Intelligent Document Processing (IDP) to Optimize Business Operations in Utilities

Data extraction from utility bills, customer service contracts, and regulatory documents ensures compliance, optimizes capital expenditures, predicts trends and patterns, and streamlines resource allocation for utilities. 

However, manual data extraction is error-prone, time- and resource-intensive, leading to operational inefficiencies and delayed business growth. 

Intelligent Document Processing (IDP) technology overcomes the challenges of manual data extraction, helping utilities extract data from various structured, semi-structured, and unstructured documents. It also performs analysis to derive actionable insights and enhances business efficiency.

This blog discusses the role of Intelligent Document Processing (IDP) in the utilities industry, challenges in manual data extraction, the benefits of IDP, and a detailed process of extracting data with its use cases and key considerations while implementing IDP.

The role of intelligent document processing in the utilities industry

Intelligent Document Processing is an automation technology that uses advanced capabilities such as Optical Character Recognition (OCR), Machine Learning (ML), Natural Language Processing (NLP) algorithms, and computer vision technologies to automate end-to-end document processing workflows for businesses. It extracts data effortlessly from structured, semi-structured, and unstructured documents with a 70-99% accuracy rate. 

Utilities rely on highly accurate data to address issues on time, allocate resources, and streamline business operations. Incorporating IDP in the utility industry transforms the document processing workflow and helps extract highly accurate data from diverse documents. 

In addition to enhanced accuracy, intelligent document processing workflows for utilities also benefit utilities by increasing efficiency, optimizing operations, reducing costs, and making strategic decisions. 

Benefits of implementing intelligent document processing solutions in utilities

1. Increased efficiency

Implementing IDP technology in the utility industry significantly improves efficiency by processing multiple documents, such as utility bills, service manuals, and contracts (in batches), and extracting data from them in less than a minute. 

It processes documents 24/7, allowing employees to devise strategies that meet consumers’ energy demands, minimize downtime, and prevent system overload. 

For instance, Westland, owner of multi-family residential and retail properties in Los Angeles, automated portfolio management using Docsumo. Docsumo’s auto-classification helped Westland accurately extract data from non-uniform utility bills. 

2. Enhanced accuracy

Unlike manual extraction, an IDP platform massively improves accuracy in several utility operations. It creates accurate customer bills by validating meter readings with existing databases, previous readings, and customer usage patterns. 

The other benefit is that it helps capture accurate data from application forms and correctly enter them into the CRM for customer onboarding purposes.

3. Improved compliance

The IDP platform extracts accurate, up-to-date, and relevant data from utility documents and automatically validates them to ensure compliance with local, state, national, and international regulations such as GDPR and SOC-2. These automated compliance audits and validations prevent non-compliance issues and maintain your utility’s reputation. 

4. Cost savings

Incorporating an IDP platform in your utility document processing workflows reduces costs and eliminates the need to hire more employees to process growing data volumes. Even the same team can process a large amount of data with automation. 

Extracting accurate data from utility bills and validating them ensures precise customer billing, preventing financial losses for your utility business. 

5. Better decision-making

ML and NLP algorithms in IDP effectively analyze unstructured data and convert it into actionable insights, uncovering hidden opportunities and potential risks in asset management and customer retention processes.  

IDP allows businesses to identify trends and patterns in customer energy usage patterns by analyzing historical data and customer meter readings using IDP, helping them optimize resource allocation and asset management.  

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How to extract data from utility bills with intelligent document processing

IDP solutions enhance data extraction from utility bills by accurately capturing and interpreting information from various document types. A detailed step-by-step process shows how IDP extracts data from utility documents.

Step 1: Document ingestion

Data extraction process using an IDP solution starts by scanning physical documents such as utility bills and service manuals using a high-resolution scanner. Place these documents straight on a flat surface, adjust the scanner’s colour and resolution settings, and ensure good lighting to capture clear digital copies. 

The IDP platform would process these digitised documents to extract relevant data. You can also automate document ingestion and the IDP solution would directly intake digital copies of documents such as utility bills, contracts, and manuals from emails or computer storage. 

Step 2: Preprocessing

Advanced preprocessing steps enhance the quality of the source data, helping the OCR technology distinguish characters from the background.

