Issue link: https://read.uberflip.com/i/1492173
THE TOTAL ECONOMIC IMPACT™ OF AMAZON INTELLIGENT DOCUMENT PROCESSING 1 Executive Summary Amazon's Intelligent Document Processing (IDP) solution leverages machine learning to automate data processing and extract key structured and unstructured data from various document formats. Companies can harness Amazon's IDP solutions to improve document processing efficiency, save costs, gain new insights from their data, and bring new products and services to market faster. With Amazon IDP, organizations can extract text from millions of documents, understand the sentiment between these documents, and manually validate machine learning (ML) results for higher accuracy and compliance. Amazon's IDP solution offers both pretrained IDP ML models and services to create custom IDP ML models. The interviewees' companies used three Amazon IDP pretrained models: Amazon Textract, Amazon Comprehend, and Amazon Augmented AI (A2I). Amazon Textract is a ML service that automatically extracts text, handwriting, and data from scanned documents, going beyond simple optical character recognition (OCR) to identify, understand, and extract data f rom forms and tables. Amazon Comprehend is a natural-language processing (NLP) service that uses ML to uncover information in unstructured data. Amazon A2I is a ML service that makes it easy to build the workflows required for human review. Machine learning model developers at the interviewees' companies used Amazon SageMaker to develop proprietary ML models. Amazon commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying the Amazon Intelligent Document Processing solution. 1 The purpose of this study is to provide readers with a f ramework to evaluate the potential financial impact of Amazon IDP on their organizations. To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed f our decision-makers with experience using Amazon IDP. For the purposes of this study, Forrester aggregated the interviewees' experiences and combined the results into a single composite organization. Prior to using Amazon IDP, these interviewees noted how their organizations typically relied on large document processing teams to manually update documents that had been digitized via a legacy OCR system. The process was time-consuming and often introduced errors. It was difficult to digitize unstructured information and review document content to classify and identify key information within the documents. ML model development was inef f icient. Af ter the investment in Amazon IDP, the interviewees noted their organizations could more efficiently extract information from millions of documents and use the inf ormation and insights to better manage Return on investment (ROI) 73% Net present value (NPV) $4.60M KEY STATISTICS