Approximately 30 percent of the energy used is wasted – mostly through simple actions such as leaving lights on or running heat and cooling simultaneously. The problem for utilities is that these saving opportunities have been historically hard to find and even more difficult to communicate to their customers.

To achieve the market and savings potential, utilities need to engage commercial customers on a mass scale. Based on our experience and work in the industry, utilities only have the time, budget and resources to engage between 10-30 percent of their commercial customers. Data analytics is providing the pathway to engage the other 70 percent.

Onsite Audits Limit Scale

Commercial customer engagement has historically been driven by the onsite audit, an inherently scale-limiting approach.  These audits are created by doing simple building walk-throughs and are based on only a few days worth of data.

The result? They take months to deliver, are often poor in quality, and miss many of the savings opportunities customers should take.  They’re also time intensive for the customer and costly for the utilities.  This combination of factors erodes even the most enthusiastic customer’s will to act and limits their use to large organizations that are already on the path to engagement.  This limits their use to large customers who are already engaged enough to work through to their results.

Utilities can only afford this approach for a fraction of their largest customers, leaving many large customers, and almost all mid-sized and small business, completely untouched.

Big Data Ushers in Commercial Customer engagement

Large amounts of data now available has made large-scale commercial customer engagement possible and is the key to unlocking the potentially hundreds of billions in energy efficiency savings in this market.

Simple meter data can be used to identify more comprehensive savings, engage a broader portfolio of customers, and generate a stronger uptake.  Here at FirstFuel, we’re using advanced analytics to turn hourly interval meter data into detailed insights about buildings; identifying missed savings opportunities such as what times the lights are being left on, what temperatures activate the HVAC system, how the ventilation can be upgraded, and more. These are the hard to find, easy to implement saving opportunities that yield results without costing the customers.

By using this information earlier in the discussion, and prior to customer investment of time or money, the no-touch audit informs and engages. Commercial customers can now realize real insight into energy use, accompanied by specific energy saving solutions or actions at the outset.  Interval data also serves as the foundation of an ongoing relationship with the customer. Utilities can deliver customized reports that track and measure building changes over time, providing a mechanism for follow-up on a consistent basis.

The data can also be analyzed and used to tailor engagement efforts at specific groups of commercial buildings – providing specific recommendations that resonate for different audiences. Large office towers will receive different recommendations from the pizza shop around the corner.  This level of targeting is critical in achieving savings on a mass scale.

There are three primary market segments utilities need to focus on:

• Large Buildings:  Big offices, federal/state buildings, universities, etc… These often have a common manager with multiple buildings in a portfolio.  They’re characterized by complex and multi-million dollar energy bills.  Successful engagement starts with an understanding of the energy use for the entire portfolio, prioritizing energy savings opportunities across a campus or syndicate of buildings.  This helps justify customer projects and obtain investment capital – and is true engagement.
• Medium Buildings: Consists mainly of schools, municipal buildings, etc…  These are smaller in size and consumption, but usually have complex systems.  To reach this market, utilities need scale – pushing out energy-usage data to thousands of contacts at the same time.  Big data enables the utility to use Internet portals as a two-way interface to engage customers deeply, generating leads and data-based prioritization that can be followed by sales reps.
• Small Business:  The biggest, yet most overlooked portfolio, consists of the pizza shops, dentists offices and similar businesses.  These are cost-conscious owners that are very aware of every dollar they spend on energy – yet lack insight into how the energy is been used.  Utilities need to empower these businesses to self-serve, complete with benchmarks and education that connects their building to energy savings.  But don’t confuse this with the consumer market – they require business-specific information tied to saving targets.

Commercial buildings represent the most realistic pathway to a more energy efficient future in the U.S. and big data is the key to unlocking the savings potential.  Utilities need to embrace the availability and use of this data to engage commercial customers on a consistent and meaningful basis.

