Navigant Research Report Finds Machine Learning Has Several Advantages Over Existing Utility Analytics Techniques

Falling costs, new technological advancements, and a fresh
approach to analytics procurement make machine learning deployments
easier than ever, report finds

BOULDER, Colo.–(BUSINESS WIRE)–#Analytics–A new report from Navigant
Research examines use cases for machine learning in the utilities
industry, detailing its advantages over other analytics techniques, and
providing future requirements and recommendations.

Machine learning is rapidly moving into the mainstream and is high on
the agenda of many utilities. While the technology has existed in parts
of the utility value chain for years, various drivers are expected to
increase its use throughout other areas of the business. Click
to tweet: According to a new report from @NavigantRSRCH,
machine learning has several advantages over existing utility analytics
techniques when performing customer segmentation, pricing forecasts,
anomaly detection, fraud detection, and predictive maintenance.

“The utilities industry is already using self-learning algorithms,
particularly in the field of asset monitoring and predictive
maintenance, and several reasons suggest the use of machine learning
will expand to many more use cases and its adoption will accelerate,”
says Stuart Ravens, principal research analyst with Navigant Research.
“During the past decade, it has become easier for companies to deploy
machine learning thanks to falling costs, new technological
advancements, a softening of conservative attitudes, and a fresh
approach to analytics procurement.”

Utilities are encouraged to investigate how and where machine learning
can help their businesses now and in the future, but should be aware of
existing limitations. According to the report, machine learning is best
suited for a handful of specific analytical processes, including
clustering, regression, and classification.

The report, Machine
Learning for the Digital Utility, describes several use cases
for machine learning and examines why machine learning has an advantage
over existing analytics techniques. Future requirements for machine
learning—specifically for distributed energy resources (DER) management
and transactive energy—are also discussed, as are several
recommendations for utilities developing their machine learning
strategies. An Executive Summary of the report is available for free
download on the Navigant
Research website.

About Navigant Research

Navigant Research, the dedicated research arm of Navigant, provides
market research and benchmarking services for rapidly changing and often
highly regulated industries. In the energy sector, Navigant Research
focuses on in-depth analysis and reporting about global clean technology
markets. The team’s research methodology combines supply-side industry
analysis, end-user primary research and demand assessment, and deep
examination of technology trends to provide a comprehensive view of the
Energy Technologies, Utility Transformations, Transportation
Efficiencies, and Buildings Innovations sectors. Additional information
about Navigant Research can be found at www.navigantresearch.com.

About Navigant

Navigant Consulting, Inc. is a specialized, global professional services
firm that helps clients take control of their future. Navigant’s
professionals apply deep industry knowledge, substantive technical
expertise, and an enterprising approach to help clients build, manage
and/or protect their business interests. With a focus on markets and
clients facing transformational change and significant regulatory or
legal pressures, the Firm primarily serves clients in the healthcare,
energy and financial services industries. Across a range of advisory,
consulting, outsourcing, and technology/analytics services, Navigant’s
practitioners bring sharp insight that pinpoints opportunities and
delivers powerful results. More information about Navigant can be found
at navigant.com.

* The information contained in this press release concerning the
report, Machine Learning for the Digital Utility, is a summary
and reflects Navigant Research’s current expectations based on market
data and trend analysis. Market predictions and expectations are
inherently uncertain and actual results may differ materially from those
contained in this press release or the report. Please refer to the full
report for a complete understanding of the assumptions underlying the
report’s conclusions and the methodologies used to create the report.
Neither Navigant Research nor Navigant undertakes any obligation to
update any of the information contained in this press release or the
report.

Contacts

Navigant Research
Lindsay Funicello-Paul, +1-781-270-8456
[email protected]