big data analytics market include: SAP SE (SAP), IBM Corporation, Oracle Corporation, MicroStrategy Incorporated, Genpact Limited, SAS Institute Inc., Sage Clarity Systems, Salesforce.com Inc (Tableau Software Inc.), Birst Inc., Capgemini Group, Kinaxis Inc., Accenture PLC, Aera Technology, JDA Software Group, Inc., Lockheed Martin Corporation, and Maersk Group. To further enhance their market share, these companies employ various strategies, including mergers and acquisitions, partnerships, joint ventures, license agreements, and new product launches.

The in-depth analysis of the report provides information about growth potential, upcoming trends, and statistics of Global Supply Chain Big Data Analytics Market. It also highlights the factors driving forecasts of total market size. The report promises to provide recent technology trends in Global Supply Chain Big Data Analytics Market and industry insights to help decision-makers make sound strategic decisions. Furthermore, the report also analyzes the growth drivers, challenges, and competitive dynamics of the market.

Table of Contents

1. Research Framework

  • 1.1. Research Objective
  • 1.2. Product Overview
  • 1.3. Market Segmentation

2. Executive Summary

3. Global Supply Chain Big Data Analytics Market Insights

  • 3.1. Industry Value Chain Analysis
    • 3.1.1. DROC Analysis
    • 3.1.2. Growth Drivers
      • 3.1.2.1. Rising Adoption of IOT Solutions
      • 3.1.2.2. Demand for Advanced Analytics Solutions
    • 3.1.3. Restraints
      • 3.1.3.1. High Inventory Cost
    • 3.1.4. Opportunities
      • 3.1.4.1. Advancement in Technology
    • 3.1.5. Challenges
      • 3.1.5.1. Security and Privacy Concern
  • 3.2. Technology Advancements/Recent Developments
  • 3.3. Regulatory Framework
  • 3.4. Porter's Five Forces Analysis
    • 3.4.1. Bargaining Power of Suppliers
    • 3.4.2. Bargaining Power of Buyers
    • 3.4.3. Threat of New Entrants
    • 3.4.4. Threat of Substitutes
    • 3.4.5. Intensity of Rivalry

4. Global Supply Chain Big Data Analytics Market Overview

  • 4.1. Market Size & Forecast, 2019-2029
    • 4.1.1. By Value (USD Million)
  • 4.2. Market Share & Forecast
    • 4.2.1. By Solution
      • 4.2.1.1. Logistics Analytics
      • 4.2.1.2. Manufacturing Analytics
      • 4.2.1.3. Planning & Procurement
      • 4.2.1.4. Sales & Operations Analytics
      • 4.2.1.5. Visualization & Reporting
    • 4.2.2. By Service
      • 4.2.2.1. Professional
      • 4.2.2.2. Support & Maintenance
    • 4.2.3. By End User
      • 4.2.3.1. Retail
      • 4.2.3.2. Transportation & Logistics
      • 4.2.3.3. Manufacturing
      • 4.2.3.4. Healthcare
      • 4.2.3.5. Others
    • 4.2.4. By Region
      • 4.2.4.1. North America
      • 4.2.4.2. Europe
      • 4.2.4.3. Asia Pacific (APAC)
      • 4.2.4.4. Latin America (LATAM)
      • 4.2.4.5. Middle East and Africa (MEA)

5. North America Supply Chain Big Data Analytics Market

  • 5.1. Market Size & Forecast, 2019-2029
    • 5.1.1. By Value (USD Million)
  • 5.2. Market Share & Forecast
    • 5.2.1. By Solution
    • 5.2.2. By Service
    • 5.2.3. By End User
    • 5.2.4. By Country
      • 5.2.4.1. US
      • 5.2.4.1.1. By Solution
      • 5.2.4.1.2. By Service
      • 5.2.4.1.3. By End User
      • 5.2.4.2. Canada
      • 5.2.4.2.1. By Solution
      • 5.2.4.2.2. By Service
      • 5.2.4.2.3. By End User

