You remember Zeno’s famous Dichotomy paradox. Roughly paraphrased it says: if you want to walk, for example, from your chair to the door, first you have to walk halfway there. And before you walk halfway there, you have to walk a quarter of the way, and so on ad infinitum. You can never reach your destination. Of course, after all that you simply stand up and walk to the door.
Could it be that the act of merely contemplating implementing Big Data in an organization can brings on an attack of Zeno’s conundrum?
Writing in Forbes, Matt Ariker, McKinsey & Company COO of the company’s Consumer Marketing Analytics Center notes that “Many who make the Big Data journey are overly fixated on making it to the ‘Promised Land.’ In far too many cases I see people who plan to build out a complete system and architecture before using a single insight or building even one predictive model to accelerate revenue growth.”
He recommends first clearly defining your end game – knowing where you are going before you start the journey. Then the trick is to avoid the fallacy of believing that you can’t gain any insights until the entire Big Data infrastructure is in place. Says Ariker, “Think of it more like a tool factory making all sorts of specific tools for specific jobs. Every time one tool is complete you can begin using it; you don’t have to wait for all tools to be complete.”
The consultant then offers four helpful pieces of advice that he uses to counsel his clients. These include: assigning the creation of an Insights Roadmap to a highly skilled team with the relevant skills; creating a detailed business case that focuses on P&L impact; and starting small by cherry picking already available data sets. Here’s the fourth and final step.
Build a roadmap. I know this step sounds obvious but I’m constantly surprised by how little effective planning takes place,” comments Ariker. “As counterintuitive as it may sound, it takes planning to work fast. Make sure you’re focusing on the models and necessary infrastructure that deliver the most value, and sequencing them all to minimize delays. Put in place clear data delivery deadlines and test timelines for each model to ensure timely delivery… One high tech company followed this “Insights Roadmap” route. By following the four steps I laid out above, the company started generating insights within two months of the project starting, long before the two-year Big Data warehouse build project was completed. Within three months, the company was able to book $5m in additional revenue. By end of year one, incremental revenue exceeded $75m. Your journey to reach Big Data’s promised land will take time. But realizing value doesn’t have to.”
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