Energy and Utilities Analytics Market
Energy and Utilities Analytics Market by Application (Outage Prediction, Predictive Maintenance, Carbon Accounting, Grid Reliability, Sustainability Analytics), End User (Power, Water & Waste Utilities, Renewable Energy Operators) - Global Forecast to 2031
OVERVIEW
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
The energy and utilities analytics market is projected to reach USD 10.10 billion by 2031 from USD 6.10 billion in 2026, at a CAGR of 10.6%. The energy and utilities analytics market is shifting towards an integrated, intelligence-led model that prioritizes predictive and prescriptive analytics for real-time decision-making. As the demand for energy increases and operations become more complex, utilities are leveraging AI-driven analytics to optimize efficiency, enhance energy distribution, and promote sustainability. Key technologies such as IIoT, AI/ML, and digital twin technologies, along with edge computing, are enabling better forecasting and operational visibility. This holistic approach is driving innovations that lower costs and improve efficiency, positioning the sector to adapt to evolving energy demands and environmental challenges.
Market Size and Forecast:
- Market Size Value in 2025: USD 5.36 Billion
- Market Size Value in 2026: USD 6.10 Billion
- Revenue Forecast in 2031: USD 10.10 Billion
- Growth Rate: CAGR of 10.6% from 2026 to 2031
- Data available from 2021 to 2031
- Base year: 2025
- Forecast period: 2026–2031
Key Market Trends and Insights
- Market Growth: Growth is driven by smart grid investments, rising renewable energy integration, and AI-powered predictive maintenance.
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IoT Impact: IoT integration accelerates real-time data stream processing, enhancing operational visibility across smart grids.
- Growing Trends: The market is driven by AI-powered predictive analytics, smart grid modernization, and increased renewable energy integration.
- Growth Opportunities: It include AI-driven predictive maintenance and load analytics for electric vehicle growth
KEY TAKEAWAYS
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BY REGIONNorth America is estimated to be the leading market for energy and utilities analytics, with a 33.5% regional share in 2026, driven by rapid digitalization across power generation, smart grids, renewable integration, and utility asset management.
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BY OFFERINGPlatforms remain the largest offering segment in the energy and utilities analytics market, projected at USD 6,664.3 million by 2031, owing to rising adoption of AI-powered utility analytics, smart grid technologies, and real-time energy management platforms.
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BY SERVICESManaged services emerge as the fastest-growing services subsegment, at a CAGR of 12.1%, driven by growing adoption of cloud-based analytics platforms, remote monitoring, and outsourced utility analytics management.
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BY ORGANIZATION TYPELarge integrated utilities remain the largest organization type segment in the energy and utilities analytics market, driven by increasing investments in smart grid modernization, enterprise-wide analytics platforms, and operational optimization initiatives.
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BY DEPLOYMENT MODECloud deployment is projected to be the largest and fastest-growing deployment mode in the energy and utilities analytics market, driven by increasing adoption of scalable, AI-enabled, and real-time utility analytics platforms.
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BY APPLICATIONGrid & network analytics remains the largest application segment in the energy and utilities analytics market, driven by increasing investments in smart grid modernization, outage management, and real-time grid monitoring solutions.
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BY END USERPower utilities remain the largest end-user segment in the energy and utilities analytics market, driven by increasing investments in smart grids, outage management, and real-time grid optimization technologies.
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COMPETITIVE LANDSCAPE - KEY PLAYERSGE Vernova, Siemens, Schneider Electric, ABB, Hitachi, Oracle, IBM, SAP, Microsoft, Itron, Google, and Landis+Gyr are the leaders with broad energy & utilities analytics offerings, strong utility-domain expertise, and continuous investments in digital energy technologies to achieve high market share.
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COMPETITIVE LANDSCAPE - STARTUPS/SMEsC3.ai, Enel X, Voltus, EnergyHub, TIBCO, Uplight, Sphera, and KUBRA excel in the energy and utilities analytics space by consistently delivering customized services and adopting strategies to maintain and grow their market share.
