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Making Your Data Come Alive: Step 3 - Leveraging Analytics as a Key Differentiator

In parts one and two of this article series, we discussed the process of readying data for use by business intelligence (BI) applications. If we assume that a company ultimately has data available in a well-organized and technologically appropriate structure, the next step is to make the data "come alive."

In one of those old TV commercials the pitchman shouted how the gadget being sold 'slices and dices,' and he persuaded us that such a capability is essential in every kitchen. Similarly, slicing and dicing business data into business intelligence using advanced data analytics is a critical business imperative and should be a part of any business strategy. In parts one and two of this article series, we discussed the process of readying data for use by business intelligence (BI) applications. If we assume that a company ultimately has data available in a well-organized and technologically appropriate structure, the next step is to make the data "come alive."

First of all, when beginning a BI initiative, abandon any expectations that analytic tools or data exploration will be performed widely by many people throughout the business. It is important to recognize that not everyone has the aptitude, the patience or the interest to learn how BI software works, how datamarts are structured or how to perform complex statistical analysis - remember all those perpetually blinking VCRs that show 12:00 on the clock? In an earlier article we discussed how companies should have a "Data Czar" responsible for the quality and integrity of enterprise data. Similarly, companies should have numerous BI gurus scattered throughout the organization who have the passion, drive and institutional knowledge to learn the subtleties of the data residing in the data marts. These people will also have the aptitude to learn the software, which will allow data to be queried, transformed, mined, summarized, reported and modeled. People who best fill this role have special skill sets, are technically savvy and often have deep institutional knowledge and business acumen. More often than not these people already exist within organizations and currently serve in informal roles where they are the go-to people for management information - the business equivalent of Radar O'Reilly from the M*A*S*H TV show. The objective should be to identify these people and structure BI careers for them to create loyal and ambitious BI missionaries who will develop and spread BI learning throughout the organization. Companies that can quickly mobilize this analytic army within their organization will be able to leverage BI faster, cheaper and more efficiently than those companies expecting broad organizational adoption of BI tools as a first step.

Another important ingredient is to identify essential management dashboard criteria and metrics, as well as strategic data usages, as the DNA for core BI analytics. If people throughout the organization recognize that the BI process is the source for the information they are expected to use, BI tools will be more readily accepted and a culture that has a "need to know" and the "need to learn" will evolve. And since so much in business needs to be done fast and smart, BI tools and applications should be selected to respond to the "need for speed." This is another reason why BI Gurus are essential: They insulate the business from the often subtle technicalities of the requisite queries and analysis.

In the near future we are likely to see watershed years resulting from the billions of dollars that have been spent on data aggregation and technologies leading up to BI. Throughout the business community senior executives are now expecting results from their investment. How BI technologies will ultimately redefine the winners and the losers remains to be seen. But as companies move BI beyond the mundane to the truly technically advanced, incredible improvements should be realized. Already key analytic technologies with very high ROI have emerged. Some such tools that come to mind are predictive models and data mining tools that help to retain the best customers, select new profitable customers, price products and services more optimally, more accurately assess risk and better manage a more productive and profitable sales force. But these and other BI tools don't produce business benefits just through their mere existence; they must be implemented and leveraged in an effective end-to-end business process, not from mere technical projects.

Every business should keep this in mind and avoid technology churn and "analysis paralysis." Do what you can yourself and hire outside help when necessary and expeditious but focus on achieving business value as rapidly and strategically as possible. Making data "come alive" in new and unique ways is where the money is, and it is this ability to achieve data mastery that will be one of a company's ultimate key differentiators and potent competitive weapons.

John Lucker is principal, Deloitte Consulting LLP, Practice Leader - Advanced Quantitative Services (Data Mining & Predictive Modeling). He can be reached at [email protected], 860-543-7322.

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www.deloitte.com

John Lucker is Deloitte's global advanced analytics and modeling market leader and a leader for Deloitte Analytics. He provides clients with end-to-end strategy, business, operational, and technical consulting services in the areas of advanced business analytics and analytic ... View Full Bio

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