Apologies for the lack of blog post last week. We had some issues with our site and were unable to post. That being said, we have made a lot of progress in the last few weeks! We have conducted upwards of 30 interviews in the last two weeks and have learned a lot through the process and updated our MMC and design of our prototype.
- Changes to the Design:
- -Circuit design, antennas and form factor modification
- -Goal: to create an alpha prototype by the end of April
- Changes to the MMC:
- -Moved NextFlex to Key Partners
- -Changed the Key Activities section to reflect the focus on the alpha prototype construction by the end of the semester
- -New Value Proposition: Concealed Weapons Detection in Mobile Operation – such as detection of a weapon when approaching a suspect
- -Changed the Mission Achievement: Revenue Streams: Achieve ~99% accuracy rate on detecting people, with few false negatives from 90%
We have been talking with many subject experts in the area and have started to look into different antennas, different form factors and have changed some aspects of the electronic components and circuit design.
Mission Model Canvas Changes:
The major changes we made to the MMC were all across the board this week. Starting from the left, we moved Nextflex to the key partners section after our interview with them last week because it seems as though they will be instrumental in obtaining and sourcing parts for our prototypes. We also changed the Key Activities sector to focus on the alpha prototype. We have now decided on the goal of creating an alpha prototype by the end of the semester (end of April) and so our MMC will be focused on creating this MVP. We also added a new Value Proposition of Concealed Weapons Detection in Mobile Operation, which we have heard about from multiple operators and police officers. They would like to be able to detect objects such as suicide vests and guns while approaching a person or area. Moving to Mission Achievement, we edited the Revenue Streams: Achieve ~90% accuracy rate on detecting people, with few false positives to Achieve ~99% accuracy rate on detecting people, with few false negatives. Although this is a very high standard we are setting for ourselves, we have heard over and over again from operators that they need this device to be accurate. Also, they would prefer false positives over false negatives because they would rather be overly prepared than underprepared.