To meet growing energy demands and navigate complex operations, utilities are increasingly adopting AI-driven analytics to boost efficiency and promote sustainability. Technologies such as IIoT, AI/ML, digital twins, and edge computing are enhancing forecasting and operational visibility. This comprehensive approach is fostering innovations that cut costs and improve efficiency, equipping the sector to meet evolving energy needs and environmental challenges.
TRENDS & DISRUPTIONS IMPACTING CUSTOMERS' CUSTOMERS
The energy and utilities analytics market is undergoing a significant transformation, shifting from traditional asset monitoring and operational reporting to an intelligent, AI-driven ecosystem fueled by real-time analytics and cloud-native platforms. While historical revenue was primarily concentrated in conventional areas like legacy SCADA systems and manual reporting, the future is increasingly dominated by AI-powered predictive analytics, grid intelligence, and IoT-enabled asset performance monitoring. Vendors are enhancing their offerings with machine learning and edge computing to improve grid resilience, optimize renewable energy integration, and support decarbonization initiatives. Key client segments, including power utilities and renewable energy providers, are focusing on operational resilience and customer experience, leading to improved grid reliability and sustainability reporting. This evolution marks a transition from reactive models to proactive, intelligent energy operations centered around real-time analytics.
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
MARKET DYNAMICS
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Grid Modernization Investments Expanding Analytics Deployment
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Rising Renewable Energy Penetration Is Increasing Forecasting Requirements
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Legacy Infrastructure Limits Analytics Integration
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Cybersecurity and Data Privacy Requirements Increase Deployment Costs
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AI-driven Predictive Maintenance Is Creating New Value Streams
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Electric Vehicle Growth Is Expanding Demand for Load Analytics
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Demonstrating ROI Across Large Scale Deployments Remains Difficult
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Real-time Processing Requirements Increase Infrastructure Complexity
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
Driver: Grid Modernization Investments Expanding Analytics Deployment
Utilities in both developed and emerging economies are ramping up investments in grid modernization, driving demand for advanced analytics platforms and operational technologies. Governments and energy providers are prioritizing smart grids, digital substations, and modern distribution infrastructure to meet rising electricity demand and energy transition goals. The International Energy Agency (IEA) emphasizes that grid investment is crucial for electrification, renewable integration, and long-term energy security. This modernization generates vast amounts of data that utilities analyze in real time for improved efficiency and reliability. Consequently, utilities are adopting analytics for outage management, load forecasting, asset monitoring, and network optimization. The shift toward decentralized energy generation further requires enhanced operational visibility across complex networks. As aging infrastructure is upgraded, analytics solutions are evolving into essential layers for intelligent, automated grid management.
Restraint: Legacy Infrastructure Limits Analytics Integration
Many utility companies still rely on outdated operational technology systems that complicate modern analytics integration. These legacy systems often lack interoperability and real-time communication, resulting in fragmented environments and disconnected data across generation, transmission, distribution, and customer management. Upgrading infrastructure demands significant investment and complex migration, which slows adoption. Regulatory and financial constraints further hinder modernization efforts, preventing the establishment of unified analytics environments for better visibility and decision-making. The coexistence of new digital platforms with old technologies complicates maintenance and implementation, making large-scale deployment of advanced analytics in utility markets challenging.
Opportunity: AI-driven Predictive Maintenance Is Creating New Value Streams
Utilities are increasingly utilizing AI-driven predictive maintenance solutions to enhance asset reliability and optimize infrastructure performance in energy networks. These platforms analyze sensor and operational data to detect early signs of component degradation and maintenance needs, helping minimize unplanned outages and reduce costs. Key application areas include transmission networks, substations, wind turbines, and power generation facilities. The rise of industrial IoT devices is enhancing real-time data availability, supporting maintenance optimization. By employing machine learning, utilities can prioritize maintenance schedules based on asset importance and historical data. As energy providers focus on efficiency and resilience, predictive maintenance analytics is expected to be a major investment area, driven by the complexity of energy systems and the need to prevent service disruptions.
