Supply Chain Analytics Market

Supply Chain Analytics Market By Deployment (On-premise, Cloud-based); By Enterprise Type (Small and Medium Enterprises (SMEs), Large Enterprises); By Application (Demand Planning, Inventory Analytics, Procurement Analytics, Logistics Analytics, Others); By Industry (Healthcare, Retail & E-commerce, Transportation & Logistics, Automotive, Manufacturing, Oil & Gas, Chemical, Others) – Growth, Share, Opportunities & Competitive Analysis, 2024 – 2032

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Published: | Report ID: 10136 | Report Format : Excel, PDF
REPORT ATTRIBUTE DETAILS
Historical Period  2019-2022
Base Year  2023
Forecast Period  2024-2032
Supply Chain Analytics Market Size 2024  USD 6,125 Million
Supply Chain Analytics Market, CAGR  17.7%
Supply Chain Analytics Market Size 2032  USD 22,558.8 Million

Market Overview

The global Supply Chain Analytics Market is projected to grow from USD 6,125 million in 2024 to USD 22,558.8 million by 2032, registering a robust CAGR of 17.7% during the forecast period.

The supply chain analytics market is driven by the increasing adoption of data-driven decision-making to optimize operations, reduce costs, and enhance efficiency. Rising e-commerce activities and globalization have intensified the need for real-time visibility and predictive analytics in supply chain management. Technological advancements, including AI, machine learning, and IoT, further boost the integration of advanced analytics tools. Additionally, the growing emphasis on sustainability and compliance with regulatory frameworks encourages businesses to leverage analytics for environmental and operational efficiency. The demand for supply chain resilience and risk management strategies amid market uncertainties also fuels the adoption of analytics solutions globally.

The geographical landscape of the supply chain analytics market highlights North America and Asia-Pacific as leading regions due to advanced technological adoption and rapid industrial growth. North America benefits from its strong technological infrastructure and early adoption of AI and IoT, enhancing supply chain operations. Meanwhile, Asia-Pacific’s dynamic manufacturing and e-commerce sectors drive demand for analytics to optimize logistics and inventory management. Key players in this market include IBM Corporation, Oracle Corporation, SAP SE, Accenture, and SAS Institute Inc., which offer innovative analytics solutions. These companies are pivotal in shaping the global market through advanced tools and strategic partnerships.

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Market Drivers

E-Commerce Boom and Complex Supply Chains

The surge in e-commerce has transformed consumer expectations, demanding faster delivery and access to a broader product range. For instance, a significant logistics provider has reported handling over 2 billion parcels since its inception, demonstrating the scale of e-commerce operations. This growth has led to increasingly complex supply chains, involving multiple vendors and logistics partners that require seamless coordination. Supply chain analytics plays a vital role in addressing these challenges by enhancing visibility, streamlining operations, and enabling efficient inventory management to meet customer demands. With the e-commerce landscape continuously evolving, businesses are leveraging advanced analytics to maintain a competitive edge and ensure operational efficiency in their supply chain networks.

Disruptions and the Need for Resilience

Global events such as the COVID-19 pandemic, geopolitical tensions, and natural disasters have exposed vulnerabilities in supply chains, emphasizing the need for resilience. For instance, a Deloitte report highlights that 73% of respondents either have or will implement dual or multi-sourcing strategies to enhance supply chain resilience. Businesses are adopting analytics-driven solutions to anticipate and mitigate potential disruptions, enabling continuity and adaptability in operations. By integrating predictive analytics, organizations can identify risks, optimize contingency plans, and build supply chains capable of withstanding uncertainties. This focus on resilience ensures uninterrupted service delivery and strengthens customer trust amid a volatile market environment.

Data Explosion and Customer-Centric Strategies

The proliferation of technologies such as IoT has generated an unprecedented amount of real-time data, offering actionable insights into supply chain performance. Advanced analytics techniques process this data to improve decision-making, enhance operational efficiency, and identify cost-saving opportunities. Simultaneously, growing customer expectations for personalized experiences and real-time order tracking drive businesses to adopt supply chain analytics for better visibility and improved service delivery. By aligning operations with customer demands, organizations can foster loyalty and gain a competitive advantage.

