7 Mistakes That Can Ruin Your Test Metric Program

Test metrics are used by QA managers, testers, and agile teams as a quantitative measure for estimating the progress and quality of a software testing process. There is no better way of improving a test than selecting a relevant test metric, drawing a baseline, and tracking the progress over time.

Testing metrics lets you make a decision for what’s coming next. It can also help you understand what types of improvement are needed. This program makes decision-making easier. Of course, it can help you out when you are deciding which one of the Cox Internet plans to settle for. The success of a test metric program can be halted by common mistakes, which we are going to discuss moving forward.

1. Weak Leadership

When there is a lack of strong governance when it comes to owning and driving initiatives, this could ruin many things. The top management must stay committed to what they initiate and continue practicing it throughout the program’s cycle.

If the management decides to discontinue the program, this will affect its success and demotivate the team as well.

2. Poor Definition of Metrics

It can be dangerous to have unclear metrics as every individual involved could understand them in different ways. This would result in inaccurate outcomes. Therefore, each metric must be defined clearly and there should be clear goal-setting. This information must pass on a clear message of what needs to be collected and generated.

3. Non-Communication or Less Communication

Communication is key even in the success of a test metric program. Failing to communicate the expectations and importance of data can alter the effectiveness of the program. You must explain why the item in question is to be measured, how useful it’s going to be, and the expectations. Encourage everyone involved to ask questions, even if they think these questions are silly.

4. Not Sharing Results

Imagine your team puts their day and night into the test metric program and the outcome isn’t shared with them. By doing so, you are demotivating your team, which can impact the effectiveness of a program when conducted in the future.

When you share the results, you are motivating your team to participate in test metric activities. Keep on sharing the trends and summaries with your team on a regular basis. This will help them in understanding data.

5. Attitudes of Team Members

The success and failure of a test metric program highly depend on the attitude of people involved in data collection, sharing, calculating, and reporting. Accuracy depends on the approach and attitude of people. Some consider it a waste of time. Others consider it’s just an activity of showing off the good stuff to sponsors for making an impression. Such an
attitude can impact the results.

The best way of avoiding human error and biases in measurement is to use a metric that motivates your team. Pass on the message that this activity is for everyone’s better so that your team sets the right expectations, to begin with. Another way to minimize human impact is to provide continuous feedback on data collection. Involve your team in data analysis and process improvement. This way you will benefit from the unique experience and knowledge of your team. As a result, the data collected will be accurate, consistent, and timely.

6. Identifying Too Many Metrics

Collecting data and generating several unnecessary metrics can make you deviate from the initial goal. Make it a practice of collecting data for only the metrics that are relevant and align with your goals. Remember, several metrics don’t really add value to the process.

7. Lack of Training

All members involved in the test metric program must understand the relevance of the data that is being collected. This is only possible if all team members receive the necessary training before the program starts.

Training will make it clear what data is being collected, how it’s collected, and how it will be used. Once the initial training is complete, this shouldn’t be the end of the story. Keep on receiving feedback on the data being collected. The metrics model in question can only be implemented successfully with proper training.

Be sure to avoid these mistakes and make your test metric program a success!

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