Predictive Analytics In Supply Chain Market Growth, Trends, and Analysis by 2031

Coverage: Predictive Analytics in Supply Chain Market covers analysis by Component (Solution, Services); Deployment Model (Cloud-based, On-premises); Enterprise Size (Small and Medium Enterprises, Large Enterprises); Industry Vertical (Food and Beverage, Consumer Goods and Retail, Automotive, Aerospace and Defense, Industrial Manufacturing, Pharmaceutical, Others) , and Geography (North America, Europe, Asia Pacific, and South and Central America)

  • Report Code : TIPRE00005023
  • Category : Technology, Media and Telecommunications
  • No. of Pages : 150
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The Predictive Analytics in Supply Chain Market is expected to register a CAGR of 20.2% from 2025 to 2031, with a market size expanding from US$ XX million in 2024 to US$ XX Million by 2031.

The report is divided into two segments:Modules (Load Flow, Short Circuit, Arc Flash, Device Coordination Selectivity, Harmonics, Others) and End User (Commercial, Industrial). The worldwide study is further subdivided into main nations and regions.

Purpose of the Report

The report Predictive Analytics in Supply Chain Market by The Insight Partners aims to describe the present landscape and future growth, top driving factors, challenges, and opportunities. This will provide insights to various business stakeholders, such as:

  • Technology Providers/Manufacturers: To understand the evolving market dynamics and know the potential growth opportunities, enabling them to make informed strategic decisions.
  • Investors: To conduct a comprehensive trend analysis regarding the market growth rate, market financial projections, and opportunities that exist across the value chain.
  • Regulatory bodies: To regulate policies and police activities in the market with the aim of minimizing abuse, preserving investor trust and confidence, and upholding the integrity and stability of the market.

Predictive Analytics in Supply Chain Market Segmentation

Modules
  • Load Flow
  • Short Circuit
  • Arc Flash
  • Device Coordination Selectivity
  • Harmonics
  • Others
End User
  • Commercial
  • Industrial

Strategic Insights

Predictive Analytics in Supply Chain Market Growth Drivers
  • Increasing Supply Chain Complexity: The growing complexity of global supply chains, with multiple nodes and diverse stakeholders, necessitates advanced analytics tools.
  • Rising Demand for Supply Chain Visibility: Real-time visibility into supply chain operations is critical for efficient decision-making and risk mitigation.
  • Advancements in Data Analytics Technologies: The development of advanced analytics techniques, such as machine learning and AI, is driving the adoption of predictive analytics in supply chain management.
Predictive Analytics in Supply Chain Market Future Trends
  • AI-Powered Demand Forecasting: AI-powered demand forecasting models will provide more accurate and timely predictions, improving inventory management.
  • Digital Twin Technology: Digital twins of supply chains will enable simulation and optimization of various scenarios.
  • Integration with IoT: IoT devices will generate vast amounts of data, which can be analyzed using predictive analytics to optimize supply chain operations.
Predictive Analytics in Supply Chain Market Opportunities
  • Inventory Optimization: Predictive analytics can help optimize inventory levels, reducing holding costs and preventing stockouts.
  • Risk Management: By identifying potential disruptions and risks, predictive analytics can help organizations develop contingency plans.
  • Supply Chain Resilience: Predictive analytics can enhance supply chain resilience by enabling proactive response to disruptions and uncertainties.

Market Report Scope

Key Selling Points

  • Comprehensive Coverage: The report comprehensively covers the analysis of products, services, types, and end users of the Predictive Analytics in Supply Chain Market, providing a holistic landscape.
  • Expert Analysis: The report is compiled based on the in-depth understanding of industry experts and analysts.
  • Up-to-date Information: The report assures business relevance due to its coverage of recent information and data trends.
  • Customization Options: This report can be customized to cater to specific client requirements and suit the business strategies aptly.

The research report on the Predictive Analytics in Supply Chain Market can, therefore, help spearhead the trail of decoding and understanding the industry scenario and growth prospects. Although there can be a few valid concerns, the overall benefits of this report tend to outweigh the disadvantages.