Sustainability and Compliance Focus

Increasing consumer and regulatory emphasis on sustainability has encouraged businesses to adopt eco-friendly practices, such as reducing waste and minimizing carbon emissions. Supply chain analytics supports these initiatives by identifying areas for improvement and tracking progress toward sustainability goals. Additionally, businesses must navigate complex regulatory environments, including customs and environmental compliance. Analytics solutions enable risk management by ensuring adherence to regulations, mitigating potential liabilities, and fostering long-term operational sustainability.

Market Trends

Advanced Technologies Driving Supply Chain Innovation

The integration of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) is revolutionizing supply chain operations. AI and ML algorithms enable predictive analytics to forecast demand fluctuations and identify potential disruptions, while prescriptive analytics recommends optimal strategies to enhance supply chain efficiency. For instance, companies like Ocado use sophisticated AI and ML algorithms to predict demand, optimize stock levels, and manage logistics operations, significantly reducing order fulfillment times. These technologies also automate routine tasks, such as inventory management and demand forecasting, allowing teams to focus on strategic priorities. Similarly, IoT devices deliver real-time data on goods’ location and condition, improving visibility and control. IoT-powered predictive maintenance solutions further minimize downtime by identifying potential equipment failures early, reducing maintenance costs and enhancing reliability. These technologies collectively empower businesses to make informed decisions and maintain resilience in an increasingly dynamic market landscape.

Blockchain, Cloud, and Sustainability Shaping the Future

Blockchain and cloud-based solutions are transforming supply chain operations through enhanced security, scalability, and cost-efficiency. Blockchain technology ensures data integrity and transparency by tracking the origin and journey of products, helping prevent fraud and ensuring compliance. Cloud-based solutions provide scalability to adapt to changing business needs, while their accessibility fosters collaboration and decision-making from remote locations. These systems are cost-effective, reducing upfront and maintenance expenses. Additionally, the growing focus on sustainability has prompted businesses to leverage supply chain analytics to identify areas to minimize waste, emissions, and energy use. Ethical sourcing and adherence to sustainable practices are increasingly supported by analytics tools, ensuring compliance with environmental regulations and fostering positive stakeholder relationships. This holistic adoption of advanced technologies and sustainable strategies is paving the way for more efficient, transparent, and eco-friendly supply chains.

Market Challenges Analysis

Data Complexity and Integration Challenges

Data-related challenges remain a significant hurdle in the adoption of supply chain analytics. Inconsistent data quality and varying formats can compromise the accuracy of insights, requiring extensive cleaning and normalization efforts that are both time-consuming and resource-intensive. For instance, a survey by the Ministry of Commerce revealed that over 60% of companies struggle with data integration from multiple sources, such as ERP, WMS, and TMS systems. Furthermore, integrating data from diverse systems such as Enterprise Resource Planning (ERP), Warehouse Management Systems (WMS), and Transportation Management Systems (TMS) presents complexities due to data silos and lack of standardization. These silos can limit the depth and scope of analysis, reducing the effectiveness of supply chain strategies. Protecting sensitive information, including customer data and proprietary business details, adds another layer of complexity, especially with stringent compliance requirements like GDPR and CCPA. Ensuring data security and adhering to privacy regulations demand robust frameworks, creating an ongoing challenge for businesses seeking to leverage analytics effectively.

Technological and Organizational Barriers

Implementing advanced supply chain analytics tools comes with technological and organizational challenges. These tools often require specialized skills and expertise, posing a steep learning curve for many users and limiting widespread adoption. As supply chains grow and data volumes increase, scalability becomes critical, particularly for smaller businesses that may lack the infrastructure to handle the workload. Real-time analytics, essential for timely decision-making, requires substantial computational power and efficient data processing, but latency issues can hinder its effectiveness. On an organizational level, resistance to change can slow the adoption of new technologies, requiring strong leadership and strategic change management to overcome. A shortage of skilled data scientists and analysts further complicates implementation efforts, highlighting the need for investment in training and workforce development. Additionally, fostering a culture that prioritizes data-driven decision-making is crucial but demands time and effort to align organizational values with analytics-driven objectives.

