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Shainin Adopts Photizo Predictive Analysis to Minimize Investment and Emphasize System Performance

By CIOReview | Wednesday, April 13, 2016

FREMONT, CA: Shainin, a consulting firm specializing in engineering and manufacturing has signed a partnership deal with Photizo Group - a market expert in delivering Predictive Analytics as a Service (PAaaS); to leverage predictive analytics solutions for driving the operational efficiency of Shainin customers. The solutions will help in minimizing the initial expenditure as well the overall investment.

The effective predictive analytics tool understands how to operate with industrial customers and engage them. Instead of investing large chunks of revenue on hiring analysts and data engineers to build the technological infrastructure, clients are now more focused on taking advantage from the enhanced analytics. Shainin has designed a business based model to successfully solve the complicated task of increasing the system performance and eliminating the risk involved in the complete process of product life cycle.

“Shainin is a leader in the manufacturing sector and has pioneered one of the key methodologies for problem solving – Red X Strategies. Their deep knowledge of manufacturing in the automotive, aerospace, and other sectors is the perfect complement to our PAaaS offering. When you combine this industry expertise and with our knowledge in predictive analytics – the operational benefits for Shainin’s clients can be tremendous!” remarks Ed Crowley, CEO, Photizo Group.

The PAaaS model delivers clients with analytics solution to address Shainin customer’s pain points that include certain critical issues, without venturing a seven figure investments in predictive analytics technology infrastructure, data scientists, and data engineers. Moreover, Photizo helps customers during crisis to hit higher targets and take agile decision in a precise and accurate manner. Shainin has further crafted unique strategies to isolate the few vital factors that hamper the product performance and system reliability.