Example Reflection: Learning Launch

Challenge:

I work in an organization which involves design and manufacture of racecars. One of the essential  areas is aerodynamics. This involves study and modification of airflow around the car. Our work  involves design of various parts that would improve the airflow, and use it to have a better  performing car. The part design is done by a big group of people, having diverse ideas. Hence, a  selection has to be made from the multiple ideas that are generated, based on predefined  criteria.

Picture: The racecar for 2020 season

Selection:

We decided to use the ‘Learning Launch’ tool covered in this course to help us decide which part  would be the best suited. This tool is basically experimentation based out of assumptions. These  experiments would then generate data. The data, when analyzed according to the requirements/  criteria, would yield a result for the experiment. We may choose to select or scrap that  assumption or modify it. Thus, it is the ‘What works’ stage of Design Thinking.

Application:

We had various designs for a particular part of the car. The criteria for selection was predefined.  In order to generate data, each part had to be analyzed using a computer software. The values  obtained after analysis were ‘downforce’ and ‘drag’. A map of the airflow around the car was also  obtained.

This data was made available for each prospective part. The selection criteria included cost and  feasibility of manufacture, performance gains for the car and reusability. Thus, using the Learning  Launch tool, we could decide which part works best for the car. We were able to have an  informed decision. We also became aware of the shortcomings in other parts and that became  an input for further development. Thus, we realized the ‘What works’ part of our design.

Insights:

Use of the Learning Launch tool as a part of Design Thinking was helpful to ensure that all ideas  are analyzed properly and given justice. This is very important in an organization where multiple  ideas are generated and a decision has to be made. It also helped us in generating input for the  design of new parts, which becomes and additional benefit.

Approach:

I would aim at including the Visualization tool to the initial stage of the racecar design. The  racecar is made up of hundred of parts, and it is important to have a common goal for all  departments involved. This tool would help in developing a framework for collaboration between  all the mechanisms involved and help in reducing delay.


Example Reflection : Learning Launch Challenge : I work in an organization which involves design and manufacture of racecars . One of the essential areas is aerodynamics . This involves study and modification of airflow around the car . Our work involves design of various parts that would improve the airflow , and use it to have a better performing car . The part design is done by a big group of people , having diverse ideas . Hence , a selection has to be made from the multiple ideas that are generated , based on predefined criteria . Picture : The racecar for 2020 season Selection : We decided to use the ‘ Learning Launch ’ tool covered in this course to help us decide which part would be the best suited . This tool is basically experimentation based out of assumptions . These experiments would then generate data . The data , when analyzed according to the requirements/ criteria , would yield a result for the experiment . We may choose to select or scrap that assumption or modify it . Thus , it is the ‘ What works ’ stage of Design Thinking . Application : We had various designs for a particular part of the car . The criteria for selection was predefined . In order to generate data , each part had to be analyzed using a computer software . The values obtained after analysis were ‘ downforce ’ and ‘ drag ’ . A map of the airflow around the car was also obtained . This data was made available for each prospective part . The selection criteria included cost and feasibility of manufacture , performance gains for the car and reusability . Thus , using the Learning Launch tool , we could decide which part works best for the car . We were able to have an informed decision . We also became aware of the shortcomings in other parts and that became an input for further development . Thus , we realized the ‘ What works ’ part of our design . Insights : Use of the Learning Launch tool as a part of Design Thinking was helpful to ensure that all ideas are analyzed properly and given justice . This is very important in an organization where multiple ideas are generated and a decision has to be made . It also helped us in generating input for the design of new parts , which becomes and additional benefit . Approach : I would aim at including the Visualization tool to the initial stage of the racecar design . The racecar is made up of hundred of parts , and it is important to have a common goal for all departments involved . This tool would help in developing a framework for collaboration between all the mechanisms involved and help in reducing delay .