Conversion from paper-based filing to an electronic document management system (EDMS) requires significant planning. Indexing digital documents is not optional. This paper distinguishes between field-based and full-text indexing and recommends a combination of the two. Tangible and intangible organizational benefits of indexing digital documents are outlined. The various costs associated with indexing are detailed, and specific price information from service bureaus is presented. Recommendations for choosing an EDMS are included, as well as a model for assessing the organization's indexing needs.
Organizations have traditionally relied on paper filing systems for document storage and retrieval. However, paper records are extremely difficult to manage because they have to be stored in and retrieved from only one place. Electronic document management systems ( EDMSs) solve many of the storage and retrieval problems inherent in paper filing systems while simultaneously reducing business costs. EDMSs manage storage and retrieval of many different types of digital documents, including word processing files, spreadsheets, database files, e-mail, voice mail, scanned images, and Internet/intranet HTML documents.
While EDMSs provide much faster access to and retrieval of documents (which is a financial benefit in itself), the mere availability of a new technology does not justify its acquisition. The real measure of value "should not be how much faster you are able to respond to a situation with new technology, but rather what value is added to the business process through faster response" ( Koulopoulos, 1995). Effective indexing can add value to the organization far beyond mere speed of retrieval by enabling users to retrieve documents in many different ways. Think of business records as part of a hierarchy of "containers" which include Folder, Section, Document, and Page. A folder can have many sections, and sections can contain many documents, and documents can consist of many pages. Yet traditional paper-based filing systems require users to retrieve all information at the "Folder" level of the hierarchy. By contrast, EDMSs allow information to be retrieved at many levels. This retrieval is built on indexing, the bedrock of EDMSs. The accurate and consistent indexing of digital records is absolutely critical to the success of the organization.
So what do you need to know about indexing to increase your document retrieval efficiency and save money? There are many factors which affect indexing needs. First, an understanding of the two basic types of indexing is needed.
Types of Indexing
Indexing can be field-based, full-text, or a combination of the two. Index field data make unique identification of documents possible. For example, the United States Department of Defense is considering the user of a pair of index fields as unique identifier: creation date/time and creator ID. Adding other indexing fields provides additional, controlled ways to access individual records or groups of similar records. Retrieval from index fields is consistent and accurate because it is based on a controlled search vocabulary. Ideally, field indexing is performed at the point when business documents are created. Some field indexing can be done automatically (more on this in the costs analysis), but human indexers are also required.
Full-text indexes are created automatically. Computer software reads every word of every document in a database and creates an inve rted index of words and their locations in the database. End-users can search the database using any words they want to (this is called "natural language"); the computer will find every match between the search term(s) and the text of the documents. Full-text searching makes it easy to locate documents when users are not exactly sure what they need, but it also finds a high number of irrelevant items (for example, Internet search engines are based on full-text indexes). The organization pays for time employees spend browsing through irrelevant documents (or "misses") to find the relevant ones ("hits"). In the interest of quick and accurate retrieval, some field-based indexing is recommended. Indexing digital documents exclusively with full-text indexes is not recommended.
All organizations benefit from some combination of field-based and full-text indexing, but determining what particular combination is most beneficial to a given organization is a very complicated process. Before you choose an EDMS to manage your digital documents, your indexing needs should be weighed against the benefits and costs of indexing. Indexing is not an option with EDMSs--the documents have to be indexed in some way. Different EDMSs offer different types of indexing, and the organization should be aware of their capabilities. Organizations have different indexing needs because their documents and their users vary. This article details the benefits and costs of indexing digital documents and includes a model for assessing the indexing needs of the organization.
Indexing digital documents produces both tangible and intangible benefits to the organization. Tangible benefits include financial, legal, employee, and value-added benefits. Intangible benefits include less concrete measures of success, such as improved perception of the organization by both employees and customers. Combined tangible and intangible benefits result in financial gain for the organization through increased employee productivity, customer service, and competitive advantage in the marketplace.
Financial Benefits:
Increased production. The speed of many routine
office procedures (such as
production of statistical reports, records management tasks, access to and
retrieval of digital documents, etc.) is increased.
Decreased future staff requirements. Increases in
production can be handled by current staff.
Increased access to current information.
Quick and accurate updates of
indexes throughout the organization decreases information retrieval
time and increases accuracy of information.
Improved customer service. Prompt, accurate
information
retrieval increases repeat revenue for the organization.
