Data Quality

The Data Quality Company

Success Factor

The value of your data depends upon its clarity.

Data quality in the age of eBusiness

Global players started first, and now smaller

companies are following their lead. Electronic

business processes have become a crucial

element in today’s business world. eBusi-

ness increases corporate reaction speeds

and efficiency. These factors have become

a prerequisite for success, especially in view

of the increasing competitive pressure in the

marketplace.

There are a multitude of software applications

designed for today’s eBusiness world, ranging

from CRM/ERP to Business Intelligence, and

on to Supply Chain Management. However,

these programs are only as good as the data

they can access about your customers, mate-

rials, and products. Therefore, it is imperative

to ensure high-quality data throughout your

whole company: not just once, but perma-

nently.

With Omikron Data Quality solutions, you can

rest assured that all your data fulfils your

requirements at all times and in every detail.

You can select the underlying business logis-

tics yourself. Thanks to the integrated Web

Service interface offered by Omikron Data

Quality Server, we are in a position to sup-

port virtually every strategy for data quality

improvement.

Carsten KrausManaging Director and CEO of Omikron Data Quality GmbH

Remove growth inhibitors with Omikron Data Quality.

Open a new dimension of quality04 Why you should tackle your data quality

projects right now, and not procrastinate

any longer.

Reduce costs and save money06 Data quality may not be everything, but

without high-quality data, electronic

business processes cannot perform as

well as they should.

Strategies used by successful companies08 Manage data quality processes effective-

ly, using powerful Omikron technology.

Solve problems permanently instead of dealing with them again and again10 Omikron improves the quality of your

data to the highest possible level in just

four steps.

Omikron products & services12 Always be on the safe side: Omikron’s

comprehensive performance portfolio is

suitable for every data quality initiative.

Data quality as a process14 SOA-based performance: Omikron’s Data

Quality Server safeguards every critical

location in your IT infrastructure.

Lean MDM: the efficient alternative to never-ending MDM projects16 Start modestly and increase gradually.

Superior data quality solutions grow with

your needs.

Keep your customers in full view18 Data quality in CRM

Optimal use of business resources 19 Data quality in ERP

Correct data for correct decisions20 Data quality in BI

Sell more with less effort 21 Data quality in eCommerce

Put your data in the very best hands: ours!22 Each project is different, and each solu-

tion is unique. You too can profit from

Omikron’s extensive experience, covering

a multitude of fields.

References23 Satisfied customers are our best recom-

mendation: your success is our success.

Case Studies24 What others can do, you can do, too.

We can help you to reach your goals.

Electronic processes are

always founded on data

processing: without proper

data, even the best process

cannot make a difference.

04

Every company is aware of the importance of

high-quality data. Unfortunately, implementing

the software and processes that are needed is

a topic that intimidates many managers, just

because of its complexity. This can mean that

it takes far too long before concrete steps are

taken. This is not just unfortunate: it costs real

money. High-quality data doesn’t just make

your work easier; it also makes it far more

effective:

` Data from various sources and systems

flow together with standardised and uni-

form quality. This reduces the time and

effort required by your IT department.

` Virtually every process runs automatically,

reducing subsequent manual corrections to

a bare minimum.

` Implementation of new CRM or ERP sys-

tems doesn’t interfere with daily business

operations, and it takes less time.

` New products can be placed into the

market quickly, using verified information,

ideally before the competition can act.

` Technology and information from partner

companies is easy to integrate, because

corresponding data structures and field

formats are automatically adapted.

` Avoid the typical data chaos resulting

from business mergers and take-overs by

combining information from separate data

systems into a single, uniform master data

repository.

` Business Intelligence evaluations become

more meaningful, providing the ideal foun-

dation for smooth business transactions

and successful strategic management

decisions.

` Master data processing becomes transpar-

ent and quantifiable, activating valuable

potential for optimisation.

If these characteristics already apply to your

own situation, then your data quality is prob-

ably already at a high level. But if your situa-

tion is not this ideal, with processes that do

not run optimally, then you should speak with

us. We can provide the experience, technology,

and processing expertise necessary to execute

highly successful data quality initiatives in an

astonishingly short time.

Open a new dimension of quality.

The prerequisite for trouble-

free data exchange, lean

processing, and meaningful

analysis is to ensure that

master data is available

uniformly throughout the

company.

