The Eora global supply chain database consists of a multi-region input-output table (MRIO) model that provides a time series of high-resolution IO tables with matching environmental and social satellite accounts for 190 countries.

Sample purchasing data containing information on suppliers, the products they provide, and the projects those products are used for. Data created or adapted from publicly available sources.

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Supply Chain Analytics Market Size 2024-2028

The supply chain analytics market size is forecast to increase by USD 10.38 billion at a CAGR of 19.28% between 2023 and 2028.

The market is experiencing significant growth due to the increasing need to optimize business processes and enhance operational efficiency. A key driver is the increased adoption of predictive analytics in the supply chain, enabling organizations to anticipate demand and proactively manage inventory. However, challenges persist in implementing supply chain analytics, including data integration and security concerns. In the context of e-commerce and fleet management, real-time data analysis is crucial for effective order fulfillment and fleet optimization. Market trends include the integration of machine learning algorithms and the use of cloud-based solutions for data processing and storage. Overall, the market presents opportunities for businesses to gain a competitive edge through data-driven insights and improved decision-making.

What will be the Size of the Supply Chain Analytics Market During the Forecast Period?

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The global supply chain management software market is experiencing significant growth due to the increasing digitization of business operations and the demand for customized solutions. Logistics optimization, cost optimization, and network design are key focus areas, with businesses seeking cost-efficient solutions to enhance their supply chain performance. Automation plays a crucial role in improving efficiency and enabling data-driven decision-making, while customer loyalty and strategy are also driving market growth.
Traceability, finance, and performance metrics are essential elements of supply chain analytics, providing valuable insights into inventory transactions, transportation management, and warehouse management. Cost reduction is a primary objective, with companies addressing security breaches and disruptions through consulting services and innovation. Sustainability, demand planning, and resilience are emerging trends, with a focus on cost savings, management software, and optimization. Procurement optimization, training, logistics management, and CRM systems are also integral to the market's development.

How is this Supply Chain Analytics Industry segmented and which is the largest segment?

The industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Deployment

  Cloud-based
  On-premises


End-user

  Retail
  Manufacturing
  Transportation
  Healthcare
  Others


Geography

  North America

    US


  Europe

    Germany
    UK
    France


  APAC

    China


  Middle East and Africa



  South America

By Deployment Insights

The cloud-based segment is estimated to witness significant growth during the forecast period.

Cloud-based supply chain analytics enables organizations to adapt to their expanding analytics requirements and data volumes through on-demand resources. Eliminating the need for significant upfront investments in hardware and infrastructure, cloud solutions offer a pay-as-you-go model, ensuring cost savings and predictable budgeting. Remote access to analytics tools and data fosters collaboration among stakeholders, enhancing communication and informed decision-making. Real-time data analysis facilitates timely responses to supply chain challenges, such as elevated warehousing costs, data loss, demand-supply gaps, and customer requirements. Cloud-based analytics optimizes resource utilization, business growth, and performance, addressing inventory risks, procurement transactions, and retail trends.

Additionally, it integrates with ERP systems, warehouse management systems, SCM strategies, procurement analytics, artificial intelligence, and big data technologies to improve business productivity, efficiency, and manufacturing processes. Cloud solutions address waste minimization, economic viability, and unethical activities, ensuring accountability for large enterprises.

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The Cloud-based segment was valued at USD 2.47 billion in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 38% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The North American market is projected to expand due to the region's technological advancements and complex business environments. Advanced analytics technologies, such as arti

The asset contains commodity shipment data describing all anti-retroviral and rapid test kit shipments into PEPFAR countries. Included are SCMS’ transactions, not all purchases made under PEPFAR. The data are not intended to determine lead times or total landed cost because a single order may have different freight costs, points of origin, or delivery dates (e.g., emergency orders). Not all orders include cost of freight and/or insurance. None of the data include costs of customs clearance, security, or in-country distribution costs. See more information in the “Data Dictionary”.

This dataset provides supply chain health commodiy shipment and pricing data. Specifically, the data set identifies Antiretroviral (ARV) and HIV lab shipments to supported countries. In addition, the data set provides the commodity pricing and associated supply chain expenses necessary to move th ecommodities to countries for use.

Success.ai’s Supply Chain Data for Business Supplies & Equipment Professionals Worldwide offers a comprehensive dataset designed to help businesses connect with key stakeholders in the global supply chain and business equipment sectors. Covering procurement managers, operations directors, and supply chain professionals, this dataset provides verified contact details, business registration insights, and firmographic data.

With access to over 700 million verified global profiles and data from 70 million businesses, Success.ai ensures your outreach, market analysis, and business development strategies are powered by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution supports your efforts to thrive in the dynamic global supply chain industry.