Decreases in human filing mistakes. Large legal
practices often spend 8 or
more hours to locate misfiled documents (Socha , 1996).
CASE STUDY
A legal firm using an image management system found that their cases could be handled by 2.5 fewer temporary full-time clerks than before they implemented the system. With the previous paper-based system, clerks spent large amounts of time retrieving documents identified in database searches, photocopying the documents, delivering the copies to attorneys and legal assistants, and refiling the originals. The clerks also spent considerable time searching for misfiled originals. 2.5 clerks earning $14/hour for 160 hours/month over 14 months would have cost the firm $78,400 ( Socha, 1996).
Legal Benefits:
Litigation protection. In a lawsuit,
records need to be produced very
quickly. An indexing system that can identify and retrieve documents
needed for litigation can pay for itself if a single multi-million
dollar lawsuit is avoided.
Response to Rule 26. A new law requires
parties involved in a federal
lawsuit to identify and produce relevant records within 85 days of the
beginning of the litigation (Skupsky, 1995). Quick
and accurate retrieval
of records is required.
Records retention compliance. Federal,
state and local governments
regulate record retention periods for organizations. There are over 10,000
federal recordkeeping laws alone (Skupsky, 1989). Good indexing systems
include indexing fields related to retention (such as creation date,
retention period, and disposition date).
CASE STUDY
As a result of Rule 26, courts will probably require each party involved in a lawsuit to make a full disclosure of their records in the early stages of the case. Sanctions will follow for parties which fail to produce relevant information. Disorganization of records will not excuse parties from compliance. For instance, in United States v. ABC Sales & Service, the court concluded that "'a business that generates millions of files cannot frustrate discovery by creating an inadequate filing system so that individual files cannot readily be located'" (Skupsky, 1995).
Employee Benefits:
Currency of business information. New
documents can be added to the
indexing system quickly, and if documents are indexed when they are
created, all users can access them immediately. Employees can do their
jobs better.
Document version control. Indexing
digital documents
makes it possible to control which version of a document users can access.
Employees don't waste time working on outdated documents, or updating a
version that's already been revised.
Remote access. An organization-wide standard
indexing language allows
authorized users to retrieve documents from anywhere in the world.
Employees don't have to take their whole office with them when they travel.
Simultaneous access. Employees can share a
document if it is indexed
properly and retrieved from a computer network. The "file folder" is never
missing from the file cabinet. Hard copy production and distribution are
also eliminated.
Decreased training time. New employees become
quickly and fully productive
in the organization.
CASE STUDY
When the U.S. Patent and Trademark Office (PTO) implemented a new imaging system, its most noticeable benefits involved customer service and employee training. The PTO Commissioner said that new patent examiners learned the business much faster because of the indexing system. The old manual indexing system required about 12 years to master; new examiners trained on the imaging system were up to speed in just a few months (Koulopoulos, 1995).
Value-Added Benefits:
Customer service improvements. Organizations
that provide high levels of
service will gain customer loyalty and increase business.
Competitive advantage. Organizations that can
retrieve information quickly
and accurately will be able to accomplish more during the work week. Time
is money, and indexing saves time.
Perceived excellence. Companies that project
an image of excellence will
attract more clients and better employees.
CASE STUDY
Pharmaceutical giant Glaxo implemented an EDMS and saved over $1 million per year associated with search and retrieval time. However, financial benefits were not the most valuable benefits realized. Each New Drug Application process requires about 50,000 pages of data preparation and documentation; the EDMS and its indexing system allowed Glaxo to prepare this documentation and receive clearance from the Food and Drug Administration much more quickly than before. Thus, EDMS implementation enabled Glaxo to collapse their business cycle and get their product to market sooner than their competitors ( Perkins, 19??).
How much will it cost to index your digital documents? One vendor quickly replied, "How much do you have?" But that answer is neither realistic nor helpful. Companies contemplating development of an indexing system for digital documents want to spend as little as possible to obtain a retrieval system that is needed to conduct business. More specifically, they want a system that provides quick and accurate access to frequently-retrieved information and reliable (but not necessarily fast) access to infrequently-retrieved information.
Because the types of business documents which meet these criteria in different organizations vary so widely, it is obvious that there is no one "best" indexing scheme. One size will never fit all. Therefore, indexing costs will be detailed in two ways: 1) factors that affect the cost of indexing, and 2) cost information reported in published studies (see Table 1).
