Any modern software tester knows that the cost of delivering poor quality software has never been higher. And they also know that the time companies have in which to deliver that high quality software continues to get shorter. This situation has put a squeeze on testing by eliminating room for error. As a result, testers need to make the right decisions the first time around every single time, and doing that requires using data.
Fortunately, we software testers have all the data we need at our disposal. But using that data in the right way to make the right decisions isn’t so cut and dry. As it stands currently, we have so much data on everything we do, that it’s difficult to put all the disparate pieces together and find the right signal in all the noise. Nevertheless, finding the signal in the noise is exactly what we need to do to get a grasp on the right software test metrics and make informed, data-backed decisions that can improve our testing efforts and the quality of our software.
Finding the signal in the noise is exactly what we need to do to get a grasp on the right software test metrics and make informed, data-backed decisions that can improve our testing efforts and the quality of our software.
How Do You Know If You Need Better Software Test Metrics?
Knowing we need the right metrics to inform our testing efforts is one thing. Knowing whether or not we have the right metrics is quite another. So how do you know if you need better test metrics? Start by asking yourself the following five questions, and if the answer to any or all of them is yes, it’s time to consider making a change.
1) Does it seem like you spend all your time staring at spreadsheets?
Once upon a time, spreadsheets were the best we could ask for, but in the age of big data using a spreadsheet to analyze data is akin to using an abacus to calculate numbers. We now have a simpler, faster way to consolidate and analyze data, and if you’re not using it, you’re leaving a lot of value on the table. That better way is a modern, automation-driven toolset that’s specifically designed to consolidate, filter, and present real-time data in different formats. Using this type of tool not only makes pulling data together quick and easy, but it also makes understanding and analyzing the metrics in front of you simple. Best of all, these solutions can present data in interactive formats so that you can move beyond a static spreadsheet and analyze any number of different scenarios.
2) Is your data often incorrect or inconsistent because you’re constantly pulling in from different number sources?
Software testing data is fragmented in how it’s created — there’s no getting around that. But once that data is created, you need to break down the silos. Manually consolidating the data is significantly time-consuming and, more importantly, leaves room for human error as numbers get pulled from different systems. Once again, a modern toolset can help by consolidating data from different systems in an automated fashion in real-time. This automation eliminates human error and speeds up the entire process, leaving you with more accurate, consistent, and timely data on which to base decisions.
3) Are you unable to answer simple questions related to testing metrics?
What percentage of planned tests have you run at any given point within a sprint? This seems like a simple enough question — it just requires you to know the number of planned tests and the number of tests you’ve already run — but without the right access to the right data, such a simple question can become a difficult one. And if answering even the simplest of questions proves challenging, what happens when you’re faced with a more in-depth question, such as what the defects per requirement or charter bug detection rate looks like? All of these questions are ones that need to be answered quickly and confidently in order to keep pace with today’s testing demands.
4) Are you unable to get any real actionable insight from your reporting?
Software test metrics are important when it comes to taking proactive measures to course-correct current testing efforts and to properly planning for future testing cycles. However, using metrics in this way requires you to understand how what you’ve done and what you’re doing currently will affect what happens next. In other words, you need to be able to predict what will happen if you stay the course and what changes you need to make to achieve a certain set of results. And in order to do that, you need to derive actionable insight (often in real-time) from your test metrics. Without that insight, you lose the ability to make changes when they count in order to do things like improve your test coverage or increase your velocity to deliver everything as planned in the expected timeframe.
5) Do you have to spend hours creating custom reports for your executive team?
Because we live in such a fast paced world, having the right data isn’t enough on its own. You also need instant access to real-time data. For example, if it takes you hours to create custom reports for your executive team, not only have you dedicated a significant amount of time to preparing the reports, but by the time the reports are ready, the data is very likely outdated. A modern, automation driven toolset can solve this conundrum by automatically compiling data in any number of ways and by populating those reports with real-time data. This setup not only saves time (think minutes, not hours) and ensures everyone is always looking at the most up to date version of the data, but it also guarantees that everyone has the same data.
How Do You Get Better Software Test Metrics?
If asking yourself these five questions revealed that you do in fact need better software test metrics, don’t fret. The answer lies in — you guessed it — implementing a modern, automation driven toolset designed specifically for the purpose of analyzing test metrics. Once you have that solution in place, you can create the reports you need to give your entire team constant access to consolidated, accurate, real-time test metrics as well as the ability to view and interact with those metrics in a way that makes deriving actionable insight quick and easy.