Open a new dimension of quality

The Omikron Strategy: Solve problems permanently instead of dealing with them again and again

Although the name may suggest otherwise, “master” data is subject to

continual changes. Customers change their addresses, marital status,

credit cards, and bank accounts. Incorrect entries and duplicates can

distort the data pool as well. Depending on the company, 15% to 30% of

the records may be affected.

In practical terms, this means that data quality can be swamped by

ongoing developments. The result is a vicious circle that can be broken

only by introducing data quality as a fixed component in the business

environment. Omikron’s data quality solutions will support you in your

work. With our help you can model processes and structures to pro-

vide a secure, consistent, error-free, and uniform basis for master data

throughout your company.

Iterative data optimizationThe first question company managers ask when faced with new data

quality campaigns is usually “Where do we start?”

The answer is simple: start where the potential results are of greatest

value. Begin in just one area, and gradually expand later. This strategy

has proven effective in numerous cases. It allows you complete freedom

of choice and planning, and produces remarkable results in a relatively

short time. With Omikron’s technology, it does not matter whether you

begin with ERP, CRM, or any other system. The quality of your evalua-

tions improves immediately with clean information, and with the newly

formed master data repository you will lay the foundation for powerful

master data management.

Working processes and seamless structures: data quality is the fuel for

your business success.

06

Poor data quality leads to

immense cost overruns.

Much of the problem is

concealed beneath the

surface, but sometimes it

is accepted simply because

no proper alternatives have

been found.

High-quality data saves more than it costs.

Reduce costs with Omikron

Minimum effort –maximum benefitsMany data quality solution providers can inte-

grate complex processes to safeguard data

quality, while placing very high demands on

time and personnel resources. This results in

long projects that have an extremely negative

effect on profitability.

Omikron has shown that this can be done dif-

ferently, by cleansing and restructuring data-

bases in an extremely short time with efficient,

standardised processes complying with indi-

vidual demands and requirements. Omikron’s

Data Quality Server also allows customised

data quality processes to be defined that can

be used by every element in the IT environment.

Data quality then becomes an integral compo-

nent of every electronic business process.

Identify potentialCosts incurred by data quality projects are

normally far lower than the effects and conse-

quences of poor quality data. The more efficient

the software tools that are used, the better the

cost/benefit ratio becomes.

Whether Data cleansing, data comparison, data

migration, or data integration: Omikron has

the suitable solution for every scenario. This

provides you with a comforting assuredness

of reaching your goals with the least possible

amount of effort, and with maximum reliability.

Inaccurate reporting

Poor decisions due to false definitions

Inadequate customer service

Inefficient marketing

Inefficient procurement

Delayed introduction of new products

Miscellaneous

54%

35%

32%

18%

17%

8%

81%

Data quality problems affect every corporate area.

dissatisfied personnel

increased IT costs

lost commission payments

reductions in new business

increased processing costs

increased cleansing costs

increased personnel costs

standard risk costs

interest costs

lost business

auditing costs

lost customers

opportunity costs

equity costs

loss of revenue

wrong decisions

reworking costs

risk costs

penalty payments

Direct costs:

Indirect costs:

Effects of poor data qualitySource: CIO 6/2007

08

We all profit differently, but everyone profits.

Eliminate duplicates totalling 40% or moreWith Omikron’s assistance, a leading car rental com-

pany was able to identify duplicates that made up 40%

of its customer database. By permanently safeguarding

the quality of its master data, the company improved its

customer service considerably while at the same time

drastically reducing running costs.

Cross-business data transparencyA full-service provider in the field of sanitary hygiene,

occupational clothing, and protective floor mats optimised

its cross-market processes by targeting the removal

and avoidance of duplicate master data addresses and

records. Today, marketing and sales benefit equally from

the resulting transparency of the data.

Uniform address structuresIn the field of tourism, personal contact with customers,

service quality, and process efficiency are decisive fac-

tors to determine who books what, and how much profit a

booking can generate. This was reason enough for a large

travel company to transfer its entire customer archive into

a single database. The biggest challenge faced was incon-

sistent address structures adopted from various countries.

Omikron mastered this challenge while simultaneously

integrating data quality processes into their existing CRM

system.