Factors That Affect the Cost of Indexing:
One of the first decisions which must be made is whether documents not currently in digital form will be converted. A paper or mICRofilm document is converted to digital format by scanning it into a computer; OCR/ICR (optical character recognition/intelligent character recognition) software may then be used to convert the document to ASCII text (Thiel, 1992). Documents can be indexed before or after they are scanned. Spencer (1996) estimates that the true cost of batch scanning 10,000 documents is about $.09/page before indexing costs are included. Thus, undertaking a large document conversion project can be costly. DocuCon, a full-service document conversion firm, comments that at least 20% of the documents to be scanned will require special handling (because of size or condition) and that rated equipment speeds are not reliable guides to how long jobs will actually take; special conditions like these further increase the cost of document conversion ( Cullen, 1991) . Other factors which affect the costs of indexing include the cost of keying index field data, technological costs, retrieval costs, and costs of updating.
Manual field indexing of digital documents can be performed when the documents are created or when they are stored. For example, electronic document processing systems often require that employees who produce letters and reports using word processing/spreadsheet software fill some index fields when the document is saved. Although the time required to index a single word-processed document is small, the individuals who do this indexing may be highly paid, which increases the overall cost of indexing digital documents. The most variable (and often the highest) cost associated with indexing is labor.
Indexing cost can be minimized by searching for ways to fill index fields from information already contained in existing corporate databases. If manual entry of a customer number allows the system to automatically access name, address, or zipcode, a great deal of manual keying time may be eliminated (Devlin, 1996). Barcoding is a new and cost-effective way to quickly and accurately identify batches of document types or individual documents (Spencer, 1994). For example, if a type of business form is preprinted with a bar code that identifies what type of document it is, the EDMS can automatically populate the "document type" indexing field when the document is scanned and OCRed. No one has to key the document type, which decreases cost.
The number of index fields used to identify a particular document is a significant cost factor, especially when indexing is performed manually. A study of indexing projects showed that the average number of index fields is 8-12 (Cisco, 1993). However, an ANSI Technical Report prepared by the Association for Information and Image Management International suggests 50 possible index fields which might be used with electronic image management systems (AIIM, 1995). If the average field contains 12-20 characters, the cost difference between manually keying each additional field must be considered.
Sometimes the cost of indexing documents can be reduced or eliminated by using full text retrieval systems which create an additional file (usually called an inverted file) in which each non-trivial word is listed with a locator key (Thiel, 1992). full text retrieval systems also allow users to construct search queries in their own words, rather than having to conform to the restraints of pre-selected terms (Fidel, 1994). However, full-text systems often return an unacceptably low number of relevant documents, fewer than 20% in one study (Blair & Maron, 1985). Some organizations will be unable to afford the cost of not finding relevant documents every time they look for them.
Technological Costs
Although most organizations are already computerized and the cost of adding computer capability and memory storage is becoming increasingly economical, there still remain technological cost implications in choosing indexing systems. The size of the index itself must be considered. Inverted files (used by full text retrieval systems) are often very large, sometimes requiring more storage space than the documents which they index (Thiel, 1992). Timely document retrieval may require faster processing speeds than the organization presently supports. And if documents are being shared by many users, local area networks may have to be installed.
The cost of data migration (which includes index migration) must also be considered. Organizations should appoint an information management professional to administer data migration and indexing so that documents remain accessible as technological change occurs. Many organizations already own systems that contain non-standard or proprietary software which makes integration and migration difficult. Planning for future technological change now will save costs later.
Retrieval Costs
If minimizing the costs of indexing documents ultimately increases the cost of retrieval, it may be false economy. Kind and Eppendahl (1992) suggest a number of questions which must be asked about document retrieval, including who performs searches, how frequently items are needed, how long each search takes, how quickly the information must be made available, and how often a needed document cannot be found. Answers to such questions have cost implications which must be considered when designing an indexing system. For example, an inexpensive indexing system will require more search and retrieval time than a more expensive one. Can you afford to have your highly-paid employees spend time searching for and retriving documents? If you don't invest in the indexing system, you will pay for it (and pay more for it) in retrieval.
Another retrieval cost involves training employees to use the system. The more complicated the indexing scheme, the more time and training will be required before users feel comfortable and confident about their ability to access the information they need.
Cost of Updating
Two different Kinds of updating costs must be considered. First is updating the documents in the system. If most documents exist in only one version, it may be economically feasible to simply start indexing over each time a document is revised, essentially giving it a new identity. However, if documents are frequently revised or modified, the organization may need to identify the most recent or official version of a document. Additional indexing fields may be needed to ensure that multiple users all have access to the latest version.
