Posts Tagged Metrics
Ventana Research CEO Mark Smith has an interesting blog post up with the subtle title “The Pathetic State of Dashboards”.
I’ve always been a bit of a dashboard skeptic. The fluff promoted by vendors (gauge-type displays for business metrics, for example) has always struck me as noisy and silly. A gauge-type display makes sense in a car, where second-by-second changes in pressure on the gas pedal create immediate changes in a gauge, that then feeds back to the pressure you apply (assuming you are paying attention) but there are few business requirements like this. Highlighting outliers is easily accomplished by conditional formatting. Using the “dashboard” as a metaphor – taking it from the real world of for example, a car, and mapping it to business activity – is an idea that in my experience doesn’t often stand up to scrutiny. The driver’s seat of a car is a different kind of place than the chair in a cubicle, and BI tools are generally too generic for the kind of moment-to-moment operational-level activity implied by dashboards.
Dashboards as an entry point to data discovery may make a certain amount of sense, but drill-through reporting has been around for a long time. Clear exception reports, the kind that can be created easily with out-of-the-box reporting software, are generally of far greater utility than the products of graphics-rich “dashboard” software.
Business Intelligence (or BI as it is commonly known) is the reporting of corporate data using a variety of methodologies meant to give timely, accurate and in-depth knowledge of a organization’s performance. These methodologies may include dashboards for a visual depiction of corporate performance, metrics and scorecards to indicate when performance is on or off target, data warehouses to serve as highly optimized stores of data for fast and efficient reporting, and data cubes which are structured for dimensional (or OLAP) analysis. Another feature that is sometimes included is data mining which delves into data looking for correlations. A BI environment at minimum contains some sort of reporting system and can also include any number of the other features mentioned.
The idea behind BI is to make data accessible and easy to understand. It must correctly reflect the reality of the business, so data quality control is also a key consideration.
Many software vendors have complete lines of Business Intelligence tools, including IBM Cognos, Microsoft, Oracle, Business Objects and SAP just to name a few. Each tool pertains to a particular task in the BI environment, and usually a suite will tie them all together. For example, in Cognos there is Reporting Studio for generating reports, Analysis Studio for OLAP analysis of data cubes, Metrics Studio for KPIs and scorecards, Events Studio for handling certain system activities, Planning for scenario analysis, Framework Manager for data modeling, Transformer for data cube generation, and Data Manager for data warehouse generation. All of these tools are pulled together by Cognos 8, which is the reporting portal. It is not uncommon for companies to employ a multi-vendor solution and so these tools often need to work together. For example, a source system might be on an Oracle platform which may be read by Microsoft SQL Server Integration Services and then reported by Cognos 8.