Flexible judgement leads to correct decisions

09

Each company has its own requirements for

data quality, and for the processes that safe-

guard it. Smaller companies work with different

strategies and personnel structures than larger

companies. International corporations need

a much higher data throughput for their data

quality solutions than a regional medium-sized

company does. This also means that a proper

data quality solution will stand out not only

because of its high performance, but most of

all because of its flexibility – both during imple-

mentation and in use.

When choosing your provider, special attention

should be paid to the following criteria:

` Multi-domain ability

Only individually configurable and expandable

data quality solutions can give you complete

freedom when cleansing, maintaining, and

enhancing internal and external master and

transient data; without this, up-scaling the sys-

tem will automatically upscale the errors.

` Individual workflow arrangement

Your data quality solution should be capable

of dealing with entire processes and be able to

control them according to your own individual

requirements. Modern systems offer graphic

user interfaces that can be used intuitively by

employees, without requiring special program-

ming knowledge.

` Lower integration effort

There are many data quality solutions that can

be adapted (albeit laboriously) to Service-Ori-

ented Architecture (SOA), but only a few of them

are actually designed for this purpose from the

outset.

Once a Web Service interface has been inte-

grated into the software application, various

data quality processes can be incorporated at

each and every location in a heterogeneous

system infrastructure, and at whatever depth

required. The establishment of company-wide

data quality measures is freed from technical

limitations. In addition implementation and

project running times are reduced considerably.

` Language independency

Language-independent matching processes

have clear advantages over traditional solu-

tions; particularly for international business.

In most cases, the Unicode capabilities are

not sufficient to reliably recognize and elimi-

nate duplicates, because different languages

require different similarity evaluations. Asso-

ciative processes are truly suitable for compar-

ing international master data, eliminating the

need for diversions via European character sets

(“transliteration”), while forming a direct simi-

larity relationship between different character

sets and scripts.

Data quality is not simply

data quality. Omikron has

the best solution for each

individual scenario.

Flexible judgement leads to correct decisions

Some important items to watch carefully.

10

You will hardly notice our work – but you will certainly notice the results.

Humans can make sense of

unstructured data and grasp

the clear picture. Computers

do not have this capability.

Top data quality in four steps

Whether you want to upgrade your data pool, or

implement a new system, whether you want to

integrate data from a newly acquired subsidi-

ary, or plan a fusion of a wide range of data in a

data warehouse: with competent consultation,

intelligent software, and wide-ranging data

quality services, we can help you to make your

data ready for the challenges you face today –

as well tomorrow – while scarcely affecting your

daily business operations.

Data analysis and workshopsOmikron will examine a sample of your master data records. Every relevant detail about

the current quality status is presented in a workshop, developing strategies that are

optimally coordinated to your individual requirements. The crucial question is not only

how you want to manage your data in the future, but also what you actually intend to

do with it.

Initial master data cleansingIn the second step your data is comprehensively restructured, starting with duplicate

cleansing and postal address correction. Data enrichment can also be included as an

option.

Safeguarding data qualityBy incorporating Omikron’s Data Quality Server into your CRM and/or ERP system, data

maintenance during live operations is possible.

Periodic examination of data qualityAdditional cleansing and preparatory steps safeguard your data quality for the long-

term. The necessary processes can be executed as needed: in real time, as batch runs,

or upon request.

11Top data quality in four steps

Masterdata

1

2

3

45

6

7

8

1 MeasurementDetermination of error types and error rates

2 Data analysesAnalysis of error sources and determination of

reasons for the incorrect data

3 TransformationNormalisation and restructuring of data and

data formats, transliteration of data into the

target structure you require

4 CleansingExamination, adaptation, and correction of data

based upon reference indexes from our partner

5 Duplicate checkBy implementing “fuzzy” similarity processes,

duplicates are grouped into different quality

levels, while permitting examination between

tables.

6 EnrichmentSupplementing data with additional valuable

information

7 ConsolidationConsolidation of various data sources

8 ReportMonitoring and reporting the data quality

process

A coordinated package of measures: the Omikron Data Quality Circle includes all relevant Omikron services, ranging from analysing and cleansing your data, to safeguarding and testing data quality.

12

Omikron products and services

There is no such thing as static data. Your data flows continuously, because it is collected and processed at different locations and in different formats.