The index itself must be kept current and updated. Griffiths and King (1993) survey 16 organizations and suggest that direct costs of an "index maintenance" project average $.29 per document (the project included creation and addition of new terms, removal of obsolete terms, and authority and location control work). Index maintenance may cost more that the original cost of indexing documents. Time and effort spent on initial index design may eliminate costly projects to correct or update after the system is in place.
Cost of Indexing
Table 1 shows examples of costs and ranges found in published studies of indexing projects. Koulopoulos(1995) reports that the time spent designing a typical system is divided among field identification and data standardization (20%), data entry (20%), and system correction and fine-tuning (60%). Initial purchase of digital imaging systems with capacity to process and store 300,000 to 3 million pages per year costs $.15 to $.25 per page, depending on use.
Costs reported by companies indexing their documents in-house range from $.12 to $.20 per page (Cisco, 1993). Typical service bureau charges currently range from $.15 to $.30 per page for scanning and indexing (it is not clear how many index fields would be included).
So how few index fields can your organization get by on? You need at least two fields to ensure data retrieval--one uniquely identifies each document, and another provides an alternate pathway in case the first one fails. W. Wiggins of DocuCon recommends indexing a unique identifier and the document type for each document (personal communication, August 3, 1996) . You need additional fields to manage records retention and disposal. You also need to index processing information about the software and hardware used to create each document so that data can be properly migrated when necessary. The Association For Information and Image Management (AIIM) identifies 30 possible processing information fields and 20 possible retrieval information fields (1995). The United States Department of Defense uses 22 records management fields to index their documents (Prescott, Underwood, & Kindl, 1995).
Answering the questions in "Taking Stock of Your Company's Indexing Needs: Full-Text, Field or a Combination?" will help you identify what sort of data needs to be stored in index fields. Obviously, we cannot recommend a minimum number of indexing fields needed to effectively retrieve business documents. Each organization has unique requirements that should be thoroughly studied before implementing an indexing system.
Document Demographics
What requirements do your documents fulfill?
Business purposes (to make payroll, pay
bills, write reports, serve
customers)
Legal purposes (to prepare for litigation,
audits, regulatory
reporting)
Records management purposes (to manage
retention, disposition,
vital records protection)
Archival purposes (to conduct longitudinal
studies, genealogical
research)
What is the condition of the documents and the
information contained on the
documents?
(Are the documents legible enough
for more than 90% to be
Do you have documents that are created
electronically? (Example: word-processed documents, IRS income tax returns
submitted
electronically)
What indexing data are already available in
existing corporate databases?
How accurate, complete, and consistent are the available data?
User Demographics
Who are the primary users? How do they ask
for the documents?
Who are the secondary users (such as outside
auditors, strategic business
partners, customers)? How do they ask for the documents?
Benchmarking
How do other organizations in your industry
index documents?
How do other organizations outside your
industry index documents?
Are there industry standards for indexing?
The purpose of indexing is retrieval.
If documents cannot be found, they
may as well not exist.
Think about ways people in different parts of
the organization might want
to retrieve the same information. You may have secondary users with
different indexing requirements than the primary users. It is better to
purchase and implement an indexing system that fits your users than to try
to change your users to fit the system.
Make sure that your users are trained to use the indexing system that you
have implemented. Ask your vendor if their system includes the costs of
training your employees.
More is not necessarily better. Six to ten index fields may be as useful
to your users as fifty, at much lower cost. However, one or two extra
fields may be worth the investment if they help avoid litigation or
simplify compliance with regulations. Every organization has different and
unique indexing needs.
Think about how to use information you already have in digital format to
avoid additional indexing and re-keying. You may be able to automatically
populate some index fields.
Use a full-text index in addition to indexing fields
to index documents that are created electronically (such as word-processed
documents, online application forms, etc.). To further reduce costs,
consider introducing more digital document creation
in the future.
Include controlled vocabulary indexing fields to
standardize indexing terminology. You don't want different departments
calling the same kind of document different things (such as
"bill,"
"voucher," and "invoice").
Work with a reliable vendor who uses non-proprietary programming language.
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ANSI (American National Standards Institute): an
institution which develops and publishes standards for use within the
United States.
Automated Indexing: computerized indexing which
doesn't require human decision-making or data entry. Automatic indexing
software populates index fields by reading information from bar codes or
scanning digital documents which have undergone OCR conversion.