REGIONAL FRAMEWORK
World Geography

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Report Coverage
Report Coverage

Revenue forecast, Company Analysis, Industry landscape, Growth factors, and Trends

Segment Covered
Segment Covered

This text is related
to segments covered.

Regional Scope
Regional Scope

North America, Europe, Asia Pacific, Middle East & Africa, South & Central America

Country Scope
Country Scope

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to country scope.

Frequently Asked Questions


What are the options available for the customization of this report?

Some of the customization options available based on request are additional 3-5 company profiles and country-specific analysis of 3-5 countries of your choice. Customizations are to be requested/discussed before making final order confirmation, as our team would review the same and check the feasibility.

Which are the leading players operating in the Predictive Analytics in Supply Chain Market?

The leading players in the Predictive Analytics in Supply Chain Market are: Alpine Electronics, Inc., Clarion Company, Ltd., Continental AG, Delphi Automotive plc, Denso Corporation, Garmin, Ltd., Harman International Industries, Inc., Panasonic Corporation, Robert Bosch GmbH, Visteon Corporation

What is the expected CAGR of the Predictive Analytics in Supply Chain Market?

Predictive Analytics in Supply Chain Market is expected to grow at a CAGR of 20.2% between 2023-2031

What are the future trends of the Predictive Analytics in Supply Chain Market?

The future trends of the Predictive Analytics in Supply Chain Market are: Integration with IoT and Real-Time Analytics, Ethical considerations and responsible AI

What are the driving factors impacting the Predictive Analytics in Supply Chain Market?

The driving factors impacting the Predictive Analytics in Supply Chain Market are: Growing Data Generation and Availability, Advancements in Artificial Intelligence and Machine Learning

What are the deliverable formats of the Predictive Analytics in Supply Chain Market report?

The report can be delivered in PDF/PPT format; we can also share excel dataset based on the request.

TABLE OF CONTENTS

1. INTRODUCTION
1.1. SCOPE OF THE STUDY
1.2. THE INSIGHT PARTNERS RESEARCH REPORT GUIDANCE
1.3. MARKET SEGMENTATION
1.3.1 Predictive Analytics In Supply Chain Market - By Component
1.3.2 Predictive Analytics In Supply Chain Market - By Deployment Model
1.3.3 Predictive Analytics In Supply Chain Market - By Enterprise Size
1.3.4 Predictive Analytics In Supply Chain Market - By Industry Vertical
1.3.5 Predictive Analytics In Supply Chain Market - By Region
1.3.5.1 By Country

2. KEY TAKEAWAYS

3. RESEARCH METHODOLOGY

4. PREDICTIVE ANALYTICS IN SUPPLY CHAIN MARKET LANDSCAPE
4.1. OVERVIEW
4.2. PEST ANALYSIS
4.2.1 North America - Pest Analysis
4.2.2 Europe - Pest Analysis
4.2.3 Asia-Pacific - Pest Analysis
4.2.4 Middle East and Africa - Pest Analysis
4.2.5 South and Central America - Pest Analysis
4.3. ECOSYSTEM ANALYSIS
4.4. EXPERT OPINIONS

5. PREDICTIVE ANALYTICS IN SUPPLY CHAIN MARKET - KEY MARKET DYNAMICS
5.1. KEY MARKET DRIVERS
5.2. KEY MARKET RESTRAINTS
5.3. KEY MARKET OPPORTUNITIES
5.4. FUTURE TRENDS
5.5. IMPACT ANALYSIS OF DRIVERS, RESTRAINTS & EXPECTED INFLUENCE OF COVID-19 PANDEMIC

6. PREDICTIVE ANALYTICS IN SUPPLY CHAIN MARKET - GLOBAL MARKET ANALYSIS
6.1. PREDICTIVE ANALYTICS IN SUPPLY CHAIN - GLOBAL MARKET OVERVIEW
6.2. PREDICTIVE ANALYTICS IN SUPPLY CHAIN - GLOBAL MARKET AND FORECAST TO 2028
6.3. MARKET POSITIONING/MARKET SHARE

