On the basis of regions, the global supply chain analytics market is segmented into North America, Europe, Asia Pacific, Latin America, Middle East, and Africa. North America region accounted for largest market share of global supply chain analytics market in 2016 due to wide application of supply chain in healthcare sector. Accuracy is one of the major concerns in the healthcare sector. Machine learning have the capabilities to provide more accurate diagnosis and healthcare services, which in turn has augmented demand for supply chain analytics in healthcare sector. For instance, diagnosis of diabetic eye disease requires frequent examination of pictures at the back of an eye by the specialist. The features in the image helps to identify sensitivity of disease, which indicates fluid leakage and bleeding. In 2016, Google has developed a deep learning algorithm, which analyze images and provides training to the system by using a data set of 128,000 images. Thus, the system diagnose the disease with a level of accuracy similar to human ophthalmologists. Google healthcare sector is focused on developing a deep learning algorithm for early diagnosis of skin cancer and breast cancer.
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Supply chain analytics is an algorithm that consists of mathematics, statistics, predictive modeling and machine-learning techniques. It helps convert business data including order, shipment, and transactional data of several industries such as, manufacturing, retail & consumer, healthcare, and transportation into meaningful insights.
Supply chain analytics analyses data to provide accurate forecasting that is in tune with current and future market trends. Moreover, supply chain analytics solution is involved in providing real time analysis for huge data set. Rampant growth of unstructured data set through the data or record management of forecasting, transportation logistics, retail and manufacturing, data or transaction of banks and finance, and business tax are expected to boost the growth of overall supply chain analytics market globally, owing to the requirement of analysis and management of huge unstructured data set in shorter time span, which is labor intensive. For instance, machine learning algorithms are used in warehouses to demonstrate an intelligent stock management system for the prediction of resupply requirement in future. In Finance sector, supply chain analytics are used to predict capital costs or the probability of working capital, which helps to target the best suppliers and also provides prompt warning of budget overruns. In transportation, supply chain analytics software can forecast the impact of weather on shipments.
However, data security concern is the factor, which may restraint the growth of global supply chain analytics market.
Major players operating in the global supply chain analytics market are IBM Corporation, Microstrategy, Oracle Corporation, SAP SE, SAS Institute, INC., Capgemini Inc., Genpact, Kinaxis INC., Tableau Software, and Birst, Inc.
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