Technological innovation can help companies to differentiate their products and services from the rest and stay ahead of their competitors. Specific business analytics solutions help these businesses identify areas of improvement and plan for the future.
Accretive Technologies is one that offers high-performance predictive analytic solutions for companies to capitalize on game-changing technological trends such as big data, cloud computing and more.
In a recent statement, Accretive claimed that hundreds of global 1000 companies are currently using its predictive analytic capabilities, which include the company’s patented X-Act Platform.
Featuring highly sophisticated algorithms, Accretive’s X-Act Platform helps prescribe solutions to future problems so that companies are able to attain the most critical goals, that is, to innovate, contain costs, and grow.
The company’s client list includes big brands such as McDonalds, Credit Suisse, La Poste, Thompson Reuters (News - Alert) and more – all of which have reportedly acknowledged that with better success rate than traditional analytics solutions, Accretive’s solutions are helping their executives to maximize market opportunities like big data, cloud computing and other future trends.
With Accretive’s X-Act platform, one can derive a holistic view of a company’s overall health and find solutions to critical challenges like cloud computing, corporate mergers, global outsourcing, equipment modernization and capacity planning.
“While big data analytics help companies gain historical perspective, they alone cannot arm business leaders with the foresights they need to plan for the future,” said Dr. Nabil Abu el Ata, founder and CEO at Accretive Technologies. “Our customers successfully avoid impending crisis and achieve optimal business performance by using Accretive’s patented X-Act Platform – which includes highly sophisticated algorithms like the ones trusted for space exploration – to predict and prescribe solutions to future problems which cannot be identified using historical or statistical approaches.”
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Edited by Braden Becker