세계의 공급망 분야 AI 시장 : 제공별, 전개별, 조직 규모별, 용도별, 최종 사용 산업별, 지역별 - 예측(-2030년)

The AI in supply chain market is projected to grow from USD 9.15 billion in 2024 and is expected to reach USD 40.53 billion by 2030, growing at a CAGR of 28.2% from 2024 to 2030. AI has improved customers satisfaction toward consumer products. This improvement benefits the organization by maintaining sales tracking and hence garnering more customers. The machine learning techniques that involve deep analytics and real-time monitoring significantly enhance the supply chain visibility of the businesses and hence enable them to deliver better customer experiences and maintain the pace within the delivery timelines. Therefore, market players are employing AI-based supply chain management solutions to increase efficiency and productivity.

"The cloud segment in the AI in supply chain market to witness higher growth rate during the forecast period."

Cloud segment is mainly driven by cloud-based solutions that are increasingly being adopted by small and medium enterprises, primarily because they provide the flexibility, scalability, and cost-effectiveness features that the organizations require. In addition, the speed in developing sophisticated security solutions for cloud-based deployment offers answers to issues that existed on data privacy and thus attract businesses seeking to adopt AI without investing in big premises-based infrastructure.

"The US is expected to hold the largest market size in the North America region during the forecast period."

The US companies face pressure and competition to reduce costs while maintaining high levels of customer service. AI supply chain solutions allow for the automation of tasks, analyzing big data, and generating actionable insights that might make efficiency, transparency, and agility inside the supply chain more efficient. There has been a manufacturing and logistics labor shortfall in the US. The use of AI helps to eliminate a human workforce so that activities relate more to higher-value tasks requiring expertise and experience. Further, the US is a leading country in AI research and development. This encourages the development of advanced AI solutions specifically for supply chain applications.

• By Company Type: Tier 1 - 20%, Tier 2 - 35%, and Tier 3 - 45%
• By Designation: C-level Executives - 15%, Directors -20%, and Others - 65%
• By Region: North America -20%, Europe - 15%, Asia Pacific- 60%, and RoW - 5%

Players profiled in this report are SAP SE (Germany), Oracle (US), Blue Yonder Group, Inc. (US), Kinaxis Inc. (Canada), Manhattan Associates (US), NVIDIA Corporation (US), Advanced Micro Devices, Inc. (US), Intel Corporation (US), Micron Technology, Inc. (US), Qualcomm Technologies, Inc. (US), SAMSUNG (South Korea), IBM (US), Microsoft (US), Amazon Web Services, Inc. (US), Google (US), Anaplan, Inc. (US), Logility Supply Chain Solutions, Inc. (US), Coupa (US), O9 Solutions, Inc. (US), Alibaba Group Holding Limited (China), FedEx Corporation (US), Deutsche Post AG (Germany), ServiceNow (US), Project44 (US), Resilinc Corporation (US), FourKites, Inc. (US), RELEX Solutions (Finland), C.H. Robinson Worldwide, Inc. (US), e2open, LLC (US), FERO.Ai (UAE) among a few other key companies in the AI in supply chain ecosystem.

Report Coverage

The report defines, describes, and forecasts the AI in supply chain market based on offering, deployment, organization size, application, end-use industry, and region. It provides detailed information regarding drivers, restraints, opportunities, and challenges influencing the growth of the AI in supply chain market. It also analyzes competitive developments such as acquisitions, product launches, expansions, and actions carried out by the key players to grow in the market.

Reasons to Buy This Report

The report will help the market leaders/new entrants in the market with information on the closest approximations of the revenue for the overall AI in supply chain market and the subsegments. The report will help stakeholders understand the competitive landscape and gain more insight to position their business better and plan suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provides them with information on key drivers, restraints, opportunities, and challenges.

The report will provide insights into the following pointers:

• Analysis of key drivers (Big data enhance supply chain efficiency through data-driven decision making) restraints (Shortage of skilled workforce)

opportunities (Surge in increasing demand for intelligent business processes and automation), and challenges (Difficulties in data integration from multiple sources) of the AI in supply chain market.