Even the best data quality designs are doomed

to fail when the IT applications needed cannot

fully support you. With Omikron’s Data Qual-

ity Server, you can control electronic business

processes according to your own requirements

– and not those defined by your software –

across all systems, even when the data formats

are completely different.

The SOA concept plays a decisive role. Every

function in Omikron’s Data Quality Server is

designed to be completely independent. You

may call them individually or sequentially in an

SOA environment, thereby creating customised

processes tailored exactly to fit your needs.

Even though Omikron’s data quality solutions

provide the maximum possible independence

in every respect, our experts are still avail-

able whenever you need them. If your in-house

capacity or expertise is not sufficient, Omikron

can provide personalised service to fit your

needs.

13

Data MigrationOmikron employs special processing and

analysis tools from the very start of planning.

After restructuring the field contents, duplicate

cleansing and postal address correction is per-

formed. The new data is then transferred into

the data structure for the target system.

Fraud PreventionInternet crime is continually increasing. ECom-

merce companies (such as online shops or

direct banks) must protect themselves against

fraud. Omikron’s technology identifies falsified

addresses and people placing joke orders in real

time. This means that potential commercial

damage is avoided before it starts.

Compliance CheckThe Omikron Compliance Check is integrated

directly into your system infrastructure. Intelli-

gent screening technology compares each busi-

ness partner with international sanction lists

(as required by EU regulations!). Suspicious

addresses are reported, marked, or collected in

a list, as desired.

Data EnrichmentUsing sophisticated enrichment and compari-

son processes, Omikron enhances your cus-

tomer data with valuable information, such as

branch codes, telephone or fax numbers, sales

figures, and socio-demographic information.

Dialog CheckOmikron’s Dialog Check can ensure the qual-

ity of new data before it even finds its way

into your system. Staff members in the sales

department or call centres are made aware of

duplicates, postal address errors, or potential

fraud, together with suggestions for correction,

right as the data is entered.

Process MonitoringReports with individual evaluation criteria

provide an accurate image of the current data

quality situation in your company. Weak areas

are quickly identified. Managers can prescribe

clearly defined, measurable goals, and can be

certain that these can be achieved.

FACT-FinderWith the error-tolerant and language-inde-

pendent FACT-Finder search application, all

desired information is quickly available for your

employees, regardless of where or how it is

stored.

The European Commission

sees the establishment of

standards for data exchange

between companies, sup-

pliers, and customers as a

key factor for the success of

eBusiness.

Omikron products and services

14

Data quality as a process

Design custom workflowsSecurity and effectiveness of data quality

measures depend highly upon the under-lying

workflow. The Management Studio in Omikron’s

Data Quality Server permits you to conveniently

control the optimisation steps you wish to

make, and the order in which they will be per-

formed. No special programming knowledge is

necessary. With just a few mouse clicks, you

can organise processes coordinated perfectly to

your current demands, simply and easily with

drag & drop. This provides a solid foundation

for fulfilling operational requirements and legal

regulations at all times.

Data quality as a process

Workflow design using drag & drop: the Management Studio’s graphic user interface enables rapid adaptation of data quality processes to suit current requirements.

15

Top performance with integrated server-based processingThe latency of server queries normally lies in the

millisecond range. Nevertheless, in the case of

large data quantities, performance advantages

can save significant amounts of time. Sequen-

tial implementation of all data quality functions

is fully integrated into Omikron’s Data Quality

Server, meaning that the workflow is not sent

to the server function-by-function. Instead, it is

done in a single “black-box” step. This reduces

the latency of all data quality processes to a

minimum. Input, cleansing measures, queries

and evaluations – all the information you need

is available at all times and in proven quality.

Postal address correction according to your wishesIn a world full of changes, one must be prepared

for rapid changes. The Postal Address Correc-

tion facility provided by Omikron’s Data Quality

Server provides you with all the necessary tools.

A completely new offline interface has been

created for this purpose, allowing you complete

freedom for your selected information provider.

This option is particularly interesting for rapidly

developing markets, saving you from dealing

with substantial lists of addresses.

Speed saves processing costsSimilarity comparison of data is the foundation

of many data quality operations. The FACT®

algorithm developed by Omikron identifies

duplicates, errors, and multiple registrations,

even when typographic mistakes or misplaced

words make comparisons difficult.

