Joe Weinman describes, in understandable terms, what leading companies such as Netflix, GE, Nike and Amazon are doing to leverage information technology to create competitive advantage. He has discovered four generic strategies: information excellence, solution leadership, collective intimacy and accelerated innovation, which differ substantially from the business strategies available only a few years ago. Rather than offering indecipherable platitudes, he lays out the critical steps that any company, regardless of vertical, can follow to exploit today’s and tomorrow’s digital technologies. For example, innovation has followed a long history from individual inventor and tinkerer, to “shop invention” such as Edison’s Menlo Park Lab, to the first true industrial research lab at GE, through a period of “open innovation.” Now, however, innovation must also encompass ad hoc relationships through idea markets, crowdsourcing and challenges/contests such as the Netflix Prize or GE’s FlightQuest. Products are becoming smart, digital and cloud-connected, enabling solution leadership strategies such as the Nest Thermostat but also the Nike Hyperdunk+ Basketball shoe, which has pressure sensors that can connect to cloud services for activity tracking and on to social networks. Weinman also explains how to leverage common threads across the disciplines, such as behavioral economics and gamification.
This talk is for select audiences only. It is highly relevant for cloud and information technology practitioners, vendors, service providers, investors and analysts, and uses extremely quantitative analysis to examine utilization benefits associated with workload aggregation and implications for cloud market provider size; latency reduction through service node dispersion and its implication for public cloud economics; trade-offs in network architecture and performance benefits from intelligent network services; optimal breakeven points for hybrid clouds based on workload statistics; and quantifies benefits associated with provisioning interval reduction in light of demand characteristics.