LEARNING LAUNCH

APPLICATION:  Learning launches are a tool for evaluating ideas to see which ones are viable business ventures.  Learning launches have been referred to as "placing small bets early" because they can happen  quickly and at a low cost.  Unfortunately, some executives have misinterpreted the term to mean that limited sales  opportunities should be pursued, which is not the case. The majority of good growth companies are  on the lookout for scaleable growth opportunities that will result in needlemovers. Small bets  quickly, on the other hand, is a research technique rather than a strategy decision.        CHALLENGE AND SELECTION:  A learning launch is a well-planned project or prototype that aims to validate the core underlying  value-generating assumptions of a potential new-growth initiative.A learning launch, as opposed to  a complete new-product launch, is a learning experiment performed rapidly and cheaply to collect  market-driven data to decide whether a growth concept has enough merit to warrant thorough  investigation with the investment of additional time, staff, and money.    INSIGHT AND APPROACH:  A learning launch is a business-world implementation of the scientific method; it is a way of  thinking that is based on hypotheses generation and testing. It all begins with creating hypotheses  by asking a what-if question, which helps you to discover a new possibility to pursue. The  possibility is your hypothesis, which is essentially an informed guess on what you think would be a  good idea. That's the part where you get to be imaginative.  Then you decide what scientists refer to as boundary conditions to test your hypothesis. To put it  another way, you're asking: Under what circumstances will that theory be a good idea? Or, to put it  another way, what would have to be true for my idea to be a good one? So, you'll bring to the  surface the assumptions that lie under your hypothesis, and then you'll find the right data to test  them. That's the analytical part of it. If it turns out that your conclusions are not correct, and your  theory is disproved,\sthen you can take the new data and go back and use it to restate the  hypothesis\sbetter. Then you put the new and improved theory to the test. It is a continuous iterative  process in which you learn something new each time, allowing you to create a better theory for the  next pass.


LEARNING LAUNCH APPLICATION : Learning launches are a tool for evaluating ideas to see which ones are viable business ventures . Learning launches have been referred to as " placing small bets early " because they can happen quickly and at a low cost . Unfortunately , some executives have misinterpreted the term to mean that limited sales opportunities should be pursued , which is not the case . The majority of good growth companies are on the lookout for scaleable growth opportunities that will result in needlemovers . Small bets quickly , on the other hand , is a research technique rather than a strategy decision . CHALLENGE AND SELECTION : A learning launch is a well - planned project or prototype that aims to validate the core underlying value - generating assumptions of a potential new - growth initiative . A learning launch , as opposed to a complete new - product launch , is a learning experiment performed rapidly and cheaply to collect market - driven data to decide whether a growth concept has enough merit to warrant thorough investigation with the investment of additional time , staff , and money . INSIGHT AND APPROACH : A learning launch is a business - world implementation of the scientific method ; it is a way of thinking that is based on hypotheses generation and testing . It all begins with creating hypotheses by asking a what - if question , which helps you to discover a new possibility to pursue . The possibility is your hypothesis , which is essentially an informed guess on what you think would be a good idea . That 's the part where you get to be imaginative . Then you decide what scientists refer to as boundary conditions to test your hypothesis . To put it another way , you 're asking : Under what circumstances will that theory be a good idea ? Or , to put it another way , what would have to be true for my idea to be a good one ? So , you 'll bring to the surface the assumptions that lie under your hypothesis , and then you 'll find the right data to test them . That 's the analytical part of it . If it turns out that your conclusions are not correct , and your theory is disproved,\sthen you can take the new data and go back and use it to restate the hypothesis\sbetter . Then you put the new and improved theory to the test . It is a continuous iterative process in which you learn something new each time , allowing you to create a better theory for the next pass .