With FACT-Finder’s error-tolerant search, your

employees can immediately find the correct

contact or make real time enquiries in the man-

agement system. This efficiency saves time and

money.

We research for your success.Together with increasing requirements on data quality, background challenges and proc-

esses are also subject to continuous change. In addition to its development department,

Omikron also has its own research department, making it fully prepared to support every

eBusiness data quality strategy – for today as well as in the future.

Data quality as a process

Fast implementation and

flexible adaptation to

customised processes – this

is the criteria that differenti-

ates Omikron Data Quality

solutions from many others.

16

Efficient, fast, safe: Lean Master Data Management

“The solution offered by

Omikron achieved the best

test results and offers an

excellent price/performance

ratio.”

Tom Orvei / Avis Scandinavia

Lean Master Data Management

Heterogeneous system infrastructuresAlmost every company has to contend with

various systems that have grown during its

history, supporting various different business

processes. Customer data is normally distrib-

uted around the whole company, and master

data lies in separate data silos, often at differ-

ent locations and in different systems. The end

result is inconsistent data quality.

It is here that the fundamental conflict between

CRM systems and standard IT architecture is

to be found. The single system philosophy of a

CRM provider harmonises with a multitude of

data channels, fields, and departments only to

a limited extent. In practical terms, a uniform

overview of customers is impossible, and this

often leads to erroneous evaluations in cus-

tomer service.

Overview of master source dataAssistance is provided by the so-called “Master

Data Management”. A comparison engine iden-

tifies similarities and duplicates, consolidating

all data into a central master data repository

with appropriate references made to the original

sources. The structure of the source systems

remains untouched. Master Data Management

is suitable for cross-branch representation of

widely varying activities within a value-added

chain.

Unfortunately, Master Data Management is not

a universal remedy. Although the data quality

strategy is perfectly suited to modern corpo-

rate structures, the structure is not decisive

for long-term success, but rather the contents.

Many MDM system providers do not possess

the necessary knowledge and experience to

Host-System

ERP-System 1

ERP-System 2

CRM-System

Web-Shop

Cross-systemrepository with

the “golden” records

Omikron Data Quality Servercleansing, matching and

restructuring

Lean MDM – the efficient alternative to “never-ending” data quality projects

17Lean Master Data Management

Making your data quality project successful.Each source system has a person responsible for it, and each of these individuals has

different demands on data quality and MDM. Omikron’s “Lean MDM” concept leaves the

structure and contents of source files as they are. By comparing source data with the

cleansed master data, you can clearly show errors and deficits in a transparent manner,

without interfering with the responsibilities of the system managers.

safeguard the validity and consistency of their

master data concurrently with MDM processes.

There is also the question of the laborious

implementation required by traditional MDM

projects. Project running times of several years

are not unusual – which is even more reason

to harmonise each of the individual corporate

areas.

Lean MDM: quick-win for modern companiesOmikron’s data quality solutions provide the

technological prerequisites for efficient, high-

performance Master Data Management. We

call this “Lean MDM”. Even before information

from a wide range of sources finds its way to the

master database, it is cleansed and structured

according to the individual business logic. This

enables managers, controllers, and the market-

ing and sales departments to have a complete

overview of customers within all databases,

suitable to each individual business process,

and entirely independent of the IT architecture

involved.

Thanks to the integrated interfaces in Omikron’s

Data Quality Server, long programming and

adaptation times are no longer necessary. It

is also possible to split the entire optimisation

process into less complicated single projects,

creating a quick-win situation for every busi-

ness department involved – and setting an

example for other departments to follow.

5%

18

CRM is an important instrument for building up

customer relationships and maintaining their

long-term stability. Such concepts can only

be successful with clean data. No company

today can afford to send documents, letters, or

e-mails with incorrect address data. Duplicates

cost money every time they are sent – not to

mention the damage caused to the corporate

image.

Better data pays for itselfHigher data quality multiplies the effective-

ness of many other measures. This particularly

applies when your data quality system is able to

dynamically adopt new communication chan-

nels and information sources.

Customer master dataCustomer master data consists of

` Contact information

The quality of CRM data starts with personal

information and addresses. Good data reduces

the effort needed for further research, and low-

ers the rate of returns.

