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AI & RPA in Energy & Utilities

AI & RPA in Energy & Utilities
November 26, 2018

The utility industry is shifting from a highly traditional, regulation-driven marketplace to an advanced technology-driven environment. For Infrastructure optimization and supply-demand balance, use of the smart devices has increased exponentially in the last two decades. These smart devices and automated systems generate large volumes of customer financial and usage data. Artificial Intelligence is helping to analyze this data for deciding market quotes, better rates for consumers on geographic and demographic bases, lesser equipment failure and replacement and maintenance of hardware. AI also enables players in the utilities industry to apply the power of human insights to their existing business models. This can significantly bring about a paradigm shift in design thinking which thereby provides deeper insights into customer needs and helps apply advanced technologies to gaining advantages in production and innovation while enhancing business capabilities.

Most of the utilities focus on renewable energy. However, renewable energy sources are unpredictable owing to dependency on weather and geographic conditions. AI in energy and utilities can help here by offering a solution for demand and supply management facilitating decisions regarding storage and release of energy over the grid using predictive analysis.

At the moment, a significant portion of the budget of utility companies is dedicated to infrastructure and operations. A small amount is allocated for customer service, so here comes the role of AI in the customer service domain of the utilities industry. The Risks associated with investment in AI for Customer Experience and Digital Marketing is negligible compared to its benefits in improving speed and efficiency in operations, better data processing, and analytics and customer experience of support services.

Most of the Energy & Utility Industry products are driven by predictive analytics which utilizes historical data, predictive algorithms and data analytics techniques to identify the future results. For example, Oracle Customer Care and Billing and Oracle MDM can provide energy intelligence by forecasting high energy consumptions in a geographic area and can alert distribution companies regarding increase in demand.

Since utilities are generating a vast amount of data with smart devices, it significantly increases the chance of human errors. Robotic Process Automation (RPA) is an effective technology which makes use of software robots that typically imitate an employee to automate day-to-day tasks. These tasks are often related to utilities business processes such as billing, payments, move in and move out processes and other office tasks.

Utilities are experiencing the first wave of automation with the advent of RPA bots. RPA can empower analytics platforms with data streams integration and by providing a comprehensible view of the consumers, by creating personalized customer experience and achieving superior business outcomes. Further, advantage of RPA implementation is scaling which is cost effective and results in significant reduction in audit costs enabled by bots.

In finance and accounting, a U.S. investor-owned utility recently implemented RPA bots to manage the billing for commercial and industrial consumers (Source: Utility Dive). In operational process a water utility implanted RPA in CIS which resulted in a rise in percentage of service orders from 6% to 50% (Source: Utility Dive).

Utility distribution is the worst performing sector in customer services in majority of the developing countries. Here, RPA can play a more significant role in improving customer service and reducing operating cost. In the case of electricity grids which need to be continuously monitored, human intervention is necessary to de-energize the problematic areas of the grid. Any error may lead to huge fines and give rise to potential risk of life and property. RPA can check this by logging into the related systems (SCADA, GIS, other applications) to detect problems which will further help engineers in decision making. This can save a utility player from a human error, untimely planning of outages and accidents during maintenance exercises.

AI and RPA are revolutionizing E&U enterprises to overcome the inertia of huge operations and disruptions

With all these case studies and examples, one can conclude that AI and RPA are revolutionizing E&U enterprises to overcome the inertia of huge operations and disruptions. Both the technologies are providing a boost in the ponderous environment where the need for change is the only constant.