Market Segmentation Analysis:

By Deployment:

The deployment segment of the supply chain analytics market is bifurcated into on-premise and cloud-based solutions. On-premise solutions are preferred by enterprises prioritizing data security and control, particularly in industries dealing with sensitive or proprietary information. These solutions offer customization options and integration with existing systems but often require significant upfront investments in infrastructure and maintenance. In contrast, cloud-based solutions are gaining traction due to their scalability, cost-efficiency, and remote accessibility. Cloud deployments enable businesses to adapt to dynamic market conditions and handle growing data volumes with ease. Furthermore, the rise of Software-as-a-Service (SaaS) models has facilitated faster implementation and minimized operational disruptions. The growing preference for real-time analytics and collaborative tools has further fueled the adoption of cloud-based supply chain analytics, especially among businesses seeking agility and streamlined operations. As industries increasingly prioritize digital transformation, the cloud segment is poised to dominate, driven by advancements in security protocols and connectivity solutions.

By Enterprise Type:

The supply chain analytics market serves diverse organizational needs, segmented by small and medium enterprises (SMEs) and large enterprises. Large enterprises have been early adopters of advanced analytics, leveraging these tools to optimize complex supply chains, reduce costs, and enhance customer experiences. Their ability to invest in sophisticated analytics platforms and skilled personnel has driven substantial market demand. On the other hand, SMEs are gradually embracing supply chain analytics to remain competitive and enhance operational efficiency. Cloud-based solutions have played a crucial role in democratizing access to analytics for SMEs, offering cost-effective and scalable alternatives to on-premise systems. The rising awareness of analytics’ benefits, coupled with increasing competitive pressures, has spurred SMEs to adopt these tools for demand forecasting, inventory management, and procurement optimization. As digital transformation initiatives gain momentum, both segments are expected to witness robust growth, with tailored analytics solutions catering to their distinct operational complexities and budgetary constraints.

Segments:

Based on Deployment:

  • On-premise
  • Cloud-based

Based on Enterprise Type:

  • Small and Medium Enterprises (SMEs)
  • Large Enterprises

Based on Application:

  • Demand Planning
  • Inventory Analytics
  • Procurement Analytics
  • Logistics Analytics
  • Others

Based on Industry:

  • Healthcare
  • Retail & E-commerce
  • Transportation & Logistics
  • Automotive
  • Manufacturing
  • Oil & Gas
  • Chemical
  • Others

Based on the Geography:

  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • Germany
    • France
    • U.K.
    • Italy
    • Spain
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • South-east Asia
    • Rest of Asia Pacific
  • Latin America
    • Brazil
    • Argentina
    • Rest of Latin America
  • Middle East & Africa
    • GCC Countries
    • South Africa
    • Rest of the Middle East and Africa

Regional Analysis

North America

North America holds a commanding position in the global supply chain analytics market, accounting for approximately 35% of the market share. This dominance is fueled by the region’s robust technological infrastructure and early adoption of advanced analytics tools. Major industries, including retail, healthcare, and manufacturing, have integrated analytics solutions to enhance efficiency and gain a competitive edge. The presence of leading technology providers and the rapid deployment of cloud-based solutions contribute to market growth. Additionally, the region’s focus on innovation, such as the application of AI and IoT in supply chains, supports real-time decision-making and predictive analytics. Companies in North America are leveraging these technologies to streamline operations and address challenges posed by global disruptions. Government initiatives promoting digital transformation, coupled with stringent regulations around data security, further accelerate the adoption of supply chain analytics in the region. With a growing demand for sustainable practices, the integration of analytics to optimize energy consumption and reduce emissions is also gaining traction.

Asia-Pacific

The Asia-Pacific region is experiencing remarkable growth in the supply chain analytics market, with an estimated 28% market share. This growth is driven by rapid industrialization, expanding e-commerce activities, and increasing globalization of supply chains. Countries such as China, India, and Japan are at the forefront of adoption, leveraging analytics to enhance efficiency and manage the complexity of diverse supply chains. The region’s dynamic manufacturing sector heavily relies on analytics for demand planning, inventory optimization, and logistics management. Additionally, the growing popularity of cloud-based solutions has enabled small and medium enterprises to embrace analytics, overcoming traditional budgetary constraints. Asia-Pacific’s focus on digital transformation, supported by government initiatives and investments in smart technologies, has further propelled the market. The region also faces unique challenges, such as fragmented supply chains and varying regulatory requirements, driving the demand for solutions offering enhanced visibility and compliance. As industries prioritize resilience and adaptability, Asia-Pacific is poised to emerge as a significant contributor to the global market.