Challenge: Real-time Processing Requirements Increase Infrastructure Complexity
Modern utility operations produce vast amounts of streaming data from smart meters, renewable energy sources, and industrial sensors, complicating analytics infrastructure. Utilities need advanced platforms for real-time data processing to ensure grid reliability and operational efficiency. Managing high-speed data streams with low latency demands robust computing power, scalable storage, and resilient networks. Continuous system availability is crucial, as outages can impact critical services. The integration of cloud computing, edge analytics, and IoT adds to the complexity. As renewable energy and smart grids grow, the volume and speed of operational data will rise, necessitating sophisticated architectures for secure and real-time analytics in modern energy networks.
ENERGY AND UTILITIES ANALYTICS MARKET: COMMERCIAL USE CASES ACROSS INDUSTRIES
| COMPANY | USE CASE DESCRIPTION | BENEFITS |
|---|---|---|
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BKW partnered with Siemens Advanta to implement a centralized cloud-based digital utility platform integrating smart meter information, operational systems, and enterprise datasets. The solution improved interoperability, enabled advanced analytics, and supported scalable modernization of utility operations. | Improved integration and accessibility of utility and smart meter data, reduced data silos through centralized infrastructure, enhanced operational analytics, and enabled scalable modernization initiatives with better decision-making capabilities |
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Anglian Water collaborated with IBM to modernize utility infrastructure and operational data management through integrated enterprise modernization solutions. The implementation improved interoperability, streamlined enterprise data integration, and strengthened operational intelligence across utility systems. | Increased operational efficiency and resilience, improved data accessibility and visibility across utility operations, enhanced coordination between enterprise systems, and supported scalable long-term digital transformation initiatives |
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ABB implemented an integrated automation and analytics platform for Eya-Bantu to enhance operational monitoring, infrastructure visibility, and asset management capabilities. The system centralized operational data analysis and enabled real-time performance monitoring across utility environments. | Improved operational visibility and infrastructure performance, enabled proactive maintenance planning, reduced inefficiencies through centralized analytics, accelerated decision-making with real-time insights, and supported scalable digital utility transformation |
Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.
MARKET ECOSYSTEM
The applications ecosystem consists of interconnected digital platforms, analytics services, and operational technologies that facilitate intelligent, data-driven decision-making in energy and utility operations. These innovative solutions aid in monitoring grids and networks, managing asset performance, engaging customers, optimizing energy production, trading energy, and overseeing sustainability efforts through advanced analytics, artificial intelligence, automation, and cloud solutions. By integrating operational, commercial, and market data, this ecosystem enables organizations to enhance reliability, optimize operational performance, improve customer experiences, support the integration of renewable energy and distributed energy resources (DER), manage trading and risk activities, and achieve sustainability and environmental, social, and governance (ESG) goals, all while ensuring scalability, interoperability, and resilience in operations.
Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.
MARKET SEGMENTS
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
Energy and Utilities Analytics Market, by Offering
Platforms are estimated to the largest offering segment in the energy and utilities analytics market. The complexity of modern energy systems has heightened the need for analytics platforms that can handle large volumes of structured and unstructured data in real time. These platforms are essential for demand forecasting, grid optimization, outage management, energy trading analysis, and predictive maintenance. The growing popularity of cloud-based analytics offers scalability, cost efficiency, remote access, and quicker deployment compared to traditional systems. Many vendors are also integrating AI, machine learning, and advanced visualization to enhance insights and forecasting accuracy. As utilities modernize and invest in smart grid technologies, these analytics platforms are crucial for improving operational efficiency, customer engagement, and long-term grid reliability.
