Industry 4.0 generates a lot of hype — making it easy to forget the essential purpose of implementing the technology; running and growing the business.
C-suite executives rarely interact directly with this smart tech, but that doesn’t make it any less vital for businesses, according to Forbes.
It improves customer service, achieves operational efficiencies, innovates for the future, reduces risk, meets standards and regulations while improving company management. Let’s not forget the most important challenge — meeting the expanding demand for increased agility, speed, predictability and quality.
The demand never ends, creating an arms race to serve the customer the way they want while maintaining cost-effective production.
“What used to take generations is happening at a very rapid pace now,” says Erik Nistad, director of ITS for Mondelez International, in Forbes.
As a consumer products company, Mondelez must produce different products in different packages to serve different customers throughout the globe – all with the same high quality, he says.
In China, for example, customers want green tea-flavored Oreos. In developed countries, the company sells big packages of cookies; in developing countries, it sells smaller packages to customers with less discretionary income.
Meeting that variation drives the need to do localization and customizations. What was previously a “black box” to the C-suite, the factory is now the core in a demand-driven supply chain. Plants are more predictable, reliable and responsive in order to meet the needs of a changing market.
New approaches to product development are now possible thanks to digital transformation, creating an intelligent infrastructure that seamlessly connects design, manufacturing, automation and the supply chain.
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Large universities in the U.S. are faced with the increasingly emergent problem of updating their building’s aging infrastructure, with many campuses housing buildings built in the 1800’s.
As the 10th largest university in the U.S., Pennsylvania State University is a highly competitive institution. When it came time to upgrade their dated infrastructure across their expansive campus, the stakes were high.
Resources were right and the project couldn’t wait, forcing the Penn State IT and Plant Services departments to put a plan in action — fast.
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Companies dominating the life sciences world have begun to embrace the opportunities of Big Data & AI, with predictions to really make a difference in 2018.
Notable progress in drug development and the quality of insights produced at the research stage are a result, however opportunities to utilize the data for larger gains continues to grow, according to Forbes.
Here’s five major ways Big Data and AI will impact life sciences in 2018:
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The environment in the US will be increasingly hostile to high drug prices. This will make it essential for life science firms to defend their research budgets and profit margins by utilizing robust data and clearly demonstrate the value of their products.
Life science firms have had a hard time improving the speed and quality of bi-directional learning between patients and the drug discovery process due to poor data access and quality issues. As new best practices in data strategy are created, the industry continues to move towards the value unlocked by such translational medicine to accelerate.
Risk and inefficiencies continue to be life science supply chains’ biggest challenge. The employment of new technologies, such as blockchain, offers the potential to radically improve levels of control and quality measurements. Overall costs for infrastructure dramatically reduce as a result.
New branches of science are deepening our knowledge of genomics — the study of structure, function and mapping of DNA/ genes — creating opportunities for utilizing AI to gain previously impenetrable insights. Although still at the research stage, it’s predicted these techniques will impact fields such as oncology.
With all of the different fields of study opening up, at the end of the day the most important is the economical impact. Accessing and analyzing the right data to deliver sustainable business value remains the central purpose for life science firms.
Whatever the coming year holds, one thing is beyond doubt: Exciting new ways to create value and improve patient care await those firms willing to exploit the data tools and techniques that are now emerging.
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