Second Step

Knowing Your Limitations

Improved Document Automation Tools

Improved recognition and learning are separate capabilities, though they are typically combined in newer products. The results are much better than what you got from the older OCR tools. First, the new tools are better in how they recognize the text –in how they classify docs, paginate pages and extract documents.

In a sense, they have changed from how young children read to how adults read. Young children focus on letters, then words in a painful slow process. Adults use more context, including existing knowledge, the overall document and page layout and look, what the document’s probably about, etc. The new tools may use computer vision, pattern analysis and other methods to take advantage of more context. Second, the new tools are better in how they improve that recognition –in how they continuously improve the accuracy of their opinion in light of evidence.

The learning capabilities range from not-so-intelligent to brilliant:

1) The human supervisor must do everything (e.g., drawing bigger zones in the template).

2) The human must provide them with positive and negative feedback (“these are correct answers” or “these are wrong answers”).

3) It’s a mix of assisted and automated.

4) The system can brilliantly improve its recognition automatically 100% by itself.

Understanding Your Capture Operation

Let’s look at where next-generation Intelligent Capture can help your organization. The first step is to understand your capture operation - it may include:

A centralized operation using one of the popular capture platform vendors.
Some significant part that is outsourced to a for-profit capture vendor that does it for you.
Some decentralized ingestion that takes in documents and data from multiple locations and multiple technology channels –paper, email, fax, smart phone and portal upload.

Many companies suffer from the same disorganization, their capture operation, is messy, too late, too damaging and too expensive. Often mistakes don’t get addressed until they are far downstream, meaning lost time, unhappy citizens and inefficiency. It’s possible to address these issues with document automation.

Many operations have been having the same operation system since the late 1990s. For many of them, it’s a mess. There are opportunities to greatly improve efficiencies in all these scenarios with the next generation intelligent capture tools.

Look For Labor Reduction

There is a real business case for using the next generation Intelligent Capture tools to reduce the labor in the capture workflow.

The following table illustrates some of the potential that’s just sitting there –showing some typical costs from inhouse and outsource capture operations.

Doculabs collected these costs from 25 years of capture benchmarking research. Your costs are likely similar to what is displayed in the Peer column.

The rows are the various tasks that are performed in a capture workflow. Note Automated Recognition at the bottom – that’s cheap because it has very low labor costs. You can get significant improvement by moving the data entry labor to the Automated Recognition row. But that’s not all. You can also significantly reduce the sort and prep labor and the exception handling labor (what I call here the Research activities). General QA, error detection and error correction can also be reduced or avoided.

Many organizations only look at how they can use IC for reducing data entry, rather than the other labor activities in the capture workflow. They are leaving savings on the table.

Service

Unit

Ex. Peer

Industry

For-Profit

In-House

Sort & Prep

Scanning

Per Hour

Per Image

$35.50

$0.0546

$35.28

$0.0398

$34.15

$0.0298

$36.40

$0.0497

Data Entry (Onshore)

Tier 1 (<10 Keystrokes)

Tier 2 (11-30 Keystrokes)

Tier 2 (Av. 50 Keystrokes)

Per Index

$0.0650

$0.0950

$0.3750

$0.0891

$0.2264

$0.4589

$0.0665

$0.1630

$0.3460

$0.1117

$0.2898

$0.5717

Retrieval/ Lookup/ Research

Tier 1 Research

Tier 2 Research

Per Hour

$47.75

$63.75

$49.70

$58.50

$49.00

$59.40

$50.40

$57.60

Automated Recognition

Per Image

$0.0225

$0.0206

$0.0132

$0.0280

What You Can Expect to Achieve

Let’s address what kinds of problems these new tools solve that the older generations of capture technology could not.

Complexity: Easy

Classification Capabilities: Page classification

Extraction Capabilities: English machine text-structured layout, mark and signature detection, barcode recognition

Validation Capabilities: Document type, page number and order, signature presence, date validation, field completeness; Data validation with source system, name/entry validation (against e.g. registry)

Complexity: Moderate

Classification Capabilities: Document classification (single page type may belong to multiple documents)

Extraction Capabilities: English machine text-unstructured layout, multilingual machine text-structured, multilingual machine text-unstructured

Validation Capabilities: Document field value consistency

Complexity: Difficult

Classification Capabilities: Package classification

Extraction Capabilities: English handwriting-structured, English handwriting-unstructured, multilingual handwriting-structured, multilingual handwriting-unstructured, sentiment analysis

Validation Capabilities: Signature correctness, package completeness, package field value consistancy

Has this eBook provided valuable information so far?

Yes, it's been extremely informative
Sort of, I already knew some of this information
No, I don't have a use for Intelligent Automation

At first glance, you can probably solve the easy problems with the solutions you have today, assuming you’ve kept up with newer versions of your capture software. Your biggest opportunity in the next couple years will likely be to focus on the Moderate problems and some of the Difficult problems. After that, you can consider tackling the more complex, Difficult tasks once you have that set in happy production.

For example, if you can do a good job at Document Classification, you don’t have to do much document preparation. These new tools can automate - or near automate - this task better than previous tools. Once you tackle that, in a few years, you can take on package classification. This is where you identify a whole set of documents and prepare extraction and validation for what to expect.

In terms of extraction, you can increase accuracy on machine text well beyond 99%. You can also address handprint and handwriting, first in structured English and then later in unstructured other languages (e.g., Spanish).

For validation, you can check for completeness and correctness in entire documents – what’s called NIGO (Not in Good Order) processing.

Later on, you can do NIGO processing for entire packages of documents such as in a loan application. Or, check not just signature presence, but correctness.

Where to Apply Intelligent Capture

What are some typical use cases that would be worth pursuing with next-generation Intelligent Capture that formerly were intractable?

1) Change of address forms with English, French, and Spanish machine print and handprint, multiple checkboxes. The multiple languages, handprint, and checkboxes were often non-starters, but are straightforward now.

2) Survey forms with 5 free-form comment boxes. You might want to separate and paginate the surveys and extract the comments. (We can also use the tools to do the simpler extraction tasks like barcode or machine text reading or use our platform capabilities for those tasks.)

3) Invoices in your AP process which come from a wide variety of smaller suppliers. We want to separate the invoices and pull the relevant data from them. This is a case where next generation Intelligent Capture brings automation from 85% to 99% - an incremental but significant improvement.