As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n
Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n
Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n
Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n
As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n
Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n
As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n
Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n
For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n
As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n
Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n
For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n
As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n
Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n
An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n
For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n
As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n
Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n
An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n
For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n
As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n
Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n
One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n
An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n
For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n
As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n
Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n
One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n
An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n
For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n
As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n
Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n
There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n
One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n
An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n
For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n
As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n
Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n
This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n When we think of testing and quality engineering, our concepts shouldn\u2019t be narrowed only to the confines of the system testing or end to end testing stages. It should be looked at the system as a whole. If you refer to this link<\/a>, you can understand systems thinking better. <\/p>\n\n\n\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n Role of Quality Engineering teams can be focused towards early and thorough testing and that can be achieved only by automation through the devOps cycle. It cannot be thought of in a siloed manner.<\/p>\n\n\n\n When we think of testing and quality engineering, our concepts shouldn\u2019t be narrowed only to the confines of the system testing or end to end testing stages. It should be looked at the system as a whole. If you refer to this link<\/a>, you can understand systems thinking better. <\/p>\n\n\n\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n Role of Quality Engineering teams can be focused towards early and thorough testing and that can be achieved only by automation through the devOps cycle. It cannot be thought of in a siloed manner.<\/p>\n\n\n\n When we think of testing and quality engineering, our concepts shouldn\u2019t be narrowed only to the confines of the system testing or end to end testing stages. It should be looked at the system as a whole. If you refer to this link<\/a>, you can understand systems thinking better. <\/p>\n\n\n\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n A matrix of criticality of the functionality by the frequency of usage need to be used to prioritize the test automation in the top of the test pyramid<\/a>. Focus on number of cases or pass percentage towards value of the test automation scripts and how close to the test automation mimic to the actual day in life of the user brings a mammoth difference in the confidence in the test automation suite. <\/p>\n\n\n\n Role of Quality Engineering teams can be focused towards early and thorough testing and that can be achieved only by automation through the devOps cycle. It cannot be thought of in a siloed manner.<\/p>\n\n\n\n When we think of testing and quality engineering, our concepts shouldn\u2019t be narrowed only to the confines of the system testing or end to end testing stages. It should be looked at the system as a whole. If you refer to this link<\/a>, you can understand systems thinking better. <\/p>\n\n\n\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n What are the confirmation parameters that are critical to automation end to end along with the functionalities that are most often used.<\/p>\n\n\n\n A matrix of criticality of the functionality by the frequency of usage need to be used to prioritize the test automation in the top of the test pyramid<\/a>. Focus on number of cases or pass percentage towards value of the test automation scripts and how close to the test automation mimic to the actual day in life of the user brings a mammoth difference in the confidence in the test automation suite. <\/p>\n\n\n\n Role of Quality Engineering teams can be focused towards early and thorough testing and that can be achieved only by automation through the devOps cycle. It cannot be thought of in a siloed manner.<\/p>\n\n\n\n When we think of testing and quality engineering, our concepts shouldn\u2019t be narrowed only to the confines of the system testing or end to end testing stages. It should be looked at the system as a whole. If you refer to this link<\/a>, you can understand systems thinking better. <\/p>\n\n\n\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n Central premise of test automation needs to move beyond number of tests that have turned pass or Fail and instead moving toward Intimate business workflows<\/p>\n\n\n\n What are the confirmation parameters that are critical to automation end to end along with the functionalities that are most often used.