Learning launch 

 Challenge   As Head of Sales&Marketing of a construction materials Company , I developed the   perception that we could create an offer around waste collection from our customers ’   jobsites . This was based on conversations with Sales Reps and some customers in Region A ,   who claimed that , since we were delivering materials to jobsites , we could seize backhaul   opportunities and transport demolition waste from jobsites to landfill sites ( located next to   our production sites ) .   At the same time , a lot of uncertainties remained : technical feasibility ( avoiding overloading   for instance ) , regulatory compliance ( making sure we have a proper Goods Delivery Note ) ,   level of investment required ( mobile weighbridge ? ) , customer willingness to pay , scalability ,   and probably other challenges we were not thinking about .     Selection   My team and I knew that we had to be very concrete and avoid making assumptions or   multiplying guesses . Our new business project involved measuring customer appetite and   identifying operational constraints , so only field observations would help us .   This is why we opted for a learning launch : we knew it would allow for different experiments   that would help us confirm or disconfirm our intuitions .     Application   In order to perform our learning launch , we started by stating our hypothesis , which was the   following : our company can help our construction customers who do n’t have their own fleet   to get rid of their demolition waste in a more effective way ( cheaper , faster ) than with their   other alternatives .   Then we selected the 5 largest customers in Region A that satisfied our criteria , and   approached them to offer the opportunity to take care of their demolition waste on their   next jobsite . We presented it as a new service that we were developing and made it clear   that the service would be all the best suited to their needs if they could share as much   information as they could on their current practices and painpoints .   Internally , we briefed our teams ( sales reps , supply chain group ) and our subcontracted   haulers on the initiative , stating that we needed as much feedback and observations from   their side as possible .   Also , to make the experiment as insightful as possible , we opted to price our offer at a level   we thought fair and potentially sufficiently value - creating .     We probably did a good job envisioning the different topics we wanted to learn on . However   we lacked effectiveness in the way we formalized the assumptions and how each contributor   to the experiment would feed data to support or disprove our assumptions . The feedback   collection process was therefore somewhat painful and not always as accurate as it could   have been .      Insight   Our first area of insights was around customer perception . Spending time on jobsites   focusing on demolition waste elimination , taking time for in - depth conversations with 

 customers , and testing our idea of new service was worth the effort : we learned that half of   the jobsites were reusing demolition waste on the spot ( therefore not needing our service ) ,   that on a case by case basis the demolition waste could be reused on a jobsite nearby , that   the way we had designed our price made sense , and that waste evacuation , under certain   circumstances ( space available , time constraints ) could be a burning issue .   In a nutshell : there was a potential , but the addressable market was much smaller than what   we had thought ( probably 20 % of our initial assumption ) .   Out of the 5 customers tested , only 1 decided to entrust us with waste evacuation for his   next job . This allowed us to learn a lot on the operational reality : long waiting time , difficulty   for loading , need to create new documents to comply with the regulation , and some safety   issues . Taking this into consideration , we realized that we needed to increase our price by   15 % in order to create some value for us as well .     As a result of this learning launch , we decided to go for a different route , because the   market was much smaller than expected , both in volume and value , and this was adding a   lot of constraints to our main business . Yet , because we had learned that it was at times a   burning issue for our customers , and we wanted to support them in that respect , we   approached a demolition waste trading company and entered in a partnership with them .      The approach we took for this new business evaluation , derived from a design thinking   methodology , was somewhat new in our company . Traditionally , we tended to go for   customer surveys , educated guesses , business plans . We surely saved a lot of time and   money by deciding to do a learning launch .     Approach   As mentioned earlier , one area of improvement is around the way we formalized our   assumptions and organized feedback collection .    Another space to do things differently next time is how we communicated with the top   management of our Company : while we were in a test and learn mode , our management   was taking success for granted and had already committed to additional revenue to the   Group we were part of . Takeaway : a learning launch must be approached in a very open- minded way by all parties involved . It may result in our hypothesis to be confirmed , or it may   result in the opposite . The good news is that we should know pretty quickly and with limited   costs what the outcome looks like . 


