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In this appendix, I'll share some of my favorite tools and some that come highly recommended by colleagues and friends. Please don't buy any of these tools on the basis of their inclusion here; instead, if something sounds good to you, research it further. Just as with metrics themselves—you'll need to marry the possibilities to your specific requirements. Based on your root questions, your environment, and the programs you develop—different tools and resources may be called for.

Tools

Some tools play multiple roles, but most specialize in a primary function and have other functions as a supplement. Most trouble-ticket tracking tools work this way. They are designed (and do a good job at) capturing and tracking trouble tickets, and may also provide basic graphing tools. They don't provide much in analysis; and provide nothing toward being a complete metric tool. But trouble-tracking tools are good at what they are supposed to do. The key is not to try to make a specific tool do more than it is designed to do.

The really good news is that a meaningful and useful metrics program doesn't require a ton of statistical analysis or complicated charting. Always keep in mind that the purpose of a metrics program is to provide insights that can support decisions, direct investigations, and expose areas of concern.

Tools simply provide different ways of looking at the information you've gathered. Depending on your root question and what you are trying to learn from your metric, you can use many different forms of analysis. The tools I cover in this appendix are the few that I find useful and simple. They are simple for me to produce/use and simple for my audience to understand. Always remember your audience when displaying your metrics. Even if you use more complex analysis to get to your answers, you may need to find ways to display them in more simplistic terms.

Microsoft Excel

I've found Excel to be much more than spreadsheet software. I guess it was originally created to assist with accounting or bookkeeping. Ages ago, I used to explain that spreadsheet programs were good for working on numbers. If you wanted to perform math on your data, spreadsheets were the way to go. Today, Microsoft Excel has grown to be much more than a glorified calculator. I use it for much of my metrics work. Like most current software applications, Excel has more capabilities than most users realize or will ever use. Besides the breadth of functionality, Excel also provides a lot of flexible power, as in macros (mini programs) and add-ins like PowerPivot. I collect, analyze, and produce graphs for most of my work in Excel. With Excel add-ins, I can also perform more complex analysis inside the spreadsheets. With Excel 2010, I can handle as many records as I need. I use Excel as the foundation for my work.

Excel has a statistical add-in that comes with the full version, but you have to “turn it on.” It doesn't come with this functionality preset. Turning it on will give you some basic statistical tools like histograms and regression tests.

SigmaXL

SigmaXL is a tool that can be accessed through Excel. It creates a more intuitive set of menu items in its own tab than the statistical add-in that comes with Excel. I was especially happy to find that it had a BoxPlot tool (graph), which I was unable to find in any other add-in. I am truly impressed with the SigmaXL capabilities.

Minitab

While working on my Green Belt in Six Sigma, I fell in love with SigmaXL. Before the honeymoon was over, my instructors told me about Minitab. They described it as better, smarter, easier to use, and more comprehensive than SigmaXL. The biggest problem with statistics is they're just too hard to deal with, especially for the benefits gained. SigmaXL makes it worth the effort; and if Minitab is better (I haven't used it yet), I want a copy.

Visualization Tools

Visualization tools are primarily (if not solely) designed to provide access to your data—in the form of dashboards, scorecards,