Energy and Utilities Analytics Market, by Service
Managed services emerge as the fastest-growing services subsegment. Utilities are increasingly turning to managed services to simplify the maintenance of their analytics systems while gaining access to specialized technical expertise and scalable operational support. The growing use of smart grids, connected infrastructure, and real-time operational data is driving demand for outsourced management of analytics within the energy sector. Managed service providers also assist utilities in enhancing system availability, ensuring regulatory compliance, and strengthening cybersecurity across critical infrastructure. Moreover, the rising adoption of cloud computing, artificial intelligence, and predictive analytics technologies is fueling the demand for managed analytics operations and monitoring services. As utilities continue to expand their digital infrastructure and data-driven operations, the role of managed services is becoming vital for supporting operational continuity, infrastructure management, and long-term analytics performance.
Energy and Utilities Analytics Market, by Organization Type
Large integrated utilities remain the largest organization type segment in the energy and utilities analytics market. Large integrated utilities use analytics platforms for grid monitoring, outage management, asset performance, customer operations, renewable energy integration, and infrastructure planning. They enhance operational coordination across distributed systems and multi-service operations. The rise of smart grid infrastructure and advanced metering systems is increasing real-time analytics use. Utilities are also investing in AI and predictive analytics for reliability management and forecasting, driven by regulatory pressures and modernization efforts.
Energy and Utilities Analytics Market, by Deployment Mode
Cloud deployment is projected to be the largest and fastest-growing deployment mode in the energy and utilities analytics market. Cloud deployment allows utilities to access analytics solutions remotely, reducing the need for extensive on-premises infrastructure. This model promotes scalability, centralized data access, remote monitoring, and quicker implementation of analytics across operations. Utilities increasingly use cloud-based analytics for smart grid management, demand forecasting, outage monitoring, renewable energy integration, and customer analytics. SaaS offers subscription access to applications, while PaaS supports development and customization. Cloud environments efficiently handle large volumes of data from IoT devices and enable AI integration, advanced forecasting, and automated reporting. The push for digital transformation, lower management costs, and demand for scalability drive the adoption of these models in the energy sector.
Energy and Utilities Analytics Market, by Application
Grid & network analytics remains the largest application segment in the energy and utilities analytics market. Utilities are increasingly using grid analytics solutions to manage the complexities of smart grids, distributed energy resources, renewable energy integration, and rising electricity demand. Key applications include outage prediction, network performance monitoring, voltage optimization, load balancing, and fault detection. These platforms enhance infrastructure utilization, operational visibility, and real-time decision-making across transmission and distribution systems. The rise of IoT devices, smart meters, and connected substations is generating vast amounts of operational data, driving the adoption of advanced analytics. Utilities leverage these tools to improve service continuity, optimize network efficiency, and strengthen resilience against disruptions. As digital grid modernization expands globally, grid analytics is vital for stable and efficient utility operations.
Energy and Utilities Analytics Market, by End User
Power utilities remain the largest end-user segment in the energy and utilities analytics market. Power utilities use analytics to enhance grid reliability, monitor infrastructure, optimize energy flow, and aid decision-making in interconnected systems. The rise of smart grids, advanced metering, connected substations, and distributed energy resources is expanding analytics use in utility operations. Moreover, utilities are integrating AI and predictive analytics for maintenance planning, outage prediction, and performance analysis. Increasing operational complexity, renewable energy integration, and infrastructure modernization further drive analytics adoption in power utilities.
REGION
Asia Pacific to be the fastest-growing region in the global energy and utilities analytics market during the forecast period
The Asia Pacific region is poised to be the fastest-growing market for energy and utilities analytics, fueled by government mandates for energy security and decarbonization, as well as capacity additions. Leading this demand are China and India, which are making substantial investments in AI-driven analytics for power management. In more mature markets like Japan, Australia, and South Korea, analytics is being employed to support energy diversification and achieve net-zero goals. Meanwhile, countries in Southeast Asia, such as Indonesia and Vietnam, are rapidly adopting analytics for outage management and network planning. However, the diverse regulatory environments across the region present both challenges and opportunities for analytics vendors. In newer digital markets, cloud-native deployments are on the rise, while larger utilities in China and India tend to favor on-premise solutions, influenced by government initiatives that promote the use of AI and machine learning in the power sector.