6. Europe Supply Chain Big Data Analytics Market

  • 6.1. Market Size & Forecast, 2019-2029
    • 6.1.1. By Value (USD Million)
  • 6.2. Market Share & Forecast
    • 6.2.1. By Solution
    • 6.2.2. By Service
    • 6.2.3. By End User
    • 6.2.4. By Country
      • 6.2.4.1. Germany
      • 6.2.4.1.1. By Solution
      • 6.2.4.1.2. By Service
      • 6.2.4.1.3. By End User
      • 6.2.4.2. UK
      • 6.2.4.2.1. By Solution
      • 6.2.4.2.2. By Service
      • 6.2.4.2.3. By End User
      • 6.2.4.3. Italy
      • 6.2.4.3.1. By Solution
      • 6.2.4.3.2. By Service
      • 6.2.4.3.3. By End User
      • 6.2.4.4. France
      • 6.2.4.4.1. By Solution
      • 6.2.4.4.2. By Service
      • 6.2.4.4.3. By End User
      • 6.2.4.5. Spain
      • 6.2.4.5.1. By Solution
      • 6.2.4.5.2. By Service
      • 6.2.4.5.3. By End User
      • 6.2.4.6. The Netherlands
      • 6.2.4.6.1. By Solution
      • 6.2.4.6.2. By Service
      • 6.2.4.6.3. By End User
      • 6.2.4.7. Rest of Europe
      • 6.2.4.7.1. By Solution
      • 6.2.4.7.2. By Service
      • 6.2.4.7.3. By End User

7. Asia-Pacific Supply Chain Big Data Analytics Market

  • 7.1. Market Size & Forecast, 2019-2029
    • 7.1.1. By Value (USD Million)
  • 7.2. Market Share & Forecast
    • 7.2.1. By Solution
    • 7.2.2. By Service
    • 7.2.3. By End User
    • 7.2.4. By Country
      • 7.2.4.1. China
      • 7.2.4.1.1. By Solution
      • 7.2.4.1.2. By Service
      • 7.2.4.1.3. By End User
      • 7.2.4.2. India
      • 7.2.4.2.1. By Solution
      • 7.2.4.2.2. By Service
      • 7.2.4.2.3. By End User
      • 7.2.4.3. Japan
      • 7.2.4.3.1. By Solution
      • 7.2.4.3.2. By Service
      • 7.2.4.3.3. By End User
      • 7.2.4.4. South Korea
      • 7.2.4.4.1. By Solution
      • 7.2.4.4.2. By Service
      • 7.2.4.4.3. By End User
      • 7.2.4.5. Australia & New Zealand
      • 7.2.4.5.1. By Solution
      • 7.2.4.5.2. By Service
      • 7.2.4.5.3. By End User
      • 7.2.4.6. Indonesia
      • 7.2.4.6.1. By Solution
      • 7.2.4.6.2. By Service
      • 7.2.4.6.3. By End User
      • 7.2.4.7. Malaysia
      • 7.2.4.7.1. By Solution
      • 7.2.4.7.2. By Service
      • 7.2.4.7.3. By End User
      • 7.2.4.8. Singapore
      • 7.2.4.8.1. By Solution
      • 7.2.4.8.2. By Service
      • 7.2.4.8.3. By End User
      • 7.2.4.9. Philippines
      • 7.2.4.9.1. By Solution
      • 7.2.4.9.2. By Service
      • 7.2.4.9.3. By End User
      • 7.2.4.10. Vietnam
      • 7.2.4.10.1. By Solution
      • 7.2.4.10.2. By Service
      • 7.2.4.10.3. By End User
      • 7.2.4.11. Rest of APAC
      • 7.2.4.11.1. By Solution
      • 7.2.4.11.2. By Service
      • 7.2.4.11.3. By End User

