The global supply chain analytics (SCA) market, valued at USD 6.12 billion in 2022, is expected to grow at a compound annual growth rate (CAGR) of 17.8% from 2023 to 2030. The increasing demand for SCA solutions is driven by the significant benefits they offer, such as enhanced forecasting accuracy, optimized supply chains, minimized waste, and comprehensive business data analysis. The rise in small and medium enterprises (SMEs) and their growing investment in analytics to maintain competitive market positioning are also expected to propel market growth over the forecast period.
The COVID-19 pandemic highlighted the need for resilient supply chain solutions, as organizations were compelled to adapt their operations to mitigate pandemic-induced disruptions. Supply chain analytics helped businesses identify vulnerable areas and anticipate shortages, enabling them to bridge the demand-supply gap more effectively. Additionally, SCA providers actively introduced solutions to help companies reduce the pandemic's adverse effects on global supply chains.
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Supply chain analytics also plays a key role in helping organizations make informed decisions about technology adoption, organizational structure, strategic partnerships, and resource management. For instance, in April 2023, Accenture PLC acquired EINR AS, a logistics solution provider, to bolster its SAP capabilities and accelerate supply chain innovation in consumer electronics and retail sectors.
By providing an overarching view of supply chain activities, SCA solutions empower businesses to address potential profitability and sustainability issues more effectively. Mobile-based analytics tools are particularly advantageous, enabling companies to monitor inefficient supplier networks, high warehousing costs, inaccurate forecasts, and other operational challenges. These solutions contribute to improved inventory management and cost reduction, both of which support business growth. The increasing adoption of mobile-based solutions is expected to drive further growth in the SCA industry.
Despite promising advancements, unethical activities and rising cyber threats pose concerns that could hinder the adoption of SCA solutions. Industry stakeholders are mindful of potential data breaches, which may affect market growth. However, SCA providers are working diligently to offer secure solutions that mitigate these risks, thus supporting sustained market growth in the future.
End-Use Insights
In 2022, the manufacturing sector led the SCA market, accounting for over 23% of the market share. SCA solutions in manufacturing enable performance enhancements by providing access to real-time data across the entire value chain and tracking updates throughout all processes and regions. Increasing customer demand and the need to ensure product availability and timely delivery are driving the demand for improved supply chain efficiency. For example, in April 2023, Snowflake, a data cloud company, launched the Manufacturing Data Cloud for the automotive, technology, and industrial sectors. This platform facilitates collaboration between manufacturers, suppliers, and partners, improving supply chain performance and supporting smart manufacturing initiatives.
The Manufacturing Data Cloud offers tools that allow manufacturers to work securely with various stakeholders, boosting agility and visibility across the value chain. In today's digital and industrial landscape, solutions like Snowflake’s platform help companies improve their supply chains, initiate smart manufacturing projects, and build a robust data foundation for operational enhancements.
Efficient supply chain planning is becoming increasingly essential as online retail continues to grow and companies compete to deliver a seamless experience for customers. The expanding e-commerce industry, coupled with the integration of big data and artificial intelligence (AI) into supply chain analytics, is expected to drive global demand for efficient supply networks. These factors are anticipated to fuel growth in the retail and consumer goods segment over the forecast period.
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