BI & Analytics

Good news for all business managers that would love to have their business metrics — for which the data reside in databases behind the firewall (on-premise) — available on their smart-phone. We have made the integration of on-premise data into KPI Dashboard much easier with our Data Collector.

One of the problems with analytics and business intelligence (BI) information is that these techniques do not always complete the task of solving a problem or moving to the next step of creating and realizing value. I refer to this as the syndrome of “What? So what? Then what?” My concern is that many organizations use analytics and BI to answer only the first question, but then they are stymied when it comes to answering the next two questions.

The standard measure of wealth is GDP per capita. The chart below shows that Americans have been getting continually wealthier for decades, with a few blips here and there (source of data). The measure of wealth—Gross Domestic Product, is based on the dollar value of economic transactions.

As IT budgets continue to shrink and expectations traditionally rise, you may be interested in finding a high yield on your IT spend. How about a 966% return on your investment? A recent examination of Nucleus Research found organizations earn an average of $10.66 for every dollar spent on deployments of analytics applications such as business intelligence (BI), performance management (PM), and predictive analytics. See here for an excerpt of the research note.

Pardon my deception by attracting you to read this blog article by stating “business analytics” in its title. Analytics are a means to an end where the end-game is enterprise performance improvement. That is, analytics are enablers, not necessarily the root cause for improvement. And there are obviously multiple other contributors to organizational improvement including having enough money to spend on improving and having good executive leadership.

Where would you rank yourself and your organization with applying analytics to gain insights and make better decisions? Are you advanced so you can out-smart other organizations like yours to create and sustain value creation? Or are you at the opposite end of the continuum and muddling through by basing decisions and strategies relying on intuition and gut feel rather than using fact-based data, modeling, and probabilistic what-if scenarios.