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This vendor-written tech primer has been edited by Network World toeliminate product promotion, but readers should note it will likelyfavor the submitter's approach. CIOs at companies that rely on scientific R&D to differentiatethemselves have highly specific information management challenges. In a tough economy, they need to help theirorganizations reduce R&D costs and do more with less. They needto help shrink time-to-market by streamlining the numerousactivities and processes involved in transforming a great idea intoa great product, whether that product is a new shampoo, a drugtherapy, or a state-of-the-art polymer used to improve theperformance of an airplane wing. And in a world where globalcompetition is fierce, they need to deploy tools that support fast,first-rate and cost-effective innovation. It's clear to businesses that IT has big role to play in drivingbetter, faster and smarter innovation. The problem is that thecurrent R&D value chain is highly fragmented, with gaps inautomation that render many processes largely manual, resulting indelays and reworks; as well as inability to fully capitalize oncritical data. From early research at the chemical and molecularlevel, through to safety and QA/QC testing and production scale-up,the goal is to empower stakeholders -- including scientists,engineers, lab managers, plant managers, business executives andmore -- to extract maximum value from R&D information andperform more efficiently, collaboratively and cost effectively. REPORT: US losing high-tech jobs, R&D dominance to Asia So why not extend the data and process management capabilities of ERP and PLM systems into R&D? The answer is that optimizingR&D is similar in principle to ERP and PLM, but it can be verydifferent in practice. When it comes to the innovation lifecycle,an information management solution that provides an end-to-endframework for automation and governance is important, but it alsoneeds to be able to support the unique requirements of the R&Dfunction. Here are some key considerations for CIOs to think about: * Innovation is not like an assembly line. PLM systems have beeninstrumental in squeezing time, cost and waste out of manufacturingand supply chain activities. They are designed to facilitate highlystructured, stage-gate processes that move information through theproduct manufacturing and distribution pipeline as quickly,accurately and efficiently as possible. The reason it's so difficult to do the same with R&Dinformation is that innovation doesn't work in a linear way.Researchers and other innovation stakeholders need to be able tofollow ideas where they lead. Usually this calls for processes thatare ad hoc or out of sequence, and information streams that travelbackward before moving forward. As a result, rigid attempts atstructuring R&D activities will likely fail. Some kind of information framework is needed to capture, integrateand leverage complex knowledge and also to streamline theactivities that support innovation. For example, tedious manualactivities and processes associated with moving R&D databetween systems and applications , or integrating and formatting it for reports, can and should beautomated so that users can also reuse process protocols that maybe time-consuming or difficult to recreate. * R&D data is extraordinarily complex. Advances in R&Dtechnology and techniques have led to leaps in innovation --consider the evolution of the computer chip or the medical discoveries enabled through the mapping of thehuman genome. Simultaneously, the increasing sophistication ofR&D has also left IT departments with two sizeable issues tocontend with: data overload and data complexity. From chemical structures and biological sequences to outputs fromhigh-throughput testing equipment and other data streams, the sheervolume is enormous. And unlike the structured data that is commonlyprocessed through PLM and ERP systems, R&D information isexponentially more varied and complex. Beyond standard row and column-based data sets, it may includescientifically meaningful text, images, two- and three-dimensionalmodels and more -- and it's generated by a multitude of diversesoftware systems, laboratory equipment, sensors, instruments anddevices. All too often, critical information is locked in system,departmental or disciplinary silos making it difficult to share andreuse throughout the organization. This complexity is the No. 1barrier to realizing greater efficiencies, so any solution deployedby IT to streamline the innovation cycle must be able to capturehighly scientific data, integrate information from diverse sources,run processes across it and report it in a way that makes sense formultiple users from executives to manufacturing engineers. * Flexibility and simplicity are essential. Brilliant scientists,expert modelers, experienced engineers, star formulators -- theseare an R&D organization's crown jewels. Any informationmanagement system needs to be simple to use and flexible enough toallow them to work the way they want to work. The tools that R&D experts rely on are varied and specializedand may include things like megapixel cameras and fluorescentmicroscopes, high-throughput testing rigs, or molecular modelingand simulation software. A framework for innovation lifecyclemanagement should never attempt to replace these tools. Rather, it should extract the data generated by individuals in thelab, in the field or at their desktops, integrate it, give itcontext and make it available for use throughout the product valuechain. The key to widespread adoption is that all the informationmanagement heavy lifting should be done "behind the scenes," withlittle end-user interaction. * The time for Innovation Information Integration has come. Intoday's highly connected information ecosystem, the moment hasarrived for R&D to e-enable itself, just as the manufacturingand supply chain side has done with PLM and ERP. Thanks to theadvent of cloud computing , service-oriented architecture and the use of Web services andtechnologies that support advanced search and data mining,innovation management that streamlines R&D, yet respects itscomplexity, is now a real possibility. IN DEPTH: From IT to ET: Cloud, consumerization, and the next wave of ITtransformation Web services can, for example, be used to support "plug and play"integration of multiple data types and formats without requiringcustomized (and expensive) IT intervention. As data previously scattered throughout the R&D organization ismade accessible through a single framework to the ERP and PLMsystems, a number of time, cost and efficiency benefits can berealized. First, information, no matter where or how it was generated, can beutilized by contributors across the product development valuechain, enhancing collaboration and speeding cycle times. Toxicologists can make their history ofassay results available to formulators developing recipes, forexample, or chemists can work more closely with sourcing experts toensure that the compounds they are developing in the lab are viablecandidates for large-scale production. Second, processes, such as product specification management, thatwere previously disjointed due to critical data being locked withinisolated databases and proprietary systems, can be streamlined andautomated without hampering the unique R&D methods deployed byindividual contributors. And third, the company as a whole canbetter track and reuse valuable data to bring the final product tomarket, speeding that process. Furthermore, cloud technologies provide an ideal forum forstakeholders engaged in product development to interact and shareideas regardless of where they are located or how much data isinvolved. Advanced categorization techniques such as semantic search and text analytics can also help remove the time and costconstraints involved in extracting the context from complexcontent. CIOs have deployed technologies to help their organizations tostreamline manufacturing and the supply chain. The next step is tobring the innovation lifecycle into the fold. Solutions that offeran underlying framework for innovation lifecycle management whilestill providing capabilities uniquely suited to the complexities ofR&D will help today's organizations close productivity gapsbetween the research lab and final product. Accelrys.com is a leading provider of scientific informatics software andsolutions for the life sciences, energy, chemicals, aerospace andconsumer products industries. The author's blog can be found at: blog.accelrys.com/author/michael/ Read more about infrastructure management in Network World's Infrastructure Management section. We are high quality suppliers, our products such as Windows Genuine Microsoft Software Manufacturer , China Windows Product Key Sticker for oversee buyer. To know more, please visits Windows COA Sticker.
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