The 11/11/13 workshop aimed to help participants develop innovative algorithm and application ideas, with the goal of achieving deep and widespread energy savings.
The process formulated for this experimental workshop was designed to multiply, accelerate, and increase the effectiveness of energy-saving applications:
- We started with the Data Jam + Hackathon concept (workshops where ideas and apps are born), build in market analysis and product design workflow, and add out-of-the-box design thinking methods.
- To expand the idea space, we provided expert-compiled cheat sheets listing everything from available data sets, to behavior design principles, to example energy apps to serve as inspiration.
We design applications "backwards" compared to the user's experience. This allows us to emphasize the end goal of having the user make significant energy savings, and progressively constrain the core solution of our app based on that, and only then flesh out the overall app design which is what the user would see first. So, as an example, a designer of the nest thermostat may have picked residential buildings and HVAC for its large potential energy savings, then identified an action to change like having the thermostat turn down while away, with their core solution being smart thermostat defaults and a learning algorithm, then fleshed out the overall product design. Nest is obviously complicated with multiple core solutions etc. but you get the idea. We're working this way to be certain we're designing apps that really have the potential for big energy savings.
1. Carrie Armel, PEEC
2. Ian Kalin, Socrata
3. Adam Rein, Mission Point Capital
4. Rajiv Bansal, Bidgely
5. Sam Baron, Habitable
6. Nick Cisek, Facebook
7. Jonathan Koomey, Stanford Steyer-Taylor Center
8. Joe Kwiatkowski, Ecofactor
9. Daniel Roesler, TerraVerde Renewable Partners
10. Betsy Scherzer, The CleanWeb Initiative
Data Jam Process and Supporting Resources
What follows are instructions for using the resources linked here:
Our goal is to develop an effective algorithm or application. To be effective, the user experience should result in 1) many users becoming engaged with the application, and 2) using its targeted core functionality to save substantial energy. The design process supporting the development of such an application is illustrated in reverse order to emphasize the fact that the end goal for our user is the primary constraint in our design. Thus, we start with identifying where to achieve the biggest energy savings; next identify a specific opportunity and core solution; and finally flesh out a compelling overall product design – which is what the user would see first.
Next, on the Team Worksheet, the process is elaborated, with instructions on what to do during guided brainstorming, and an example filled in. The rest of the materials provide information and ideas to help with that process. Specifically, in:
- Step 1: You'll select one SECTOR/END-USE, guided in part by its energy savings potential, as well as an audience. You'll find a breakdown of sectors and end-uses by its Energy Consumption in the Target Datasheet Guide .
- In Step 2: You'll identify one or more ACTIONS to target. Many ideas are listed on the Cheat Sheet [hold up] next to their corresponding end use. Feel free to come up with your own or talk to the facilitators about ideas.
- In Step 3: You'll explore CORE SOLUTIONs – for the action (s) you selected. Again, many ideas are listed on the Cheat Sheet [hold up] next to their corresponding end use. And again, feel free to come up with your own or talk to the facilitators about ideas...Then choose one Solution.
- Finally, in Step 4: You'll Design the PRODUCT by fleshing out your chosen Solution w/the Behavioral Techniques and Design Principles. These are also listed on the Cheet Sheet , as well as in the Behavioral Techniques Guide.
Follow ups can include competitions, funding, mentorship:
- Google Hangout
- American Energy Data Challenge
- Startup Weekend
- The CleanWeb Initiative
- Accelerator at VERGE SF
- Clean Tech Open
- VC channels - Y Combinator, GreenStart, etc.