Impacting several buildings a year is great, but using technology to scale residential energy retrofits is what is drastically needed to solve our building energy crisis.
Since utilities and implementation contractors aren’t exactly on the cutting-edge of innovation to streamline residential energy efficiency projects, why haven’t tech and building savvy start-ups jumped at the glaring opportunity to drive residential EE with data?
Some of the reasons are obvious:
- The bang-for-the-buck on homes is less than large apartment buildings and C/I buildings, where huge savings can be achieved by clear operation and ‘low hanging fruit’ direct install improvements.
- Residential buildings and their owners require a different level of engagement. The conversation is never just about ROI as it is with investor types.
- The diversity of house styles and retrofit challenges post a conundrum to any effort to streamline and build systems that cast broad nets over a building type.
- Residential buildings can have complex energy profiles and split-incentive challenges.
- Public data and occupant usage data is poorly organized and difficult to capture.
Companies like Opower, Retroficiency, and FirstFuel can analyze and crunch data to understand energy profiles for buildings and occupant behavior. This analysis is great, but it would be great to levereage the power of data to support a custom on-site energy audit to identify deep saving opportunities. Data analysis can bolster the productivity of the in-building assessment process. For residential dwellings the in-home process is very important. With existing data we can make the site visit more effective.
Energy use analysis and other public data sets can support in-home energy assessments by improving the efficiency, accuracy, and customer engagement.
By using data to support the in-home energy assessments, not replace the visit, the purpose is shifted from calculating the cost effectiveness of efficiency upgrade investments, to supporting the success of the in-home building professional. These goals may include:
- Reduced energy assessment time: visits are more cost-effective.
- Deeper savings: more savings opportunities identified.
- Happier customers: custom assessments are smoother with less surprises.
- Higher conversion rates: easier to make the case for investment in building performance solutions.
There are likely many types of data, but two general categories are usage data and public data. WIth Green Button hopefully the discrepancy between these categories goes away.
1. Occupant energy usage data:
The benefits are obvious. As an energy professional, understanding patterns of energy use help give a snap-shot of the efficiencies of building components and mechanical equipment. With some nice (accurate!!) pie-charts showing how their behavior and building components impact their usage profile, the consumer is on the way to overcoming the ‘information barrier’. There are many companies using usage data in interesting ways. MyEnergy is my favorite behavioral tool for the residential sector.
2. Public data about the home:
This includes municipal assessor data and GIS (map) info. Also MLS records and appraiser data (if it’s public) will help convey the value of investing in different tiers of solutions. Public data is what I am most intrigued with as it is already available and can very easily impact the effectiveness of the in-home energy assessment.
Think about this energy assessment scenario:
I am an energy auditor for Honeywell, CSG, or some other large outfit tasked with providing huge volumes of in-home energy assessments and resulting weatherization projects. I have to perform 2-3 house visits a day without having spoken to the customer. If I’m lucky I have a record of the intake call with bullet points conveying the goals of the client.
During the energy audit I have to interview the client, inspect the home, perform diagnostics, and collect a slew of data about the existing insulation to inform a retrofit that will likely be done by another company. Ultimatly my success is measured by conversion rates, and size of the project scope, so some charm and top-notch customer service is useful.
Now if I had access to a software data and reporting tool....I can know the following before stepping foot inside the home:
- The layout and dimensions of the house - save 30minutes measures the home.
- Energy fuels on site - how many heating systems to test
- Size, age, style of home - this alone tells me what I will likely find in the guts of the home.
- Recent permits pulled : new kitchen? wiring re-done? new Jacuzzi? These will impact how I look at the home.
- Date that the occupants moved in - this will give me clues about the relationship they have with the home.
With this information, my time in the home can be reduced by 25-50% while delivering more accurate results and happier customers.
This Publicly available data combined with a well presented snap-shot of the customers energy profile, can be really effective. A simple software tool to collect and present this data for energy assessment providers,could go a long way to improving the effectiveness of in-home visits.
What’s the market for this?
Since this post is too long already, I’ll leave that for next time. The market includes:
- Utility companies tasked with delivering cost-effective energy savings
- Municipalities looking at developing a local energy efficiency program or PACE program.
- Larger government programs such as federal rebate programs, to identify opportunities based on analysis
- Companies delivering energy efficiency services or those that are interested in behavioral energy efficiency
- and hopefully YOU - let me know if you want to build this!