SAN DIEGO, April 17, 2012 /PRNewswire/ -- Accelrys, Inc. (NASDAQ: ACCL), a leading scientific enterprise R&D software and services company, today issued an industry-wide call to close the productivity gap from innovation through commercialization that is slowing product development and time-to-market and hampering competitiveness for science-driven organizations.
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Currently, only 25 percent of projects in industries ranging from pharmaceuticals to aerospace result in the commercialization of new products, according to IDC Manufacturing Insights. Of the 25 percent of products that make it to market, 66 percent fail to meet original design or consumer expectations.
"There is growing consensus that new product development is increasingly ineffective – especially for science-driven innovation," said Joe Barkai, research vice president, product lifecycles strategies at IDC Manufacturing Insights. "Scientific-driven research and development organizations are at a critical juncture – their homegrown systems no longer meet the demands of today's fastest-to-market environment. They need to be managing the innovation cycle in a new way, and with the same rigor that they have managed their commercialization processes."To accelerate innovation and profitability across industries, Accelrys is challenging science-driven organizations to focus on closing the productivity gap from innovation through commercialization. Accelrys also is introducing a scientifically aware enterprise platform as a component of a broader strategy to facilitate a new approach to effectively managing scientific innovation. The Problem: The Productivity Gap For science-driven organizations – particularly those developing products based on modeling at the atomic or molecular level – there is a productivity gap that spans the entire innovation-to-commercialization cycle. This productivity gap exists because traditional information technology solutions have proved incapable of adequately managing the complexity of scientific data and processes and the volumes of unstructured data characteristic of scientific R&D. Scientific processes, for example, are difficult to automate and track, and therefore information is hard to access and reuse during the scientific and product innovation and commercialization cycles. Critical scientific insights and context from the discovery and development stages are never transferred to the commercialization operations of a business because downstream enterprise software cannot handle the unstructured data generated in the R&D cycle. Key parts of the innovation process are consequently lost, along with actionable insights that could bring novel products to market more quickly and cost effectively.
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