7. PREDICTIVE ANALYTICS IN SUPPLY CHAIN MARKET - REVENUE AND FORECASTS TO 2028 - COMPONENT
7.1. OVERVIEW
7.2. COMPONENT MARKET FORECASTS AND ANALYSIS
7.3. SOLUTION
7.3.1. Overview
7.3.2. Solution Market Forecast and Analysis
7.3.3. Demand sensing Market
7.3.3.1. Overview
7.3.3.2. Demand sensing Market Forecast and Analysis
7.3.4. Inventory Management Market
7.3.4.1. Overview
7.3.4.2. Inventory Management Market Forecast and Analysis
7.3.5. Shipping Planning Market
7.3.5.1. Overview
7.3.5.2. Shipping Planning Market Forecast and Analysis
7.3.6. Predictive pricing Market
7.3.6.1. Overview
7.3.6.2. Predictive pricing Market Forecast and Analysis
7.3.7. Procurement Market
7.3.7.1. Overview
7.3.7.2. Procurement Market Forecast and Analysis
7.3.8. Promotion planning Market
7.3.8.1. Overview
7.3.8.2. Promotion planning Market Forecast and Analysis
7.3.9. After-sales modeling Market
7.3.9.1. Overview
7.3.9.2. After-sales modeling Market Forecast and Analysis
7.4. SERVICES
7.4.1. Overview
7.4.2. Services Market Forecast and Analysis
8. PREDICTIVE ANALYTICS IN SUPPLY CHAIN MARKET - REVENUE AND FORECASTS TO 2028 - DEPLOYMENT MODEL
8.1. OVERVIEW
8.2. DEPLOYMENT MODEL MARKET FORECASTS AND ANALYSIS
8.3. CLOUD-BASED
8.3.1. Overview
8.3.2. Cloud-based Market Forecast and Analysis
8.4. ON-PREMISES
8.4.1. Overview
8.4.2. On-premises Market Forecast and Analysis
9. PREDICTIVE ANALYTICS IN SUPPLY CHAIN MARKET - REVENUE AND FORECASTS TO 2028 - ENTERPRISE SIZE
9.1. OVERVIEW
9.2. ENTERPRISE SIZE MARKET FORECASTS AND ANALYSIS
9.3. SMALL AND MEDIUM ENTERPRISES
9.3.1. Overview
9.3.2. Small and Medium Enterprises Market Forecast and Analysis
9.4. LARGE ENTERPRISES
9.4.1. Overview
9.4.2. Large Enterprises Market Forecast and Analysis
10. PREDICTIVE ANALYTICS IN SUPPLY CHAIN MARKET - REVENUE AND FORECASTS TO 2028 - INDUSTRY VERTICAL
10.1. OVERVIEW
10.2. INDUSTRY VERTICAL MARKET FORECASTS AND ANALYSIS
10.3. FOOD AND BEVERAGE
10.3.1. Overview
10.3.2. Food and Beverage Market Forecast and Analysis
10.4. CONSUMER GOODS AND RETAIL
10.4.1. Overview
10.4.2. Consumer Goods and Retail Market Forecast and Analysis
10.5. AUTOMOTIVE
10.5.1. Overview
10.5.2. Automotive Market Forecast and Analysis
10.6. AEROSPACE AND DEFENSE
10.6.1. Overview
10.6.2. Aerospace and Defense Market Forecast and Analysis
10.7. INDUSTRIAL MANUFACTURING
10.7.1. Overview
10.7.2. Industrial Manufacturing Market Forecast and Analysis
10.8. PHARMACEUTICAL
10.8.1. Overview
10.8.2. Pharmaceutical Market Forecast and Analysis
10.9. OTHERS
10.9.1. Overview
10.9.2. Others Market Forecast and Analysis

