Global Supply Chain Big Data Analytics Market - Segmented by Type (Solutions, Services), End-user (Retail, Manufacturing, Healthcare), and Geography - Growth, Trends, and Forecast (2018 - 2023)
|出版商||Mordor Intelligence LLP||商品編碼||393915|
|出版日期||內容資訊||英文 115 Pages
|供應鏈、巨量資料分析的全球市場:成長率、市場趨勢、未來預測 Global Supply Chain Big Data Analytics Market - Segmented by Type (Solutions, Services), End-user (Retail, Manufacturing, Healthcare), and Geography - Growth, Trends, and Forecast (2018 - 2023)|
|出版日期: 2018年05月14日||內容資訊: 英文 115 Pages||
The global Supply Chain Big Data Analytics market was valued at USD 51.82 billion and is expected to reach a value of USD 402.54 billion, registering a CAGR of 40.73% during the forecast period (2018 - 2023).
Supply chain Big Data analytics and procurement software helps organizations to automate the processes involved in material purchase and inventory maintenance. For optimum business performance, proper alignment of supply chains with business strategy is required. Supply chains have to be managed well to ensure an organization's competitiveness. Supply chain analytics is useful in overcoming the challenges of supply chain management and reducing costs. Increased costs in different operations of the supply chain made many organizations to adopt automated procurement systems. Small and Medium Enterprises are most active in implementing the procurement software.
Growing need of Business Data to Improve Efficiency
The increasing customer demands and increasing price wars have led to intense competition in the recent business environment. As a result, enterprises are more interested in gaining visibility into multiple business operations, like the supply chain. This encourages enterprises to develop new competitive strategies. Advanced analytics software helps enterprises to conduct consumer analytics to identify and retain new consumers. This transforms the raw marketing and customer data into useful information. In addition, the solutions automate decision-making processes that help avoid process delays involved in human decision making.
Retail Sector holds a Significant Market Share
Due to fluctuating demand and supply in the marketplace, organizations in the retail sector are adopting analytics tools to maintain appropriate inventory levels in order to fulfil customer demand. Analytics tools allow organizations to track inventory throughout the order and delivery process, and monitor inventory in the warehouse and delivery to the store. BI tools enable organizations in the retail sector to produce daily and weekly inventory reports quickly and easily. Analytics tools help monitor lost sales due to lack of inventory, track actual and forecast order quantity, and forecast utilization of inventory assets
North America to hold the Major Market Share
Enterprises in the Americas have a higher Business Intelligence and analytics adoption rate compared to those in other regions. The increasing volume of information generated from enterprise applications is primarily driving the market in the region. Companies are adopting an acquisition strategy to strengthen their presence in the US market.
Key Developments in the Market
Mar 2018 - SAP SE has introduced SAP Predictive Engineering Insights, a cloud-based solution that creates virtual equivalents of physical assets to provide real-time, intelligent analysis based on sensor feeds
The major players include - SAS INSTITUTE INC., SAP SE, IBM CORPORATION, ORACLE CORPORATION, SAGE CLARITY SYSTEMS, KINAXIS INC., MICROSTRATEGY INC., GENPACT LTD., CAPGEMINI GROUP, BIRST, INC., and TABLEAU, amongst others.
Reasons to Purchase this Report
Impact of increasing awareness of supply chain analytics
Analyze various perspectives of the market with the help of Porter's five forces analysis
Growth across various end-users, such as retail, healthcare, and manufacturing
Regional analysis of the market
Identify the latest developments, market shares, and strategies employed by the major market players
3-month analyst supports, along with the Market Estimate sheet (in Excel)
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List Not exhaustive