ENERGY AND UTILITIES ANALYTICS MARKET: COMPANY EVALUATION MATRIX
GE Vernova (Star) holds a strong position in the energy and utilities analytics market through its extensive portfolio of grid modernization, digital energy management, and industrial analytics solutions. The company benefits from its broad presence across power generation, transmission, and renewable energy infrastructure, enabling it to integrate advanced analytics capabilities into large-scale utility operations. Its focus on predictive asset monitoring, grid optimization, and AI-enabled operational intelligence supports utilities in improving reliability, reducing downtime, and enhancing energy efficiency across increasingly complex energy networks. Autodesk provides a range of cloud-connected solutions for water infrastructure, operational analytics, and digital twin capabilities aimed at enhancing utility network management and hydraulic modeling. Its integrated tools, including Info360 Insight and Autodesk Tandem, help utilities improve visibility, resilience, and asset performance. With strengths in real-time analytics, simulation modeling, and GIS integration, Autodesk enables optimized water distribution, wastewater management, and flood forecasting, establishing itself as a leading provider for the Energy and Utilities market.
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
KEY MARKET PLAYERS
- ABB (Switzerland)
- GE Vernova (US)
- Autodesk (US)
- IBM (US)
- Schneider Electric (France)
- Google (US)
- Microsoft (US)
- Oracle (US)
- SAP (Germany)
- Hitachi Energy (Switzerland)
- Bentley Systems (US)
- SAS Institute (US)
- Teradata (US)
- Snowflake (US)
- Itron (US)
MARKET SCOPE
| REPORT METRIC | DETAILS |
|---|---|
| Market Size in 2025 (Value) | USD 5.36 Billion |
| Market Size in 2026 (Value) | USD 6.10 Billion |
| Market Forecast in 2031 (Value) | USD 10.10 Billion |
| Growth Rate | 10.6% |
| Years Considered | 2021–2031 |
| Base Year | 2025 |
| Forecast Period | 2026–2031 |
| Units Considered | Value (USD Million/Billion) |
| Report Coverage | Revenue forecast, company ranking, competitive landscape, growth factors, and trends |
| Segments Covered |
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| Regions Covered | North America, Europe, Asia Pacific, Middle East & Africa, Latin America |
WHAT IS IN IT FOR YOU: ENERGY AND UTILITIES ANALYTICS MARKET REPORT CONTENT GUIDE
DELIVERED CUSTOMIZATIONS
We have successfully delivered the following deep-dive customizations:
| CLIENT REQUEST | CUSTOMIZATION DELIVERED | VALUE ADDS |
|---|---|---|
| Electric Utility Company (North America) | Regional Energy & Utilities Analytics Market Assessment: Analysis of smart grid analytics, outage management, predictive maintenance, smart meter deployments, and grid modernization initiatives across North America | Identifies high-growth utility analytics segments, benchmarks technology adoption trends, supports vendor evaluation, reduces investment risk, and enables data-driven grid modernization strategies |
| Renewable Energy Developer | Competitive Landscape Assessment: Profiling of analytics providers across renewable forecasting, asset performance management, predictive maintenance, energy trading, and operational intelligence solutions | Expands qualified vendor options, identifies emerging technology capabilities, benchmarks competitive offerings, accelerates technology selection, and supports renewable asset optimization initiatives |
| Energy Retailer (Europe) | Customer Analytics And Demand Forecasting Assessment: Analysis of customer segmentation, consumption analytics, demand forecasting, churn prediction, and personalized energy management solutions | Improves customer engagement strategies, identifies revenue optimization opportunities, enhances forecasting accuracy, supports customer retention initiatives, and enables data-driven business decision-making |
RECENT DEVELOPMENTS
- March 2026 : ABB enhanced its ABB Ability™ Energy Management System with generative AI capabilities, enabling users to access energy, emissions, and operational data through natural-language queries. The solution accelerates insight generation, simplifies energy analysis, improves operational efficiency, and supports sustainability and energy management initiatives.