<\/p>\n\n\n\n A matrix of criticality of the functionality by the frequency of usage need to be used to prioritize the test automation in the top of the test pyramid<\/a>. Focus on number of cases or pass percentage towards value of the test automation scripts and how close to the test automation mimic to the actual day in life of the user brings a mammoth difference in the confidence in the test automation suite. <\/p>\n\n\n\n Role of Quality Engineering teams can be focused towards early and thorough testing and that can be achieved only by automation through the devOps cycle. It cannot be thought of in a siloed manner.<\/p>\n\n\n\n When we think of testing and quality engineering, our concepts shouldn\u2019t be narrowed only to the confines of the system testing or end to end testing stages. It should be looked at the system as a whole. If you refer to this link<\/a>, you can understand systems thinking better. <\/p>\n\n\n\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n Central premise of test automation needs to move beyond number of tests that have turned pass or Fail and instead moving toward Intimate business workflows<\/p>\n\n\n\n What are the confirmation parameters that are critical to automation end to end along with the functionalities that are most often used.<\/p>\n\n\n\n A matrix of criticality of the functionality by the frequency of usage need to be used to prioritize the test automation in the top of the test pyramid<\/a>. Focus on number of cases or pass percentage towards value of the test automation scripts and how close to the test automation mimic to the actual day in life of the user brings a mammoth difference in the confidence in the test automation suite. <\/p>\n\n\n\n Role of Quality Engineering teams can be focused towards early and thorough testing and that can be achieved only by automation through the devOps cycle. It cannot be thought of in a siloed manner.<\/p>\n\n\n\n When we think of testing and quality engineering, our concepts shouldn\u2019t be narrowed only to the confines of the system testing or end to end testing stages. It should be looked at the system as a whole. If you refer to this link<\/a>, you can understand systems thinking better. <\/p>\n\n\n\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n This is an extremely important step that leadership needs to solve prior to providing wings under the team. The sense of loss of ownership on skill set and being central to the decision of Go-NoGo has been one that needs to be unlearnt before these new skills can be learnt.<\/p>\n\n\n\n Central premise of test automation needs to move beyond number of tests that have turned pass or Fail and instead moving toward Intimate business workflows<\/p>\n\n\n\n What are the confirmation parameters that are critical to automation end to end along with the functionalities that are most often used.<\/p>\n\n\n\n A matrix of criticality of the functionality by the frequency of usage need to be used to prioritize the test automation in the top of the test pyramid<\/a>. Focus on number of cases or pass percentage towards value of the test automation scripts and how close to the test automation mimic to the actual day in life of the user brings a mammoth difference in the confidence in the test automation suite. <\/p>\n\n\n\n Role of Quality Engineering teams can be focused towards early and thorough testing and that can be achieved only by automation through the devOps cycle. It cannot be thought of in a siloed manner.<\/p>\n\n\n\n When we think of testing and quality engineering, our concepts shouldn\u2019t be narrowed only to the confines of the system testing or end to end testing stages. It should be looked at the system as a whole. If you refer to this link<\/a>, you can understand systems thinking better. <\/p>\n\n\n\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n When the entire team starts pitching on test automation as well as overall health of the product, what translates as the role of the traditional Engineering Quality Division in agile teams? <\/p>\n\n\n\n This is an extremely important step that leadership needs to solve prior to providing wings under the team. The sense of loss of ownership on skill set and being central to the decision of Go-NoGo has been one that needs to be unlearnt before these new skills can be learnt.<\/p>\n\n\n\n Central premise of test automation needs to move beyond number of tests that have turned pass or Fail and instead moving toward Intimate business workflows<\/p>\n\n\n\n What are the confirmation parameters that are critical to automation end to end along with the functionalities that are most often used.<\/p>\n\n\n\n A matrix of criticality of the functionality by the frequency of usage need to be used to prioritize the test automation in the top of the test pyramid<\/a>. Focus on number of cases or pass percentage towards value of the test automation scripts and how close to the test automation mimic to the actual day in life of the user brings a mammoth difference in the confidence in the test automation suite. <\/p>\n\n\n\n Role of Quality Engineering teams can be focused towards early and thorough testing and that can be achieved only by automation through the devOps cycle. It cannot be thought of in a siloed manner.<\/p>\n\n\n\n When we think of testing and quality engineering, our concepts shouldn\u2019t be narrowed only to the confines of the system testing or end to end testing stages. It should be looked at the system as a whole. If you refer to this link<\/a>, you can understand systems thinking better. <\/p>\n\n\n\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n When the entire team starts pitching on test automation as well as overall health of the product, what translates as the role of the traditional Engineering Quality Division in agile teams? <\/p>\n\n\n\n This is an extremely important step that leadership needs to solve prior to providing wings under the team. The sense of loss of ownership on skill set and being central to the decision of Go-NoGo has been one that needs to be unlearnt before these new skills can be learnt.