EMAIL: 
ID_NUM: 
NAME_STUDENT: 
PHONE_NUM: 
STREET_ADDRESS: 
URL_PERSONAL: 
USERNAME: 

### Task: You are a PII (Personal Identity Information) Detection. Given a essays written by students, you have to identify ONLY the following:
NAME_STUDENT - The full or partial name of a student that is not necessarily the author of the essay. This excludes instructors, authors, and other person names.
EMAIL - A student’s email address.
USERNAME - A student's username on any platform.
ID_NUM - A number or sequence of characters that could be used to identify a student, such as a student ID or a social security number.
PHONE_NUM - A phone number associated with a student.
URL_PERSONAL - A URL that might be used to identify a student.
STREET_ADDRESS - A full or partial street address that is associated with the student, such as their home address.
### Input: Learning launch 

 Challenge   As Head of Sales&Marketing of a construction materials Company , I developed the   perception that we could create an offer around waste collection from our customers ’   jobsites . This was based on conversations with Sales Reps and some customers in Region A ,   who claimed that , since we were delivering materials to jobsites , we could seize backhaul   opportunities and transport demolition waste from jobsites to landfill sites ( located next to   our production sites ) .   At the same time , a lot of uncertainties remained : technical feasibility ( avoiding overloading   for instance ) , regulatory compliance ( making sure we have a proper Goods Delivery Note ) ,   level of investment required ( mobile weighbridge ? ) , customer willingness to pay , scalability ,   and probably other challenges we were not thinking about .     Selection   My team and I knew that we had to be very concrete and avoid making assumptions or   multiplying guesses . Our new business project involved measuring customer appetite and   identifying operational constraints , so only field observations would help us .   This is why we opted for a learning launch : we knew it would allow for different experiments   that would help us confirm or disconfirm our intuitions .     Application   In order to perform our learning launch , we started by stating our hypothesis , which was the   following : our company can help our construction customers who do n’t have their own fleet   to get rid of their demolition waste in a more effective way ( cheaper , faster ) than with their   other alternatives .   Then we selected the 5 largest customers in Region A that satisfied our criteria , and   approached them to offer the opportunity to take care of their demolition waste on their   next jobsite . We presented it as a new service that we were developing and made it clear   that the service would be all the best suited to their needs if they could share as much   information as they could on their current practices and painpoints .   Internally , we briefed our teams ( sales reps , supply chain group ) and our subcontracted   haulers on the initiative , stating that we needed as much feedback and observations from   their side as possible .   Also , to make the experiment as insightful as possible , we opted to price our offer at a level   we thought fair and potentially sufficiently value - creating .     We probably did a good job envisioning the different topics we wanted to learn on . However   we lacked effectiveness in the way we formalized the assumptions and how each contributor   to the experiment would feed data to support or disprove our assumptions . The feedback   collection process was therefore somewhat painful and not always as accurate as it could   have been .      Insight   Our first area of insights was around customer perception . Spending time on jobsites   focusing on demolition waste elimination , taking time for in - depth conversations with 

 customers , and testing our idea of new service was worth the effort : we learned that half of   the jobsites were reusing demolition waste on the spot ( therefore not needing our service ) ,   that on a case by case basis the demolition waste could be reused on a jobsite nearby , that   the way we had designed our price made sense , and that waste evacuation , under certain   circumstances ( space available , time constraints ) could be a burning issue .   In a nutshell : there was a potential , but the addressable market was much smaller than what   we had thought ( probably 20 % of our initial assumption ) .   Out of the 5 customers tested , only 1 decided to entrust us with waste evacuation for his   next job . This allowed us to learn a lot on the operational reality : long waiting time , difficulty   for loading , need to create new documents to comply with the regulation , and some safety   issues . Taking this into consideration , we realized that we needed to increase our price by   15 % in order to create some value for us as well .     As a result of this learning launch , we decided to go for a different route , because the   market was much smaller than expected , both in volume and value , and this was adding a   lot of constraints to our main business . Yet , because we had learned that it was at times a   burning issue for our customers , and we wanted to support them in that respect , we   approached a demolition waste trading company and entered in a partnership with them .      The approach we took for this new business evaluation , derived from a design thinking   methodology , was somewhat new in our company . Traditionally , we tended to go for   customer surveys , educated guesses , business plans . We surely saved a lot of time and   money by deciding to do a learning launch .     Approach   As mentioned earlier , one area of improvement is around the way we formalized our   assumptions and organized feedback collection .    Another space to do things differently next time is how we communicated with the top   management of our Company : while we were in a test and learn mode , our management   was taking success for granted and had already committed to additional revenue to the   Group we were part of . Takeaway : a learning launch must be approached in a very open- minded way by all parties involved . It may result in our hypothesis to be confirmed , or it may   result in the opposite . The good news is that we should know pretty quickly and with limited   costs what the outcome looks like .
### Output: 