Key Player Analysis

  • IBM Corporation (U.S.)
  • Oracle Corporation (U.S.)
  • SAP SE (Germany)
  • Accenture (Ireland)
  • Manhattan Associates (U.S.)
  • SAS Institute Inc. (U.S.)
  • Sigmoid Analytics (U.S.)
  • Mecalux, S.A. (Spain)
  • Analytics8, LLC (U.S.)
  • SS Supply Chain Solutions Pvt. Ltd. (3SCSolutions) (Netherlands)

Competitive Analysis

The supply chain analytics market is marked by intense competition, with leading players leveraging advanced technologies to maintain their edge. Key players such as IBM Corporation, Oracle Corporation, SAP SE, Accenture, and SAS Institute Inc. focus on innovation, strategic collaborations, and acquisitions to expand their market presence. These companies offer a wide range of analytics solutions that integrate AI, IoT, and machine learning to enhance decision-making and optimize supply chain operations. Their commitment to cloud-based platforms and scalable solutions caters to both large enterprises and SMEs, ensuring accessibility and flexibility. Additionally, these players invest significantly in research and development to improve product capabilities and meet the evolving demands of diverse industries, including manufacturing, retail, and logistics. Their global reach and ability to adapt to regional market requirements have positioned them as dominant forces in driving the growth of the supply chain analytics market.

Recent Developments

  • In May 2023, SAP SE formed a partnership with Microsoft Corporation and developed an AI-powered solution named SAP Business AI, which helps customers expand their logistics capabilities to handle future supply chain difficulties.
  • In January 2023, Brain Corporation entered into a partnership with Google Cloud and developed “BrainOS Inventory Insights,” an analytics solution for retailers to deliver accurate inventory insights to improve the customer experience.
  • In January 2023, SAS entered into a partnership with Project44, a supply chain visibility platform provider, to reduce the disruptions impacting the customer experience by providing real-time visibility of the business operations.
  • In November 2022, 3SC, a SCA software provider, launched SCAI, a supply chain planning and execution platform for businesses to synchronize their supply chain of products and services. This SCAI solution is used to enhance business efficiency and to provide significant opportunities for enterprises to boost their revenue.
  • In May 2022, Moody’s Analytics, a financial analytical and intelligent tool provider, launched Supply Chain Catalyst, a data and analytics platform for identifying enterprises’ supply chain risks. This platform is used to manage disruptions by delivering a 360-degree view of suppliers across various financial and operational risk factors of the business.

Market Concentration & Characteristics

The supply chain analytics market exhibits moderate to high market concentration, characterized by the dominance of a few key players offering advanced solutions across industries. Established companies such as IBM Corporation, Oracle Corporation, and SAP SE lead the market, leveraging their extensive portfolios and technological expertise. The market’s competitive nature drives innovation, with players focusing on integrating AI, IoT, and real-time analytics into their solutions to enhance efficiency and visibility. The adoption of cloud-based platforms is a defining characteristic, enabling scalability and cost-effectiveness for businesses of all sizes. Smaller players contribute to market diversity by addressing niche requirements, particularly for SMEs. The market also reflects a customer-centric approach, emphasizing tailored solutions to meet unique supply chain challenges. As industries prioritize digital transformation and sustainability, the market continues to evolve, characterized by a blend of intense competition, technological advancements, and growing demand for data-driven decision-making.

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Report Coverage

The research report offers an in-depth analysis based on Deployment, Enterprise Type, Application, Industry and Geography. It details leading market players, providing an overview of their business, product offerings, investments, revenue streams, and key applications. Additionally, the report includes insights into the competitive environment, SWOT analysis, current market trends, as well as the primary drivers and constraints. Furthermore, it discusses various factors that have driven market expansion in recent years. The report also explores market dynamics, regulatory scenarios, and technological advancements that are shaping the industry. It assesses the impact of external factors and global economic changes on market growth. Lastly, it provides strategic recommendations for new entrants and established companies to navigate the complexities of the market.

