Odds and ends
The cloud-to-edge debate was a hot topic, but it was hardly the only theme tackled by Levine and his panel peers -- Accel partners Rich Wong and General Catalyst Managing Director Steve Herrod offered some other thoughts about emerging trends.
From big data to machine learning: Big data 1.0 included collecting lots of information but the next wave involves predicting what is going to happen in the future, said Levine. "Machine learning unlocking these vast stores of information that we have... that can help us predict the future in better ways is absolutely happening right now," Levine said. For example, machine learning is used to predict cybersecurity attacks and IT system failures.
Wong said that enterprises can use machine learning to automate IT service functions, such as password resets for customers. Entrusting such corporate operations to machine algorithms can yield anywhere from 30 percent to 100 percent cost savings, the VCs said.
Bottoms up, the polite euphemism for shadow IT: Wong said that while VCs encourage portfolio companies to deploy a "land and expand" strategy and get into businesses through departments rather than going through the CIO,it's a delicate balance. The CIO must grapple with the challenges and risks associated with adopting potentially unproven technology but benefits from the speed of on-boarding employees. Thanks to the cloud, many are onboarding themselves. Levine says that shadow IT has extended to developers. "I've seen situations where if the organization doesn't provide what the developer needs, they go to another company to get services and tools," Levine says.
Proof-of-concepts -as-a-service: It's become fashionable for CIOs to fancy themselves as "IT-as-a-service" providers, essentially brokers of digital capabilities, including cloud, mobile, analytics and IoT. In this model, it makes sense for CIO to recognize that proof of concepts are a valuable way to evaluate new technology, Herrod said. He suggested that startups offer proof-of-concepts as a service to help.
The winner for hardest position for CIOs to hire goes to… Data analysts: Levine says that if data is the most important ingredient in unlocking business value, then data scientists and analysts who can derive insights from the data and turn it into actionable information will be the toughest positions to fill.
Herrod disagrees and says that he’s found the hardest hires are DevOps leaders because there is little consensus on what defines DevOps, a model for rapid software development model popularized by consumer internet companies. Herrod says that he's heard descriptions of DevOps managers range from as scrum masters who run agile computing systems for speed and innovation to specialists who optimize cloud infrastructure.
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