The Global Cognitive Supply Chain Market size is expected to reach $20.7 billion by 2030, rising at a market growth of 14.8% CAGR during the forecast period.
Internet of Things (IoT) technology aids companies massively in improving supply chain visibility. Therefore, the Internet of Things (IoT) segment registered $3,083.1 million revenue in the market in 2022. The integration of Internet of Things (IoT) technology into the market has revolutionized the way businesses manage their operations. IoT devices, such as sensors and RFID tags, enable real-time tracking and monitoring of goods, assets, and equipment throughout the supply chain, providing unprecedented visibility and data insights. This influx of data is harnessed by cognitive technologies like artificial intelligence and machine learning, which analyze and predict supply chain patterns, demand fluctuations, and potential disruptions. Some of the factors affecting the market are advancements in artificial intelligence and machine learning, cost reduction and efficiency improvements and challenges associated with data privacy and security.
AI and ML can process and analyze massive amounts of data at speeds and complexity levels beyond human capacity. In the supply chain, this translates into the ability to extract valuable insights from vast datasets, including historical data, real-time sensor data, market trends, and external factors. Machine learning algorithms have improved demand forecasting accuracy significantly. These algorithms can provide more precise predictions of future demand by analyzing historical data and considering multiple variables, such as seasonality and market trends. AI-driven algorithms can optimize various aspects of the supply chain, including routing, transportation, inventory management, and production scheduling. This optimization leads to cost savings, increased efficiency, and improved overall supply chain performance. Additionally, these solutions powered by AI and data analytics enable companies to maintain optimal inventory levels. This minimizes excess inventory carrying costs while ensuring products are readily available, reducing working capital tied up in inventory. Accurate demand forecasting is critical for efficient supply chain operations. This automation reduces procurement cycle times, minimizes manual errors, and lowers administrative costs. Cost reduction and operational efficiency remain crucial for organizations adopting cognitive supply chain technologies. These technologies provide the tools and insights necessary to optimize supply chain procedures, reduce waste, and enhance overall profitability, making them a strategic imperative for many businesses, which can lead to market growth.
However, Data privacy and security are substantial challenges in the market. Compliance with data protection regulations, like the General Data Protection Regulation (GDPR) in Europe or the California Consumer Privacy Act (CCPA) in the United States, can be complex. Cognitive supply chain solutions often involve processing personal and sensitive data, and companies must ensure they handle this data in compliance with applicable laws. Cyberattacks on supply chain partners can have cascading effects on the entire supply chain. Companies must monitor and secure their supply chain ecosystem against such attacks. These challenges can hinder the adoption and effective implementation of the market.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Acquisitions, and Partnerships & Collaborations.
On the basis of deployment type, the market is segmented into cloud and on-premise. The cloud segment acquired a substantial revenue share in the market in 2022. One of the primary reasons cloud deployment's rising popularity in the market is its scalability. Cloud-based solutions allow businesses to adjust their resources based on demand fluctuations and evolving business needs. As supply chain operations often vary seasonally or due to changes in market conditions, the cloud provides a dynamic infrastructure that can efficiently handle varying workloads without significant reconfiguration. Cost-effectiveness is another compelling advantage of the cloud deployment segment.
By technology, the market is categorised into internet of things (IoT), machine learning, and others. The machine learning (ML) segment recorded a remarkable revenue share in the cognitive supply chain in 2022. ML automation enables businesses to consolidate and optimize their supply chain processes, lower operational costs, enhance efficiency, and make data-driven decisions in this market segment. ML-driven solutions can help businesses gain a competitive advantage by automating repetitive duties, analyzing vast amounts of data, and identifying patterns and insights. Several factors have contributed to the expansion of ML automation on the market. First, AI and ML adoption is increasing as businesses recognize these technologies' potential supply chain management benefits.