IDP solutions automatically perform preprocessing techniques such as binarization, skew correction, noise removal, geometric correction, right-sizing, page rotation, contrast and density adjustments, whitening background, and merging and splitting documents to ensure data quality. This helps to extract data with high accuracy rate. 

Step 3: Document classification

What if you can automate document classification using IDP solutions and reduce document processing time and errors? Auto-classification of documents using ML and NLP algorithms in an IDP solution is more accurate and faster compared to manual classification. 

Once the documents are ingested into the IDP platform, it automatically identifies the document type (PDF, JPG, PNG, TIFF) and document structure (structured, semi-structured and unstructured) to direct them to the necessary workflows. It categorizes single-page and multi-page documents for data extraction and assigns them efficiently to the respective team members for post extraction analysis. 

For instance, if you’re processing a combination of water bills and service contracts, the IDP would understand the difference in the data type, classify these two documents separately, and redirect to the particular data processing workflows based on their complexity. 

Step 4: OCR and text extraction

OCR technology accurately scans texts from scanned images, printed documents, and PDF files and converts them into machine-readable formats for further processing. 

But how does it work? OCR technology uses pattern recognition and feature extraction processes to isolate characters and break down its features. It then compares these features to find the closest match in the various stored databases and present you the recognized characters. 

Step 5: Natural Language Processing (NLP)

NLP analyzes large sets of extracted data and performs several techniques, such as sentiment analysis, word clouds, and keyword detection, to identify repetitive patterns in energy usage, predict future trends, and prevent customer service interruptions. This analysis derives actionable insights, streamlining business operations for utilities. 

For instance, the IDP platform would analyze historical data and understand customer energy usage patterns from meter readings to help utilities forecast demand and optimize strategies that prevent outages.  

Step 6: Data extraction

Regardless of the document type and data format (structured, semi-structured, and unstructured), the IDP platform adapts to different structures and templates and captures data without human intervention. 

It first captures key-value pairs (a set of two data items) from utility bills using OCR and ICR technologies. Then it employs image detection and segmentation algorithms and computer vision technologies to locate tables and extract accurate line items from them. 

For instance, the IDP platform would process utility bills automatically to extract key-value pairs such as customer data (names, addresses, phone numbers), and total amounts and line items, such as meter readings and payment details, issue and due dates, taxes, and miscellaneous charges. 

Step 7: Data validation

Pretrained API models in the IDP platform validate the extracted data with predefined rules and cross-verify the data with available databases and internal computations using Excel-like formulas/rules to detect errors, inconsistencies, and anomalies in the extracted data. 

You can then employ skilled experts to review the uncertain and low-confidence data extraction values and make corrections, ensuring accuracy and improving the API models. Finally, approve all the fields and transfer the data to business systems. 

Step 8: Data integration

Download the extracted data in the desired format (PNG, PDF, Excel, JPG, etc.) and integrate them into downstream systems to streamline business operations. 

Step 9: Quality assurance

Analyze the extracted information and look for errors, inconsistencies and missing values to confirm data integrity and accuracy. You can also verify the data with its source documents to ensure error-free data. 

Step 10: Feedback loop

Collect employee feedback on the tool’s performance, including accuracy and automation rate, security, and storage. Based on the input, work with the IDP vendor to customize the IDP platform to your business needs and improve its capabilities. 

Sign up for a free trial of Docsumo and extract accurate and reliable data from your utility documents. 

Understanding the challenges in utilities bill data extraction

1. Data complexity

Utility industry documents can contain intricate tables, paragraphs, varying structures and templates, and handwritten notes, making manual data extraction strenuous. Employees need to adapt to these variations, which constantly increase errors and inconsistencies. 

Using an intelligent document processing tool overcomes this challenge as it learns and adapts to documents automatically without human intervention. 

The chosen IDP software would be able to capture relevant data from handwritten notes by understanding their context and adapt effectively to variations in templates, fonts, and formats to extract accurate data. 

2. Compliance requirements

Maintaining compliance while extracting data is a serious challenge, as regulatory requirements are complex in the utility industry. Utilities should comply with industry-specific regulations such as FERC, NERC, and EPA and federal, local, state, and regional laws. 

Failing to meet compliance rules invites regulatory fines, penalties, and legal issues, resulting in financial losses and reputational damage.