• Product development /Innovation: Detailed insights on upcoming technologies, research & development activities, and new product launches in the AI in supply chain market.
• Market Development: Comprehensive information about lucrative markets; the report analyses the AI in supply chain market across various regions.
• Market Diversification: Exhaustive information about new products launched, untapped geographies, recent developments, and investments in the AI in supply chain market.
• Competitive Assessment: In-depth assessment of market share, growth strategies, and offering of leading players like SAP SE (Germany), Oracle (US), Blue Yonder Group, Inc. (US), Kinaxis Inc. (Canada), Manhattan Associates (US) among others in the AI in supply chain market.

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 STUDY OBJECTIVES
• 1.2 MARKET DEFINITION
• 1.3 STUDY SCOPE
  • 1.3.1 MARKET SEGMENTATION
  • 1.3.2 INCLUSIONS AND EXCLUSIONS
• 1.4 YEARS CONSIDERED
• 1.5 CURRENCY CONSIDERED
• 1.6 UNITS CONSIDERED
• 1.7 STAKEHOLDERS
• 1.8 SUMMARY OF CHANGES

2 RESEARCH METHODOLOGY

• 2.1 RESEARCH DATA
  • 2.1.1 SECONDARY DATA
    • 2.1.1.1 List of secondary sources
    • 2.1.1.2 Key data from secondary sources
  • 2.1.2 PRIMARY DATA
    • 2.1.2.1 List of interview participants
    • 2.1.2.2 Breakdown of primary interviews
    • 2.1.2.3 Key data from primary sources
    • 2.1.2.4 Insights from industry experts
  • 2.1.3 SECONDARY AND PRIMARY RESEARCH
• 2.2 MARKET SIZE ESTIMATION
  • 2.2.1 BOTTOM-UP APPROACH
    • 2.2.1.1 Approach to estimate market size using bottom-up analysis (supply side)
  • 2.2.2 TOP-DOWN APPROACH
    • 2.2.2.1 Approach to estimate market size using top-down analysis (demand side)
• 2.3 DATA TRIANGULATION
• 2.4 RESEARCH ASSUMPTIONS
• 2.5 RESEARCH LIMITATIONS
• 2.6 RISK ASSESSMENT

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

• 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI IN SUPPLY CHAIN MARKET
• 4.2 AI IN SUPPLY CHAIN MARKET, BY OFFERING
• 4.3 AI IN SUPPLY CHAIN MARKET, BY DEPLOYMENT
• 4.4 AI IN SUPPLY CHAIN MARKET, BY ORGANIZATION SIZE
• 4.5 NORTH AMERICA: AI IN SUPPLY CHAIN MARKET, BY DEPLOYMENT AND COUNTRY
• 4.6 GLOBAL AI IN SUPPLY CHAIN MARKET, BY COUNTRY

