Challenge

I would like to talk about an opportunity in my organization where we applied the learning launch  process. I work in the global data center operations space for a large the firm and my group was  responsible for implementing new process improvement strategies every year. We wanted to decrease  the time to install new cable by 7-10% or more and we believed that implementing a new design of fiber  cabling that was more robust, easier to handle and faster to install would help get us to that very target.

Selection

We knew that we needed a tool from the design thinking toolbox that would push us to test our ideas,  frame our hypothesis, engage customers, quantify the impact and iterate. The learning launch tool was  the optimal one to assist us with this approach. As we had a few potential design ideas we knew that we  would have to experiment quickly and compare each alternative design and also to the current status  quo. The cable manufacturers had sample data that asserted efficiency improvements with the new  design of fiber cabling compared to the current one, however, it was under different conditions and an  unknown data set. What really made learning launch an applicable tool in our project was that we had  to quantify and test the hypothesis that we would see an efficiency improvement with experimentation,  reducing the possibility for confirmation bias. We also knew that having pictures, anecdotes and  feedback would be important too so we coupled learning launch with visualization. We aligned on this  approach and proceeded.

Application

I start the process by answering the basic foundational questions of any problem-what is the problem  and what are we trying to accomplish. I was careful not to over index or over commit to a specific  number. As mentioned earlier, we had four designs that could be tested for efficiency improvements.  We had to come up with a way to test these designs. We answered the following learning launch  questions:

1. Idea- implementing one of the 4 new cable manufacturer designs would yield a 7-10% efficiency

gain

2. Specific person-this was for global data techs  3. Has specific need-to work as effectively and efficiently as possible delivering capacity to

customer

4. Idea met the need-?  5. Better than current alternative-?

The last two questions, we didn’t have the answer to initially. I proceeded to create pilot plans with the  right amount of samples, experimentation conditions and data tech users. In addition to capturing time  study data, in my pilot forms I also encouraged the techs to put feedback, use pictures and be as  descriptive as well to capture anecdotal feedback. After few months of testing we evaluated the results- both qualitatively and quantitatively. There was a clear winner-a figure 8 design sample that met the  need. It was quicker to install with 10% efficiency gain and much easier to use, the users had very  positive feedback.  To re-validate the design I had a few more users test it. Their feedback echoed what  was previously stated and confirmed the improvement. In essence we were able to answer the  questions of the learning launch process

1. Idea- implementing one of the 4 new cable manufacturer designs would yield a 7-10% efficiency

gain

2. Specific person-this was for global data techs  3. Has specific need-to work as effectively and efficiently as possible delivering capacity to

customer

4. Idea met the need-yes, it met the efficiency and usability targets  5. Better than current alternative-yes, there was a 10% improvement in efficiency,

Insight and Approach

The learning launch method proved to be a very valuable process in selecting the right design for the  installation job. The specific elements of the tool encouraged to develop hypothesis, experiments,  validate and select the optimal answer. As mentioned in my pilot study I encouraged testers to use  pictures, photos and anecdotal feedback which in many ways added the visualization component to the  initiative this was also very important so that new testers and other stakeholders could see for  themselves the impact and confirm that the new design while faster was not more cumbersome to  handle. Hence learning launch coupled with visualization is a powerful tool.

I would say that in some cases that combing learning launch with six sigma and statistical qualification  tools can help especially since there are some elements in sampling and experimentation elements  involved that design thinking may not fully address.


Challenge I would like to talk about an opportunity in my organization where we applied the learning launch process . I work in the global data center operations space for a large the firm and my group was responsible for implementing new process improvement strategies every year . We wanted to decrease the time to install new cable by 7 - 10 % or more and we believed that implementing a new design of fiber cabling that was more robust , easier to handle and faster to install would help get us to that very target . Selection We knew that we needed a tool from the design thinking toolbox that would push us to test our ideas , frame our hypothesis , engage customers , quantify the impact and iterate . The learning launch tool was the optimal one to assist us with this approach . As we had a few potential design ideas we knew that we would have to experiment quickly and compare each alternative design and also to the current status quo . The cable manufacturers had sample data that asserted efficiency improvements with the new design of fiber cabling compared to the current one , however , it was under different conditions and an unknown data set . What really made learning launch an applicable tool in our project was that we had to quantify and test the hypothesis that we would see an efficiency improvement with experimentation , reducing the possibility for confirmation bias . We also knew that having pictures , anecdotes and feedback would be important too so we coupled learning launch with visualization . We aligned on this approach and proceeded . Application I start the process by answering the basic foundational questions of any problem - what is the problem and what are we trying to accomplish . I was careful not to over index or over commit to a specific number . As mentioned earlier , we had four designs that could be tested for efficiency improvements . We had to come up with a way to test these designs . We answered the following learning launch questions : 1 . Idea- implementing one of the 4 new cable manufacturer designs would yield a 7 - 10 % efficiency gain 2 . Specific person - this was for global data techs 3 . Has specific need - to work as effectively and efficiently as possible delivering capacity to customer 4 . Idea met the need- ? 5 . Better than current alternative- ? The last two questions , we did n’t have the answer to initially . I proceeded to create pilot plans with the right amount of samples , experimentation conditions and data tech users . In addition to capturing time study data , in my pilot forms I also encouraged the techs to put feedback , use pictures and be as descriptive as well to capture anecdotal feedback . After few months of testing we evaluated the results- both qualitatively and quantitatively . There was a clear winner - a figure 8 design sample that met the need . It was quicker to install with 10 % efficiency gain and much easier to use , the users had very positive feedback . To re - validate the design I had a few more users test it . Their feedback echoed what was previously stated and confirmed the improvement . In essence we were able to answer the questions of the learning launch process 1 . Idea- implementing one of the 4 new cable manufacturer designs would yield a 7 - 10 % efficiency gain 2 . Specific person - this was for global data techs 3 . Has specific need - to work as effectively and efficiently as possible delivering capacity to customer 4 . Idea met the need - yes , it met the efficiency and usability targets 5 . Better than current alternative - yes , there was a 10 % improvement in efficiency , Insight and Approach The learning launch method proved to be a very valuable process in selecting the right design for the installation job . The specific elements of the tool encouraged to develop hypothesis , experiments , validate and select the optimal answer . As mentioned in my pilot study I encouraged testers to use pictures , photos and anecdotal feedback which in many ways added the visualization component to the initiative this was also very important so that new testers and other stakeholders could see for themselves the impact and confirm that the new design while faster was not more cumbersome to handle . Hence learning launch coupled with visualization is a powerful tool . I would say that in some cases that combing learning launch with six sigma and statistical qualification tools can help especially since there are some elements in sampling and experimentation elements involved that design thinking may not fully address .