The Home Depot can help. Credit: iStock By Bryan Kirschner, Vice President, Strategy at DataStax Everybody’s building a data strategy. In October, we surveyed 500 executives and technical practitioners in the United States. None reported that a data strategy was not a priority for their organization. The Home Depot motto is “how doers get more done.” In a recent interview, Fahim Siddiqui, senior vice president of information technology at Home Depot, offered some raw material that’s highly relevant to doing data strategy right. In this article I’ll highlight how what he had to say maps to an analysis we conducted of 35 characteristics of a data driven enterprise. It surfaced five clusters we organized from those currently driving the most business impact with (“leaders”) to those with the most barriers to creating material impact. Make the most of cloud for data velocity. In response to the coronavirus crisis, Siddiqui and his team were able to widely deploy a pickup solution in two weeks. One of the biggest gaps we see between leaders and those lagging behind is the ability to ship data products as fast as apps and scale data with apps. To some extent, this is not a surprise: DevOps is a decade old. “DataOps” promises to do the same for data velocity, but is at an earlier stage of maturity and adoption. On the other hand, procrastination at making the most of the cloud is an unforced error. Siddiqui says that “a cloud architecture also was critical to manage a 300% spike in traffic and 80% order volume increase…being on the cloud made it all happen, basically on demand.” Most enterprises have a hybrid cloud strategy. But today’s leaders, like Home Depot, are more likely to have already implemented a hybrid data strategy. Focus on differentiation. Today’s leaders excel at turning data into revenue by focusing attention on improving operations or enhancing the customers experience. The Home Depot buys best of breed software when possible, choosing to focus the attention of its software engineers on “unique challenges in terms of our unique business model.” Data-driven enterprises get compounding returns from the scope of data, the scale of data, or both. More online purchases, for example, feeds a smarter recommendation engine, which contributes to more online purchases. But it holds true throughout the value chain. Siddiqui describes Home Depot’s delivery warehouses as “unique,” saying that “we are now able to actually hire an associate and within five minutes they are productive [in] the warehouse, no more training required.” Cascading the difference between minutes versus hours or days to productivity delivering digitally-enhanced interactions with customers (such as curbside pickup) through thousands of employees feeds a similar virtuous cycle. Make the most of open source. The world will create more than three times the data over the next five years than it did in the previous five. As the ratio of “data with which to create value to humans with the skills to do it” multiplies, the opportunity cost of re-implementing something already built explodes. Leaders are overwhelmingly increasing their use of open source technologies. The Home Depot is all-in, with all of its home-grown apps built on open source. Read about why data-driven enterprises should feel optimistic here. About Bryan Kirschner:Bryan is Vice President, Strategy at DataStax. For more than 20 years he has helped large organizations build and execute strategy when they are seeking new ways forward and a future materially different from their past. He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing. Related content brandpost Sponsored by DataStax Ask yourself: How can genAI put your content to work? Generative AI applications can readily be built against the documents, emails, meeting transcripts, and other content that knowledge workers produce as a matter of course. By Bryan Kirschner Dec 04, 2023 5 mins Machine Learning Artificial Intelligence brandpost Sponsored by DataStax Generative AI: now is the time to ‘learn by doing’ New survey reveals that IT practitioners are confident in their ability to build and benefit from generative AI. 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