5 MARKET OVERVIEW

• 5.1 INTRODUCTION
• 5.2 MARKET DYNAMICS
  • 5.2.1 DRIVERS
    • 5.2.1.1 Growing implementation of big data and AI technologies
    • 5.2.1.2 Need for enhanced visibility in supply chain processes
    • 5.2.1.3 Rapid AI integration to improve customer satisfaction
    • 5.2.1.4 Shift toward cloud-based supply chain solutions
  • 5.2.2 RESTRAINTS
    • 5.2.2.1 Shortage of skilled workforce
    • 5.2.2.2 Security and data privacy concerns
  • 5.2.3 OPPORTUNITIES
    • 5.2.3.1 Surge in demand for intelligent business processes and automation
    • 5.2.3.2 Improved operational efficiency with AI
  • 5.2.4 CHALLENGES
    • 5.2.4.1 Difficulties in seamless data integration from multiple sources
• 5.3 VALUE CHAIN ANALYSIS
• 5.4 ECOSYSTEM ANALYSIS
• 5.5 TRENDS AND DISRUPTIONS IMPACTING CUSTOMER BUSINESS
• 5.6 TECHNOLOGY ANALYSIS
  • 5.6.1 KEY TECHNOLOGIES
    • 5.6.1.1 Machine Learning
    • 5.6.1.2 Natural Language Processing
    • 5.6.1.3 Computer Vision
  • 5.6.2 COMPLEMENTARY TECHNOLOGIES
    • 5.6.2.1 Internet of Things
  • 5.6.3 ADJACENT TECHNOLOGIES
    • 5.6.3.1 Robotic Process Automation
    • 5.6.3.2 Internet of Things
    • 5.6.3.3 Edge Computing
• 5.7 INVESTMENT AND FUNDING SCENARIO
• 5.8 PORTER'S FIVE FORCES ANALYSIS
  • 5.8.1 INTENSITY OF COMPETITIVE RIVALRY
  • 5.8.2 BARGAINING POWER OF SUPPLIERS
  • 5.8.3 BARGAINING POWER OF BUYERS
  • 5.8.4 THREAT OF SUBSTITUTES
  • 5.8.5 THREAT OF NEW ENTRANTS
• 5.9 KEY STAKEHOLDERS AND BUYING CRITERIA
  • 5.9.1 KEY STAKEHOLDERS IN BUYING PROCESS
  • 5.9.2 BUYING CRITERIA
• 5.10 CASE STUDY ANALYSIS
  • 5.10.1 INTEL CORPORATION BRINGS GRAPHICS PROCESSING UNIT TO VEHICLE COCKPIT
  • 5.10.2 IBM AND NABP DEVELOP BLOCKCHAIN-BASED PLATFORM TO ENHANCE DRUG SUPPLY CHAIN SECURITY
  • 5.10.3 UNIPER SE ENHANCES ENERGY OPERATIONS WITH MICROSOFT COPILOT
  • 5.10.4 NORGREN STREAMLINES SUPPLY CHAIN WITH SAP SE INTEGRATED SOLUTIONS
  • 5.10.5 TERADYNE ENHANCES SUPPLY CHAIN EFFICIENCY WITH C.H. ROBINSON WORLDWIDE'S INTEGRATED LOGISTICS SOLUTIONS
• 5.11 TRADE ANALYSIS
  • 5.11.1 IMPORT SCENARIO (HS CODE 854231)
  • 5.11.2 EXPORT SCENARIO (HS CODE 854231)
• 5.12 PATENT ANALYSIS
• 5.13 KEY CONFERENCES AND EVENTS, 2024-2025
• 5.14 REGULATORY LANDSCAPE
  • 5.14.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • 5.14.2 REGULATORY STANDARDS
  • 5.14.3 GOVERNMENT REGULATIONS
• 5.15 PRICING ANALYSIS

6 AI IN SUPPLY CHAIN MARKET, BY OFFERING

• 6.1 INTRODUCTION
• 6.2 SOFTWARE
  • 6.2.1 INCLINATION TOWARD SMART AUTOMATION TO DRIVE MARKET
• 6.3 SERVICES
  • 6.3.1 MANAGED SERVICES
    • 6.3.1.1 Extensive use in supply chain management to drive market
  • 6.3.2 PROFESSIONAL SERVICES
    • 6.3.2.1 Critical role in business innovation to drive market

7 AI IN SUPPLY CHAIN MARKET, BY DEPLOYMENT

• 7.1 INTRODUCTION
• 7.2 CLOUD
  • 7.2.1 GROWING POPULARITY DUE TO SIGNIFICANT ADVANTAGES TO DRIVE MARKET
• 7.3 ON-PREMISES
  • 7.3.1 COMPLIANCE WITH STRINGENT REGULATORY REQUIREMENTS TO DRIVE MARKET
• 7.4 HYBRID
  • 7.4.1 NEED FOR CLOUD SCALABILITY AND ON-PREMISES CONTROL TO DRIVE MARKET

8 AI IN SUPPLY CHAIN MARKET, BY ORGANIZATION SIZE

• 8.1 INTRODUCTION
• 8.2 LARGE ORGANIZATION
  • 8.2.1 RAPID AI INTEGRATION ACROSS GLOBAL SUPPLY CHAIN NETWORKS TO DRIVE MARKET
• 8.3 SMALL & MEDIUM ORGANIZATION
  • 8.3.1 ADVENT OF SCALABLE AND COST-EFFECTIVE AI SOLUTIONS TO DRIVE MARKET

9 AI IN SUPPLY CHAIN MARKET, BY APPLICATION

• 9.1 INTRODUCTION
• 9.2 DEMAND PLANNING & FORECASTING
  • 9.2.1 REAL-TIME DATASET PROCESSING CAPACITY TO DRIVE MARKET
• 9.3 PROCUREMENT & SOURCING
  • 9.3.1 AUTOMATION OF DATA-DRIVEN DECISION-MAKING TO DRIVE MARKET
• 9.4 INVENTORY MANAGEMENT
  • 9.4.1 NEED FOR STEADY FLOW OF SUPPLIES AND FINISHED GOODS TO DRIVE MARKET
• 9.5 PRODUCTION PLANNING & SCHEDULING
  • 9.5.1 ENHANCED SCHEDULING AND INVENTORY MANAGEMENT WITH AI ALGORITHMS TO DRIVE MARKET
• 9.6 WAREHOUSE & TRANSPORTATION MANAGEMENT
  • 9.6.1 AI-DRIVEN DEMAND FORECASTING AND ROUTE OPTIMIZATION CAPABILITIES TO DRIVE MARKET
• 9.7 SUPPLY CHAIN RISK MANAGEMENT
  • 9.7.1 ABILITY TO MITIGATE POTENTIAL DISRUPTIONS TO DRIVE MARKET
• 9.8 OTHER APPLICATIONS