<\/p>\n\n\n\n Central premise of test automation needs to move beyond number of tests that have turned pass or Fail and instead moving toward Intimate business workflows<\/p>\n\n\n\n What are the confirmation parameters that are critical to automation end to end along with the functionalities that are most often used.<\/p>\n\n\n\n A matrix of criticality of the functionality by the frequency of usage need to be used to prioritize the test automation in the top of the test pyramid<\/a>. Focus on number of cases or pass percentage towards value of the test automation scripts and how close to the test automation mimic to the actual day in life of the user brings a mammoth difference in the confidence in the test automation suite. <\/p>\n\n\n\n Role of Quality Engineering teams can be focused towards early and thorough testing and that can be achieved only by automation through the devOps cycle. It cannot be thought of in a siloed manner.<\/p>\n\n\n\n When we think of testing and quality engineering, our concepts shouldn\u2019t be narrowed only to the confines of the system testing or end to end testing stages. It should be looked at the system as a whole. If you refer to this link<\/a>, you can understand systems thinking better. <\/p>\n\n\n\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n Ref: Medium<\/p>\n\n\n\n When the entire team starts pitching on test automation as well as overall health of the product, what translates as the role of the traditional Engineering Quality Division in agile teams? <\/p>\n\n\n\n This is an extremely important step that leadership needs to solve prior to providing wings under the team. The sense of loss of ownership on skill set and being central to the decision of Go-NoGo has been one that needs to be unlearnt before these new skills can be learnt.<\/p>\n\n\n\n Central premise of test automation needs to move beyond number of tests that have turned pass or Fail and instead moving toward Intimate business workflows<\/p>\n\n\n\n What are the confirmation parameters that are critical to automation end to end along with the functionalities that are most often used.<\/p>\n\n\n\n A matrix of criticality of the functionality by the frequency of usage need to be used to prioritize the test automation in the top of the test pyramid<\/a>. Focus on number of cases or pass percentage towards value of the test automation scripts and how close to the test automation mimic to the actual day in life of the user brings a mammoth difference in the confidence in the test automation suite. <\/p>\n\n\n\n Role of Quality Engineering teams can be focused towards early and thorough testing and that can be achieved only by automation through the devOps cycle. It cannot be thought of in a siloed manner.<\/p>\n\n\n\n When we think of testing and quality engineering, our concepts shouldn\u2019t be narrowed only to the confines of the system testing or end to end testing stages. It should be looked at the system as a whole. If you refer to this link<\/a>, you can understand systems thinking better. <\/p>\n\n\n\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n Ref: Medium<\/p>\n\n\n\n When the entire team starts pitching on test automation as well as overall health of the product, what translates as the role of the traditional Engineering Quality Division in agile teams? <\/p>\n\n\n\n This is an extremely important step that leadership needs to solve prior to providing wings under the team. The sense of loss of ownership on skill set and being central to the decision of Go-NoGo has been one that needs to be unlearnt before these new skills can be learnt.<\/p>\n\n\n\n Central premise of test automation needs to move beyond number of tests that have turned pass or Fail and instead moving toward Intimate business workflows<\/p>\n\n\n\n What are the confirmation parameters that are critical to automation end to end along with the functionalities that are most often used.<\/p>\n\n\n\n A matrix of criticality of the functionality by the frequency of usage need to be used to prioritize the test automation in the top of the test pyramid<\/a>. Focus on number of cases or pass percentage towards value of the test automation scripts and how close to the test automation mimic to the actual day in life of the user brings a mammoth difference in the confidence in the test automation suite. <\/p>\n\n\n\n Role of Quality Engineering teams can be focused towards early and thorough testing and that can be achieved only by automation through the devOps cycle. It cannot be thought of in a siloed manner.<\/p>\n\n\n\n When we think of testing and quality engineering, our concepts shouldn\u2019t be narrowed only to the confines of the system testing or end to end testing stages. It should be looked at the system as a whole. If you refer to this link<\/a>, you can understand systems thinking better. <\/p>\n\n\n\n When I speak about Technical agility with teams, I often get a question, who is responsible to improve tech agility metrics. This is an area that has not been completely well defined. It is my belief that the Quality Engineering teams are better placed to move the needle as far as Tech Agility is concerned. <\/p>\n\n\n\n This enables Quality Engineering to move towards mentorship for the product rather than being a gate keeper of quality.<\/em><\/p>\n\n\n\n It is no longer about conflict over whether there is value in automation and creating a sense of ownership of the Tech agility. So what are the key metrics that one needs to look out for?<\/p>\n\n\n\n There are 4 parameters that each team needs to measure themselves. Actual metric that can be used can be based on the journey itself.