Why Choose Success.ai’s Supply Chain Data?

1. Verified Contact Data for Supply Chain Professionals

   • Access verified work emails, phone numbers, and LinkedIn profiles of procurement officers, logistics managers, and supply chain strategists.
   • AI-driven validation ensures 99% accuracy, enabling confident communication and effective campaign execution.

2. Comprehensive Global Coverage

   • Includes profiles from global supply chain hubs and business equipment companies in regions such as North America, Europe, Asia-Pacific, and the Middle East.
   • Gain insights into regional supply chain trends, operational challenges, and emerging opportunities.

3. Continuously Updated Datasets

   • Real-time updates reflect changes in leadership, business registrations, and supply chain dynamics.
   • Stay aligned with industry shifts and evolving market conditions.

4. Ethical and Compliant

   • Adheres to GDPR, CCPA, and other global privacy regulations, ensuring responsible data usage and compliance with legal standards.

Data Highlights:

• 700M+ Verified Global Profiles: Connect with decision-makers, operations leaders, and supply chain professionals worldwide.
• 70M Business Profiles: Access firmographic data, including business sizes, locations, and operational scopes.
• Business Registration Insights: Gain visibility into company registrations, certifications, and compliance statuses.
• Leadership Profiles: Engage with CEOs, supply chain directors, and procurement leads driving global supply chain strategies.

Key Features of the Dataset:

1. Decision-Maker Profiles in Supply Chain and Equipment

   • Identify and connect with professionals managing procurement, logistics, and operational efficiency.
   • Target individuals responsible for vendor selection, inventory management, and supply chain optimization.

2. Advanced Filters for Precision Targeting

   • Filter companies by industry focus (logistics, manufacturing, retail), geographic location, revenue size, or operational scope.
   • Tailor outreach campaigns to align with specific supply chain needs and business challenges.

3. Business Registration and Compliance Insights

   • Access verified company registration data, certifications, and compliance statuses to ensure reliable business partnerships.
   • Leverage these insights to evaluate potential partners and streamline risk management.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data enable personalized messaging, highlight unique value propositions, and improve engagement outcomes with supply chain stakeholders.

Strategic Use Cases:

1. Sales and Vendor Development

   • Offer business supplies, equipment, or technology solutions to procurement teams and supply chain managers.
   • Build relationships with companies seeking innovative tools to improve efficiency, reduce costs, or enhance sustainability.

2. Market Research and Competitive Analysis

   • Analyze global trends in supply chain operations and equipment usage to guide product development and market strategies.
   • Benchmark against competitors to identify growth opportunities, market gaps, and new industry niches.

3. Supply Chain Optimization and Risk Mitigation

   • Connect with logistics managers and operations leaders looking to streamline processes or mitigate supply chain risks.
   • Provide solutions for inventory management, logistics optimization, or compliance reporting.

4. Recruitment and Workforce Solutions

   • Engage HR professionals and hiring managers seeking skilled professionals in supply chain management or business operations.
   • Offer workforce optimization platforms, training solutions, or staffing services tailored to the supply chain industry.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality supply chain data at competitive prices, ensuring strong ROI for your marketing, sales, and strategic initiatives.

2. Seamless Integration

   • Integrate verified supply chain data into CRM systems, marketing platforms, or analytics tools via APIs o...

A DataSet of Supply Chains used by the company DataCo Global was used for the analysis. Dataset of Supply Chain , which allows the use of Machine Learning Algorithms and R Software. Areas of important registered activities : Provisioning , Production , Sales , Commercial Distribution.It also allows the correlation of Structured Data with Unstructured Data for knowledge generation.

Type Data : Structured Data : DataCoSupplyChainDataset.csv Unstructured Data : tokenized_access_logs.csv (Clickstream)

Types of Products : Clothing , Sports , and Electronic Supplies

Additionally it is attached in another file called DescriptionDataCoSupplyChain.csv, the description of each of the variables of the DataCoSupplyChainDatasetc.csv.

This statistic shows the results of a global logistics survey conducted between spring and summer of 2016, asking shippers about the most important factors in big data management in the supply chain. According to some 52 percent of the respondents, big data is valuable in improving process quality and performance.

Dataset containing detailed information about all health commodity orders delivered through the USAID Global Health Supply Chain Program - Procurement and Supply Management (GHSC-PSM) project. This includes orders funded through PEPFAR, PMI, family planning / reproductive health, maternal and child health, COVID-19, and other USAID and USG programs.

