OCR for Invoice Processing

]
ASUG 2008 Speaker Development
John Walls, Senior Principal
VerbellaCMG, LLC
John.Walls@VerbellaCMG.com
484-888-2199

[ GRETCHEN LINDQUIST
ASUG INSTALLATION MEMBER
MEMBER SINCE: 1999

[ GREG CAPPS
MEMBER SINCE:1998

[ ISRAEL OLIVKOVICH
SAP EMPLOYEE
MEMBER SINCE: 2004

Learning Objectives

As a result of this
workshop, you will be
able to:
 Clear understanding of what
OCR is and what it is not, - what
it is capable of and how it works
 How it can be used to streamline
current SAP or non-SAP process
 How to make use of the data and
documents that are captured
 What is required for an OCR
project

2

]
MEMBER SINCE: 1999 As IS To Be- Processing
What is OCR
Why should we use it
Document Structure, Types of Recognition
Template vs. Rules Based OCR
Flow, Classification, Extraction, and VRS Technology
[ GREG CAPPS
Integration and release ASUG INSTALLATION MEMBER
MEMBER SINCE:1998

Case Study
[ISRAEL OLIVKOVICH
SAP EMPLOYEE

Wrap up and Questions
MEMBER SINCE: 2004

What are we trying to achieve?

4

Traditional Indexing Method for A/P Solutions

6

OCR Definitions

Simple
 Optical character recognition- (OCR), is the
electronic translation of images of handwritten or
typewritten text (usually captured by a scanner) into
machine-editable text.

Complex
 OCR analyzes the shape of a bitmapped character and
assigns a value to it based on a template system or
mathematical feature analysis or feature extraction.
This analysis produces a likely result along with a
range of possible alternative characters. Each result is
support by a likelihood percentage. *
* Océ Document Technologies

8

OCR Definitions

Voting-
 This is when 2 more OCR recognition engines are
used and their results compared, voting on the most
likely result. It’s designed to eliminate errors (false
positives) and increase accuracy.

 All OCR engines provide multiple results with a
percentage of accuracy or likelihood.
 When scanning in Forms with Handwriting – Voting is
a very attractive scenario.

*Océ Document Technologies

9

Typical Set up – Process flow

Scan Extract Validate Release
Scan Documents Classification of Validate and Export data and
Document Type correct data images to
directory as Text or
VRS 4.1 Pro for image XML
cleanup and improved Extraction of data Look up data from
OCR accuracy fields from each databases and
Images can be
document other sources
release as full
search PDF’s or
Tiff images

10

Accounting Department
Business Process Challenges Document Management Challenges
Time Consuming A/P Process Lost invoices
High headcount and overtime High document
Unused discounts transportation cost
Incorrect data Misrouted documents
Finance charges Lengthy invoice research
Process status unknown

Key Issues
Reduce Processing Cost
Speed of processing
Accuracy of information
Receiving invoices &
preparation for processing

12

OCR- What’s in it for me?
Better utilization of human capital –
knowledge workers can focus on value-adding tasks.

Increased Faster Reduced Reduced
automation processing paper handling labor

Say Good-Bye to Never Miss a Discount Gain An Auditable
Retrieval Time Again Business Process

13

Costly facts about Invoice processing
It takes an average of 12
days to process an invoice

1 out of 5 invoices have anomalies

It takes >17 seconds to manually enter
an invoice (excluding manual handling)

96% invoice processing involves
keying data from paper

A 1000 – 5000 employee organization handles on average
24,500 invoices per month
Direct labor cost alone for payables processing averages $3.31 per
invoice
Direct labor represents 30% of fully allocated payables costs*
Average payables cost of $11.03 per invoice *
Source Kofax, *Cass information Systems

14

Typical AP Process
Cost Center Receipt & Sorting
with AP

Sort invoices based on Send invoices to the Perform more sorting or
Receive invoices at AP AP departmental AP Representative batching. Invoices may
Vendor
department structure (State, Cost responsible for be stamped with date
Center, Division, etc.) processing invoices rec’d, annotated with GL
Codes, etc.
Cost Center

Manual AP Process
AP Rep keys invoices
Correct entries as
into the ERP system.
Invoices maybe Parked needed or proceed Release batches for
Line-item matching may Perform check run
Pending Approval directly to releasing payment
be performed on P.O.-
batches for payment
based invoices

Paper Filing & Retrieval
Send invoices to
Send invoices to long-
temporary on-site
term off-site storage
storage