Barcode: a sequence of machine-readable
lines of varying widths which contain data. Barcodes can be used to
facilitate automatic indexing. For example, if standard business forms
(such as invoices) are preprinted with a barcode which indicates that the
form is an invoice, an indexing system can automatically populate the
"document type" field after the paper form is scanned and
OCRed. Barcodes also survive fax transmission intact.
Batch Processing: a technique by which items
to be processed are collected into groups prior to processing.
Controlled Vocabulary: set of rules for
choosing words and phrases to be used in an indexing system, along with
the list of approved or allowed words to be used in the system.
Data dictionary : organized collection of
information about data. The data dictionary compiles data about data, or
metadata. A data dictionary is an automatic
component of most database management systems.
Data Element : a unit of data that is
considered to be indivisible. Data elements are the building blocks for
all data processing systems. Examples: document type, creation date,
disposition date, Social Security Number, etc.
Digital Document : document
which exists in electronic form inside a computer system.
Distillation : the process of elminating,
summarizing, or in some other way reducing a body of information to its
essential components.
Document : 1. any format which contains
information. Documents may be word-processing files, e-mail messages,
spreadsheets, database tables, voice mail or other audio recordings, faxes,
business forms, images, information captured from the Internet, and so
forth. Documents are sometimes called "records." 2. According to
ANSI/AIIM TR40-1995, a collection of zero or more
pages that are related, linked, or bound to each other in some way
appropriate to the application. In an electronic image management system,
the provision of a zero-page document allows the creation of a document
entity prior to capturing and linking its page(s)..
Document Classes : types of documents
which require similar indexing fields. Examples of document classes:
invoices, contracts, timesheets, e-mail messages, and so forth. Often
called "document types."
Document Life Cycle : the period which
includes creation, maintenance, use, and ultimate disposition (destruction)
of a document. The records manager needs to know the life cycle of every
document in the organization.
EDM (Electronic Data Management): application
of technology to save paper, speed up communications, and increase the
productivity of business processes.
EIM (Electronic Image Management ): system
which organizes information in all formats for use throughout its life
cycle.
Field Data : the retrievable
information which follows the field name . Example:
for the field name document type, the field data might be
invoice or a code which represents invoice. The field data
concept is associated with many terms, including indexing value, term, and
structured or unstructured data.
Field Name : the name of the field where a
specific Kind of information is to be entered. Think of
"field name" as a
prompt for what Kind of information is stored in the
field. Field names
must be decided on before any documents are indexed. The information
stored in the field is called field data .
Example: for the field name document type, the field data might be
invoice. The "field name" concept is associated with many terms,
including "index key," "key field," "fixed field," and "indexing field."
Free Text Searching : See
Full-Text Retrieval
Full-Text Indexing : indexing method in
which the computer creates an alphabetical inverted
index consisting of all words (except stop words) in the document
along with pointers (locations) to locate the words in the document.
Full-Text indexes are inexpensive to create since humans are not needed to
define field names or enter indexing values into those fields.
Full-Text Retrieval : a type of retrieval
process that uses an inverted index to retrieve
every document that contains the word or words in the search parameter.
This type of searching requires a powerful search engine and is much slower
than retrieval processes based on indexing values. It is also much less
accurate because it is not based on standardized search terms. For instance
, a search that retrieves all documents containing the word "invoice" will
miss those which are designated as "bill" or "voucher." However, full-text
retrieval systems initially are cheaper to implement because indexing costs
are eliminated. Full-text retrieval is sometimes called "free text
searching" or "fuzzy searching." Contrast with keyword
retrieval .
Fuzzy Searching : See
Full-Text Retrieval
Homonyms : words that are spelled the same
but have different meanings. Computers don't recognize homonyms.
ICR (Intelligent Character Recognition): a
form of OCR (optical character recognifiton) which
uses sophisticated lexical tools. ICR is typically used to convert
handwritten material to ASCII text.
Indexing : 1. the process of identifying
various pieces of information in a document (such as author, document
type, creation date, etc.) and then transferring that information into a
database for search and retrieval; also called "coding" in the legal
profession. 2. the process of analyzing the information content of
recorded knowledge and expressing this information content in the language
of the indexing system (NFAIS Indexing in Perspective
Education Kit)
3. the representation of the results of the analysis of a document by
means of a controlled or natural language system
Inverted Index : a computer file in
tabular format, in which rows represent documents and columns represent
words. Intersections of rows and columns are marked when certain
documents contain certain words. At the point of retrieval, the computer
scans the entire inverted index for documents which contain the words in
the search query.
