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Editor's Pick (1 - 4 of 8)
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The Evolving Product Lifecycle Management Landscape

David DiLeo, CIO, Industrial Scientific Corp

Evolution of Information Technology

Joe Sheridan, Corporate Director Of IT & CIO, Soave Enterprises

At the Cross-Section of PLM and Technology

Brian Parnes, CIO, VP of Marketing, Design & Product Development, Downlite

Managing Technology at 360 Degrees

Jeff Palm, CIO, Allianz Life

Schiavello Manages Risk Exposure with Document Management

Bernard Wansink, CIO, Schiavello Group

Building a Cognitive Business

Kenny Hay, Director of Cloud, IBM ASEAN

Have You Done All You Could to Prepare for a Data-intensive, AI-enhanced Future?

Michael Alp, Vice President, Pure Storage Asia Pacific and Japan

Want Your Next Project to Succeed? Engage Your Stakeholders

Billy Ingram, Director of Lean Product Development, Interface

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Emerging Technologies and Product Lifecycle Management: Enabling Smart People be Smarter

Daniel Bender, VP-SAP PLM Solution Management, SAP

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Daniel Bender, VP-SAP PLM Solution Management, SAP

Emerging mobile, Big Data, and cloud technologies are fueling a revolution in information management. In product development for process manufacturing businesses, R&D staff is moving – perhaps a bit reluctantly – from analog to digital processes. Core applications and laboratory systems are becoming accessible to authorized personnel anytime, anywhere, and on any device. You are collecting an unprecedented amount of information on market and industry trends and on customer transactions and preferences. All this data helps you understand demand and evaluate profitability. Now you can spare yourself some of the chores of application management by running infrastructure components and core applications in the cloud. Learn how you can master these trends as quickly as possible by embracing an approach that gives you, your employees, and your organization a competitive advantage. Boosting Decision Making Through Enterprise Mobility Traditional lab systems often captured only predigested research data, entered primarily for delivery downstream. Initial back-of-an-envelope ideas and unstructured data like correspondence were often lost forever, and even core data sets remained isolated from one another on individual departmental systems. Each Lab Information Management System (LIMS) and each piece of equipment stored its own metrics, making comprehensive analysis a daunting task. The evolution of mobile devices like smart phones and tablet computers helps eliminate some of these data disadvantages. As researchers become comfortable using handheld devices, they can record even passing inspirations that may trigger other creative ideas. Such transparency into the creative process vastly expands access to historical issues and opportunities. Evolving User Interface (UI) technologies support rapid development of platform-independent solutions that readily accommodate the most popular devices, including those based on Apple, Android, and Microsoft operating systems. And a flood of mobile apps helps everyone share valuable experience and information with all team members – whether they’re at home, on the road, in the office, or in the laboratory. When all relevant details are a finger swipe or button click away, your product developers don’t have to reinvent the wheel each time they design a new product. And that means smarter decisions, faster production, and better products. Mobile technologies also boost collaboration by helping stakeholders share product development data across traditional departmental boundaries. What your chemist, engineer, or food scientist thinks and does is transparent to relevant players in

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Top PLM Companies

manufacturing, quality and compliance management, sales and marketing, and warehousing and logistics. These downstream workers – those responsible for the commercialization of products under development – can now contribute to the development process without having to learn a different application or use a tool that was designed only for product developers. Product development can be integrated in greater depth than ever with all other phases of the product lifecycle. Harnessing Big Data for Big Jobs Today’s end consumers grew up with mobile devic¬es and social media. They expect that “there’s an app for that” and give their allegiance to products that offer superior quality and maximum choice –at the right price. They expect companies to champion sustainability and demonstrate that commitment in product ingredients and packaging. More than ever, the adage that “the customer is king” is true even for businesses that don’t directly deal with the users of their products. To please such informed and vocal consumers, you must put them at the center of product development and either deliver what they want or convince them to want a product you’re developing. You need to collect and analyze all available information on competitive offerings and social and industry trends. To initiate tightly tailored marketing campaigns, you must deepen your insight into the personal preferences and purchasing history of each consumer. And while you’re busy gathering all this information, the number of regulatory requirements you must keep in mind during product development, manufacturing, and distribution continues its relentless increase. How to collect and manage this data – and equip your users to analyze it – is a burgeoning challenge for CIOs. You must aggregate a vast array of data sources, including online chat rooms, customer interactions, lab information, and government specifications, to help developers make smart, profitable choices. And you need to take into account other drivers of product development, such as manufacturing capability, stock position, and resource availability to ensure the smartest design. There is good news. The latest Big Data technologies have caught up with and are pushing these trends. In-memory computing now enhances both the speed and thoroughness of decision making by letting you evaluate and analyze massive amounts of data in real time; comprehensively, effectively and efficiently. Simple-to-use analytics solutions help all stakeholders make complex evaluations with similar speed and ease. In fact, some of the best analytics solutions can predict future results based on documented trends. Reducing Your Infrastructure Footprint at the Same Time Process manufacturing is not exempt from the twin squeeze facing twenty-first-century commerce. As CIO, you are under constant pressure to help people work faster and be smarter, providing solutions that are simple and easy to use while reducing overall costs. You must help your internal clients evaluate Big Data in real time and manage the newly mobile enterprise while paring down infrastructure investments and maintaining, or even cutting, IT staffing. Cloud computing saves you time, money, and effort by letting you run core systems virtually, offloading routine maintenance, administration, and tool deployment. With cloud solutions for product development, you can bring software and process enhancements online at significant cost savings while protecting innovation and moving projects into production faster. Employees can typically begin using new or updated functionality within minutes – instead of weeks – and you can shrink your total cost of ownership. In the realm of product development, cloud solutions change the very way people innovate. With an array of well-connected and user-friendly solutions, you can fully digitize the development process while providing real value to consumers of the data later in the commercialization process. Your new products quickly please consumers and drive greater profitability and brand value. Leveraging Mobility, Big Data, and Cloud Computing The latest technologies for mobility, Big Data management, and cloud computing help you fulfill three key requirements for producing successful new products while containing costs: • Integrating the development process from laboratory to factory with solutions that help developers make smart decisions quickly and easily • Delivering deep product design and development data effectively downstream to the people responsible for commercialization •  Shifting as much of your basic computing as possible into cloud-based back offices, analytics solutions, and tools.

 

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