` Personalised information

Correct personal information strengthens cus-

tomer contacts and the effectiveness of your

advertising campaigns. According to Professor

Siegfried Vögele at the Institute for Direct Mar-

keting, simply using a personal form of address

increases the rate of replies by 15%. Experience

from Omikron projects shows that approxi-

mately 3% of gender information, and almost

5% of personal salutations are incorrect. This is

disastrous for communication.

` Selective information

Specific actions for targeting groups are among

the most effective marketing instruments

available. Therefore, selective information (such

as NACE or SIC branch coding, or in the personal

customer field, age, or residence type) must be

clearly structured and uniformly coded.

Transaction dataTransaction data is linked to the master data.

Only when it is unique, meaning duplicate-free,

can it be evaluated meaningfully. Only then

can customer analysis (such as of purchas-

ing behaviour, ordering history, or customer

lifetime value) be effective and provide reliable

results for an individual, effective form of com-

munication.

Universal application possibilities

Data quality in CRM

“After extensive testing with

Scandinavian data, Bonnier

Business Information has

chosen the Omikron Data

Quality tool as part of our

new global match solution”

Andreas Gustavsson,Bonnier / Dun & Bradstreet

A total duplicate rate of 5% might seem insig-nificant, but it is actually quite high, because 30% of duplicates are from repeat purchasers, meaning the most important customers.

Data quality in ERP

19Universal application possibilities

Users of ERP systems are familiar with this problem, especially

following company mergers: parts, assemblies, or completed

articles are displayed repeatedly in separate data records, but

with different article numbers. Depending upon the opera-

tors or departments, different forms, stock entries, or material

flow plans are used. Duplicate stock entries, doubled inven-

tory control, incorrect results, and erroneous analysis increase

process costs and tie up capital, without any advantages at all

for productivity, and the potential savings through wholesale

purchasing are lost.

Clear overview of business resourcesA proper overview of finances, controlling, production and

logistics, inventory management, marketing, sales and person-

nel management is only possible with valid, consistent master

data. Conversely, poor-quality master data is the fundamental

cause of many serious problems, such as inefficient operative

business processes, or ill-advised business decisions that are

made on the basis of incorrect information.

Leading companies rely upon OmikronOmikron meets these challenges with specially adapted proc-

esses that significantly reduce the effort required for manual

data cleansing, and prevents inadmissible new entries by

using error-tolerant dialog examination. Leading German and

international companies, such as the energy supplier Vatten-

fall, depend upon technology and consultation services from

Omikron.

Missing components can bring the complete production line to a stop. With high-quality data in your ERP system, you can ensure that your company keeps neither too much, nor too little material in reserve.

20

Data quality in BI / Data Warehouse

Intelligent technology eliminates manual processingThe validity of master data records is a primary success factor for BI. Manual

data maintenance becomes increasingly complicated as a business increases

in size, so the importance of automated data quality processes steadily

increases.

Correct data for correct decisionsHigh-quality data is the foundation for valid evaluation, because proper anal-

ysis to serve as the basis for correct prognoses and informed decisions can

only be derived from high-quality data. Duplicated data records and improp-

erly maintained, missing, or outdated information often falsify important

strategic analyses.

Minimum effort – maximum effectOnce Omikron has cleansed your data, it will be correct, complete, and free

of duplicates. With the help of Omikron’s Data Quality Server (SOA), we can

continue to safeguard every critical process, for permanent high-quality data.

21

Data quality in eCommerce

Profit maximisation for online sitesWhether an online shop, travel site, or direct

bank: vast quantities of article data are proc-

essed for thousands of customers in eCom-

merce every day. However, optimisation is

imperative if an online site is to achieve its

maximum potential.

Omikron’s Data Quality Server has been

equipped with a wide range of new functions,

especially developed for the challenges in

eCommerce. Particular attention has been paid

to the administration of basic types, which can

easily be adapted to specific individual require-

ments. Identification and arrangement of frag-

mented product information has been refined;

for example, duplicated attributes are automat-

ically filtered out, and wild cards are expanded

correctly.

1. Use product information for filteringThe Attribute Generator automatically extracts

filter criteria such as brand name, size, and

colour from product descriptions in the online

shop, thereby accelerating product searches.

