NEW YORK, Oct. 05, 2017 (GLOBE NEWSWIRE) -- According to the market research report titled "Cloud Supply Chain Management (SCM) Market by Solution (Demand Planning & Forecasting, Inventory & Warehouse Management, Product Life-Cycle Management, Logistics Management, Sales & Operations Planning, Order Management, Transportation Management, Procurement & Sourcing, Product Master Data Management), by Service (Training & Consulting, Managed Services, Support & Maintenance), by Deployment Type (Hybrid Cloud, Public Cloud, Private Cloud), by User Type (Large Enterprises, Small & Medium Enterprises), by Industry (Energy & Power, Retail & Wholesale, Food & Beverage, Transportation & Logistics, Manufacturing, Healthcare & Lifesciences, Hospitality, Government), by Geography (U.S., Canada, France, Germany, Russia, China, Japan, India, Saudi Arabia, Brazil) – Global Market Size, Share, Development, Growth and Demand Forecast, 2013-2023" published by P&S Market Research, global cloud SCM market size is projected to reach $11 billion by 2023.
Surging adoption in transportation management has been one of the major drivers for the cloud SCM market. As the world’s transportation networks and supply chains become increasingly intertwisted and complex, the systems that support them are advancing and improving at a rapid pace. Software vendors have been integrating more transportation optimization capabilities into their solutions, making it easier for shippers to streamline their supply chains, while also making them more cost- and time-efficient. This has been augmenting the growth of the cloud SCM market.
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During the course of our analysis, we found that demand planning and forecasting is projected to witness the highest growth, with 20.3% CAGR during the forecast period, among all solutions in the cloud SCM market. Demand management solutions help to predict and manage replenishment effectively, align price and profit margins, better leverage past product performance and maintain a leaner and more profitable supply chain.
Demand management solutions takes supply chain management to the next level by enabling an automated ecosystem that simultaneously maps demand forecasting against factors like financial predictions, supply restrictions, inventory counts and customer commitments, as well as patterns of behavior that can affect demand at any given time. These benefits of demand management solutions are thus driving the growth of the demand planning & forecasting.
Cloud SCM demand will grow at the fastest rate in small & medium enterprises during the forecast period. The market for cloud SCM in energy & power and retail & wholesale industries are projected to grow at the fastest and equal rate, during the forecast period. Support & maintenance is estimated to be the fastest growing service type in this market. Private cloud deployment is becoming the most preferred cloud supply chain management, resulting in the highest growth among all deployment types, during 2017 – 2023
Cloud SCM market has been growing at the highest pace in Asia-Pacific on account of surging industrialization in the region, and the growing adoption of automation among enterprises. Growing e-commerce market coupled with increasing focus on reducing the ownership cost are the other factors driving the cloud SCM market in the region. The regional governments have also been supporting the industrial growth, which is being translated into the growth of cloud SCM market in the region.
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There exists a high degree of rivalry for wining over the clients among the companies operating in the cloud CSM industry. In 2017, Aditya Birla Online Fashion (Abof) selected IBM Cloud and Watson to deliver a personalized and convenient shopping experience to their customers. It will endow the Abof customers with various accessibility features, such as using natural language questions within Abof’s enhanced eCommerce platform, and receiving greater personalization and product recommendations. Some of the companies operating in this market include JDA Software, IBM, Logility, Kinaxis, and Oracle.
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