Global Value Chains (GVC's) data from World Bank's WDR 2020 data

This statistic represents the results of a global logistics survey conducted between spring and summer of 2016, asking third party providers about what services their customers find more important in big data management in the supply chain. According to some 70 percent of the respondents, improving logistics optimization was among the most important factors for 3PLs' customers during that time period.

The company which provided the dataset is the world leader in manufacturing of construction and mining equipment, diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. The current revenue of the company is estimated to be on the order of tens of billions and they sell products and parts via a worldwide dealer network. The company sells more than 3 million products and 700,000 parts in more than 20 countries around the world every year. They operate with more than 3,000 suppliers and 3,000 dealerships and their logistics operations alone are worth more than 60 million dollars per year. The dataset provided is one example of supply chain problem for one product of the company - a medium size excavator. In the current dataset, the number of dealers, production facilities and shipping ports is the same as in the original problem; it is only the demand figures, the production capacities, the transportation times and costs and the sale prices that have been randomly generated. The figures have been randomly generated in an interval between 0 and an upper limit which is a random increase over the maximum value in the original data, according to a negative exponential distribution.

In 2023, there were 242 claimed supply chain attacks in the United States. This is the highest reported number since 2017. Overall, supply chain attacks saw a year-over-year increase of 115 percent between 2022 and 2023.

This dataset provides values for SUPPLY CHAIN PRESSURE INDEX reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This private company dataset provides an in-depth view of any specific company’s truck-based supply chain and its relationships with other facilities and companies within the continental US.

Also, using robust supply chain data you will be able to map US facilities (including factories, warehouses, and retail outlets).

With this private company dataset, it is possible to track the movement of trucks and devices between locations to identify supply chain connections and company data insights.

Our Machine learning algorithms ingest 7-15bn daily events to estimate the volume of goods transported between locations. Consequently, we can map supply chain connections between:

•Different companies (expressed as a percentage of volume transported).

•Locations owned by the same company (e.g. warehouse to shop).

With this novel geolocation approach, it is possible to "draw" a knowledge graph of any private or public company´s relations with other companies within the country.

This solution, in the form of a dataset, provides an in-depth view of any specific company’s truck-based supply chain and its relationships with other facilities and companies within the continental United States.

Use cases:

• Identification and understanding of relations company-to-company: It helps to identify and infer relationships and connections between specific companies or facilities and between sectors/industries.

• Identification and understanding of relations place-to-place: A logistics and domestic distribution supply chain can be mapped, both nationwide and state-wide in the US, and across countries in Europe.

• Visualization and mapping of an entire supply chain network.

• Tracking of products in any distribution or supply chain.

• Risk assessment

• Correlation analysis.

• Disruption analysis.

• Analysis of illicit networks and tracking of illegal use of corporate assets.

• Improvement of casualty risk management.

• Optimization of supply chain risk management.

• Security and compliance.

• Identification of not only the first tier of suppliers in the value chain, but also 2nd and 3rd tier suppliers, and more.

Current largest use case: global corporation using it to model risk at a facility level (+100,000 locations).

Why should you trust PREDIK Data-Driven? In 2023, we were listed as Datarade's top providers. Why? Our solutions for private company data, supply chain data, and B2B data adapt according to the specific needs of companies. Also, PREDIK methodology focuses on the client and the necessary elements for the success of their projects.

This statistic shows the supply chain intelligence efficiency benefits as a result of Big Data in the United Kingdom (UK) from 2015 to 2020, by industry. It was estimated that the manufacturing sector would receive the largest benefits. Professional services were ranked second with estimated benefits of roughly 3.5 billion British pounds.

Supply Chain Management (SCM) Market size was valued at USD 35.74 Billion in 2024 and is projected to reach USD 78.42 Billion by 2031, growing at a CAGR of 10.32% during the forecast period 2024-2031.

Global Supply Chain Management (SCM) Market Drivers

The market drivers for the Supply Chain Management (SCM) Market can be influenced by various factors. These may include:

Globalization and International Trade: The demand for reliable supply chain management (SCM) solutions is driven by the growth of international trade and the rising globalization of supply chains. Efficient supply chain management systems are necessary for businesses that operate in numerous countries in order to manage inventories, optimize logistics, and coordinate activities across intricate worldwide networks.

E-commerce and Omnichannel Retailing: In order to satisfy customer needs for quick, dependable, and seamless order fulfillment, agile and flexible SCM solutions are required given the explosive expansion of e-commerce platforms and omnichannel retailing models. Retailers, manufacturers, and logistics companies can improve customer happiness, control inventory levels, and streamline supply chain procedures with the use of SCM software.

