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Data Analytics Use Cases for Utilities

Building upon the collective wisdom for the Art of the Possible

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Your organization recognizes the importance of building a business-driven data strategy to enable digital transformation. You are having difficulty in

  • Building a list of value-driven business use cases required to develop a data analytics program.
  • Justifying the effort and cost to invest in the program.
  • Developing a practical and agile implementation plan to help solve business data challenges.

Our Advice

Critical Insight

Demonstrating the return on investment of data analytics programs rapidly is a vital step to digitally transforming your organization.

Empower data-driven decision making by leveraging Info-Tech's approach to accelerate the process and take advantage of the collective wisdom from your community.

Impact and Result

Info-Tech’s trends deep-dive report on data analytics use case for utilities can fast track the data strategy development by:

  • Accelerating your business case development by providing a curated data analytics use case repository.
  • Identifying the right data problems to solve which deliver the highest value by leveraging a rapid and effective prioritization. framework.
  • Developing an iterative and value proven roadmap based on your organizational scorecard.

Data Analytics Use Cases for Utilities Research & Tools

1. Data Analytics Use Cases in Utilities. Learn from a living repository consisting of a well-evaluated list of prioritized use cases and a multi-waved roadmap consisting of defensible prioritized business value driven use cases.

This research report provides utility leaders with a repository of pre-curated utility data analytics use cases as well as a filtering and prioritization framework. This approach can help fast-track the process of identifying the right business problems to solve strategically.

2. Data Analytics Use Cases Analysis Tool

This tool provides a pre-curated utility relevant data analytics use cases as well as a prioritization framework to develop a multi-waved roadmap consisting of defensible business value driven use cases.

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Data Analytics
Use Cases for Utilities

Building upon the collective wisdom for the art of the possible

Photo of Jing Wu, Principal Research Director, Utilities Research, Info-Tech Research Group

JING WU

Principal Research Director,
Utilities Research
Info-Tech Research Group

Analyst Perspective

Transitioning to the adaptable utilities of the future, organizations are addressing unprecedented challenges through their Digital Transformation journeys. Data Analytics becomes all that more important to enable utilities to transform digitally. Although the level of maturity varies, the importance of data-driven business decision-making has been well acknowledged and somewhat supported across the utility industry.

The Big Data challenges manifest in the process of developing a data strategy, coined by the characteristics of 3V – Volume, Variety, Velocity and then expanded to 5V, 7V, and the latest 10V. With the advent of industrial 4.0, the amount of data collected by utilities will only grow as more and more IIoT devices are deployed. Utilities are struggling to figure out how to effectively leverage the data. Turning data into actionable insights is a key challenge for utility leaders.

Data strategy development could be time-consuming, and the heavy lifting is mostly building a list of prioritized business cases that truly deliver value. This research report provides utility leaders with a repository of pre-curated utility data analytics use cases and a filtering and prioritization framework. This approach can help fast-track the process of identifying the right business problems to solve strategically.

Executive Summary

Your Challenge

Your organization recognizes the importance of building a business-driven data strategy to enable digital transformation. You are having difficulty in:
  • Building a list of value-driven business use cases required to develop a data analytics program.
  • Justifying the effort and cost to invest in the program.
  • Developing a practical and agile implementation plan.

Common Obstacles

  • Large effort and long duration required to develop defendable use cases.
  • Risks of failure often due to complex and lengthy projects.
  • Uncertainties about how and where to start among the seemingly complex data strategy and data analytics landscape.
  • Ability to demonstrate the measurable business benefits to gain executives’ buy-in.

Info-Tech’s Approach

  • Accelerate your business case development by providing a curated data analytics use case repository.
  • Identify the right data problems to solve that deliver the highest value by leveraging a rapid and effective prioritization framework.
  • Develop an iterative and value proven roadmap based on your organizational scorecard.

Info-Tech Insight

Demonstrating the return on investment (ROI) of data analytics programs is vital to digitally transforming your organization. Empower data-driven decision-making by leveraging Info-Tech's approach to accelerate the process and take advantage of your community.

Data analytics is a key enabler for digital transformation

Utilities today are facing unprecedented challenges that are categorized into the Trifecta of Change in the Info-Tech Future of Utilities Strategic Foresight Report.

Digitally transforming the utility business to strengthen its business capabilities is key to building its resilience. Proactive plans to address the external disruptions and internal interruptions call on actions to enhance foundational technology capabilities.

Digitalization accelerates the risks; expanding attack surfaces.

The enablement of an advanced data analytics platform to support data-driven digital utilities is the foundational step necessary to support any core business transformation initiatives.

Predicted 11.28% CAGR growth (2022-2027)
of big data analytics in the energy sector
[GlobeNewsWire, 2022]

Triangular diagram titled 'Trifecta of Change'. The three points are 'Expectation of regulators and customers', 'Commitment to decarbonization', and 'Risk of reliable infrastructure'.

Data challenges for utilities are elevated during digital transformation

How to process rapid generation?

Existing systems such as billing application is not effective in handling the fast generated data such as the interval data from smart meters.

How to develop actionable insights?

Collecting data is useless unless you turn it into business insights to deliver value.

How to synergize data consistently?

Data that is collected from different sources have disparate meaning and types. For example, a utility customer could mean different things for different departments.

[tdwi, 2017; IOP Conf.Ser.:Mter.Sci.Eng, 2020; IJOIR, 2021]
Circle of 'Big data challenges' beginning with the letter V. On the left from top to bottom are 'Velocity', 'Value', and 'Variability', and on the right from top to bottom are 'Volume', 'Variety', 'Veracity', and 'Visualization'. How to handle the exponential growth?

Number of IIoT devices and field sensors are collecting unprecedented amounts of data. On-premise data storage becomes costly and not elastic enough.

How to harvest different data, integrated?

Utilities are collecting varied data, both internal operational data and external data, but often siloed.

How to gain trust of data quality?

Quality of data could be measured in many ways such as accuracy, timeliness, and completeness, but the effort to track is often insurmountable.

How to present data meaningfully?

The same set of raw data can be presented in many ways. Effective and meaningful storytelling can drive decision making.

Data Analytics Use Cases for Utilities preview picture

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Author

Jing Wu

Contributors

  • Gaudy Jandron, VP of IT, Energy United Electric Membership Corporation
  • Loic Barancourt, CCO, UnaBiz
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