As Vince Lombardi once said: “If you’re not keeping score, you’re only practicing… not playing.” In business and institutional settings, analytics is how we keep score.
Analytics is defined as the process of analyzing statistical data to gain insight. The depth and scope of insight to be gained is demonstrably substantial; so interest in metrics, analytics, infographics and visualization continues to grow in businesses and institutions. In some settings, like federally-supported health care systems, moving to an analytics-based model is a mandate with looming deadlines. In a sense, small-to-medium size businesses have some serious deadlines approaching as well.
For the most part, business executives understand the need to harness the power of “big data,” analytics and predictive analysis to stay competitive; but many have no idea where to begin, or how to transition to a data- and analytics-driven business model. Much of the material in this post come from a Foreword that I wrote for a new e-book on the subject entitled: Analytics 2 Insight.
Quoted in a recent Forbes article, Michael Cristiani at Powerhouse Factories might have captured it best, telling Reuters that small businesses already have most of the data they need. “The world runs on data and analytics,” he said. “They’re starving for the insights.”
Analytics can be applied to identify trends, patterns, and anomalies so that businesses, institutions and agencies can lower costs; reduce risks, enhance performance and increase value through data-based decision making.
Analytics is a powerful decision support tool, and is particularly useful to aligning strategy to business/institutional objectives. By combining statistics, operations, marketing, and financial analysis with data from internal and external sources, a better understanding of trends, patterns, and interactions can be established. That is what insight is all about.
Analytics service engagements range from predictive and propensity modeling to sensor monitoring and anomaly detection. Analytics and “big data” are the next revolution in the digital world. Data visualization decreases time-to-insight, ensuring relevancy and magnifying actions and interventions.
Editor's Note: this is the first installment of a series of articles I have planned on the subject. So stay tuned, more to follow. #BigData #Analytics #Metrics #NewBook #Business