Practical Software Measurement

Demand the (Right) Right Data with SLIM-DataManager

A few weeks ago, Thomas C. Redman posted Demand the (Right) Right Data on the Harvard Business Review blog, about how managers should set the bar higher, in terms of data.

Why are managers so tolerant of poor quality data? One important reason, it seems to me, is that most managers simply don't know that they can expect better!  They've dealt with bad data their entire careers and come to accept that checking and rechecking the "facts," fixing errors, and accommodating the uncertainties that using data one doesn't fully trust are the manager's lot in life.

Although Redman suggests that managers should demand higher quality data, I immediately thought about how to check the quality of SLIM-DataManager databases using the Validate function and SLIM-Metrics.

If you're using SLIM-DataManager to create your own historical database, you can use the Validation feature to help you demand the (right) right data.  The Validation feature in SLIM-DataManager analyzes the projects in your database, highlights suspect projects, and offers a brief explanation tool tip.  Simply go to File|Maintenance|Validate to run this feature and wait for SLIM-DataManager to analyze your database.  If SLIM-DataManager detects anomalies, it will highlight that project in blue.  If you hover over that project, a tooltip will explain what is wrong with that project data and what you need to take a second look at.

Another way to demand the (right) right data using SLIM Suite is to create a SLIM-Metrics workbook to help "automate" validation.  You can create views to replicate SLIM-DataManager tabs to help you look for data that just doesn't look quite right (for example, a PI of 40 or a project that only lasts one day).  While this process is not as intensive as scrubbing your own data, you can get an at-a-glance view of which projects are falling way outside the bounds of reality.

If you're using SLIM Suite, you already have all the right tools to manage your own historical database and help you demand the (right) right data.  While SLIM Suite can't eliminate poor quality data completely, it can quickly identify suspect project data for further review while increasing the accuracy of your historical project data.