Based on enterprise size, the market is fragmented into small & medium-sized enterprises and large enterprises. The SMEs segment garnered a significant revenue share in the market in 2022. Cost-effectiveness is a major contributor to the growth of the SME segment of the market. Now, SMEs have access to cognitive supply chain platforms in the cloud that require a lower initial investment than conventional on-premise solutions, making them more affordable for smaller budgets. This decreased financial barrier has allowed small and medium-sized enterprises to adopt innovative technologies and acquire a competitive edge in their respective industries. In addition, the scalability of cognitive supply chain solutions has been an essential factor in their adoption by SMEs.
On the basis of vertical, the market is classified into manufacturing, retail & e-commerce, logistics & transportation, healthcare, food & beverage, and others. The healthcare segment projected a prominent revenue share in the market in 2022. Cognitive supply chain solutions can help hospitals and healthcare facilities manage their inventory of medical supplies and pharmaceuticals more efficiently. AI and machine learning algorithms can analyze usage patterns, forecast demand, and optimize inventory levels to ensure that essential items are always in stock while minimizing excess. In pharmaceutical supply chains, cognitive technologies can be used to ensure the traceability of drugs from manufacturing to distribution to the end-user.
| Report Attribute | Details |
|---|---|
| Market size value in 2022 | USD 7 Billion |
| Market size forecast in 2030 | USD 20.7 Billion |
| Base Year | 2022 |
| Historical Period | 2019 to 2021 |
| Forecast Period | 2023 to 2030 |
| Revenue Growth Rate | CAGR of 14.8% from 2023 to 2030 |
| Number of Pages | 303 |
| Number of Table | 450 |
| Report coverage | Market Trends, Revenue Estimation and Forecast, Segmentation Analysis, Regional and Country Breakdown, Market Share Analysis, Companies Strategic Developments, Company Profiling |
| Segments covered | Technology, Enterprise Size, Deployment Type, Vertical, Region |
| Country scope | US, Canada, Mexico, Germany, UK, France, Russia, Spain, Italy, China, Japan, India, South Korea, Singapore, Malaysia, Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria |
| Growth Drivers |
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| Restraints |
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Region-wise, the market is analysed across North America, Europe, Asia Pacific, and LAMEA. In 2022, the North America region generated the highest revenue share in the market. The increasing demand for efficacy and cost savings is one of the primary contributors to the expansion of the market in North America. Companies actively seek methods to streamline their supply chain operations, reduce costs, and increase output. Cognitive supply chain solutions enable them to recognize patterns, predict demand, and optimize inventory and logistics processes to increase resource allocation and decrease waste. In addition, big data and analytics proliferation play a vital role in accelerating the adoption of cognitive supply chain technologies.
Free Valuable Insights: Global Cognitive Supply Chain Market size to reach USD 20.7 Billion by 2030
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include SAP SE, Oracle Corporation, Accenture PLC, IBM Corporation, Intel Corporation, NVIDIA Corporation, Honeywell International, Inc., C.H. Robinson Worldwide, Inc., Amazon.com, Inc. and Panasonic Holdings Corporation
By Deployment Type
By Technology
By Enterprise Size
By Vertical
By Geography
This Market size is expected to reach $20.7 billion by 2030.
Advancements in Artificial Intelligence and machine learning are driving the Market in coming years, Challenges associated with data privacy and security restraints the growth of the Market.
SAP SE, Oracle Corporation, Accenture PLC, IBM Corporation, Intel Corporation, NVIDIA Corporation, Honeywell International, Inc., C.H. Robinson Worldwide, Inc., Amazon.com, Inc. and Panasonic Holdings Corporation
The On-premise segment is generating the maximum revenue in the Market, By Deployment Type in 2022; thereby, achieving a market value of $11.9 billion by 2030.
The Large Enterprises segment is leading the Market, By Enterprise Size in 2022; thereby, achieving a market value of $13.6 billion by 2030
The North America region dominated the Market, By Region in 2022, and would continue to be a dominant market till 2030; thereby, achieving a market value of $6.98 billion by 2030.
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