<\/p>\n\n\n\n One of the teams that I work, found that they take 45 min to complete one check in and find that developers check in code approximately once for every story. This is an area that led teams to relook at their Definition of Done and working agreements to improve for the product. <\/p>\n\n\n\n An example above on Planner provides reference on how to use these metrics to enable the level of investment required by the team as a whole. The leadership also continuously provided the needed support for the team to increase the coverage. <\/p>\n\n\n\n For a middleware product, there would always be code coverage metrics that were constantly shown to justify the automation investment. When we started sharing the ROI on how often the automation scripts were run, there was a paradigm shift in mindset started. In this team\u2019s case, the automation was run once every release (3 months) and it took approximately a week for the automation environment to be set. This was almost 3.5 years back. Since then, the middleware product have improved their automation to run on a weekly basis with minimal manual effort. <\/p>\n\n\n\n As is true in most scientific discoveries, truth lies somewhere in the middle. Analysis of the right set of testing tools, creation of environments and spawning the right environments certainly stay in the side of engineering or science. While motivation to keep adding one additional script, identifying the critical path, bringing collaborative mindset within all the team members is firmly in the side of mindset.<\/p>\n\n\n\n Can the scientific analysis and right mindset come together to increase the Test automation? There lies the Billion Dollar Business Agility question. <\/p>\n","post_title":"Test automation - mindset or science?","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"open","post_password":"","post_name":"test-automation-mindset-or-science","to_ping":"","pinged":"\nhttps:\/\/pm-powerconsulting.com\/blog\/how-i-finally-learnt-systems-thinking\/","post_modified":"2024-10-04 08:37:23","post_modified_gmt":"2024-10-04 03:07:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/pm-powerconsulting.com\/?p=15131","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};
\n An example set of tools that are available in the market to manage the test automation are here.<\/p>\n\n\n\n Ref: Medium<\/p>\n\n\n\n When the entire team starts pitching on test automation as well as overall health of the product, what translates as the role of the traditional Engineering Quality Division in agile teams? <\/p>\n\n\n\n This is an extremely important step that leadership needs to solve prior to providing wings under the team. The sense of loss of ownership on skill set and being central to the decision of Go-NoGo has been one that needs to be unlearnt before these new skills can be learnt.<\/p>\n\n\n\n Central premise of test automation needs to move beyond number of tests that have turned pass or Fail and instead moving toward Intimate business workflows<\/p>\n\n\n\n What are the confirmation parameters that are critical to automation end to end along with the functionalities that are most often used.<\/p>\n\n\n\n A matrix of criticality of the functionality by the frequency of usage need to be used to prioritize the test automation in the top of the test pyramid<\/a>. Focus on number of cases or pass percentage towards value of the test automation scripts and how close to the test automation mimic to the actual day in life of the user brings a mammoth difference in the confidence in the test automation suite. <\/p>\n\n\n\n Role of Quality Engineering teams can be focused towards early and thorough testing and that can be achieved only by automation through the devOps cycle. It cannot be thought of in a siloed manner.<\/p>\n\n\n\nQuality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
Early and thorough testing and Mentorship over conflict<\/h3>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
Early and thorough testing and Mentorship over conflict<\/h3>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
Early and thorough testing and Mentorship over conflict<\/h3>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
Early and thorough testing and Mentorship over conflict<\/h3>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
Thinking beyond pass or fail towards Intimate Business Understanding<\/h3>\n\n\n\n
Early and thorough testing and Mentorship over conflict<\/h3>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
Thinking beyond pass or fail towards Intimate Business Understanding<\/h3>\n\n\n\n
Early and thorough testing and Mentorship over conflict<\/h3>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
Thinking beyond pass or fail towards Intimate Business Understanding<\/h3>\n\n\n\n
Early and thorough testing and Mentorship over conflict<\/h3>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
What are the skills required and expected from Testing specialization?<\/h2>\n\n\n\n
Thinking beyond pass or fail towards Intimate Business Understanding<\/h3>\n\n\n\n
Early and thorough testing and Mentorship over conflict<\/h3>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
What are the skills required and expected from Testing specialization?<\/h2>\n\n\n\n
Thinking beyond pass or fail towards Intimate Business Understanding<\/h3>\n\n\n\n
Early and thorough testing and Mentorship over conflict<\/h3>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
![\"\"](\"https:\/\/pm-powerconsulting.com\/wp-content\/uploads\/2020\/07\/Automation2-1024x236.png\")
<\/figure>\n\n\n\nWhat are the skills required and expected from Testing specialization?<\/h2>\n\n\n\n
Thinking beyond pass or fail towards Intimate Business Understanding<\/h3>\n\n\n\n
Early and thorough testing and Mentorship over conflict<\/h3>\n\n\n\n
Quality Automation Governance Dashboards<\/h2>\n\n\n\n
Test automation - mindset or science?<\/h2>\n\n\n\n
<\/figure>\n\n\n\nWhat are the skills required and expected from Testing specialization?<\/h2>\n\n\n\n
Thinking beyond pass or fail towards Intimate Business Understanding<\/h3>\n\n\n\n
Early and thorough testing and Mentorship over conflict<\/h3>\n\n\n\n
