I speak to C-level management frequently who look for business systems to create efficiencies, scalability and business intelligence that contributes to their bottom lines. Everyone seems able to get a handle on what they mean by efficiencies and scalability, but are all over the board regarding business intelligence. Some are thinking of dashboards, some reporting, some say it is all about analytics and some don’t honestly know what they want except that they were told they need “
To me, Business Intelligence (BI) is all of the above and more. To clarify, let me differentiate reporting and analytics and use this as a springboard about BI.
Reporting’s primary purpose is communication; it is pre-defined, highly formatted, scheduled and mainly textual. Checkbooks and Profit/Loss statements are examples of reporting. In contrast, analytics’ primary purpose is investigation, with the end users doing ad-hoc manipulation of data depending on what they deem material and timely. Sales “what if” scenarios and inventory relationships are typical uses of analytics. To me, BI encompasses reporting, analytics, the tools to create reporting/analytics and the techniques to gather data and disseminate in various formats.
There are many myths around BI; let me give you a few and a comment or two.
Myth 1 - All business users want feature-packed BI tools so they can slice and dice data.
Some users are just not interested BI; so consider who the tool is for before building one for a user.
Myth 2 - Static reporting is dead.
Six-inch-thick, monthly green-bar reports may be all but dead, but static reports are still more than one-half of a company’s BI requirements.
Myth 3 - Excel spreadsheets are the work of the devil.
The most widely used BI tool today is the spreadsheet. If you are a BI vendor or a data warehouse manager, you need harbor no illusions that your main competition is the spreadsheet. But because it is competition for more complex BI software, does not make it the work of the devil, no matter what the BI software developers say.
Myth 4 - Standardizing on a BI tool will solve the problem.
See Myth 3 about what BI software developers are saying.
As I said, there are misunderstandings about the uses and definitions of BI. As a