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Enterprise Data Management and harnessing the power of data in the Power & Utilities sector

This item is part of the Special Issue - 2020-12 - Data Analytics & Intelligence, click here for more

Introduction

Businesses that can adapt and innovate will be able to stay competitive and grow as the Power & Utilities industry undergoes transformational change.

At the heart of this change is the ability to maximise the immense potential of data to unlock new opportunities and create value along the power & utilities value chain from supply to the customer. Data is at the core of every business. How organisations maintain, govern, and utilise their data will either hinder or fast-track their efforts to reshape their business models and capture new market opportunities.

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Data availability allows faster and more insightful decision making. Embracing new technology and innovative solutions will increase the effective use of data, provide user-friendly solutions, and create new services.

Enterprise Data Transformation

Enterprise Data Management focuses on the processes and activities around the quality, accuracy, security, availability, and governance of data within an organisation. It provides a view of the data produced and consumed across an organisation.

An assessment of an organisation’s Data Management Maturity level is an important step in understanding the current maturity state. It will identify issues such as siloed data and poor data quality and lack of data management standards.  The data management assessment should also include a review of current working practices that will shine a light on deficiencies that need to be addressed.

Actionable improvements can then be planned to improve capability and impact performance. This enables organisations to implement new ways of working to be more productive, reduce costs and streamline inefficient processes. These changes will be an integral part of a strategic roadmap that fully considers the people, processes, data, and technology elements required in any successful transformation.

The roadmap will include addressing urgent remedial actions as well as the delivery of value creating solutions and processes. Remedial actions will include addressing non-compliance, increasing business resilience, and improving safety. This will improve data quality, promote better data governance standards, and accelerate the journey to becoming a high performing data-driven business.

Value Creation opportunities

Improvements in how enterprise data is collected, secured, and accessed provides the foundation for better data integration allowing value creation opportunities that include:

  • Digitising work processes
  • Mobile and Industrial Applications
  • Advanced Analytics
  • Machine Learning/Artificial Intelligence
  • Geospatial Analytics

Front line teams can work more effectively by digitising work processes and utilising integrated digital platforms. Implementing mobile solutions for field operations will replace manual and paper-based processes with standardised digital and automated processes.

The creation of a connected workforce brings end-to-end visibility of operational workflows and allow better data-driven decisions. Mobile and connected worker solutions can also enable remote assistance from an expert or enable wider collaboration both of which can increase productivity and enhance safety.

Data or Industrial historians are typically used to collect and store operational data that are used by other systems for analysis and reporting. Industrial applications use operational data for monitoring and Asset Performance Management.

Intelligent Plant have an open and secure Industrial Internet of Things (IIoT) portal known as the Industrial App Store. The app store provides cloud-based solutions that can be used for the remote performance monitoring of equipment through the analysis and visualisation of real-time data. Intelligent Plant and ORE Catapult collaborated on a project to demonstrate the ability to safely collect and share offshore wind real-time turbine SCADA data whilst adhering to cyber security best practice. The success of this collaboration provided clear evidence that better data management and analytics is key to improving both operations and maintenance.

Condition-based monitoring and predictive analytics are used to enhance functionality, improve asset reliability, and reduce maintenance costs. AI-driven solutions can further assist engineers and technicians in detecting emerging issues early and providing analysis to optimise operations. AI and Machine Learning also allow further improvements such as the reduction in Outage Management & Equivalent Forced Outage Rate (EFOR) and enhanced Distributed Generation Management.

Geospatial applications can be used across the value chain for both operational teams and customers in providing location-based services and analytics. Mapping and real-time spatial analytics provide users with key up to date information for real-time decision making and positive customer experiences. The use of edge computing technology allows the processing of data at or closer to a location increasing response times and business agility.

Conclusion

Harnessing the power of data gives companies competitive advantages by improving operational efficiency, improving asset reliability, and increasing the speed of decision making. However, to fully maximise the potential of this opportunity, better data management and data utilisation need to be key factors of this transformational change.

An assessment of current working practices, a review of data management and the implementation of value creating solutions will enable better operational decision-making, improved asset reliability and increased profit margins.

Mo Kamuss's picture
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