The Decision Maker

Report from the Frontier

Posted by Aaron Wang on Jan 19, 2014 3:34:21 PM

In the December 2013 issue of the Harvard Business Review, reporting and analytics guru Thomas Davenport writes about how far the innovators in the analytics field have advanced.

Davenport divides the evolution of analytics into three eras.

Analytics 1.0 – This first era was marked by the first widespread use of data to support fact-based decision making. The idea of data warehouses became more main stream as enterprises began to organize their internal data specifically for the purpose of better analyzing historical data.

Analytics 2.0 – The next big change was in the mid-2000’s when innovative online firms started to amass very large sets of data from both inside and outside the organization. Advanced analytical techniques were developed to dissect these immense data volumes. A signature breakthrough in this “Big Data” era was the rise of predictive analytics that among other things helped anticipate consumer demand and deploy individually tailored ads.

Analytics 3.0 – Davenport sees the emergence of a new era where “every firm in every industry” is harnessing the power of data in multiple forms and from multiple sources to drive performance. A hallmark of this era will be the embedding of data-driven processes in both internal tools and in products and programs facing the customer. Among numerous examples is a UPS logistics application using sensor data from its 46,000 truck fleet to reconfigure delivery routes in real time. In 2011the program led to 85 million less miles driven with 8.4 million gallons in fuel savings.

Leading U.S. credit unions and community banks have been working through the steps to becoming fully effective at the Analytics 1.0 stage. However, many others are still waiting to begin the journey. The message for those considering adopting an analytics program is the time for waiting can no longer be justified. The cost and complexity of tools for embarking on such an initiative have decreased significantly in the last five years.

At the same time, consumers expect their credit unions and banks to be technology-savvy. Deposits and loan business will inevitably flow to up-to-date organizations because they can offer the best rates and service.

An organization doesn’t need to aspire immediately be an Analytics 3.0 competitor. However, taking those first steps into Analytics 1.0 is required to remain relevant in this rapidly evolving marketplace.

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Topics: Reporting and Analytics, Credit Unions, Data Analytics