Pull invoices for audits
and various other
business requirements

15

Typical AP Process with OCR

Cost Center Automated Sorting
Receipt & Sorting & Routing
with AP
AUTOMATED AUTOMATED AUTOMATED
Sort invoices based on Send invoices to the Perform more sorting or
Receive invoices at AP AP departmental AP Representative batching. Invoices may
Vendor
department structure (State, Cost responsible for be stamped with date
Center, Division, etc.) processing invoices rec’d, annotated with GL
Codes, etc.
Cost Center

Automated Process
Manual AP AP Process
AUTOMATED
AP Rep keys invoices AUTOMATED AUTOMATED AUTOMATED
AP Rep keys invoices Correct entries as
into the ERP system.
into the ERP system. Invoices maybe Parked needed or proceed Release batches for
Line-item matching may Perform check run
Line-item matching may
Line-item matching Pending Approval directly to releasing payment
be performed on P.O.-
may be performed on
be performed on P.O.- batches for payment
based invoices
P.O.-based invoices
based invoices

Paper Filing & Retrieval
Automated Archive/Retrieval
AUTOMATED AUTOMATED
Send invoices to
Send invoices to long-
temporary on-site
term off-site storage
storage

AUTOMATED
Pull invoices for audits
and various other
business requirements

16

Information Extracted

Standard Header and Footer Data Standard Line Item Data
 Purchase order number  PO Line Item Position
 Invoice number and date  Quantity
 Subtotal  Description
 Taxes
 Unit price
 Freight
 Total price
 Discount
 Grand total
 Discount
 Supplier details  Unit measure
 Material Number
Any other data  Order number
 Using customized extraction  Delivery note number
schemes  Tax rate
17

Information comes in many forms…

 Structured Content
 Information is predictable
 Location of information is
predictable

Examples
• Waybill
• Delivery Documents
• Tax Forms
• Mail Order Forms
• Applications
• Insurance Claims

Source: Kofax

19


 Semi-Structured Content
 Information is predictable
NOT predictable

Examples
• Accounts Payable
• Accounts Receivable
• Transportation
• Bills of Lading
• Medical Billing

Source: Kofax

20


 Unstructured Content
 Information is NOT predictable
NOT predictable

Examples
• Mortgage Folders
• Medical Records
• Litigation Support

Source: Kofax

21

Types of Recognition

 OCR- Optical Character Recognition
 Used to read Machine print within images

 OMR- Optical Mark Recognition
 Used to identify checked boxes and other “selected options”

 ICR- Intelligent Character Recognition
 Used for identifying Handwriting or Hand print on a
document. Could be used to pull information from “Forms”

 IWR- Intelligent Word Recognition
 Used to read Cursive writing for example “Checks” or
“Prescriptions”

22

Rules-Based vs. Template-Based OCR
 Rules-based
 Entire document is scanned and processed via Optical Character
Recognition (OCR)
 The OCR engine is used to search for a key (key words, phrases,
or expression) and find the corresponding value (specific to
general)
 Once configured, it is most likely that new invoices can be read
 OCR rates are .5 to 5 seconds
 Template-based (logo ID) — learn, memorize, teach
 Each vendor invoice must be maintained as a template for each
resolution (DPI)
 New invoice might not be read — system learns the invoice
 Database maintained — not good for large numbers of vendors
 OCR rates are 8 - 12 seconds

24

How Does Rules-Based OCR Work?
 Configuration
 Create classification rules
 Features and index fields that classify the document as:
 PO, non-PO, credit memo, statement
 Assign index fields based on classification
 PO invoice classified — PO number, invoice date, invoice amount,
and invoice number
 Assign rules and logic to the key values (index fields)
 PO Number, PO #, P.O. Num = (45########)
 Logical expression 45[0-9]{8} validates 4512345678

Dictionaries

25

Break Down- A Single Rule

26

Overview of all the Rules

27

Template – Form Identification

Sample Pages
 Page-level form identification
 A scanned or imported image is compared against the sample pages
already "learned" by the form identification engine. Each comparison
returns a confidence and a difference.
Form identification zone
 A form identification zone can be used to assist page-level form
identification feature. It is typically used to help the form
identification engine distinguish between forms that are very similar.