Future Outlook

  1. Supply chain analytics will increasingly leverage AI and machine learning to enable predictive and prescriptive decision-making.
  2. Real-time data integration through IoT devices will enhance visibility and control across supply chain operations.
  3. The adoption of cloud-based solutions will continue to grow, driven by scalability and cost-efficiency.
  4. Advanced analytics tools will support the shift towards sustainable supply chains by optimizing energy consumption and reducing emissions.
  5. The rising complexity of global supply chains will increase the demand for analytics solutions capable of managing disruptions and ensuring resilience.
  6. Businesses will focus more on customer-centric analytics to meet growing expectations for personalized services and faster deliveries.
  7. Data security and privacy compliance will remain critical as companies adopt analytics tools handling sensitive information.
  8. SMEs will increasingly adopt analytics solutions as cost-effective, cloud-based options become more accessible.
  9. Collaboration between technology providers and enterprises will drive customized solutions for industry-specific challenges.
  10. The focus on automation in procurement, inventory management, and logistics will reshape supply chain strategies globally.

1. Introduction
1.1. Report Description
1.2. Purpose of the Report
1.3. USP & Key Offerings
1.4. Key Benefits for Stakeholders
1.5. Target Audience
1.6. Report Scope
1.7. Regional Scope
2. Scope and Methodology
2.1. Objectives of the Study
2.2. Stakeholders
2.3. Data Sources
2.3.1. Primary Sources
2.3.2. Secondary Sources
2.4. Market Estimation
2.4.1. Bottom-Up Approach
2.4.2. Top-Down Approach
2.5. Forecasting Methodology
3. Executive Summary
4. Introduction
4.1. Overview
4.2. Key Industry Trends
5. Global Supply Chain Analytics Market
5.1. Market Overview
5.2. Market Performance
5.3. Impact of COVID-19
5.4. Market Forecast
6. Market Breakup by Deployment
6.1. On-premise
6.1.1. Market Trends
6.1.2. Market Forecast
6.1.3. Revenue Share
6.1.4. Revenue Growth Opportunity
6.2. Cloud-based
6.2.1. Market Trends
6.2.2. Market Forecast
6.2.3. Revenue Share
6.2.4. Revenue Growth Opportunity
7. Market Breakup by Enterprise Type
7.1. Small and Medium Enterprises (SMEs)
7.1.1. Market Trends
7.1.2. Market Forecast
7.1.3. Revenue Share
7.1.4. Revenue Growth Opportunity
7.2. Large Enterprises
7.2.1. Market Trends
7.2.2. Market Forecast
7.2.3. Revenue Share
7.2.4. Revenue Growth Opportunity
8. Market Breakup by Application
8.1. Demand Planning
8.1.1. Market Trends
8.1.2. Market Forecast
8.1.3. Revenue Share
8.1.4. Revenue Growth Opportunity
8.2. Inventory Analytics
8.2.1. Market Trends
8.2.2. Market Forecast
8.2.3. Revenue Share
8.2.4. Revenue Growth Opportunity
8.3. Procurement Analytics
8.3.1. Market Trends
8.3.2. Market Forecast
8.3.3. Revenue Share
8.3.4. Revenue Growth Opportunity
8.4. Logistics Analytics
8.4.1. Market Trends
8.4.2. Market Forecast
8.4.3. Revenue Share
8.4.4. Revenue Growth Opportunity
8.5. Others
8.5.1. Market Trends
8.5.2. Market Forecast
8.5.3. Revenue Share
8.5.4. Revenue Growth Opportunity
9. Market Breakup by Industry
9.1. Healthcare
9.1.1. Market Trends
9.1.2. Market Forecast
9.1.3. Revenue Share
9.1.4. Revenue Growth Opportunity
9.2. Retail & E-commerce
9.2.1. Market Trends
9.2.2. Market Forecast
9.2.3. Revenue Share
9.2.4. Revenue Growth Opportunity
9.3. Transportation & Logistics
9.3.1. Market Trends
9.3.2. Market Forecast
9.3.3. Revenue Share
9.3.4. Revenue Growth Opportunity
9.4. Automotive