10 AI IN SUPPLY CHAIN MARKET, BY END-USE INDUSTRY

• 10.1 INTRODUCTION
• 10.2 RETAIL
  • 10.2.1 RAPID ADOPTION OF AI TO ENHANCE CUSTOMER EXPERIENCE TO DRIVE MARKET
• 10.3 HEALTHCARE & PHARMACEUTICALS
  • 10.3.1 INCREASED FUNDING TO ENHANCE OPERATIONAL EFFICIENCY TO DRIVE MARKET
• 10.4 FOOD & BEVERAGES
  • 10.4.1 EXTENSIVE USE OF AI IN SUPPLY CHAIN TO PREDICT DEMAND TO DRIVE MARKET
• 10.5 AUTOMOTIVE
  • 10.5.1 SURGE IN DEMAND FOR ELECTRIC AND AUTONOMOUS VEHICLES TO DRIVE MARKET
• 10.6 LOGISTICS & TRANSPORTATION
  • 10.6.1 IMPLEMENTATION OF CLOUD-BASED SOLUTIONS TO REDUCE COSTS TO DRIVE MARKET
• 10.7 AEROSPACE & DEFENSE
  • 10.7.1 GOVERNMENT INITIATIVES TO STRENGTHEN NATIONAL SECURITY TO DRIVE MARKET
• 10.8 CHEMICALS
  • 10.8.1 NEED FOR PROCESS OPTIMIZATION IN SUPPLY CHAIN TO DRIVE MARKET
• 10.9 ELECTRONICS & SEMICONDUCTOR
  • 10.9.1 RISE IN TECHNOLOGICAL INNOVATIONS TO DRIVE MARKET
• 10.10 ENERGY & UTILITIES
  • 10.10.1 NEED FOR EFFICIENT ENERGY UTILIZATION TO DRIVE MARKET
• 10.11 MANUFACTURING
  • 10.11.1 INCORPORATION OF INTELLIGENT SYSTEMS TO AUTOMATE OPERATIONS TO DRIVE MARKET
• 10.12 OTHER END-USE INDUSTRIES

11 AI IN SUPPLY CHAIN MARKET, BY REGION

• 11.1 INTRODUCTION
• 11.2 NORTH AMERICA
  • 11.2.1 MACROECONOMIC OUTLOOK
  • 11.2.2 US
    • 11.2.2.1 Increasing adoption of technology infrastructure and growth initiatives by US government to drive market
  • 11.2.3 CANADA
    • 11.2.3.1 Rising investments to boost adoption of AI across industries
  • 11.2.4 MEXICO
    • 11.2.4.1 Government initiatives to boost manufacturing capabilities in Mexico
• 11.3 EUROPE
  • 11.3.1 MACROECONOMIC OUTLOOK
  • 11.3.2 GERMANY
    • 11.3.2.1 Increasing adoption of AI to drive market growth
  • 11.3.3 UK
    • 11.3.3.1 Continuous investments and initiatives by UK government to bolster growth
  • 11.3.4 FRANCE
    • 11.3.4.1 AI initiatives and investments to push French market forward
  • 11.3.5 REST OF EUROPE
• 11.4 ASIA PACIFIC
  • 11.4.1 MACROECONOMIC OUTLOOK
  • 11.4.2 CHINA
    • 11.4.2.1 Government initiatives and rising investments to drive market growth
  • 11.4.3 JAPAN
    • 11.4.3.1 Growth in investments and government initiatives to drive innovation
  • 11.4.4 SOUTH KOREA
    • 11.4.4.1 Government investments in artificial intelligence to accelerate market growth
  • 11.4.5 INDIA
    • 11.4.5.1 Rapid surge in development and adoption of AI technologies to propel market
  • 11.4.6 REST OF ASIA PACIFIC
• 11.5 REST OF THE WORLD
  • 11.5.1 MACROECONOMIC OUTLOOK
  • 11.5.2 MIDDLE EAST & AFRICA
    • 11.5.2.1 Commitment to digital transformation and technological innovation to drive growth
    • 11.5.2.2 GCC
    • 11.5.2.3 Rest of Middle East & Africa
  • 11.5.3 SOUTH AMERICA
    • 11.5.3.1 Growing interest of private enterprises to boost market

