Metrics, nowadays, have gained importance in any mature IT organization for evaluating process effectiveness, understanding the situation, tracking progress and more. Efficient testing process measurement is the essential factor for the success of any project, we usually measure many aspects of the testing process but how and what we measure and how and what we measure is what it should be .
The main reason for this difference is the lack of a coordinated and comprehensive framework for understanding and using measurement. Many times, matrices and measurements are performed only and given less importance.
“You can’t control what you can’t measure.”
A quotation form of Demorco’s book is very accurate for controlling software projects. Testing is an activity that requires effective control and measurement to understand where we are going. Measurement is nothing but recording things of the past to quantitatively predict future things.
The metric is a measurable indication of some quantitative aspects of the system / process. Any test project or activity involves many things such as test planning, test design, test development and execution. Test metrics help measure these aspects of testing activities and provide a head to head voice for faster, more informed decision making.
I. Lack of strong governance:
There should be strong administration in the period of taking initiative and driving on an ongoing basis. Management must be committed in what they initiate and continue to practice throughout the program. Closing at a later stage will affect and collapse the team and therefore lead to failure of the metric program. The metrics should be given due importance to the program.
Second. Fuzzy Metrics Definition: Fuzzy metric definitions can be dangerous, because different people may interpret them in different ways, thus leading to inaccurate results. The metric should be clearly defined with clear goals associated with it. It should pass on a clear message as to what needs to be collected and why it needs to be generated.
Ignorance in communicating expectations:
Ignorance in communication of expected data and importance for better control and effectiveness. Explain why you want to measure the item you choose, how it would be useful, everyone has the right to know why there is some request. All data collected must be used effectively.
IV. Practice not sharing results:
It should be good practice to share the results or metrics generated after collecting data. More often, the team feels that data collection is a boring activity and is overhead on their current process. Team members will be more motivated to participate in measurement activities if you inform them about how you have used the data. Share summaries and trends with the team at regular intervals and help them understand the data. Tell them that whenever you use their data to answer a question, make a prediction or decision.
V. People’s perspectives:
The perspectives of the people involved in collecting, sharing, calculating, reporting and using data from the metrics play a critical role in the success or failure of the program. Accurate and meaningful metrics rely heavily on individuals’ attitudes and attitudes across generations. For some people it is just a useless activity and is meaningless. They often think that this is a way to show good things to customers / sponsors and make a mark. People want to look good and so they show only good measurements rather than actual ones. The best way to avoid human factors in measurement,
Avoid measuring individuals
: This is often taken at individual levels when metrics are collected and measured against individuals.
Use of metric to motivate teams: One should not use metric or pass on a message where the team feels they are being motivated to do better, it is the wrong message and the team has The inability has started showing and provides incorrect data.
Providing continuous feedback on the data collected has several advantages, such as when teams see that the data is actually being used, they are more likely to consider and value data collection activities. By involving team members in data analysis and process improvement efforts, we benefit from their unique knowledge and experience; The advantage may be more accurate, consistent and timely data.
Sixth. Identifying Multiple Metrics:
Identifying Multiple Metrics Identifying the metrics that are needed and adds value to the current process. Some test leads / managers insist on collecting data and generating multiple metrics that are not consistent with the goal and intention. There should be a practice of collecting only those metrics that are relevant and consistent with the goals, definitions.
Seventh. Lack of communication and training: VII.
Proper communication on what and why we need metrics is critical to the success of a metrics program.