The new era of data analytics requires a new approach to problem solving, and many organizations find challenges and governance models of data analytics are also changing.
Big data analytics solutions provider Mu Sigma released results of its inaugural "State of Analytics and Data Science" report which found many companies are approaching data analytics in an unproductive way.
"Many businesses are still misguidedly prioritizing data and technology needs over the need for better decision making," Tom Pohlmann, head of values and strategy at Mu Sigma, said in a statement. "Changes in consumer behaviors are leading to a scramble for new capabilities and offerings — which in turn fuels the need for analytics and insights. But because businesses aren't paying enough attention to creative problem solving, they are falling short in analytics."
The survey collected responses from 150 respondents during the first calendar quarter of 2016. Respondents represent firms with at least $500 million in annual revenue. Here are five key findings and trends from the report.
1. One-third of respondents said data quality, consistency and availability are the most important issues affecting analytics initiatives, and 30 percent said a lack of skills were the second-highest challenge. The survey found "underperforming" companies were more likely to say a deficiency in talent is their most pressing challenge in analytics.
2. There still isn't a clear picture on who oversees data analytics. Among respondents, analytics governance was spread among the C-suite, including CIOs, CFOs, chief analytics officers, chief data officers and others. While 23 percent said their CIO oversees data and analytics, 17 percent said the CFO does, and 13 percent said the relatively new CAO does.
3. There are numerous governance models, as well. Forty-four percent of respondents utilize a centralized model, where one group provides analytics services to the rest of the organization. Twenty-two percent use a decentralized model. Sixteen percent use a federated model, a combination of centralized and decentralized approaches, similar to a hub-and-spoke model.
4. The survey found organizations with centralized models were more likely to have the CIO oversee data analytics, as it likely is the governing model in traditional IT environments. Additionally, when changing the governance and organization of analytics, companies were more likely to adopt a centralized model.
5. Nearly four in 10 respondents said their organizations do not follow a consistent methodology for problem solving and instead plug holes in their data and workforce. However, 24 percent of respondents said developing a clear roadmap of how to address analytical business problems would be a top priority in the coming year.
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