Cognitive Supply Chain Market Size & Share 2023 to 2032
Market Size by Offering (Solution [Forecasting, Analytics, Inventory Management, Risk Management], Services), Deployment Model (Cloud, On-premises), Enterprise Size (SME, Large Organization), End Use & Global Forecast.
Report ID: GMI7047
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Published Date: October 2023
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Report Format: PDF
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Authors:
Preeti Wadhwani, Aishvarya Ambekar
Cognitive Supply Chain Market Size
Cognitive Supply Chain Market size was valued at USD 7.5 billion in 2022 and is anticipated to register a CAGR of over 16% between 2023 and 2032. The booming e-commerce industry with its increasing supply chain demands is fuelling the market growth. Cognitive technologies optimize operations by processing vast amounts of data in real time, enhancing inventory management, predictive analytics, and demand forecasting. According to the International Trade Association, China is the largest e-commerce market globally, generating almost 50% of the world’s transactions. In 2021, China led the e-commerce market with a revenue of USD 1.5 trillion, placing it ahead of the U.S.
Cognitive Supply Chain Market Key Takeaways
Market Size & Growth
Key Market Drivers
Challenges
Companies across industries recognize the need for real-time visibility, data-driven insights, and agile decision-making in volatile environments. The COVID-19 pandemic highlighted the need for investments in predictive analytics, demand forecasting, and adaptive inventory management to enhance resilience and ensure consistent customer service. The pandemic underscored the significance of a connected & digital supply chain.
For instance, in August 2019, Nike's proactive investment in advanced supply chain technology including the acquisition of Celect, bolstered the company's resilience during the pandemic. Celect's predictive analytics allowed Nike to foresee the decline in physical retail sales and swiftly reallocate inventory to e-commerce fulfilment centers. This adaptability enabled Nike to meet the evolving consumer demands, emphasizing the invaluable role of digital supply chain solutions in maintaining operational efficiency and customer satisfaction, particularly in disruptive times such as the pandemic.
The high cost associated with developing and deploying cognitive supply chain solutions presents a significant challenge. Building & implementing advanced technologies, such as Artificial Intelligence (AI), Machine Learning (ML), and IoT, demands substantial financial resources. Moreover, the integration of these technologies into existing supply chain systems requires time and expertise, increasing the overall expenses. Many organizations, especially smaller ones, may find these costs prohibitive, impeding the wide adoption and potentially limiting the market's growth potential.
COVID-19 Impact
The COVID-19 pandemic negatively impacted the cognitive supply chain market. It disrupted supply chains globally, creating uncertainties and supply shortages. Many companies faced financial constraints and delayed or cancelled investments in cognitive supply chain technologies. The need for immediate cost-cutting measures made long-term investments less appealing. Despite the potential benefits of cognitive supply chains during crises, the pandemic's economic strain slowed market growth as companies focused on short-term survival.
Cognitive Supply Chain Market Trends
The integration of AI and ML is an emerging trend in the cognitive supply chain industry. AI and ML technologies are revolutionizing supply chain operations by providing intelligent insights and automation capabilities. AI-driven predictive analytics and pattern recognition help in demand forecasting, inventory optimization, and dynamic route planning.
For instance, in September 2023, Alloy.ai incorporated AI features into its forecasting and supply chain platform, enhancing its capabilities for more accurate predictions and supply chain management. ML algorithms enhance real-time decision-making, improving the supply chain’s agility and responsiveness. This trend is driven by the need for data-driven, efficient, and adaptive supply chain processes, where AI and ML play a pivotal role in shaping the future of logistics and operations.
The adoption of cloud-based solutions is a rising trend in the cognitive supply chain market. Cloud technology offers scalable and flexible platforms for storing, analysing, and accessing vast amounts of supply chain data. This trend enables companies to harness cognitive computing and analytics tools that require substantial computing power and resources, all while enjoying the benefits of cost-effectiveness and accessibility. Cloud-based solutions facilitate real-time data sharing, collaboration, and visibility across the supply chain, making it easier for businesses to optimize their operations, enhance decision-making, and respond to market changes swiftly.
Cognitive Supply Chain Market Analysis
Based on offering, the solution accounted for 40% of the market share in 2022, owing to the increasing demand for AI-driven tools and platforms. Businesses are seeking comprehensive solutions that can address their supply chain complexities, optimize operations, and enhance decision-making. These solutions encompass predictive analytics, demand forecasting, inventory management, and real-time visibility. Furthermore, the integration of ML and data analytics into supply chain solutions is augmenting efficiency and performance improvements. This trend is expected to continue as companies prioritize digital transformation and seek end-to-end cognitive supply chain solutions to gain a competitive edge.
Based on deployment model, the on-premises segment held around 66% of the cognitive supply chain market share in 2022. Firstly, industries with sensitive data and regulatory constraints, like healthcare and finance, prefer on-premises solutions to maintain control over their data. Secondly, legacy systems and existing infrastructure often make it easier and more cost-effective to deploy solutions on-premises. Additionally, some companies opt for on-premises deployment to ensure low-latency processing and better integration with existing technologies, leading to a preference for this model in cognitive supply chain implementations.
North America cognitive supply chain market size dominated around USD 3 billion in 2022, attributed to several factors including the region's robust technological infrastructure, a strong presence of key industry players, and a growing emphasis on supply chain optimization. The increasing adoption of AI and ML solutions to enhance supply chain visibility, demand forecasting, and inventory management is fueling market growth.
For instance, in November 2022, Microsoft launched the Supply Chain Platform, a transformative solution designed to create agile, automated, and sustainable supply chains. By leveraging advanced technology and data-driven insights, it enhances efficiency and responsiveness in the market. North American organizations are recognizing the value of cognitive technologies in improving operational efficiency, reducing costs, and responding to market dynamics swiftly, contributing to the region's prominence in the cognitive supply chain sector.
Cognitive Supply Chain Market Share
Major companies operating in the cognitive supply chain industry are:
These companies develop advanced technologies and solutions. They provide AI, cloud, and analytics-based platforms that enhance supply chain visibility, predictive analytics, and automation. This contributes to more efficient, agile, and sustainable supply chain operations for various industries, helping businesses adapt to evolving market demands and disruptions. These companies drive innovations and support businesses in improving their supply chain performance.
Cognitive Supply Chain Industry News
The cognitive supply chain market research report includes in-depth coverage of the industry, with estimates & forecast in terms of Revenue (USD Million) from 2018 to 2032, for the following segments:
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Market, By Offering
Market, By Deployment model
Market, By Enterprise size
Market, By End use
The above information has been provided for the following regions and countries:
Research methodology, data sources & validation process
This report draws on a structured research process built around direct industry conversations, proprietary modelling, and rigorous cross-validation and not just desk research.
Our 6-step research process
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4. Market sizing
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✓ Competitive dynamics and market entry/exit expectations
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Parameters studied & evaluated
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