29

Template – Registration

Sample Pages
 Page-level registration-
 Attempts to offset all zones based on how far large features on
the page are offset from the same features on the sample page
 Registration Zones- “Text” and “Shape”
 A text registration zone can be used to augment or replace
page-level registration. Used if your images are different from
the sample pages
 Shape registration zone uses
geometric patterns that are “fixed”
in relation to the data on a form

30

Extracting Index Values-Based Document
Type (Forms)

Index Values Here
Form Identification Here

31

Classification and Extraction of Index Fields

 Documents are being classified as to the type
of document
 Once classified, the extraction of data begins

Extraction

32

Release – Text or XML and Images
 Extracted index fields are released as an .xml or .txt file to a
network share

34

]
MEMBER SINCE: 1999 As IS To Be- Processing
What is OCR
Why should we use it
Document Structure, Types of Recognition
Template vs. Rules Based OCR
Flow Classification, Extraction, and VRS Technology
[ GREG CAPPS
Integration and release ASUG INSTALLATION MEMBER
MEMBER SINCE:1998

Case Study
[ISRAEL OLIVKOVICH
SAP EMPLOYEE

Wrap up and Questions
MEMBER SINCE: 2004

OCR Processing Solution Steps

Documen
Invoice OCR Rules t
and SAP
Images
Templates Database

SAP Content
Server

Data

Scan Extraction Validate Release

SAP
Workflow
Continuous
learning
36

Classification Technologies

Layout/Image Instruction Adaptive Feature
Classification Classification Classification

 Image content  Keywords or phrases  Textual content
 Patterns “Examples”
 Patterns “Examples”  Boolean (true or false)
 Unstructured data
 Page layout  Requires OCR  Words, individual tokens
 X,Y coordinates  Logos or graphics  Mailroom application – Separates
 Small smeared thumbprint documents that a person would normally
have to read
 No OCR

Source: Kofax

37

Extraction Technology

 Locators – extraction engines
 Learn-by-example locators for rapid setup on key fields
 Additional pre-built locators or Rules for other fields
 Format, zones, tables, database, barcodes etc
 Multi-language OCR/ICR
 140+ languages
 Chinese/Japanese/Korean
 Multi-engine voting

Source: Kofax

38

Learn-By-Example
 Classic learn-by-example approach where you start with a fixed model
of the world as we see it and then present real examples to teach the
system how things vary in real-life
A an analogy would be teaching a child to read

1

2

3

 The variation between each example, known as the semantics, is learnt
by presenting lots of examples of real world invoices
Source: Kofax

39

Database Locator

 Matching of database fields
to document data
 Fast, associative, fault
tolerant search
 Works even with large
databases >1 million records
 Returns record with best
match

40

Format Locator

 Finds and reads data based on regular expressions
and keywords, e.g.:
 “d” = all single digits
 “d{4-8}” = any number from 4 and 8 digits in
length
 Multiple regular expressions can be defined to cover
all alternatives, e.g. for multiple number formats
 Useful for
 Invoice numbers
 Dates
 Account numbers

Source: Kofax
41

Direct SAP Data Validation

Finds and reads data using a
customized VB compatible
script such as VB .NET 2.0
Call Remote enabled RFC’s
For Example-
To check for the
existence of a PO or
Validate Vendor
information, look up
vendor number

Source: Kofax

42

Virtual Re-Scan (VRS) Eliminates Rescanning

Low Contrast
Logo

Dot Matrix
Text

Highlighter

Carbon Copy
Handprint

Coffee Cup
Stain

Shaded
background

Source: Kofax

44

VirtualReScan™ (VRS)
Scanned in color

Image File Size = 213 KB

Scanned in 1 bit B/W

Image further
processed with VRS
45

What happens after Release?

 Release into Pre-defined A/P solutions
 IXOS Vendor Invoice Management
 Norikkon APay Center
 170 MarkView Financial Suite
 Ebydos
 Bassware
 Brainware
 SAPERION InBound Center
 Custom Ledger solution
 Custom Programming-
 Park Invoices and route workitems for further
processing
 Post Invoices and route exceptions

47

Content Management - Direct Release

Release

ARCHIVE a.k.a.
Content Server

Jukebox CAS Storage
Centera
48

Standard Release – Using XML or TXT files
and ABAP

XML
ABAP’s
Network
Directory

s’
Release

AP
ARCHIVE a.k.a. AB
Content Server

Jukebox CAS Storage
Centera
49

Integrated Release – RFC’s and Function
Modules
1 RFC calls FM to Create URL
2 Document is stored
3 Extracted Data is passed back
into specific FM’s to create
Function workitems or post documents
RFC Modules

EMC or Net Apps
H
TT

Release HTTPS
PS

Jukebox

ARCHIVE a.k.a.
Content Server

50

Template Case Study – Communications
Industry
 Situation:
 Customer receives 10,000 returned billing statements from the USPS
per month. 1.5 FTE were 4 months behind in processing the return mail
and updating the system that the billing address was wrong. So
statements were continually going out as undeliverable.
 Pain:
 Postage cost alone were running at $4,000 a month
 Labor cost to process the return mail 1.5 FTE
 Missed opportunities for Customer Service to obtain current address
information from the customer when they had them on the phone
Solution: Template OCR
 Scanned in the first page of each statement and read the customer
account number and then released this information in a text file. A
process then reads this file and updated the billing system (Non-SAP)
 Return Mail is processed daily within 15 minutes on average