Demand for Real-time Transparency and Visibility: Those involved in supply chains want to be able to see real-time information on order fulfillment procedures, shipment status, and inventory levels. SCM technologies provide for end-to-end visibility, traceability, and data-driven decision-making throughout the whole supply chain ecosystem. Examples of these technologies include blockchain, Internet of Things (IoT), and RFID tracking.

Emphasis on Cost Optimization and Efficiency: Through efficient SCM procedures, companies aim to minimize operational inefficiencies, maximize supply chain expenses, and boost profitability. In order to achieve cost savings and operational efficiency, SCM solutions assist businesses in minimizing the costs associated with maintaining inventory, cutting down on transportation costs, and optimizing production scheduling.

Risk Mitigation and Resilience Planning: Demand for Supply Chain Management (SCM) solutions that improve risk mitigation and resilience planning is driven by heightened awareness of supply chain risks, interruptions, and vulnerabilities. In order to lessen the effects of interruptions like natural disasters, geopolitical crises, and supply chain disruptions, supply chain management software (SCM) offers proactive risk identification, scenario analysis, and contingency planning.

Stressing Corporate Social Responsibility (CSR) and Sustainability: Increasing focus on CSR, ethical sourcing, and sustainability affects supply chain management techniques and tactics. Supply chain visibility, compliance monitoring, and sustainability reporting are made possible by SCM systems, which also support ethical procurement, environmental stewardship, and sustainable sourcing.

Technological Development and Digital Transformation: Digital transformation efforts in supply chain management are propelled by the quick developments in artificial intelligence (AI), machine learning (ML), and big data analytics. In order to optimize supply chain operations, increase forecast accuracy, and strengthen decision-making capabilities, advanced SCM platforms make use of AI-driven insights, predictive analytics, and prescriptive optimization algorithms.
Trade rules and regulatory compliance: Supply chain management faces difficulties in adhering to industry standards, trade regulations, and regulatory obligations. SCM solutions assist businesses in navigating complicated regulatory environments, guaranteeing adherence to trade agreements, tariffs, and customs laws, and reducing the risk of supply chain disruptions and noncompliance.

Customer Experience and Service Level Expectations: Agile and responsive supply chains are required to meet the growing demands of customers for prompt delivery, customized experiences, and smooth order fulfillment. Through effective supply chain management, SCM solutions help businesses achieve customer service level agreements (SLAs), accurately and promptly fulfill orders, and improve the entire customer experience.

Partnerships and Collaboration in Supply Chain Networks: To maximize the performance and agility of the supply chain, partnerships and collaboration are crucial between suppliers, manufacturers, distributors, and logistics companies. Supply chain visibility, responsiveness, and resilience can be increased by trading partners working together, exchanging information, and coordinating activities through SCM systems.

A 2018 survey found that the biggest challenge for global supply chain executives was visibility, with 21.8 percent of respondents selecting this response. Fluctuating customer demand was second, with 19.7 percent, while data management was lowest with 1.3 percent. Visibility The nature of the challenges generated by visibility differs depending on whether a company is a producer or a supplier of goods. Producers were most concerned with having oversight on how materials were provisioned to their production facilities, while suppliers were concerned with visibility over the quality and availability of the products they intend to sell. Both producers and suppliers though were concerned with being able to trace the flow of materials and/or goods through their supply chain process. Supply chain management Given the concerns producers and suppliers have over visibility, supply chain management (SCM) software has been a growing industry over the last decade. One sub-segment of this industry expected to see very strong growth is supply chain analytics, whereby the data captured in a SCM system is used in more sophisticated ways (for example, to identifying the main causes and predict the risk of supply chain disruptions). A 2016 survey found that advanced analytics was the technology manufacturing executives expected to impact their supply chain the most, while some analysts expect the size of the supply chain analytic market to almost double between 2018 and 2023.

The supply chain analysis market size is predicted to reach $7.68 billion in 2024 to $47.96 billion by 2035, growing at a CAGR of 18.12% from 2024 to 2035.

United States SBP: LA: Experienced Supply Chain Disruptions data was reported at 3.300 % in 20 Sep 2020. This records a decrease from the previous number of 4.900 % for 13 Sep 2020. United States SBP: LA: Experienced Supply Chain Disruptions data is updated weekly, averaging 30.050 % from Apr 2020 (Median) to 20 Sep 2020, with 14 observations. The data reached an all-time high of 51.000 % in 26 Apr 2020 and a record low of 3.300 % in 20 Sep 2020. United States SBP: LA: Experienced Supply Chain Disruptions data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S042: Small Business Pulse Survey: by State: South Region: Weekly, Beg Sunday (Discontinued).