9.4.1. Market Trends
9.4.2. Market Forecast
9.4.3. Revenue Share
9.4.4. Revenue Growth Opportunity
9.5. Manufacturing
9.5.1. Market Trends
9.5.2. Market Forecast
9.5.3. Revenue Share
9.5.4. Revenue Growth Opportunity
9.6. Oil & Gas
9.6.1. Market Trends
9.6.2. Market Forecast
9.6.3. Revenue Share
9.6.4. Revenue Growth Opportunity
9.7. Chemical
9.7.1. Market Trends
9.7.2. Market Forecast
9.7.3. Revenue Share
9.7.4. Revenue Growth Opportunity
9.8. Others
9.8.1. Market Trends
9.8.2. Market Forecast
9.8.3. Revenue Share
9.8.4. Revenue Growth Opportunity
10. Market Breakup by Region
10.1. North America
10.1.1. United States
10.1.1.1. Market Trends
10.1.1.2. Market Forecast
10.1.2. Canada
10.1.2.1. Market Trends
10.1.2.2. Market Forecast
10.2. Asia-Pacific
10.2.1. China
10.2.2. Japan
10.2.3. India
10.2.4. South Korea
10.2.5. Australia
10.2.6. Indonesia
10.2.7. Others
10.3. Europe
10.3.1. Germany
10.3.2. France
10.3.3. United Kingdom
10.3.4. Italy
10.3.5. Spain
10.3.6. Russia
10.3.7. Others
10.4. Latin America
10.4.1. Brazil
10.4.2. Mexico
10.4.3. Others
10.5. Middle East and Africa
10.5.1. Market Trends
10.5.2. Market Breakup by Country
10.5.3. Market Forecast
11. SWOT Analysis
11.1. Overview
11.2. Strengths
11.3. Weaknesses
11.4. Opportunities
11.5. Threats
12. Value Chain Analysis
13. Porters Five Forces Analysis
13.1. Overview
13.2. Bargaining Power of Buyers
13.3. Bargaining Power of Suppliers
13.4. Degree of Competition
13.5. Threat of New Entrants
13.6. Threat of Substitutes
14. Price Analysis
15. Competitive Landscape
15.1. Market Structure
15.2. Key Players
15.3. Profiles of Key Players
15.3.1. IBM Corporation (U.S.)
15.3.1.1. Company Overview
15.3.1.2. Product Portfolio
15.3.1.3. Financials
15.3.1.4. SWOT Analysis
15.3.2. Oracle Corporation (U.S.)
15.3.3. SAP SE (Germany)
15.3.4. Accenture (Ireland)
15.3.5. Manhattan Associates (U.S.)
15.3.6. SAS Institute Inc. (U.S.)
15.3.7. Sigmoid Analytics (U.S.)
15.3.8. Mecalux, S.A. (Spain)
15.3.9. Analytics8, LLC (U.S.)
15.3.10. SS Supply Chain Solutions Pvt. Ltd. (3SCSolutions) (Netherlands)
16. Research Methodology

Frequently Asked Questions:

What is the current size of the Supply Chain Analytics Market?

The supply chain analytics market is valued at USD 6,125 million in 2024 and is projected to reach USD 22,558.8 million by 2032, growing at a CAGR of 17.7%.

What factors are driving the growth of the Supply Chain Analytics Market?

Key drivers include the increasing adoption of data-driven decision-making, rising e-commerce activities, demand for real-time visibility, integration of advanced technologies like AI and IoT, and a growing focus on sustainability and supply chain resilience.

What are the key segments within the Supply Chain Analytics Market?

The market is segmented by deployment (on-premise, cloud-based), enterprise type (SMEs, large enterprises), application (demand planning, inventory analytics, logistics analytics), and industry (healthcare, retail & e-commerce, manufacturing, transportation & logistics).

What are some challenges faced by the Supply Chain Analytics Market?

Challenges include data complexity, integration of multiple systems, ensuring data security and compliance, technological barriers, and organizational resistance to adopting new analytics tools.

Who are the major players in the Supply Chain Analytics Market?

Major players include IBM Corporation, Oracle Corporation, SAP SE, Accenture, SAS Institute Inc., Manhattan Associates, and Analytics8, among others.

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