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Enhancing Utility Business with Data Analytics and Artificial Intelligence

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Bhagvan Kommadi's picture
Founder of First Quantum Computing Startup in India Architect Corner

Bhagvan Kommadi is the Founder of Architect Corner - AI startup and has around 20 years of experience in the industry, ranging from large-scale enterprise development to help incubate software...

  • Member since 2019
  • 14 items added with 17,786 views
  • Dec 8, 2021

This item is part of the Data Analytics & Intelligence - December 2021 SPECIAL ISSUE, click here for more

The evolving trend in Utility Vertical is to create a true data ecosystem.  They are building a go to market engine is based on AI, Machine Learning, and Analytics. Energy industry enterprises can use this engine for improving customer service.  Customer service agents can use this engine to resolve the customer’s issue by using the engine for understanding customer history and profile. Energy enterprises can execute their marketing strategies and campaigns using the engine. Marketing automation can be a reality  which can integrate customer profiles, history, concerns, issues, and contact center solution. Energy industry enterprises can improve their businesses by  business transformation initiatives and operational efficiency improvement programs.

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Data analytics is being used in energy industry for predictive models and for finding issues in the equipment for replacements and repairs. Predictive analytics are used for sustainable energy generation, distribution, supplying, and consumption. Consumer energy demand is predicted by using the data analytics and historical data.  Data analytics can help to react on possible failures in important equipment and the resources.  Energy industry operators can respond and be flexible to demand signals and provide energy with lesser cost. There are digital initiatives related to control systems, energy grid management, and analytics. The predictive analytics will help the operators to be resilient, performant, reliable, and provide energy at affordable cost.

AI solutions in the utility industry are being developed and deployed on Cloud platforms like Amazon Web Services, Azure, IBM Blue Mix, and Google Cloud. These solutions are developed on cloud specific  AI services and platform components. They help in overcoming obstacles related to inventory, energy management, maintenance, and equipment reliability.  These solutions are also applied in energy storage management and to make the utility industry more efficient and performant. Storage solutions are being developed using AI algorithms to manage capacity needs using renewable energy sources, and make the energy management resilient. These AI solutions can handle energy demand changes due to weather and ensure efficient energy distribution and production. These solutions are built using Machine learning and AI  algorithms to develop different models to handle storage management and generate predictive analytics for energy generation. The latest AI solutions are helping energy industry to target campaigns  to households not just to manage energy requirements for the households but also for Electric vehicles. These campaigns provide discounts on electric equipment and help in increase in the energy consumption rates.

Predictive analytics and AI solutions are helping in developing trust and improving customer loyalty. They also provide features such as personalization, digital platform, process automation, workflow automation, and others to improve the energy distribution, management, and efficiencies. Rationalization and consolidation initiatives are also happening in utility industry to cut down redundant systems and integrate different systems to avoid silos. These solutions will have the ability to extend by using the commercial software packages. They can have capabilities to use specific features. Features related to security and licensing are also provided by these solutions. They can handle features like adding, modifying, removing, and monitoring the actions and events. They can have capabilities to configure, user access management, and handles entity context events.  These solutions are based on microservices and multi tiered architectures.  They provide features like configurable user interfaces, user fields, page flows, and meta data management. The configuration can have design time, development time, deployment time and run time settings.  These solutions can be upgradeable, customizable, and handle development lifecycle issues. No code platform are being used in the utility industries to cut down the cycle time and improve time to market. These platforms can handle multiple languages, locations, search, reporting, data sharing, collaboration, and other features for users to create applications. Globalization, localization, and internationalization implementations can be handled easily by using the no code platforms.

AI based platforms are also providing customer relationship management  features to improve the market share. These solutions help in integrating different data sources to create a unified data management system.  Customer energy usage is provided by the energy grid through smart and analog meters. This data and the customer profiles are used by these solutions to create different segments to target campaigns. They also provide customer engagement features in the platform. Marketing automation and unifying the end to end systems in the operations are part of these platforms. Location intelligence solutions help in improving the understanding of the customer using the profiles, energy usage trends, types of appliances being used. No code AI/ML platforms are also evolving to  develop different AI applications using ML techniques. These platforms will help in quickly trying out different algorithms, models, and derive business value to different utility enterprises. They can also help out in accelerating the development of data analytical applications  for better decision making and providing customer insights to the companies in energy sector.

Matt Chester's picture
Matt Chester on Dec 8, 2021

AI based platforms are also providing customer relationship management  features to improve the market share. These solutions help in integrating different data sources to create a unified data management system.  Customer energy usage is provided by the energy grid through smart and analog meters. This data and the customer profiles are used by these solutions to create different segments to target campaigns. 

This is interesting-- would the customers notice the difference in that service they got before and after such a tool was implemented? Or would it just be more efficient from the utility side and look the same to the customer? 

Bhagvan Kommadi's picture
Bhagvan Kommadi on Dec 8, 2021

Efficiency increases from the utility side and customer is engaged more because of the AI-based platforms. Customer life events help in targeting campaigns, offers, and insights by the AI platforms.

Paul Korzeniowski's picture
Paul Korzeniowski on Dec 27, 2021

Good points. Technology has been changing so utilities can collect more information now than ever before. With the large volumes of data, it becomes challenging to correlate information. AI and machine learning offer companies a way to do that and leverage the information that they have and gain insights so they run their organization more efficiently. 

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Thank Bhagvan for the Post!
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