Islands of Information : corporate
information stored in separate and unlinked repositories (such as
individual workstations). Storing corporate knowledge in islands of
information leads to duplication of effort and difficult (at times even
impossible) retrieval.
Keyword Retrieval : a type of retrieval
process that searches an index with fields to locate documents which
contain information related to the search parameter. Contrast with
full-text retrieval . Keyword retrieval requires
indexing of documents but provides extremely accurate retrieval as long as
the indexing is accurate. To guarantee accuracy of indexing, data elements
and indexing values should be carefully designed to match the retrieval
needs of the document users, and quality control should be part of the
indexing process. As one vendor told us, "you get what you pay for in
indexing."
Life Cycle : See Document
Life Cycle
Mark Sense Code : a method of automatic
indexing in which the person responding to a questionnaire or form does so
by filling in bubbles or other spaces. A scanner passes over the marks
and reads them automatically into the computer, digitizing the responses.
Metadata : data about data. Metadata is
information required to document the characteristics of and relationships
between information contained within databases (field names, length of
field, type of data, etc.). Sometimes called "higher level information"
or "processing information."
OCR (Optical Character Recognition): the
process of electronically reading digital images (those which have already
been scanned) and converting them to text. After OCR conversion, a
document is "live," or editable. For instance, users can edit OCRed
documents on the computer as if they were word processing documents that
they created.
OCR Repair : manual examination and
correction of OCR conversion. Some OCR software is capable of flagging
documents which it couldn't convert, so that a human is needed to examine
and correct only the flagged documents (rather than all of them)..
Ontology : a taxonomy of everything that
divides human knowledge (or more commonly, a subset of human knowledge)
into a clean set of categories. Example: the Dewey Decimal system.
Page : a page is equivalent to one side of a
2-dimensional sheet of paper, microfilm, transparency, etc. In the case of
input media other than paper, a page will be the data in a single image
frame (ANSI/AIIM TR40-1995)..
Remote byproduct image capture : the process
of reusing scanned images or indexing captured for some other purpose.
Typically, digital documents are transmitted to a central collection point
and indexing software captures pre-processed information (this information
may be housed in a pre-existing database, encoded in bar codes, etc.).
"Captured" information doesn't need to be keyed by data entry operators
and therefore reduces the cost of indexing. The more byproduct capture a
document management system includes, the more cost-efficient it will be
(Spencer)..
Retrieval : recovering desired
information or data from an organized collection of information.
Retrieval Information : that
information necessary for an end-user to retrieve the document after the
document has been captured (ANSI/AIIM TR40-1995). Retrieval information
may be field names , field data
, or a combination.
Single Point of Access : a user-centric
information system that provides access to all information through one
interface. Information may be housed in databases, word processing files,
spreadsheets, e-mail archives, the Internet, voice mail archives, etc.
Single point of access is presently a concept, not a reality.
Spider : a simple computer program that
scans the World Wide Web, "crawling" from link to link in search of new
sites. The Inktomi internet search engine is a massive spider.
Strategic gain : "an influence which goes
beyond meeting immediate operational objectives, and which can positively
impact organization structure and/or direction, and therefore performance."
Structured Database Index : a database
that has been constructed with fields to receive structured information.
Structured information is information about something is known. For
example, a field designed to receive a Social Security number must be
exactly 9 characters long. A field designed to receive a name should be
about 30 characters long to accommodate long names.
Synonyms : words that are spelled
differently but have the same meaning. Computers don't recognize synonyms
very well. Example of synonymous terms: invoice, bill, and voucher.
Verification : the process by which
data entry is performed twice by one operator, or once by two operators,
and the computer verifies that the same data were entered each time. If
there is a discrepancy in the data, the computer prompts the operator to
enter the data a third time.
Version Control : a method to ensure that
the most recent or official copy of a document is the one available for use.
White paper : an authoritative report issues
by an organization. Can also refer to an official government report.
Workflow : the amount and flow of work to
and from an employee, department, or office. The efficiency of workflow is
greatly facilitated by imaging systems which electronically transfer
documents from person to person (as opposed to a paper file folder
traveling from inbox to inbox). Imaging systems can also transfer
electronic documents which are part of the same file to different
people and then reassemble the information at a later point.
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Image Scanning of America, 2363 Teller Rd. #127,
Newbury Park, CA 91320.
(805)375-0422;fax (805) 375-3062;
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