11. PREDICTIVE ANALYTICS IN SUPPLY CHAIN MARKET REVENUE AND FORECASTS TO 2028 - GEOGRAPHICAL ANALYSIS
11.1. NORTH AMERICA
11.1.1 North America Predictive Analytics In Supply Chain Market Overview
11.1.2 North America Predictive Analytics In Supply Chain Market Forecasts and Analysis
11.1.3 North America Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Component
11.1.4 North America Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Deployment Model
11.1.5 North America Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Enterprise Size
11.1.6 North America Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Industry Vertical
11.1.7 North America Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Countries
11.1.7.1 United States Predictive Analytics In Supply Chain Market
11.1.7.1.1 United States Predictive Analytics In Supply Chain Market by Component
11.1.7.1.2 United States Predictive Analytics In Supply Chain Market by Deployment Model
11.1.7.1.3 United States Predictive Analytics In Supply Chain Market by Enterprise Size
11.1.7.1.4 United States Predictive Analytics In Supply Chain Market by Industry Vertical
11.1.7.2 Canada Predictive Analytics In Supply Chain Market
11.1.7.2.1 Canada Predictive Analytics In Supply Chain Market by Component
11.1.7.2.2 Canada Predictive Analytics In Supply Chain Market by Deployment Model
11.1.7.2.3 Canada Predictive Analytics In Supply Chain Market by Enterprise Size
11.1.7.2.4 Canada Predictive Analytics In Supply Chain Market by Industry Vertical
11.1.7.3 Mexico Predictive Analytics In Supply Chain Market
11.1.7.3.1 Mexico Predictive Analytics In Supply Chain Market by Component
11.1.7.3.2 Mexico Predictive Analytics In Supply Chain Market by Deployment Model
11.1.7.3.3 Mexico Predictive Analytics In Supply Chain Market by Enterprise Size
11.1.7.3.4 Mexico Predictive Analytics In Supply Chain Market by Industry Vertical
11.2. EUROPE
11.2.1 Europe Predictive Analytics In Supply Chain Market Overview
11.2.2 Europe Predictive Analytics In Supply Chain Market Forecasts and Analysis
11.2.3 Europe Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Component
11.2.4 Europe Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Deployment Model
11.2.5 Europe Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Enterprise Size
11.2.6 Europe Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Industry Vertical
11.2.7 Europe Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Countries
11.2.7.1 Germany Predictive Analytics In Supply Chain Market
11.2.7.1.1 Germany Predictive Analytics In Supply Chain Market by Component
11.2.7.1.2 Germany Predictive Analytics In Supply Chain Market by Deployment Model
11.2.7.1.3 Germany Predictive Analytics In Supply Chain Market by Enterprise Size
11.2.7.1.4 Germany Predictive Analytics In Supply Chain Market by Industry Vertical
11.2.7.2 France Predictive Analytics In Supply Chain Market
11.2.7.2.1 France Predictive Analytics In Supply Chain Market by Component
11.2.7.2.2 France Predictive Analytics In Supply Chain Market by Deployment Model
11.2.7.2.3 France Predictive Analytics In Supply Chain Market by Enterprise Size
11.2.7.2.4 France Predictive Analytics In Supply Chain Market by Industry Vertical
11.2.7.3 Italy Predictive Analytics In Supply Chain Market
11.2.7.3.1 Italy Predictive Analytics In Supply Chain Market by Component
11.2.7.3.2 Italy Predictive Analytics In Supply Chain Market by Deployment Model
11.2.7.3.3 Italy Predictive Analytics In Supply Chain Market by Enterprise Size
11.2.7.3.4 Italy Predictive Analytics In Supply Chain Market by Industry Vertical
11.2.7.4 United Kingdom Predictive Analytics In Supply Chain Market
11.2.7.4.1 United Kingdom Predictive Analytics In Supply Chain Market by Component
11.2.7.4.2 United Kingdom Predictive Analytics In Supply Chain Market by Deployment Model
11.2.7.4.3 United Kingdom Predictive Analytics In Supply Chain Market by Enterprise Size
11.2.7.4.4 United Kingdom Predictive Analytics In Supply Chain Market by Industry Vertical
11.2.7.5 Russia Predictive Analytics In Supply Chain Market
11.2.7.5.1 Russia Predictive Analytics In Supply Chain Market by Component
11.2.7.5.2 Russia Predictive Analytics In Supply Chain Market by Deployment Model
11.2.7.5.3 Russia Predictive Analytics In Supply Chain Market by Enterprise Size
11.2.7.5.4 Russia Predictive Analytics In Supply Chain Market by Industry Vertical
11.2.7.6 Rest of Europe Predictive Analytics In Supply Chain Market
11.2.7.6.1 Rest of Europe Predictive Analytics In Supply Chain Market by Component
11.2.7.6.2 Rest of Europe Predictive Analytics In Supply Chain Market by Deployment Model
11.2.7.6.3 Rest of Europe Predictive Analytics In Supply Chain Market by Enterprise Size
11.2.7.6.4 Rest of Europe Predictive Analytics In Supply Chain Market by Industry Vertical
11.3. ASIA-PACIFIC
11.3.1 Asia-Pacific Predictive Analytics In Supply Chain Market Overview
11.3.2 Asia-Pacific Predictive Analytics In Supply Chain Market Forecasts and Analysis
11.3.3 Asia-Pacific Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Component
11.3.4 Asia-Pacific Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Deployment Model
11.3.5 Asia-Pacific Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Enterprise Size
11.3.6 Asia-Pacific Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Industry Vertical
11.3.7 Asia-Pacific Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Countries
11.3.7.1 Australia Predictive Analytics In Supply Chain Market
11.3.7.1.1 Australia Predictive Analytics In Supply Chain Market by Component
11.3.7.1.2 Australia Predictive Analytics In Supply Chain Market by Deployment Model
11.3.7.1.3 Australia Predictive Analytics In Supply Chain Market by Enterprise Size
11.3.7.1.4 Australia Predictive Analytics In Supply Chain Market by Industry Vertical
11.3.7.2 China Predictive Analytics In Supply Chain Market
11.3.7.2.1 China Predictive Analytics In Supply Chain Market by Component
11.3.7.2.2 China Predictive Analytics In Supply Chain Market by Deployment Model
11.3.7.2.3 China Predictive Analytics In Supply Chain Market by Enterprise Size
