MarketsandMarkets forecasts the global Supply Chain Analytics Market to grow from USD 3.6 billion in 2018 to USD 7.1 billion by 2023, at a Compound Annual Growth Rate (CAGR) of 14.6% during the forecast period. The key factors driving the supply chain analytics market include increasing volume and velocity of data, need to enhance operational and supply chain efficiencies, and advent of Artificial Intelligence (AI) and machine learning into supply chain management.
A supply chain basically envelopes the complete network of units and processes, such as businesses, organizations, individuals, methods, and procedures, which are involved in the manufacture and distribution of a commodity. A supply chain, therefore, involves a significantly complex set of processes, right from the planning and sourcing of raw materials to the production, transportation, and distribution of the finished goods. Numerous software are being deployed by supply chain professionals to optimize forecasting accuracy, maximize product tracking and traceability, and improve logistics capabilities. In the recent past, with the propagation of data, organizations are increasingly inclined toward digitalization of their operational processes and supply chain activities. This resulted into a high volume of data generation across various industry verticals. The data plays a vital role in the supply chain industry for network optimization, decision-making, and to identify the potential customers. Hence, big data and analytics, and AI are playing a major role in supply chain activities.
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The demand analysis and forecasting software is projected to grow at the highest CAGR in the supply chain analytics market. The demand analysis and forecasting software facilitates businesses to boost their service levels, shorten cycle times, reduce inventory investment, and minimize obsolescence.
With the advancements in machine learning and AI, the demand forecasting tools has become super-efficient, which helps traders optimize resource utilization, increase product availability, and enhance profitability by managing supply and demand variability. AI-. Supply chain analytics solutions use AI-rich capabilities to automate supply chain activities across manufacturing, retail, healthcare, and other industry verticals. Algorithms used to formulate AI-based solutions provide logical models for application developers to fabricate various innovative applications with capabilities, such as speech and voice recognition, text recognition, and predictive analytics. Additionally, organizations are increasingly looking forward to AI-based analytical solutions to sustain in a competitive environment, as well as, to enhance the customer experience and the quality of the products offered. AI-rich capabilities, such as Machine Learning (ML) algorithms and tools in the manufacturing industry vertical, are used for analyzing the demand for the product. Similarly, retail companies are using visual search, speech recognition, and text recognition capabilities, offered by AI, to predict customer demand, which in turn helps in managing the overall production and supply chain management process.
The geographic analysis of the supply chain analytics market has been mainly segmented into 5 regions, namely, North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and Latin America. North America is expected to be the overall leader in the adoption and implementation of supply chain analytics software and services, followed by Europe and APAC. The presence of state-of-art manufacturing plants and giant retail chains is expected to trigger the market in North America and Europe. Rapid economic developments, globalization, and increasing digitalization are expected to drive the growth of the supply chain analytics market in APAC. The market players are expanding their operations in this region to enhance their market share through business expansions and partnerships with the existing players in the region.
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The supply chain analytics market comprises major solution providers, such as SAP (Germany), Oracle (US), IBM (US), SAS Institute (US), Software AG (Germany), MicroStrategy (US), Tableau (US), Qlik (US), TIBCO (US), Cloudera (US), Logility (US), Savi Technology (US),Infor (US), RELEX Solutions (Finland), TARGIT (Denmark), Voxware (US), The AnyLogic Company (US), Antuit (US), Axway (US), AIMMS (Netherlands), BRIDGEi2i (India), Domo (US), Datameer (US), 1010data(US), Rosslyn Analytics(UK).
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