Analytics and Decision Support
Can you articulate the financial impact of innovation on your business? Join the conversation and discuss topics that include: aligning innovation performance to strategy, increasing visibility to innovation data, improving cross-functional and global knowledge sharing, dealing with big data, and increasing the focus on results and organizational accountability.
Looking for examples of how to apply machine learning to solve real business challenges? Here’s an example of how one oil & gas company uses machine learning to get insights from high volumes of well data to optimize production and equipment performance.
Kellogg's new Caticorn cereal is covered in edible glitter and certain to make your morning special.
Smart factories, enabled by digital technologies and concepts, may not be as futuristic as you think. Need inspiration to get started? Here's our UPDATED vision of the factory of the future, and the people and processes that will be impacted.
The move to the IoMT has huge benefits, but many potential challenges along the way. Here are just a few key things to consider as you pursue your IoMT journey.
Protecting devices in the field requires an innovative approach to comprehensive information security. Here are nine security strategies to help mitigate risks while building a culture that enables innovation, compliance and operational effectiveness.
To solve the dependency of exploring a frame assortment with physical product, Warby Parker lhas aunched its Virtual Try-On app.
Amazon is piloting a program that sends customers samples, free of charge, based on consumer data and machine learning.
In the second video of our KNOW series, we explore the application of advanced analytics to product development data.
Bummed out because you didn't get everything you put on your holiday list? We have you covered with our Ultimate Innovation Wish List.
To be more nimble, productive and profitable, retail, footwear, and apparel companies need to focus on increasing efficiency in the product development process. Here’s one practical example of the application of advanced analytics to achieve this goal.
For years, eCommerce retailers have had real time data about who is on their site, what they are looking at, for how long, what they buy, etc. Brick and Mortar stores not being able to access this data is where Xenio saw a market opportunity to offer real-time customer visibility, analytics and dashboards to optimize the guest experience and the design and merchandising of physical locations.
The retail industry has drastically transformed throughout the last several years due to a multitude of factors. With the combination of factors at play, retailers are challenged to efficiently adapt to or drive value with digitalization.
Stewart specializes in finding practical analytical approaches to improve organizational performance across a wide range of industries, including healthcare, consumer goods, retail, education, and legal. He understands that good data analysis is a servant of good judgment, not a substitute for it. He would never ever apply analytics to darker ends, like sports betting, as that would be illegal and immoral.
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