OSI delivers customized software applications that model, optimize and simulate complex industrial processes and is headed by Vijay Hanagandi, Ph.D. Founded by former GE PhD Chemical Engineers, OSI's applications bring mathematical and computational support to companies' decision making processes in order to minimize energy usage, optimize manufacturing variables, increase profitability and decrease time to market.
With the advent of social media, Telemetry, Point of Sale systems, and other data sources, companies are suddenly inundated with more data and they need to manage this important information in the most optimum way to make their operations more efficient, productive and effective.
Many business owners realize that this is their opportunity to be outward and customer focused.
OSI's approach to leveraging Big Data for supply chain analytics supported by this National Science Foundation (NSF) project, involves developing novel demand forecasting algorithms. These algorithms will use massive quantities of data and enable companies to radically alter the way they plan to meet customer demand. OSI's innovation will also help companies to feed valuable data to their R&D groups in order to bring new products to the market.
As a recipient of an NJSBDC Small Business Success Award in December 2013, Dr. Hanagandi commented that, "The help received from the NJSBDC network's Tech Commercialization Consultant Randy Harmon has been invaluable. It has essentially helped OSI chart a course to become a products company while maintaining its steady consulting practice." Dr. Hanagandi appreciates the NJSBDC network's business guidance and help in securing the National Science Foundation STTR Phase I grant.
In addition to the current project, NJSBDC has assisted Dr. Hanagandi in winning two previous Department of Energy Grants.
The NSF project includes a collaboration with Rutgers Discovery Infomatics Institute (RD12) which is critical for its success," he added. "RD12 will complement our deep field and customer knowledge in supply chain analytics by providing the necessary research results in the area of text mining and application required for scalability of the eventual software product." The long term goal of the project is to help increase the global competitiveness of the U.S. manufacturing sector resulting in job retention and creation.