3. Legacy systems

Utilities use legacy systems, which may not be compatible with advanced solutions like IDP platforms. This may lead to errors, impacting business decisions and operations. 

4. Speed

Traditional data extraction methods can be time-consuming because of challenges such as vast volumes of documents, complexity, and inadequate human resources. Extracting relevant data manually may take days or weeks, delaying decision-making and business growth.

5. Accuracy

Manual data extraction is error-prone due to several factors, such as data complexity, short turnaround time, and concentration lapses. Additionally, standalone OCR-based tools don’t offer high accuracy as they struggle to extract data from semi-structured and unstructured documents. 

Simple OCR tools cannot maintain the document’s original formatting without third-party software integrations. As a result, formatting collapses, and OCR can struggle to extract data from misaligned tables, graphs, and texts. Poor lighting, low-resolution images, and blurred texts also impact accuracy. 

This results in inaccurate data, leading to unreliable decisions and potential losses. 

Real-world applications of intelligent document processing in utilities

Let's explore some of the IDP use cases and real-world applications in the utility industry.

1. Billing and invoicing

Extracting customer identity data, meter usage readings, and payment details helps automate utility billing processes. The IDP platform can validate the meter reading with the customer’s previous energy usage patterns and calculate accurate billing amounts to expedite invoice creation. 

2. Contract management

Contracts provide a wide range of data, such as utility needs, costs, agreement termination and renewal dates, payment terms, parties involved, delivery obligations, and contract duration. Extracting this data helps with negotiations and timely renewal, mitigating risks and saving utilities costs. 

3. Asset management

Extracting relevant information from asset data, equipment details, spare parts information, operational manuals, and standard procedures helps predict potential problems such as leaks, contamination, and breaks in particular assets. 

Proactive analysis ensures proper asset management, replacement of aged assets, and allocation of adequate resources to fix technical issues. 

For instance, waste management utilities can analyze relevant data and take proactive steps to manage assets effectively, such as reducing downtime, increasing asset life, replacing equipment, and disposing of waste. 

4. Customer service

Capturing data from customer billing records, meter readings, and consumption trends helps forecast demand for utility services. Pairing this with analyzing historical data such as weather and meter spending patterns optimizes the customer experience by allowing you to deliver the services without interruptions. 

For example, electric utilities can predict the power demand and optimize strategies such as preventing outages and system overload, planning workforce and adequate resources, and streamlining asset usage accordingly. 

5. Regulatory reporting

Accurate data extraction helps adhere to standard regulations, ensuring compliance and mitigating risks. 

Key considerations for implementing intelligent document processing solutions

1. Integration with existing systems

Choose an IDP tool that seamlessly integrates with your existing systems, including legacy tech, for interoperability and error-free data flow.

2. Scalability and flexibility

The IDP platform must be able to grow along with your utility business, effortlessly handling large volumes of documents and extracting data from them in minimal time. 

The IDP platform must flexibly adapt to different templates and structures of utility documents and capture accurate data without human effort. 

3. Security and Compliance

To ensure security, consider implementing an IDP platform with robust security features, including encryption, role-based access, and multi-factor authentication. 

4. Employee training 

Implement training programs for employees to educate them about the technologies employed, best practices, and features to help them leverage the platform to its full potential. 

5. Return on investment (ROI) analysis

Calculate the return on investment (ROI) of the IDP platform to ensure that it meets your budget constraints. Identify your business needs, objectives, and goals and calculate the total cost (direct and indirect costs) needed to invest in IDP software 

Direct costs are implementation and software licensing fees, hardware requirements, license renewal, support, configuration, and maintenance costs. In contrast, indirect costs include training employees to leverage the tool to its full potential.

Optimize your utility operations using Docsumo

Docsumo, an AI-powered IDP platform, helps utilities extract data with over 99% accuracy from structured, semi-structured, and unstructured documents such as contracts, manuals, utility bills, and regulatory documents. Pre-trained API models validate the extracted data with existing databases to detect errors, redundancies, missing values, and inconsistencies.

With Docsumo, you can save nearly 70% in operational costs and improve efficiency by 10X as extracting data takes only 30 seconds. Schedule a free demo to learn how Docsumo can streamline document processing workflows and optimize efficiency for your utility business.