Why Business Intelligence?
When faced with complexity, we know that our chances for optimal decision making are improved when we enjoy convenient access to relevant, accurate quantitative facts that provide meaningful decision support. However, decision makers too often experience their attempts to access this information – from traditional sources such as reports, spreadsheets, documents, meetings, e-mail trails, PostIt notes – as trying to sip water from a fire hose. Business intelligence (BI) – a term which I will use as an umbrella term for data warehousing, decision support, OLAP, data analytics, and business performance management – automatically gathers, structures, and aggregates massive amounts of quantitative data with the sole purpose of consistently presenting it accurately and conveniently to decision-makers in a unified, flexible and visually intuitive manner that matches our natural human processes of perception, thought and inquiry and making use of familiar concepts such as numeric facts, criteria, hierarchies and milestones.
Natural human thought processes?
As an example, although we may subjectively decide that last fiscal year’s revenue and profitability from Primo Product J63 were somewhere between good and very good, we would like to quickly and easily observe exactly how good they were (a) …for each quarter and month of last year; (b) …to which customer demographic groups; (c) …from which sales channels, regions and sales representatives; (d) …as a revenue contributor in Product Group Alpha vs. other product groups; (e) …as compared to products built from parts from which of our suppliers; and (f) …as compared to which similar products from which competitors? In the above example, revenue and profit are examples of what BI practitioners call numeric “facts” or “measures” and items (a-f), the criteria against which the measures are considered, are called “dimensions” and “hierarchies”. Lastly, we establish milestones, which BI practitioners call “key performance indicators (KPI’s)”, against which actual results may be subjectively yet consistently evaluated, for example, as being “Poor”, “Fair, “Good”, “Very Good”, “Excellent” or “Outstanding”. When an analyst is armed with this capability, plus the ability to follow her natural process of inquiry to quickly drill down, up and across the facts in search of insight, and then discovers these insights and acts on them, the analyst has Business Intelligence. When time-constrained executive decision makers are armed with this capability, perhaps in the more convenient, less analytical form of a dashboard with instant visual cues -- and then use this knowledge to make better decisions -- the enterprise has BI.
Is BI easy?
Although BI can be complex to build, it is easy to use when built correctly. As a result of proliferating BI expertise and maturing technology, it is now ubiquitous within large organizations for performance analysis and is trickling down to small and medium sized information-intensive businesses. Costs are coming down, too. More and more companies of varied shapes and sizes are pursuing competitive advantage by extracting more knowledge from their operational data.
Is BI fun? I think so, but I thought that building this website was fun, too.
