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Data and Analytics
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Highlights
- A powerful optical character recognition (OCR) engine is at the heart of sophisticated automation.
- Utilities can adopt OCR technology to accelerate their digital transformation journey and enhance customer experience.
- With machine learning technologies and platform-based solutions entering the market, OCR continues to evolve, driving the hyperautomation concept.
In this article
The importance of OCR automation
The first step of the digital transformation journey begins with automating manual, routine work.
A powerful optical/intelligent character recognition (OCR/ICR) engine is at the heart of sophisticated automation. It helps robots become more perceptive to distinguish between different words, characters, buttons, and text fields embedded in digital forms. According to Gartner, 90% of large organizations across the globe will have adopted robotic process automation (RPA) in some form by the end of 2022. The rising adoption of RPA underscores the importance of OCR technologies, which convert images of typed, hand-written, or printed text into a machine-readable format. These could come from a scanned document, a picture of a document, or even text that’s visible over a photograph.
While this sounds simple, OCR is one of the foundational technologies behind RPA implementation. Imagine a scenario where inputs are shared remotely, and the RPA application is responsible for sorting the data, processing relevant fields, and automatically sending the right information to stakeholders. Without OCR, a robot could never identify which characters to process, let alone complete the task in a fraction of the time taken to perform it manually.
OCR adoption will grow as companies seek agility
In the last five years, OCR technology has been growing slowly but steadily.
It now plays a massive role in reducing manual interventions across industries from financial services and healthcare to manufacturing and utilities. The result is reduced costs, greater process efficiencies, increased productivity, and better customer experience. More importantly, it makes businesses more agile and responsive in an unpredictable post-pandemic environment.
According to Transparency Market Research, the global OCR market is anticipated to expand at a compound annual growth rate (CAGR) of around 15% between 2020 to 2030. OCR technology will be used across various document types, including structured documents, such as surveys and exam papers, semi-structured documents, such as invoices and purchase orders, as well as unstructured documents, such as contracts and letters. It also helps process engineering drawings and pipe layouts, which are highly complex documents.
Unlocking value through digitization and OCR
Utility companies are prioritizing digitization to meet the constantly rising customer expectations.
Digital transformation has the potential to increase an energy company’s short-term and long-term earnings by 4% and 25%, respectively. It’s easy to see how OCR would benefit the highly regulated and increasingly complex energy and utilities sector. Utilities are closely monitored by government authorities and regulatory agencies, requiring constant documentation audits and report submissions. Though RPA automates several of these processes, dependency on paper-based processes remains.
McKinsey had predicted a while ago that automation and digital technologies could help big oil companies unlock an additional billion dollars in value. OCR is likely to play a significant role in making this happen. To start with, OCR will not only accelerate the provisioning of new services to customers but also resolve service disruptions through faster ticket processing and remote troubleshooting of cable and pipe layouts. Utilities can also accelerate invoice processing, automate compliance reporting, and digitize field notes for better collaboration. OCR will analyze the document images based on specific patterns and automatically extract text into a machine-readable format. The output can either be stored in the utilities’ business systems and database or fed into the RPA engine and added to workflows for further analysis.
Adding a new dimension to OCR with machine learning
The expectations from automation are increasing every day. New technologies should complement the OCR process to extract high-quality information and insights and drive strategic thinking.
With machine learning technologies and platform-based solutions entering the market, OCR continues to evolve, driving the hyperautomation concept. As utilities continue to invest time and resources to leverage these advancements, they also need to use the right combination of technology, tools, and strategy to further their digital transformation journey. This will result in smoother processes, deeper synergies between digital and physical assets, and truly zero-touch process flows.
