Solution Brief
Natural language processing for government efficiency
Boost your agency’s productivity by unlocking value from text data with SAS Document Analysis.
The issue
Government agencies manage a plethora of documents, forms, comments and surveys – including large stores of text-based data. There are many digital documents, but many paper documents still flow through these agencies. Transformation to a fully digital environment is stymied by:
- The digital divide. Many individuals still cannot access computers and fill out documents online. In fact, many of those who rely on government benefits disproportionately lack computer technology.
- Processing. Extracting information from paper documents and transferring it into digital systems can be difficult and subject to human errors.
- Retention requirements. Governments store documents for varying lengths of time, depending on type and purpose. In paper systems, people must manually review and remove documents that no longer fall within the retention period.
Unfortunately, manually converting piles of paper documents into searchable digital records is time-consuming and prone to costly errors. Governments need a more efficient, effective way to manage their data deluge.
Eliminating cumbersome, manual processes could address citizen demands for transparency and responsiveness, solve workforce challenges and unleash new insights from data. Techniques based in data and AI, such as optical character recognition (OCR) and natural language processing (NLP), offer promising pathways to get there.
The challenge
Extracting insights efficiently from large volumes of paper documents and unstructured data
With vast amounts of government data in analog or unstructured formats, agencies often outsource or pay highly skilled government employees to do tedious, repetitive tasks that could easily be automated.
Capturing key data manually – or extracting it from a scanned document
Many agencies either use basic OCR technology to extract the target data from a form or narrative document or rely on employees to manually enter information from paper forms into digital systems. Both approaches lead to mistakes, like extracting inaccurate data. Such errors may force additional manual reviews or result in downstream processing or analysis mistakes.
Using outdated and manual processes
Many technology platforms are designed primarily for people with technical skills. This may often be compounded by slim agency budgets that do not allow for the training of current employees or the hiring of new employees skilled at using NLP, text analytics and OCR technologies.
Fast, accurate text processing for all types of documents
Our approach
SAS helps government agencies rapidly identify and extract relevant information from paper and digital data so they’re positioned to uncover meaningful insights and make better decisions – with less effort. Freed from manual approaches, agency staff can spend more time analyzing data and improving services.
SAS helps you:
- Extract insights from various unstructured documents and put them in context, quickly using combined technologies like OCR, text analysis and machine learning.
- Capture the unrealized value of vast paper archives by digitizing them and making that data available in other applications.
- Build, deploy and govern machine learning models using an intuitive graphical interface. This approach helps address skill gaps and provides transparency, auditability and repeatability.
- Streamline workflows by automatically analyzing and classifying incoming documents.
- Uncover emerging trends and spot new opportunities for action in public documents, then explore how the trends change over time.
With SAS, you can modernize how your agency manages documents – from archives to the current inflow – to get valuable insights faster and boost productivity by serving the public faster with better programs.
SAS difference
The text analytics capabilities that SAS Document Analysis was developed to provide help make data more accessible to a wide range of users by extending cloud-based OCR to include models and utilities that streamline text extraction. That functionality is designed to foster collaboration and information sharing through an ecosystem that integrates easily with existing systems and open source technology.
You can use SAS to:
- Get more value from your analytics investments with our open, user-friendly platform, which incorporates multiple techniques: NLP and text analytics, machine learning, linguistic rules, and search and model-building capabilities.
- Transform scanned document images into structured data for reporting and analytics with an intelligent document processing (IDP) pipeline.
- Increase the accuracy of text models by combining NLP methods with a rules-based approach that can be enhanced with subject-matter expertise.
- Generate models designed to help you easily extract concepts, detect common topics and effectively analyze public sentiment – with support for 33 different languages.
With SAS, you can simplify digital transformation by converting unstructured data into usable formats, optimizing batch processing and supporting robotic process automation – all within the SAS® Viya® environment. Use your text data to help ensure all voices are heard, improving efficiency and equity. Then, you can deliver the outcomes constituents deserve – from public safety to human services, health care and beyond.