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
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