Swap Shah is co-founder and CEO of FirstFuel Software.  He has 20 years of experience leading software companies and was a key founder of three companies that went on to an IPO or acquisition, including Open Environment (IPO), WebSpective Software and mValent. Swap holds a BS from Cornell University

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The company uses multi-spectral thermal cameras on top of cars to snap images of visible energy leaks coming from buildings. Esses uses these images to create databases about the energy consumption of buildings, neighborhoods and cities and the company has algorithms that can crunch all that energy leakage image data and turn it into useful information for building owners, like energy efficiency reports. Esses sells a software as a service product.

In addition, the thermal data will enable essess to create an efficiency metric for each building — sort of like an MPG for cars. Esses CEO Storm Duncan said at the Wall Street Journal Eco:nomics conference recently that he wants to put an MPG on every building in the country, and said “It’s similar to what Zillow did for the real estate market.”

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Here are eight ways big data and analytics are already helping manage resources for a booming population:

1. SAP’s Population Demographics. In time for the 7 billion mark next week, SAP and the United Nations Population Fund created interactive maps that show the demographics of both an aging and a youthful population of 7 billion people. It only takes 13 years to add another 1 billion more people to the planet, according to the report. You can check out world stats, like birth rates, deaths, percentage of population by age, as well as gender.

2. Space-Time Insight. A startup called Space-Time Insight creates software that merges real-time geospatial data with Google Maps, and sells the software to utilities and gas and oil companies to manage their resources in real time. California’s Independent System Operator Corporation (Cal ISO) — which manages 85 percent of the state’s power load — has installed an 80-foot by 6.5-foot screen in its control room to display real-time power-grid data from thousands of endpoints. Cal ISO used to get the data in four-second intervals, but given the growth in resources, population and data feeds, it now gets updates by the millisecond.

3. The Climate Corporation. Formerly called WeatherBill, the now renamed Climate Corporation uses big data tools to offer analytics and reports to the agriculture industry, and also sells a weather insurance product to farmers, to help protect them from losses from extreme weather events. The world has seen a rise in extreme weather events, partly do to a change in climate, and farmers can expect more of this unpredictability going forward. Combined with more unpredictable weather, food prices will likely rise as the population grows and usable land becomes constrained, particularly in developing countries.

4. Google Earth Engine. Google launched Google Earth Engine, a year ago at COP 16, and the product combines an open API; a computing platform; and 25 years of satellite imagery available to researchers, scientists, organizations and government agencies. Google Earth Engine is interesting because it offers both tools and parallel processing computing power to groups to be able to use satellite imagery to analyze environmental conditions in order to make sustainability decisions. For example, the government of Mexico created the first comprehensive, high-resolution map of Mexico’s forests, using Google Earth Engine, incorporating 53,000 Landsat images, to produce a 6-gigabyte product. The Mexican government and NGOs can now use the map to make decisions about land use, sustainable agriculture, and species protection in combination with a growing population.

5. Google Oceans. Climate change and population growth will also affect how the world protects, uses and manages the oceans. In Google’s 5.0 version of its Google Earth tool, it included detailed ocean data (the ability for the user to dive beneath the surface) and “historical imagery” that features a time slider of satellite data for a location over time. (Below, Jimmy Buffet looking up at Google Oceans).

6. Building energy management. As more and more buildings are built to accommodate the growing population, the energy consumption of those buildings will need to be managed. A startup called FirstFuel Software use analytics and a set of data to remotely determine energy information about a commercial building, like consumption habits, and give recommendations for how to make the building run more energy efficiently. The company says it uses no on-site hardware or onsite energy audits, to get this data and yet says its information is as accurate as information received through an on-site energy audit, which is far more costly. The data sets needed to produce an accurate set of energy information includes, utility-based electric and gas data for a year, the location’s weather and climate data, as well as GIS mapped building data.

7. Curbing home energy. Other companies like Opower are focused on using analytics and behavioral tools to get consumers to change their energy consumption habits in homes. Opower recently announced plans to launch a Facebook application it says could one day be the world’s largest social network around energy.

8. Mobile phone data from settlements: A group of Harvard researchers is looking to use cell phone data combined with mathematical models and statistics, to better understand the needs of the 1 billion people who live in informal housing, called settlements or slums in developing countries. Other researchers in the group are looking to use big data to predict food shortages in developing countries and crime sprees due to causal events, like climate change.

Image courtesy of Smagdali.

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