- February 2026 : GE Vernova launched GridOS for Distribution, a software platform that unifies grid operations, distributed energy resource management (DERMS), planning, analytics, and field execution. The solution enabled utilities to manage increasingly complex distribution networks through a single platform, improving grid visibility, operational efficiency, resilience, and decision-making.
- January 2026 : Itron advanced its intelligent grid analytics capabilities by leveraging data from smart meters and connected utility infrastructure. The solution helped utilities improve grid monitoring, outage management, operational planning, and customer service while enabling more efficient and data-driven utility operations.
- September 2025 : Hitachi expanded its digital energy solutions portfolio to support utility modernization through advanced analytics, operational intelligence, and data-driven asset management. The initiative helped utilities improve infrastructure visibility, optimize asset performance, enhance grid reliability, and facilitate renewable energy integration.
Table of Contents
Exclusive indicates content/data unique to MarketsandMarkets and not available with any competitors.
Methodology
This research study on the energy and utilities analytics market involved extensive secondary sources, including directories, IEEE Communication-Efficient: Algorithms and Systems, and the International Journal of Innovation and Technology Management, as well as paid databases. Primary sources were mainly industry experts from core and related industries, preferred energy and utilities analytics providers, third-party service providers, consulting service providers, end users, and other commercial enterprises. In-depth interviews with primary respondents, including key industry participants and subject matter experts, were conducted to gather and verify critical qualitative and quantitative information, as well as assess the market’s prospects.
Secondary Research
In the secondary research process, various sources were referred to identify and collect information for this study. Secondary sources included annual reports, press releases, and investor presentations of companies; white papers, journals, and certified publications; and articles from recognized authors, directories, and databases. The data was also collected from other secondary sources, such as journals, government websites, blogs, and vendors’ websites. Additionally, the energy and utilities analytics spending of various countries was extracted from the respective sources.
Primary Research
In the primary research process, various sources from the supply and demand sides were interviewed to obtain qualitative and quantitative information on the market. The primary sources from the supply side included various industry experts, such as chief experience officers (CXOs), vice presidents (VPs), and directors specializing in business development, marketing, and energy and utilities analytics services. It also included key executives from energy and utilities analytics vendors, system integrators (SIs), professional service providers, industry associations, and other key opinion leaders.
Breakup of Primary Profiles
Note: Tier 1 companies’ revenue is more than USD 500 million; tier 2 companies’ revenue range between USD 500 million and 100 million; and tier 3 companies’ revenue ranges less than USD 100 million for the calendar year ended December 31st, 2025
*Others include sales managers, marketing managers, and product managers
Source: Industry Experts
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
Multiple approaches were adopted to estimate and forecast the energy and utilities analytics market. The first approach involved estimating the market size based on companies’ revenue from the sale of energy and utilities analytics products.
Market Size Estimation Methodology: Top-down Approach
The top-down approach prepared an exhaustive list of all the vendors offering products in the energy and utilities analytics market. The revenue contribution of the market vendors was estimated through annual reports, press releases, funding, investor presentations, paid databases, and primary interviews. Each vendor’s offerings were evaluated based on offering, deployment mode, organization type, application, end user, and region. The markets were triangulated through primary and secondary research. The primary procedure included extensive interviews for key insights from industry leaders, such as CIOs, CEOs, VPs, directors, and marketing executives. The market numbers were further triangulated with the existing MarketsandMarkets’ repository for validation.