11.3.7.2.4 China Predictive Analytics In Supply Chain Market by Industry Vertical
11.3.7.3 India Predictive Analytics In Supply Chain Market
11.3.7.3.1 India Predictive Analytics In Supply Chain Market by Component
11.3.7.3.2 India Predictive Analytics In Supply Chain Market by Deployment Model
11.3.7.3.3 India Predictive Analytics In Supply Chain Market by Enterprise Size
11.3.7.3.4 India Predictive Analytics In Supply Chain Market by Industry Vertical
11.3.7.4 Japan Predictive Analytics In Supply Chain Market
11.3.7.4.1 Japan Predictive Analytics In Supply Chain Market by Component
11.3.7.4.2 Japan Predictive Analytics In Supply Chain Market by Deployment Model
11.3.7.4.3 Japan Predictive Analytics In Supply Chain Market by Enterprise Size
11.3.7.4.4 Japan Predictive Analytics In Supply Chain Market by Industry Vertical
11.3.7.5 South Korea Predictive Analytics In Supply Chain Market
11.3.7.5.1 South Korea Predictive Analytics In Supply Chain Market by Component
11.3.7.5.2 South Korea Predictive Analytics In Supply Chain Market by Deployment Model
11.3.7.5.3 South Korea Predictive Analytics In Supply Chain Market by Enterprise Size
11.3.7.5.4 South Korea Predictive Analytics In Supply Chain Market by Industry Vertical
11.3.7.6 Rest of Asia-Pacific Predictive Analytics In Supply Chain Market
11.3.7.6.1 Rest of Asia-Pacific Predictive Analytics In Supply Chain Market by Component
11.3.7.6.2 Rest of Asia-Pacific Predictive Analytics In Supply Chain Market by Deployment Model
11.3.7.6.3 Rest of Asia-Pacific Predictive Analytics In Supply Chain Market by Enterprise Size
11.3.7.6.4 Rest of Asia-Pacific Predictive Analytics In Supply Chain Market by Industry Vertical
11.4. MIDDLE EAST AND AFRICA
11.4.1 Middle East and Africa Predictive Analytics In Supply Chain Market Overview
11.4.2 Middle East and Africa Predictive Analytics In Supply Chain Market Forecasts and Analysis
11.4.3 Middle East and Africa Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Component
11.4.4 Middle East and Africa Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Deployment Model
11.4.5 Middle East and Africa Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Enterprise Size
11.4.6 Middle East and Africa Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Industry Vertical
11.4.7 Middle East and Africa Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Countries
11.4.7.1 South Africa Predictive Analytics In Supply Chain Market
11.4.7.1.1 South Africa Predictive Analytics In Supply Chain Market by Component
11.4.7.1.2 South Africa Predictive Analytics In Supply Chain Market by Deployment Model
11.4.7.1.3 South Africa Predictive Analytics In Supply Chain Market by Enterprise Size
11.4.7.1.4 South Africa Predictive Analytics In Supply Chain Market by Industry Vertical
11.4.7.2 Saudi Arabia Predictive Analytics In Supply Chain Market
11.4.7.2.1 Saudi Arabia Predictive Analytics In Supply Chain Market by Component
11.4.7.2.2 Saudi Arabia Predictive Analytics In Supply Chain Market by Deployment Model
11.4.7.2.3 Saudi Arabia Predictive Analytics In Supply Chain Market by Enterprise Size
11.4.7.2.4 Saudi Arabia Predictive Analytics In Supply Chain Market by Industry Vertical
11.4.7.3 U.A.E Predictive Analytics In Supply Chain Market
11.4.7.3.1 U.A.E Predictive Analytics In Supply Chain Market by Component
11.4.7.3.2 U.A.E Predictive Analytics In Supply Chain Market by Deployment Model
11.4.7.3.3 U.A.E Predictive Analytics In Supply Chain Market by Enterprise Size
11.4.7.3.4 U.A.E Predictive Analytics In Supply Chain Market by Industry Vertical
11.4.7.4 Rest of Middle East and Africa Predictive Analytics In Supply Chain Market
11.4.7.4.1 Rest of Middle East and Africa Predictive Analytics In Supply Chain Market by Component
11.4.7.4.2 Rest of Middle East and Africa Predictive Analytics In Supply Chain Market by Deployment Model
11.4.7.4.3 Rest of Middle East and Africa Predictive Analytics In Supply Chain Market by Enterprise Size
11.4.7.4.4 Rest of Middle East and Africa Predictive Analytics In Supply Chain Market by Industry Vertical
11.5. SOUTH AND CENTRAL AMERICA
11.5.1 South and Central America Predictive Analytics In Supply Chain Market Overview
11.5.2 South and Central America Predictive Analytics In Supply Chain Market Forecasts and Analysis
11.5.3 South and Central America Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Component
11.5.4 South and Central America Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Deployment Model
11.5.5 South and Central America Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Enterprise Size
11.5.6 South and Central America Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Industry Vertical
11.5.7 South and Central America Predictive Analytics In Supply Chain Market Forecasts and Analysis - By Countries
11.5.7.1 Brazil Predictive Analytics In Supply Chain Market
11.5.7.1.1 Brazil Predictive Analytics In Supply Chain Market by Component
11.5.7.1.2 Brazil Predictive Analytics In Supply Chain Market by Deployment Model
11.5.7.1.3 Brazil Predictive Analytics In Supply Chain Market by Enterprise Size
11.5.7.1.4 Brazil Predictive Analytics In Supply Chain Market by Industry Vertical
11.5.7.2 Argentina Predictive Analytics In Supply Chain Market
11.5.7.2.1 Argentina Predictive Analytics In Supply Chain Market by Component
11.5.7.2.2 Argentina Predictive Analytics In Supply Chain Market by Deployment Model
11.5.7.2.3 Argentina Predictive Analytics In Supply Chain Market by Enterprise Size
11.5.7.2.4 Argentina Predictive Analytics In Supply Chain Market by Industry Vertical
11.5.7.3 Rest of South and Central America Predictive Analytics In Supply Chain Market
11.5.7.3.1 Rest of South and Central America Predictive Analytics In Supply Chain Market by Component
11.5.7.3.2 Rest of South and Central America Predictive Analytics In Supply Chain Market by Deployment Model
11.5.7.3.3 Rest of South and Central America Predictive Analytics In Supply Chain Market by Enterprise Size
11.5.7.3.4 Rest of South and Central America Predictive Analytics In Supply Chain Market by Industry Vertical