8. Latin America Supply Chain Big Data Analytics Market

  • 8.1. Market Size & Forecast, 2019-2029
    • 8.1.1. By Value (USD Million)
  • 8.2. Market Share & Forecast
    • 8.2.1. By Solution
    • 8.2.2. By Service
    • 8.2.3. By End User
    • 8.2.4. By Country
      • 8.2.4.1. Brazil
      • 8.2.4.1.1. By Solution
      • 8.2.4.1.2. By Service
      • 8.2.4.1.3. By End User
      • 8.2.4.2. Mexico
      • 8.2.4.2.1. By Solution
      • 8.2.4.2.2. By Service
      • 8.2.4.2.3. By End User
      • 8.2.4.3. Argentina
      • 8.2.4.3.1. By Solution
      • 8.2.4.3.2. By Service
      • 8.2.4.3.3. By End User
      • 8.2.4.4. Peru
      • 8.2.4.4.1. By Solution
      • 8.2.4.4.2. By Service
      • 8.2.4.4.3. By End User
      • 8.2.4.5. Rest of LATAM
      • 8.2.4.5.1. By Solution
      • 8.2.4.5.2. By Service
      • 8.2.4.5.3. By End User

9. Middle East & Africa Supply Chain Big Data Analytics Market

  • 9.1. Market Size & Forecast, 2019-2029
    • 9.1.1. By Value (USD Million)
  • 9.2. Market Share & Forecast
    • 9.2.1. By Solution
    • 9.2.2. By Service
    • 9.2.3. By End User
    • 9.2.4. By Country
      • 9.2.4.1. Saudi Arabia
      • 9.2.4.1.1. By Solution
      • 9.2.4.1.2. By Service
      • 9.2.4.1.3. By End User
      • 9.2.4.2. UAE
      • 9.2.4.2.1. By Solution
      • 9.2.4.2.2. By Service
      • 9.2.4.2.3. By End User
      • 9.2.4.3. Qatar
      • 9.2.4.3.1. By Solution
      • 9.2.4.3.2. By Service
      • 9.2.4.3.3. By End User
      • 9.2.4.4. Kuwait
      • 9.2.4.4.1. By Solution
      • 9.2.4.4.2. By Service
      • 9.2.4.4.3. By End User
      • 9.2.4.5. South Africa
      • 9.2.4.5.1. By Solution
      • 9.2.4.5.2. By Service
      • 9.2.4.5.3. By End User
      • 9.2.4.6. Nigeria
      • 9.2.4.6.1. By Solution
      • 9.2.4.6.2. By Service
      • 9.2.4.6.3. By End User
      • 9.2.4.7. Algeria
      • 9.2.4.7.1. By Solution
      • 9.2.4.7.2. By Service
      • 9.2.4.7.3. By End User
      • 9.2.4.8. Rest of MEA
      • 9.2.4.8.1. By Solution
      • 9.2.4.8.2. By Service
      • 9.2.4.8.3. By End User

10. Competitive Landscape

  • 10.1. List of Key Players and Their Offerings
  • 10.2. Global Supply Chain Big Data Analytics Company Market Share Analysis, 2022
  • 10.3. Competitive Benchmarking, By Operating Parameters
  • 10.4. Key Strategic Developments (Mergers, Acquisitions, Partnerships, etc.)

11. Impact of Covid-19 on Global Supply Chain Big Data Analytics Market

12. Company Profile (Company Overview, Financial Matrix, Competitive Landscape, Key Personnel, Key Competitors, Contact Address, Strategic Outlook, SWOT Analysis)

  • 12.1. SAP SE (SAP)
  • 12.2. IBM Corporation
  • 12.3. Oracle Corporation
  • 12.4. MicroStrategy Incorporated
  • 12.5. Genpact Limited
  • 12.6. SAS Institute Inc.
  • 12.7. Sage Clarity Systems
  • 12.8. Salesforce.com Inc (Tableau Software Inc.)
  • 12.9. Birst Inc.
  • 12.10. Capgemini Group
  • 12.11. Kinaxis Inc.
  • 12.12. Accenture PLC
  • 12.13. Aera Technology
  • 12.14. JDA Software Group, Inc.
  • 12.15. Lockheed Martin Corporation
  • 12.16. Maersk Group.
  • 12.17. Other Prominent Players

13. Key Strategic Recommendations

14. Research Methodology

  • 14.1. Qualitative Research
    • 14.1.1. Primary & Secondary Research
  • 14.2. Quantitative Research
  • 14.3. Market Breakdown & Data Triangulation
    • 14.3.1. Secondary Research
    • 14.3.2. Primary Research
  • 14.4. Breakdown of Primary Research Respondents, By Region
  • 14.5. Assumptions & Limitations