TROVE: Data Science for Insightful Actions

TROVE: Data Science for Insightful Actions

Ted Schultz, CEO , TROVETed Schultz, CEO
“All data is good until used,” aptly points out Ted Schultz, CEO of TROVE when talking about the issues facing energy CIOs. There are a number of data quality issues being encountered in the new energy landscape as data is being captured and analyzed in new ways to discover value beyond operational purposes. In addition, integrating the volume, velocity and variety of data that is growing exponentially with the emergence of smart grids, distributed energy resources, Internet of Things, as well as consumer behavioral patterns, is a significant challenge. Enter TROVE, a New York-based predictive data science company that enables clients to use their patented technology and cutting-edge technical team to go beyond traditional approaches to data analytics. By leveraging TROVE’s data fusion and data enrichment techniques to address data quality issues and TROVE’s Sunstone analytics platform to process massive volumes of data and integrate with existing applications, tangible business value is being delivered to clients.

TROVE targets the utility sector (electric, gas, water) with libraries of sophisticated, learning algorithms encapsulated in models that can be accessed directly from existing applications and third party visualization tools. The libraries are focused on load management and customer intelligence to unlock the true data potential and attain outcomes clients can reliably act on. Integrated load management solutions forecast demand for each individual customer with various levels of aggregation to predict events on a particular circuit in the distribution network. Besides offering load forecasts at various levels of aggregation in utility distribution networks, the solution empowers clients to understand the rationale behind the hike or drop in the demand to more effectively integrate and validate demand response events and distributed energy resources load. In future development, TROVE sees collaborating with their clients to uncover additional value from integrated load aggregation.

It is time to Stop Guessing and Take Action

“Our load management solution can fuse an enormous amount of data to better integrate activity at the edge of the grid and manage assets,” says Schultz.

The company also supports personalized customer portfolio management. TROVE spent more than two years fusing together a wide variety of external, third party data to create a robust database with more than 2,000 attributes on every consumer household and commercial property in the U.S. “Our expert data science team fuses our analytics ready third party data with our client’s internal data to gain incredible, unbiased customer insight and precision,” says Schultz. TROVE has several examples where their micro-targeting models are applied. In one such instance of micro-targeting, the company provided a list of individual customers to target for Energy Efficiency Programs that enabled a client to obtain 300 percent increase in their program’s response rate and a 37 percent rise in their energy savings. Such breakthrough improvements are a result of the company’s technology to leverage data fusion for massive volumes of structured, unstructured, and streaming data and apply predictive learning models to deliver real value.
The company plans to continue building out their data science products in close collaboration with their clients. “At TROVE, we empower our clients to build their capabilities and apply predictive data science to realize value. Actionable insights just are not enough. With our data science, it is time to Stop Guessing and take action,” says Schultz. The pragmatic approach of the company has TROVE breaking through as one of the leaders in the next frontier of big data, predictive data science.