![]() ![]() To make sense of those new streams of data, the company is also building a cloud-based platform called Predix, which combines its own information flows with customer data and submits them to analytics software that can lower costs and increase uptime through vastly improved predictive maintenance. GE is spending $1 billion this year alone to analyze data from sensors on gas turbines, jet engines, oil pipelines, and other machines and aims to triple sales of software products by 2020 to roughly $15 billion. To avoid a similar disruption as the industrial world goes online over the coming decade, Immelt is driving a radical shift in the culture and business model of his 124-year-old company. GE’s CEO is keenly aware that so far in the 21st century, the digitization of commerce and media has allowed a handful of US Internet stalwarts to capture almost all the market value created in the consumer sector. Immelt reached his conclusions from witnessing-and, in many respects, leading-the revolution. Two scenes from the front lines of the revolution (See “ Making data analytics work for you-instead of the other way around.”) This article poses questions-but not shortcuts-to help a company’s senior leaders determine where they are and what needs to change for their organization to deliver on the promise of advanced analytics. That includes a clear-eyed assessment of the fundamentals, including your company’s key value drivers, your organization’s existing analytics capabilities, and, perhaps most important, your purpose for committing to analytics in the first place. Product managers have to be different salespeople have to be different on-site support has to be different.”ĬEOs who are committed to a shift of this order, yet wonder how far the organization has truly advanced in its data-analytics journey to date, should start by stimulating a frank discussion with their top team. I thought if we hired a couple thousand technology people, if we upgraded our software, things like that, that was it. “This is something I got wrong,” admits Jeff Immelt, the CEO of GE. Critically, an analytics-enabled transformation is as much about a cultural change as it is about parsing the data and putting in place advanced tools. The shortfalls, however, are more than just a matter of perception, and the pitfalls are real. Individually, any one of these gains may appear insignificant, but when considered in the aggregate they can pack a major punch. Ironically, the results of “big data” analytics are often thousands-or more-of incrementally small improvements realized system-wide. Some of the disconnect between promise and payoff may be attributed to undercounting-the sum of the parts is not always immediately apparent. In fact, when we surveyed a group of leaders from companies that are committed to big data–analytics initiatives, three-quarters of them reported that their revenue or cost improvements were less than 1 percent. ![]() It’s easy to see how analytics could get delegated or deprioritized: CEOs are on the hook for performance, and for all of the potential associated with analytics, many leaders operating in the here and now are reporting underwhelming results. Those who ignore or underestimate the eventual impact of this radical shift-and fail to prepare their organizations for the transition-do so at their peril. Changes of this magnitude require leadership from the top, and CEOs who embrace this opportunity will increase their companies’ odds of long-term success. In the science of management, the revolution in big data analytics is starting to transform how companies organize, operate, manage talent, and create value. The revolution isn’t coming-it’s already under way.
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