2. Providing postal address correction in the dialogThe dialog correction feature offers your cus-

tomers correction suggestions in real time

when they misspell an address.

3. Identify and hinder fraudulent attemptsAn error-tolerant blacklist comparison feature

identifies fraudulent attempts and automati-

cally blocks them. A variety of tactics with vari-

ous word forms are identified immediately and

reliably.

4. Eliminate duplicate customers and addressesIntelligent matching algorithms remove dupli-

cates and postal errors.

Universal application possibilities

Get to the desired product more quickly. The attribute generator automatically generates filters

from manufacturer’s product descriptions and text stored in

the online shop.

22

Project type:Enhancing and safeguarding the quality of master address

data for ERP and CRM.

Initial situation:Input into a SAP-based donation fund accounting system with

approx. 2.1 million donors was performed both manually, and

by using a batch import interface from donor master data. No

automated measures were available to check the correctness

of addresses, or whether duplicates of new entries already

existed.

Task:Following the introduction of a new CRM system, potential

external data should be entered and controlled via a batch

import process. The organisation also needed a reliable master

data foundation in the ERP system for accounting purposes.

Implementation:Detailed specifications were created after the analyses of DQ

processes in CRM and ERP were completed. Following connec-

tion of CRM and SAP to the Omikron Data Quality Server, tests

were possible during live operation.

Recommendations for handling basic cleansing were devel-

oped based on the analysis of donor master data. After their

implementation, manual verification of the results completed

the project.

Results:Shorter search times for master data searches in accounting

and CRM. Optimised manual test measures with resultant

reduction in time and effort. Increase of campaign efficiency

with a simultaneous reduction of the rate of returns.

Personnel months: 6

Omikron project staff: 3

Best practices: Aid Agencies (NGO)

Best practices:

Aid Agency (NGO)

23

Project type:Removal and avoidance of master data and address duplicates,

cleansing addresses (postal verification), and implementation

of an error-tolerant, free-text search function; optimising the

customer search feature for flexible information management

in the ERP and CRM system.

Initial situation:Data pools were kept in two independent business areas.

Merging them led inevitably to duplicates in the ERP system

(SAP). In addition, other systems existed that ran synchro-

nously with the SAP system.

The existing CRM “Salesforce” solution permits the use of

diverse business applications from the Internet. The ASP

model has the advantage that no in-house IT infrastructure

needs to be created, and a uniform working basis is available

internationally for all company locations. Approximately 500

employees in Germany and over 2,000 employees worldwide

use this on-demand solution. However, it cannot function cor-

rectly without a clean data foundation.

Task:The overall system should ensure that duplicates are identified

in both systems, and duplicate entries and incorrect addresses

are corrected as they are entered.

Implementation:Initially about 600,000 data records were stored in the SAP

system. With the aid of the Inventory Auditing module, all

duplicates were correctly identified and distributed business

locations were merged. The “Dialog Check” module prevents

duplicates from occurring as new customer data is entered.

The customer data from SAP is transferred through an inter-

face to the CRM system and is compared with the database,

thus avoiding addressing existing customers when new cus-

tomer data is entered. The same happens for potential data on

the SAP side: Omikron’s Data Quality Server Inventory Check

traces duplicates and dialog testing hinders the creation of

new duplicate entries, such as when importing new contact

data. This is (of course) performed in both systems using

error-tolerant search algorithms.

Results:Approximately 1.3 million records of error-free data with

enhanced potential value. Shorter search times for donor

research. Optimised manual testing measures.

Personnel months: 6

Omikron project staff: 4

Best practices:

B to B

Best practices: B to B

24

Project type:Introduction of a CRM system integrated with Omikron Data

Quality Server. Integration of customer data in a collective

database.

Initial situation:Customer information from four different countries was held

in various databases. The company often had to work with

partially inaccurate data collected from different sources in the

CRM system. Because existing and potential customers were

predominantly contacted by e-mail, this presented a serious

problem.

Task:All customer information must be transferred into one collec-

tive database and then restructured, discarding the household-

based view and adopting an individual, personal approach. The

goal was to uniquely transfer the details of each individual

customer – including travel history – into the system. Each

case of multiple customer accounts must be reduced to only

one single account.

Implementation:All customer data was imported into the common database

and cleansed. More than 3 million individuals were registered

in the CRM system, including not just customers, but also

other interested parties and contacts as well.

