For encapsulation of advantageous opportunities in the energy sector, utility and energy companies are transforming their systems into smarter energy systems, which would feature a new-way flow of information in energy and utility sectors. Energy utility analytics enables near real-time analysis of processes, thereby helping in optimization of operations through efficient identification and isolation of inefficiencies and failures. The energy utility analytics market has the following perspectives: vendor performance & risk management, demand forecasting, spend analytics, inventory optimization, logistics & routing analytics, and predictive analytics. Business analytics coupled with data mining, self-service, predictive analytics, and aggregation tools is employed to get more transparent information for critical decision-making and implementing the decision support system.
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This transforms mobility and supporting communication technologies into high-investment priority areas for utilities. Virtually all new technology projects in energy utility would require a combination of IT (Information Technology), OT (Operational Technology), and planning analytics such as advanced metering infrastructure (AMI) or advanced distribution management systems (ADMSs). More than any industry, the energy utility analytics market faces the challenge of separation between IT and OT management, coupled with the importance of hybrid projects that link IT and OT systems. The energy industry would benefit by aligning their OT support, standards, and procedures with those of IT. This would shorten the time consumed to develop governance over OT.
Major forces driving the energy utility analytics market are the increasing demand for energy, need for greener environment, and increasing demand from the consumer side to know their energy consumption pattern. Big data analytics, supply chain analytics, cloud computing, and operational analytics are the latest trends applied in the energy sector. Big data analytics service puts in: place data, processes, analytics tools, and visualizations by enabling faster time to insights. It enhances the quality and reliability of insights through exploratory and self-learning models. Business outcomes are thus improved through data-driven decisions.
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Energy utility analytic’s Big Data has a smart grid development system. This smart grid development increases data quantity by high magnitude. This grid development is driven by a host of devices and new IT applications such as AMI, synchrophasors and smart appliances, microgrids, advanced distribution management, remote asset monitoring, event avoidance, and self-healing networks. AMI is one of the major constituents of smart grid that potentially provides a communication backbone for low-latency data. This is aimed at improving distribution asset utilization, failure detection and facilitating consumer inclusion in energy markets. Different market structures, regulatory drivers, and benefit expectations create different ownership models for components of the AMI technology stack. This favors different technology solutions across the globe.
The energy and utility analytics market is segmented by type (software and services), by application (predictive maintenance, load research & forecasting, and transmission & distribution management), by end-use (energy, oil & gas, and utilities), and by region (North America, Latin America, Europe, Asia Pacific, and Middle East & Africa).
North America and Europe hold the leading share of the energy and utility analytics market as of 2016. The market in Asia Pacific (APAC) is projected to expand at the maximum rate during the forecast period. This is due to flexible policies of governments in developing countries as well as the ever-expanding digital industry in the APAC region.