52

Overview of the Validation Station

53

Rules Based Case Study – Chemical
Industry

 Situation:
 2 FTE are manually entering invoice header “indexing” information
and invoices are manually posted 27 FTE’s, average invoice per
FTE / 923 invoices/month
 Pain:
 Wanted to reduce the number of days down from 6 days, reduce
resources, and reduce the potential for Ergonomic injuries
 Manual data entry, missed discounts
 Goal:
 Increase discounts taken, increase productivity, reduce by 3FTE’s,
create ability to further automate workflow exception handling
using OCR

Solution: Rules Based OCR
 Vendor invoices are scanned and run through the OCR software,
this information is then used to automatically post the top 20
vendors, and route all other invoices to AP processors.

54

Rules Based Case Study – Chemical
Industry

 Results
 Reduced by 3 FTE’s the month of implementation – from 27 FTE’s to 24 FTE’s
 1 FTE in document control
 2 FTE’s in invoice posting
 Improved ability to take term discounts
 % taken YTD:
 Jan 38%, Feb. 45%, March 35%, April 40%, May 53%, June 46%, July
55%
 Invoices processed per FTE reached 1550 in July, from 923 pre-implementation
 Reduced data entry by exploiting OCR and creating programming to post
invoices to purchase orders automatically
 Targeted high volume, suppliers for auto-post, then worked with suppliers to
ensure invoice criteria was met, then templates were created.
 7% of invoices are auto-posted, without human intervention. Approximately
1600 invoices a month. Invoices with errors are routed to processors.
 Post implementation - additional suppliers have been identified for auto-posting
and will be added

55

OCR Benefits in Accounts Payable
Processing Costs
 Reduced Labor
 Invoice Processing
 Invoice Sorting
 Filing
 Reduced Paper Handling
 No lost invoices
 Can be accessed by multiple users and locations simultaneously
 Storage space for of physical documents reduced
 Increase Processing Speed
 Invoices can be scanned and processed on the day that they are
received increasing visibility for management.
 Early payment discounts can be utilized
 Increased data accuracy
 Fewer data entry mistakes are made
 Increased Accessibility/Availability Productivity and Efficiencies
 Access to documents is Instant
 Information sharing is enhanced
56

Most OCR solutions include

Administration Client- Design or Project Builder client
Setup Batch structure and Setup project structure
process Setup classification and
Setup Release details extraction schemes
Document Separations Train the project
Scanner Configuration Define validation rules
Users Authorizations Design Validation screen
User – Solution layout
Developer/Administrator Test the project
User – Solution Developer

58

Leading Practice

 Start Slowly- Minimum disruption to existing process.
 Some companies started with 1 vendor a day
 Some companies start with the top 20% of vendors
 You still need to pay your bills
 New technology- employee need time to adjust and
embrace. Using the light switch approach may turn
employees off.
 Start Imaging before OCR and Process Automation
 Constant Improvement the process will constantly
need to be monitored, Always tweaking

59

Leading Practice

 Notify your vendors-
 Tell them that there documents will be processed via OCR
 Get them to work with you.
 Single line - line items
 Stop sending invoices on blue paper with balloons
 Clearly identify the information that you need to see
 Consolidate Vendors
 Use this as a opportunity to consolidate vendors, if they are
not going to help with the above, then consolidate
 Clean up Vendor Master records
 Vendor Address and Phone numbers will be used daily for
vendor look up, make sure the information is correct.
 Set up process to correct errors efficiently

60

What do I need to get started?

 Scanner for Document imaging
 Scanner that is supports VRS (Virtual ReScan)
 OCR Software solution
 Rules based OCR solution
 Content Management solution
 SAP Content Server
 PBS ContentLink with EMC Centra, NetApp Filer, and
DR
 OpenText (IXOS), OnBase, IBM, Documentum, or
FileNet etc
 Release to SAP system
 Automatic Posting or further processing within SAP
Workflow
61

]
 Thank you for participating.
Please remember to complete and return your
evaluation form following this session.
For ongoing education on this area of focus, visit the
Year-Round Community page at www.asug.com/yrc

[ SESSION CODE: 0403

John Walls
Verbella CMG, LLC
John.walls@verbellacmg.com
484-888-2199
www.verbellacmg.com

63

OCR for Invoice Processing

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