Results:Processes now run highly automated with SOA technology,

including even the most demanding load scenarios, such as

when dozens of queries are submitted to the server simulta-

neously, while at the same time handling a similar volume of

address comparison processes in parallel.

Personnel months: 6

Omikron project staff: 4

Best practices:

Tourism

Best practices: Tourism

25

Project type:Enhancing and safeguarding the quality of address and

product master data.

Initial situation:Registration and alteration of customer data was possible

either by using the website or by contacting the call centre.

However, the data was only superficially checked and vali-

dated, leading to considerable problems in secondary proc-

esses, including high costs for checking credit worthiness, and

the results of fraud, as well as considerable additional logisti-

cal effort. Periodic alterations of address data was not taken

into account, and multiple registrations in the shop (a common

phenomenon) were not prevented at all.

Task:A uniform view of customers data based on correct data was

to be created, with the goal of optimising business procedures,

reducing administrative effort, and making marketing meas-

ures more effective. Search procedures in the shop were to be

accelerated by generating attributes in the product data.

Implementation:Following analysis of the existing product text data in its

entirety, a set of rules for finding attributes was created and

implemented using Omikron Data Quality Server.

The problem of multiple registrations was dealt with at the

same time. Intentional multiple registrations were analysed

and optimal customisation settings were determined. Once

the workflow for identifying duplicates was created, the exam-

ination process was performed live during running operation.

Results:A uniform view of customers enables targeted customer cam-

paigns and consistent turnover analysis. Furthermore, the

increased reliability of creditworthiness checks has led to a

noticeable reduction in payment defaults. In general terms, the

company reports a huge reduction in internal effort, as well as

reduced costs for shipping and logistics. The attributes in the

product data has optimised all search functions, and custom-

ers are guided quickly by the shop to their desired products.

Personnel months: 0.5

Omikron project staff: 2

Best practices:

ECommerce

Best practices: ECommerce

26 Your partner for data quality

Your data is in the best hands with us.

Omikron – your partner for data qualityData is a highly sensitive commercial commod-

ity that no company should willingly turn over

to outsiders. It is therefore extremely important

to consider just who you can entrust your data,

and to what extent.

Omikron’s technology gives you the freedom

to conveniently control data quality processes

within your own company, but you are also wel-

come to take advantage of the services provided

by Omikron’s experts for more complex tasks.

Data Quality ConsultingFor nearly twenty years we have gathered

extensive knowledge and experience in the field

of data quality. This vast store of expertise and

experience is available for your projects in the

form of personal consultation. Combined with

customised analysis tools and expert experi-

ence, we can analyse the current condition of

your master data, and then assist you to deter-

mine what additional steps should be taken.

Software for data qualityIt all began in 1992 with the development of

FACT®, a new similarity process for duplicate

checks. In 1993 the software continued to

evolve, and in 1996 it was expanded to an entire

product range covering all aspects of address

quality. Both in 1997 and again in 2003, each

software application was modernised to a new

generation, thereby ensuring continued optimal

maintenance and adaptive capability.

Omikron’s Data Quality Server was first released

in 2007, permitting companies to safeguard all

critical data quality locations in their IT infra-

structure. In the same year, the new World-

match® matching process for international data

comparisons was presented.

Today, Omikron is a leading European provider

in the field of data quality. Omikron products

are available for all popular business systems,

including SAP®, Siebel, Salesforce, and Microsoft

CRM® integration modules.

27References

The Data Quality Company

There is an enormous amount of potential value in your data. It’s our job to

awaken this potential – with advanced data quality solutions created for

today’s complex electronic business processing.

How clean is your data?We can examine a sample of your master data free and provide you with the most

important information about the existing data quality situation in your company.

Please contact us at info@omikron.net

Omikron in Germany

Omikron Data Quality GmbH Habermehlstraße 1775172 PforzheimGERMANY

Telephone: +49 7231 12597 0 Email: info@omikron.net Website: www.omikron.net

International

Denmark: +45 31257551 France: +33 182 28 8241 Italy: +39 024 5075 238 Netherlands: +31 6 1325 2956 Poland: +48 781 580 484 Spain: +34 93 344 3321UK: +44 20 3008 7715