Client: Ford - Design Lead (Interaction Design)

Incubating Ford's first smart consumer product: next-gen vehicle security.

Incubating Ford's first smart consumer product: next-gen vehicle security.

We helped Ford incubate their first piece of consumer hardware by defining the product, service, and AI strategy.

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My Role

While at IDEO I spent a significant amount of time building out our client relationship with Ford. Especially in their commercial mobility unit. One of the projects I lead was to develop an "alpha" of a security product. Basically building a "Nest" type device that would sit in trucks and vans. I was responsible for a team of 5 engineers and designers, where we delivered a fully working product and business case.

Challenge

Truck and Van owners have seen a dramatic rise in their belongings being stolen out of their vehicles. In an effort to combat these thefts, we were tasked with building an after market security solution for truck and van owners to give them peace of mind while away from their vehicles.

Solution

We built a smart after-market security product that could easily be adapted for both van and truck users, and worked in extremely low power environments. This provided for with access to customers post-purchase and a new recurring revenue stream.

Outcomes

After the alpha, Canopy was accepted into Ford's internal incubator (FordX) where it continued to gain momentum - finally spinning out with $105M in funding through a joint venture with ADT. One of the most successful spin-outs the company has done to date.

Journey Mapping & Initial Research

The 12-week project was structured into six defined sprints, each beginning with a kickoff and concluding with a live demo. To outline our sprints, we mapped the complete customer journey—from device installation and theft detection to handling post-break-in insurance claims. Additionally, we conducted initial customer interviews and consulted with vehicle security specialists to inform our approach.

Hardware & App Prototyping

We built countless prototypes of both the hardware unit and the app to help us understand challenges like pairing, mounting in the vehicle, live streaming, latency and general useability.

We built countless prototypes of both the hardware unit and the app to help us understand challenges like pairing, mounting in the vehicle, live streaming, latency and general useability.

Machine Learning Exploration

In our search for suitable technologies to develop an algorithm capable of detecting break-ins, we collaborated with a team from the Alan Turing Institute to create an audio detection machine learning model. Thousands of sound samples were collected in an anechoic chamber, allowing us to assess the feasibility of the approach.

In our search for suitable technologies to develop an algorithm capable of detecting break-ins, we collaborated with a team from the Alan Turing Institute to create an audio detection machine learning model. Thousands of sound samples were collected in an anechoic chamber, allowing us to assess the feasibility of the approach.

User Testing

During each sprint, we organised user feedback sessions where fleet owner/ operators were invited into the design studio to give feedback on our latest work. Testing for usability and desirability of the offering.

During each sprint, we organised user feedback sessions where fleet owner/ operators were invited into the design studio to give feedback on our latest work. Testing for usability and desirability of the offering.

Ways of Working

We spent a lot of time working on/in our project space. Making sure it had 24/7 access to a real Transit van. We peppered the walls with our most recent work, as we had multiple stakeholders visiting and referencing our material. We also held large demos after each two week sprint to create momentum and find areas of cross-pollination across the organization.

We spent a lot of time working on/in our project space. Making sure it had 24/7 access to a real Transit van. We peppered the walls with our most recent work, as we had multiple stakeholders visiting and referencing our material. We also held large demos after each two week sprint to create momentum and find areas of cross-pollination across the organization.

Final Prototypes

After the 12 week sprint we had delivered a mountable piece of hardware that communicated the security state of the vehicle to an app. Highlighting the key user experiences and technical feasibility required to turn this into a large scale venture. These prototypes were carried forward and used for scoping further development milestones and user testing.

After the 12 week sprint we had delivered a mountable piece of hardware that communicated the security state of the vehicle to an app. Highlighting the key user experiences and technical feasibility required to turn this into a large scale venture. These prototypes were carried forward and used for scoping further development milestones and user testing.

Joint-Venture Spin out

The project went on to secure $105M in funding from ADT and Ford in a joint venture where the team has been shipping both aftermarket and fully integrated security features for the automotive industry. You can learn more here.

The Team

The team went on to being backed by Ford's internal incubator known as FordX and has since been one of their most successful spin-outs with a team of over 60 people located in Detroit and London.

The team went on to being backed by Ford's internal incubator known as FordX and has since been one of their most successful spin-outs with a team of over 60 people located in Detroit and London.

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