12. INDUSTRY LANDSCAPE
12.1. MERGERS AND ACQUISITIONS
12.2. AGREEMENTS, COLLABORATIONS AND JOIN VENTURES
12.3. NEW PRODUCT LAUNCHES
12.4. EXPANSIONS AND OTHER STRATEGIC DEVELOPMENTS

13. PREDICTIVE ANALYTICS IN SUPPLY CHAIN MARKET, KEY COMPANY PROFILES
13.1. IBM CORPORATION
13.1.1. Key Facts
13.1.2. Business Description
13.1.3. Products and Services
13.1.4. Financial Overview
13.1.5. SWOT Analysis
13.1.6. Key Developments
13.2. INFOR
13.2.1. Key Facts
13.2.2. Business Description
13.2.3. Products and Services
13.2.4. Financial Overview
13.2.5. SWOT Analysis
13.2.6. Key Developments
13.3. JDA SOFTWARE
13.3.1. Key Facts
13.3.2. Business Description
13.3.3. Products and Services
13.3.4. Financial Overview
13.3.5. SWOT Analysis
13.3.6. Key Developments
13.4. ORACLE CORPORATION
13.4.1. Key Facts
13.4.2. Business Description
13.4.3. Products and Services
13.4.4. Financial Overview
13.4.5. SWOT Analysis
13.4.6. Key Developments
13.5. ROSSLYN ANALYTICS
13.5.1. Key Facts
13.5.2. Business Description
13.5.3. Products and Services
13.5.4. Financial Overview
13.5.5. SWOT Analysis
13.5.6. Key Developments
13.6. SAP SE
13.6.1. Key Facts
13.6.2. Business Description
13.6.3. Products and Services
13.6.4. Financial Overview
13.6.5. SWOT Analysis
13.6.6. Key Developments
13.7. SAS INSTITUTE INC.
13.7.1. Key Facts
13.7.2. Business Description
13.7.3. Products and Services
13.7.4. Financial Overview
13.7.5. SWOT Analysis
13.7.6. Key Developments
13.8. SYNCRON AB
13.8.1. Key Facts
13.8.2. Business Description
13.8.3. Products and Services
13.8.4. Financial Overview
13.8.5. SWOT Analysis
13.8.6. Key Developments
13.9. TABLEAU SOFTWARE, INC.
13.9.1. Key Facts
13.9.2. Business Description
13.9.3. Products and Services
13.9.4. Financial Overview
13.9.5. SWOT Analysis
13.9.6. Key Developments
13.10. TIBCO SOFTWARE, INC.
13.10.1. Key Facts
13.10.2. Business Description
13.10.3. Products and Services
13.10.4. Financial Overview
13.10.5. SWOT Analysis
13.10.6. Key Developments

