Sep 24, 2020
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Making Money in the Cloud — There’s a Word for That

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By Mark Herman Industry and government have untold amounts of data at their disposal and like flecks of gold there are valuable pieces which are frustratingly hard to access given the limitations to common approaches to data analysis. But except for losing potentially priceless knowledge from this knowledge – a deficit that’s increasingly the focus of big data discussions – these institutions are leaving money at the table potentially a large number of it


Just as public companies measure their financial performance at the income measure Earnings Before Interest Taxes Depreciation and Amortization (EBITDA) the driver for advancements in data analytics should be Cloud EBITDA. More decisions about data analytics should be driven by the base line question: how can I monetize my data? Working example not too long ago an industry client widespread for its discuss efficiency expressed frustration to me about the limits of the organization s on-site technology


The firm was sharing about 40 percent of its data with financial exchanges only to be scooped up by third-party firms that repackaged it and then sold it back. Essentially the organization was buying back its own data since it had no other choice – the data couldn t be processed internally


If you re wondering what the cloud can do for you it truly is the big score. The cloud opens up a whole new way wherein companies can store manage and important analyze the untold amounts of data they have at their disposal. Today data scientists may spend up to 80 percent in their time searching the data and only 20 percent analyzing it


As analysts are free of the limitations of specific data structures that limit their queries they can ask more intuitive questions of the data or ask different new questions with a focus on what maybe profitable. They can flip the ratio conducting quick searches across all varied data and spend 80 percent in their time analyzing it


Interesting and potentially powerful combinations of data from areas not traditionally included in the mix can result in breakthrough insights and concepts for greater revenue and cost – I ve seen this happen firsthand. It truly is Cloud EBITDA realized. To illustrate one of our international airline clients mined three years and 100 gigabytes worth of data on passenger behavior the airline s performance flight connection times and more


The airline tried analyzing smaller data sets but this yielded limited results because the data was siloed into separate databases. Yet once the airline began to apply big data analytics tools within its own cloud the results were more robust. The analysis indicated among other things how to better manage and support important higher-paying passengers


Ultimately these findings and the next changes in their customer service strategy contributed to the airline s base line and helped them achieve Cloud EBITDA. PROMOTED Civic Nation BRANDVOICE | Paid Program
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Education Not Marriage: Building Better Futures For Girls In Ethiopia And that s just the direct revenue part of Cloud EBITDA


Indirect benefits of advanced analytics also can contribute to better base line results. Improvements to data collection and analysis leads to more streamlined and cost-effective operations improving profitability. Chief investment officers can use improved data analysis to build more robust peer analysis and higher know how to outperform competitors. And finally better data collection and analysis can generate more helpful information for investors building an improved case for a company s long-term performance


So if the advantages are clear and the technology is there why aren t organizations adopting advanced analytics at rapid speed? Concerns about security are a major obstacle; so too is a lack of knowledge round the role of data science. With more data available to analyze it s all the more important to appreciate what questions to ask


A strong data science team should include a mix of math computer science and statistics experts in addition domain experts from the organization. These domain experts contribute to an improved understanding of the mission at the data science team level and carry back new insights to organization decision makers. In an atmosphere where there is tightened spending and a drive for efficiency in nearly every market sector the base line benefit of Cloud EBITDA can t be ignored


But like any innovation in any good organization it will take risk innovation and a forward-thinking approach to achieve – something successful leaders are known for. Mark Herman is an executive vice president with Booz Allen Hamilton and leads the firm s Value from Data initiative. Gallery: Tim O Reilly: The World s 7 Most Powerful Data Scientists
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