There are two extreme ends of the retail business model, each with its pros and cons. At one end all stores are virtually identical (think chains like Starbucks, Gap, Subway, etc.), which makes for simpler operations and a consistent, predictable customer experience. On the flip side are chains where the owner operator has a great deal of discretion on assortment, pricing and promotions. For example, retailers like Aeon Group in Japan, ICA in Sweden and Metro in Canada give significant control to store operators.
According to IBM, 2.5 exabytes of data are generated each day. Every click, like, share and mention generates unlabeled data that can’t be dealt with by traditional statistics. Harnessing this data to deliver personalized user experiences can translate into billions of dollars of incremental revenue: This is the province and promise of deep neural networks (DNNs).
Computerization, the Internet and automation ushered in Industry 3.0, revolutionizing the way we work. Now there’s IoT, cloud computing, 3D printing, autonomous vehicles, mobile, social and Big Data. Welcome, Industry 4.0. In the not-to-distant future supply chain planners will sit in control rooms with a real-time view of inventory at all nodes of the supply chain.
Before a potential customer books a trip, applies for a loan or rents a car, he or she may be exposed to 10 or more touchpoints from a brand. How does the marketer know which ads are most effective? What are the synergies driving conversions? How does the effectiveness of marketing spend across multiple channels change over time?
Undoubtedly, “blockchain” is one of the key technology buzzwords of 2017. While there is still considerable hype around this topic, we’re starting to see real projects using blockchain, and real value emerging in certain markets. In this blog, I’ll look at several recent examples that highlight the drive for innovation behind blockchain’s adoption—but first, let’s cover some definitions.
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