Investment strengthens Ecova’s commitment to data-driven insights for Energy and Sustainability Management
Spokane, WA — February 8, 2016 — Ecova, the total energy and sustainability management company, has made an investment in TROVE Predictive Data Science, a next-generation data analytics company. Ecova will leverage TROVE’s data fusion technology to manage resources and assets, with the objective to ultimately save money for over 700,000 sites in its North American client portfolio starting as early as 2016. TROVE technology enables analytical solutions that continuously learn to deliver data-driven insights for companies interested in better managing data and assets, and reducing energy and resource consumption.
TROVE utilizes proprietary algorithms to find correlations in data. This technology has increased energy efficiency program response rates by nearly 300 percent compared to traditional methods and delivered energy reduction per customer by 37 percent.
“TROVE’s technology is a key component of our strategy as we build global capability for integrating, organizing and leveraging data from our portfolio of over 700,000 sites for insight we can use to generate action and provide powerful results to our clients,” said Jana Schmidt, president and CEO of Ecova. “The investment enhances Ecova’s dedication in helping commercial clients reduce energy consumption and costs across their portfolio of sites. It also emphasizes our commitment to data and analytics-driven customer engagement for utilities.”
Ecova makes businesses and utilities more successful through energy and sustainability management. With the investment in TROVE, Ecova can harness the power of data to help utilities deliver value, while driving measurable action and results. For Ecova’s broad base of commercial and industrial clients, this investment enables advanced predictive analytics such as benchmarking and forecasting, on top of interval data. It also enables Ecova to use interval meter and telemetry data to provide solutions that optimize consumption of individual energy assets and reduce total building energy consumption.
“TROVE goes beyond common data analytics approaches, by leveraging data fusion, data enrichment and sophisticated data science against massive volumes of structured, semi-structured and unstructured data,” said Ted Schultz, CEO of TROVE. “We are thrilled with this investment by Ecova and look forward to working with them to help companies drive value through insightful actions that deliver real results.”
Ecova joins Avista, CUBRC, Inc. and Itron in its investment in TROVE.
Ecova makes businesses and utilities more successful through energy and sustainability management. Ecova blends data and technology, with people and insight, to drive powerful results. Using insights based on consumption, cost and carbon footprint data spanning thousands of utilities, hundreds of thousands of business sites and millions of households, Ecova provides fully managed, technology-optimized solutions for saving resources, which in turn increase returns, lower risks and enhance reputations. Ecova is the total energy and sustainability management company whose sole purpose is to see more, save more and sustain more for its clients. For more information, visit the company’s website www.ecova.com, on LinkedIn, or follow Ecova on Twitter at @EcovaInc.
ABOUT TROVE PREDICTIVE DATA SCIENCE
TROVE delivers analytical solutions and data-driven insights to its clients. The company’s multi-source data fusion technology combines internal client data with over 2,000 attributes of external third-party data. TROVE’s Sunstone Platform processes massive volumes of data, including structured, semi-structured, and unstructured data, as well as high-velocity streaming data. Its data scientists develop self-learning models that predict individual customer behaviors through the lens of complex data relationships enabling its clients to stop guessing and confidently act on decisions to deliver real value. To learn more about TROVE, please visit our website at TroveData.com.