14. APPENDIX
14.1. ABOUT THE INSIGHT PARTNERS
14.2. GLOSSARY OF TERMS
The List of Companies

1. IBM Corporation
2. Infor
3. JDA Software
4. Oracle Corporation
5. Rosslyn Analytics
6. SAP SE
7. SAS Institute Inc.
8. Syncron AB
9. Tableau Software, Inc.
10. Tibco Software, Inc.

The Insight Partners performs research in 4 major stages: Data Collection & Secondary Research, Primary Research, Data Analysis and Data Triangulation & Final Review.

  1. Data Collection and Secondary Research:

As a market research and consulting firm operating from a decade, we have published many reports and advised several clients across the globe. First step for any study will start with an assessment of currently available data and insights from existing reports. Further, historical and current market information is collected from Investor Presentations, Annual Reports, SEC Filings, etc., and other information related to company’s performance and market positioning are gathered from Paid Databases (Factiva, Hoovers, and Reuters) and various other publications available in public domain.

Several associations trade associates, technical forums, institutes, societies and organizations are accessed to gain technical as well as market related insights through their publications such as research papers, blogs and press releases related to the studies are referred to get cues about the market. Further, white papers, journals, magazines, and other news articles published in the last 3 years are scrutinized and analyzed to understand the current market trends.

  1. Primary Research:

The primarily interview analysis comprise of data obtained from industry participants interview and answers to survey questions gathered by in-house primary team.

For primary research, interviews are conducted with industry experts/CEOs/Marketing Managers/Sales Managers/VPs/Subject Matter Experts from both demand and supply side to get a 360-degree view of the market. The primary team conducts several interviews based on the complexity of the markets to understand the various market trends and dynamics which makes research more credible and precise.

