Helfert Research Approach for Measuring IQ

8/3/2019 Helfert Research Approach for Measuring IQ

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HSG / IWI / CC DWS

Markus HelfertInstitute of Information Management

University of St.Gallen

[email protected]

datawarehouse.iwi.unisg.ch

Data Warehousing Strategie

Renate RadonEpicur GmbH

Germany

[email protected]

www.epicur.net

Research Approach

for Measuring Information Qualityin Data Warehousing


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HSG / IWI / CC DWS 2


EPICUR Competencies

Finance & Administration

Payroll

Project Mgt.

Engineering

Service Mgt.

Discrete Man.

Core Competencies

Shared

Servic

es

Supplier Integrator Customer

E-Services

Business Bus

Intranet

Extranet

InternetCustomerRelationshipManagement

Adding Economic Value Business Intelligence Business Networking


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Competence CenterData Warehousing Strategy

Business Case / Cost Benefit Analysis DWH Introduction

Organizational Concepts

Information Requirement Analysis Data and Information Quality

Operational Data Warehouse

Research Project covering areas of


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Content

Data Warehouse - turntable for business process integration

Information Quality and Information Characteristics

Quality Function Deployment

An Example: Process of Product Configuration

Further Research

Method-based Information Quality Management


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Turntable for End-To-End

Business Process Integration

StructureP

rocesses

TransactionalProcesses

Information

Processes

E-BusinessProcesses

Data Warehouse

Marketing

InternetMarketing

Marketing

Analysis

Sales Internet Sales

Configuration

Business Part-

ner Collaboration

. . .

Service

Service

Interaction

Field Service

Customer RelationshipManagement

nProvide value-addinginformation at any time,any location, any level

of detail, any individual

request

n Decompose traditional

value chains and recompose

according to informationchains

nAdd value to your busi-

ness partners by providingreliable, high-quality

information Operational Processes


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Traditional Products + Information = Solution

Pricing

Conditions

Formse.g. Proposals,

Invoices, Payments,etc.

Media

Business

Partners

Competitors

Others

Electronic

Catalogue

Configuration, Billing, Payment

Special Offers

Purchasing

Announcements

Product

Developmen

t

Product

Information

Manufacturin

g

Methods

Technical

Know-How

Sales

Inventory

Management

Assortment

Distribution

Contact

Management

Proposal

Managementt

Service

Management

Influencers

Data Warehouse


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Information Quality

Characteristics of information whichmeet user requirements and therebyprovide user satisfaction

Absence from informationdeficiencies that result in userdissatisfaction

Framework to specify information requirementsand measure information supply

on a uniform and consistent base (set of relevant information characteristics)

Information Process powned by user u

Information supplyfor process p and user u

Information requirementsfor process p and user u

=Correspond?

Informationsources

One accepted approach is focused on user and product fitness for use (Juran 1998)


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Information System

Information, Data and Signals

Signals

(Characters, symbols)

Data

Information

Syntax

Semantic

Pragmatic

Real World

Example

09/03/00

09/03/00 DD/MM/YY

String containing numbersNN/NN/NN

Expected Date, when the productcan be delivered to the customer

Application

Interpretation

Representation

Expected Delivery Date

Product configuration


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Information Quality Characteristics

Syntax

Semantic

Pragmatic

Syntactical correctness, consistentrepresentation,

security, accessibility

Interpretability, accuracy, consistent data

values, complete data values, precise data

definitions, objective, believability, reliable, easyto understand

Relevance, completeness, timeliness

Semiotic Level Information Quality Characteristics

Research Questions Precise Definition of information characteristics Correlation between user requirement and information characteristics

Methods and techniques for measuring information characteristics

Measurement

InformationProcess(Usage)

Real World

(Comp. with

experience andhistorical data)

SyntacticalStandards and

Agreements


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Method-based IQM

Method-based IQM

Organizational

structure

(roles and

responsibilities)

Process

organization

Methods

Techniques and

Tools

Standards, Rules

and Guidelines

Definition of informationcharacteristics and assess

quality goals

Identify and Implementsteps to improve continuously

information quality

Quality Estimation and

Measurement

User Requirements

Causes

Quality deficiencies

Consequences

Analyze

Analyze

Information Process

Information Supply


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Quality Function Deployment

Information characteristics

Userrequirements

Measurementbased on userrequirements

Measurement based onInformation characteristics

Target value

Correlation of

characteristics

Priority

Correlation

Introduced by Akao in Japan in 1966 (Manufacturing Sector)

Customer requirements as focus Method for quality planing


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Configuration as an example for

Information Quality Measurement

Load Know-ledge Base

Assigncharacteristicvalues

Checkcomplete-ness

Multi-levelinteractiveconfiguration

SaveConfi-guration

PriceConfi-guration

Classification

Materials

Dependencies

Customer-designedProductDefinition

Customer-designed&

consistency-provenProduct

GraphicalProduct Structure

Customer-

designedProductCustomer-individually

configured &priced Product

Know-ledgeBase

Prices &

Conditions


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Load Know-ledge Base

KnowledgeBase

Availibility ofProductInformation

Delivery

Date

CountryspecificFeatures

ProductDescrip-tion

ProductVersion

Configuration as an example for

Information Quality Measurement

Completeness

Relevancy

Relevancy

Completeness

Timeliness

Semantic

Pragmatic Information

Characteristics

Syntactic


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Corre

lation

Correla

tion

Measurement

Measurement

Example Product Configuration

Delivery Date (always)

Product description (if possible)

Availability of product information

Relevancy Completeness Timeliness

X

XX

X

Precise Definition for Delivery Date

Correct Delivery Date (no default value)

One Delivery Date for a product

Interpretability Accuracy Complete

data Values

Consistent

data Values

X X X

X X

X

X

unusedinformation

additional informationrequests

not timely availableinformation

Non interpretabledata values

Incorrect datavalues

Empty valuesInconsistentdata values

% of

% of

Pragmatic

Semantic

...

...


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Further Research

Generic House of Quality for each semiotic level

Integration of level specific Houses of Quality in a Model of Information Quality

Relations between requirements, characteristics and semiotic levels

Methods and techniques for measuring information characteristics

Methods to apply the Model for specific information processes (e. g. Product

Config.) Validation of research results in practical projects (e. g. Customer Relationship

Management)

Model of Information Quality as basic framework

Documents

Helfert Research Approach for Measuring IQ