12 COMPETITIVE LANDSCAPE

• 12.1 OVERVIEW
• 12.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
• 12.3 REVENUE ANALYSIS, 2019-2023
• 12.4 MARKET SHARE ANALYSIS, 2023
• 12.5 COMPANY VALUATION AND FINANCIAL METRICS
• 12.6 BRAND/PRODUCT COMPARISON
• 12.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
  • 12.7.1 STARS
  • 12.7.2 EMERGING LEADERS
  • 12.7.3 PERVASIVE PLAYERS
  • 12.7.4 PARTICIPANTS
  • 12.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023
    • 12.7.5.1 Company footprint
    • 12.7.5.2 Offering footprint
    • 12.7.5.3 Deployment footprint
    • 12.7.5.4 Organization size footprint
    • 12.7.5.5 Application footprint
    • 12.7.5.6 End-use industry footprint
    • 12.7.5.7 Region footprint
• 12.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
  • 12.8.1 PROGRESSIVE COMPANIES
  • 12.8.2 RESPONSIVE COMPANIES
  • 12.8.3 DYNAMIC COMPANIES
  • 12.8.4 STARTING BLOCKS
  • 12.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023
    • 12.8.5.1 Detailed list of key startups/SMEs
    • 12.8.5.2 Competitive benchmarking of key startups/SMEs
      • 12.8.5.2.1 Competitive benchmarking, by offering and region
      • 12.8.5.2.2 Competitive benchmarking, by application and deployment
      • 12.8.5.2.3 Competitive benchmarking, by end-use industry and organization size
• 12.9 COMPETITIVE SCENARIO
  • 12.9.1 PRODUCT LAUNCHES/DEVELOPMENTS
  • 12.9.2 DEALS