Market Size Estimation Methodology: Bottom-up Approach
The bottom-up approach identified the adoption rate of energy and utilities analytics products across different end users in key countries, considering the regions that contribute the most to the market share. For cross-validation, the adoption of energy and utilities analytics products among enterprises and other use cases for their regions was identified and extrapolated. Use cases identified in different areas were weighed for the market size calculation.
Based on the market numbers, the regional split was determined by primary and secondary sources. The procedure included an analysis of the energy and utilities analytics market’s regional penetration. Based on secondary research, the regional spending on Information and Communications Technology (ICT), socioeconomic analysis of each country, strategic vendor analysis of major energy and utilities analytics service providers, and organic and inorganic business development activities of regional and global players were estimated.
Energy and Utilities Analytics Market : Top-Down and Bottom-Up Approach
Data Triangulation
After determining the overall market size using the market size estimation processes as explained above, the market was split into several segments and subsegments. Data triangulation was employed, wherever applicable, to complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment. The overall market size was then used in the top-down approach to estimate the size of other individual markets by applying percentage splits to the market segmentation.
Market Definition
Industry experts have dimensionally varying definitions. Here are two that explained the scope of MarketsandMarkets’ study best:
According to Salesforce, energy and utilities analytics refers to the use of unified operational, customer, and asset data along with AI-driven insights to help utility companies improve decision-making, optimize operations, enhance customer engagement, and support sustainability goals. It enables organizations to analyze real-time and historical data for better forecasting, operational efficiency, and service management.
According to ScienceSoft, energy and utilities analytics refers to the use of advanced data analytics and AI technologies to help utility companies make informed decisions using data from energy generation, distribution, consumption, equipment performance, and environmental factors. It enables organizations to integrate data from multiple sources into a unified system for better operational visibility and efficiency. These analytics solutions support applications such as demand forecasting, predictive maintenance, demand-side management (DSM), and ESG monitoring. Ultimately, energy and utilities analytics help improve asset utilization, optimize resource allocation, ensure regulatory compliance, and enhance customer experience.
Key Stakeholders
- Energy and utilities analytics platform vendors
- Enterprise end users
- Distributors and Value-added Resellers (VARs)
- Government agencies
- Independent software vendors (ISVs)
- Managed service providers
- Support & maintenance service providers
- System Integrators (SIs)/migration service providers
- Technology providers
- Academia & research institutions
- Investors & venture capital firms
Report Objectives
- To define, describe, and forecast the energy and utilities analytics market, by offering, deployment mode, organization type, application, and end user
- To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing market growth
- To strategically analyze the micromarkets with respect to individual growth trends, prospects, adoption patterns, and their contribution to the total market
- To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
- To analyze the impact of macroeconomic factors on the Energy and utilities analytics market across all regions
- To analyze market opportunities for stakeholders and present a comprehensive competitive landscape of leading energy and utilities analytics vendors, OEM aftermarket players, and service providers
- To project the market size and its submarkets in terms of value (USD million) across five key regions (North America, Europe, Asia Pacific, Middle East & Africa, Latin America), along with an analysis of their respective major countries
- To strategically profile leading companies and provide an in-depth evaluation of their core competencies, product portfolios, technology capabilities, and market positioningTo examine competitive developments, including product launches, software upgrades, partnerships, integrations, strategic expansions, and mergers & acquisitions across the energy and utilities analytics ecosystem
Available customizations:
With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:
Product Analysis
- The product matrix provides a detailed comparison of the product portfolio of each company.
Regional Analysis
- Further breakup of the North American energy and utilities analytics market
- Further breakup of the European energy and utilities analytics market
- Further breakup of the Asia Pacific energy and utilities analytics market
- Further breakup of the Middle East & Africa energy and utilities analytics market
- Further breakup of the Latin American energy and utilities analytics market
Company Information
- Detailed analysis and profiling of additional market players (up to five)
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