A typical research interview fulfils the following functions:

  • Provides first-hand information on the market size, market trends, growth trends, competitive landscape, and outlook
  • Validates and strengthens in-house secondary research findings
  • Develops the analysis team’s expertise and market understanding

Primary research involves email interactions and telephone interviews for each market, category, segment, and sub-segment across geographies. The participants who typically take part in such a process include, but are not limited to:

  • Industry participants: VPs, business development managers, market intelligence managers and national sales managers
  • Outside experts: Valuation experts, research analysts and key opinion leaders specializing in the electronics and semiconductor industry.

Below is the breakup of our primary respondents by company, designation, and region:

Research Methodology

Once we receive the confirmation from primary research sources or primary respondents, we finalize the base year market estimation and forecast the data as per the macroeconomic and microeconomic factors assessed during data collection.

  1. Data Analysis:

Once data is validated through both secondary as well as primary respondents, we finalize the market estimations by hypothesis formulation and factor analysis at regional and country level.

  • 3.1 Macro-Economic Factor Analysis:

We analyse macroeconomic indicators such the gross domestic product (GDP), increase in the demand for goods and services across industries, technological advancement, regional economic growth, governmental policies, the influence of COVID-19, PEST analysis, and other aspects. This analysis aids in setting benchmarks for various nations/regions and approximating market splits. Additionally, the general trend of the aforementioned components aid in determining the market's development possibilities.

  • 3.2 Country Level Data:

Various factors that are especially aligned to the country are taken into account to determine the market size for a certain area and country, including the presence of vendors, such as headquarters and offices, the country's GDP, demand patterns, and industry growth. To comprehend the market dynamics for the nation, a number of growth variables, inhibitors, application areas, and current market trends are researched. The aforementioned elements aid in determining the country's overall market's growth potential.

  • 3.3 Company Profile:

The “Table of Contents” is formulated by listing and analyzing more than 25 - 30 companies operating in the market ecosystem across geographies. However, we profile only 10 companies as a standard practice in our syndicate reports. These 10 companies comprise leading, emerging, and regional players. Nonetheless, our analysis is not restricted to the 10 listed companies, we also analyze other companies present in the market to develop a holistic view and understand the prevailing trends. The “Company Profiles” section in the report covers key facts, business description, products & services, financial information, SWOT analysis, and key developments. The financial information presented is extracted from the annual reports and official documents of the publicly listed companies. Upon collecting the information for the sections of respective companies, we verify them via various primary sources and then compile the data in respective company profiles. The company level information helps us in deriving the base number as well as in forecasting the market size.

  • 3.4 Developing Base Number:

Aggregation of sales statistics (2020-2022) and macro-economic factor, and other secondary and primary research insights are utilized to arrive at base number and related market shares for 2022. The data gaps are identified in this step and relevant market data is analyzed, collected from paid primary interviews or databases. On finalizing the base year market size, forecasts are developed on the basis of macro-economic, industry and market growth factors and company level analysis.

  1. Data Triangulation and Final Review:

The market findings and base year market size calculations are validated from supply as well as demand side. Demand side validations are based on macro-economic factor analysis and benchmarks for respective regions and countries. In case of supply side validations, revenues of major companies are estimated (in case not available) based on industry benchmark, approximate number of employees, product portfolio, and primary interviews revenues are gathered. Further revenue from target product/service segment is assessed to avoid overshooting of market statistics. In case of heavy deviations between supply and demand side values, all thes steps are repeated to achieve synchronization.

We follow an iterative model, wherein we share our research findings with Subject Matter Experts (SME’s) and Key Opinion Leaders (KOLs) until consensus view of the market is not formulated – this model negates any drastic deviation in the opinions of experts. Only validated and universally acceptable research findings are quoted in our reports.

We have important check points that we use to validate our research findings – which we call – data triangulation, where we validate the information, we generate from secondary sources with primary interviews and then we re-validate with our internal data bases and Subject matter experts. This comprehensive model enables us to deliver high quality, reliable data in shortest possible time.

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