13 COMPANY PROFILES

• 13.1 KEY PLAYERS
  • 13.1.1 SAP SE
    • 13.1.1.1 Business overview
    • 13.1.1.2 Products/Services/Solutions offered
    • 13.1.1.3 Recent developments
      • 13.1.1.3.1 Deals
    • 13.1.1.4 MnM view
      • 13.1.1.4.1 Key strengths/Right to win
      • 13.1.1.4.2 Strategic choices
      • 13.1.1.4.3 Weaknesses/Competitive threats
  • 13.1.2 ORACLE
    • 13.1.2.1 Business overview
    • 13.1.2.2 Products/Services/Solutions offered
    • 13.1.2.3 Recent developments
      • 13.1.2.3.1 Product launches/developments
      • 13.1.2.3.2 Deals
    • 13.1.2.4 MnM view
      • 13.1.2.4.1 Key strengths/Right to win
      • 13.1.2.4.2 Strategic choices
      • 13.1.2.4.3 Weaknesses/Competitive threats
  • 13.1.3 BLUE YONDER GROUP, INC.
    • 13.1.3.1 Business overview
    • 13.1.3.2 Products/Services/Solutions offered
    • 13.1.3.3 Recent developments
      • 13.1.3.3.1 Deals
    • 13.1.3.4 MnM view
      • 13.1.3.4.1 Key strengths/Right to win
      • 13.1.3.4.2 Strategic choices
      • 13.1.3.4.3 Weaknesses/Competitive threats
  • 13.1.4 KINAXIS INC.
    • 13.1.4.1 Business overview
    • 13.1.4.2 Products/Services/Solutions offered
    • 13.1.4.3 Recent developments
      • 13.1.4.3.1 Product launches/developments
      • 13.1.4.3.2 Deals
    • 13.1.4.4 MnM view
      • 13.1.4.4.1 Key strengths/Right to win
      • 13.1.4.4.2 Strategic choices
      • 13.1.4.4.3 Weaknesses/Competitive threats
  • 13.1.5 MANHATTAN ASSOCIATES
    • 13.1.5.1 Business overview
    • 13.1.5.2 Products/Services/Solutions offered
    • 13.1.5.3 Recent developments
      • 13.1.5.3.1 Product launches/developments
      • 13.1.5.3.2 Deals
    • 13.1.5.4 MnM view
      • 13.1.5.4.1 Key strengths/Right to win
      • 13.1.5.4.2 Strategic choices
      • 13.1.5.4.3 Weaknesses/Competitive threats
  • 13.1.6 NVIDIA CORPORATION
    • 13.1.6.1 Business overview
    • 13.1.6.2 Products/Services/Solutions offered
    • 13.1.6.3 Recent developments
      • 13.1.6.3.1 Product launches/developments
      • 13.1.6.3.2 Deals
  • 13.1.7 ADVANCED MICRO DEVICES, INC.
    • 13.1.7.1 Business overview
    • 13.1.7.2 Products/Services/Solutions offered
    • 13.1.7.3 Recent developments
      • 13.1.7.3.1 Product launches/developments
      • 13.1.7.3.2 Deals
  • 13.1.8 INTEL CORPORATION
    • 13.1.8.1 Business overview
    • 13.1.8.2 Products/Services/Solutions offered
    • 13.1.8.3 Recent developments
      • 13.1.8.3.1 Product launches/developments
  • 13.1.9 MICRON TECHNOLOGY, INC.
    • 13.1.9.1 Business overview
    • 13.1.9.2 Products/Services/Solutions offered
    • 13.1.9.3 Recent developments
      • 13.1.9.3.1 Deals
  • 13.1.10 QUALCOMM TECHNOLOGIES, INC.
    • 13.1.10.1 Business overview
    • 13.1.10.2 Products/Services/Solutions offered
    • 13.1.10.3 Recent developments
      • 13.1.10.3.1 Product launches/developments
      • 13.1.10.3.2 Deals
  • 13.1.11 SAMSUNG
    • 13.1.11.1 Business overview
    • 13.1.11.2 Products/Services/Solutions offered
    • 13.1.11.3 Recent developments
      • 13.1.11.3.1 Product launches/developments
      • 13.1.11.3.2 Deals
  • 13.1.12 IBM
    • 13.1.12.1 Business overview
    • 13.1.12.2 Products/Services/Solutions offered
    • 13.1.12.3 Recent developments
      • 13.1.12.3.1 Deals
  • 13.1.13 MICROSOFT
    • 13.1.13.1 Business overview
    • 13.1.13.2 Products/Services/Solutions offered
    • 13.1.13.3 Recent developments
      • 13.1.13.3.1 Deals
  • 13.1.14 AMAZON WEB SERVICES, INC.
    • 13.1.14.1 Business overview
    • 13.1.14.2 Products/Services/Solutions offered
    • 13.1.14.3 Recent developments
      • 13.1.14.3.1 Product launches/developments
      • 13.1.14.3.2 Deals
  • 13.1.15 GOOGLE
    • 13.1.15.1 Business overview
    • 13.1.15.2 Products/Services/Solutions offered
    • 13.1.15.3 Recent developments
      • 13.1.15.3.1 Product launches/developments
      • 13.1.15.3.2 Deals
  • 13.1.16 ANAPLAN, INC.
    • 13.1.16.1 Business overview
    • 13.1.16.2 Products/Services/Solutions offered
    • 13.1.16.3 Recent developments
      • 13.1.16.3.1 Deals
• 13.2 OTHER PLAYERS
  • 13.2.1 LOGILITY SUPPLY CHAIN SOLUTIONS, INC.
  • 13.2.2 COUPA
  • 13.2.3 O9 SOLUTIONS, INC.
  • 13.2.4 ALIBABA GROUP HOLDING LIMITED
  • 13.2.5 FEDEX CORPORATION
  • 13.2.6 DEUTSCHE POST AG
  • 13.2.7 SERVICENOW
  • 13.2.8 PROJECT44
  • 13.2.9 RESILINC CORPORATION
  • 13.2.10 FOURKITES, INC.
  • 13.2.11 RELEX SOLUTIONS
  • 13.2.12 C.H. ROBINSON WORLDWIDE, INC.
  • 13.2.13 E2OPEN, LLC
  • 13.2.14 FERO.AI

14 APPENDIX

• 14.1 DISCUSSION GUIDE
• 14.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
• 14.3 CUSTOMIZATION OPTIONS
• 14.4 RELATED REPORTS
• 14.5 AUTHOR DETAILS