1 mis-information excelence
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Ridi Ferdiana Version 1.0.1
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Company IS Failure Costs
AT&T CRM $100 M
Ford Purchasing System $400 M
HP ERP $160 M
Mc Donald’s Purchasing System $100 M
NIKE SCM System $100 M
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Poor Quality Information
Systems Poor Quality
Business Information
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Assuming that Enterprise is single system
Management creates performance measures and reward systems that compromise quality for speed and cost-reduction
Not to go to find and fix the Root Causes of the broken processes
Management focuses on the needs of the investors over the needs of the end-Customers
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Falling into the techno-trap of believing their job was to put in place the information technology infrastructure
Caught up in the ever-accelerating technology "innovation" spiral, they were not able to reason through what is the purpose
That application "solutions" sic. "systems" is their product
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Never ignore potential waste
“Inspect and Correct" model of data profiling and data "cleansing“
Total Information Quality Management by designing quality and error-proofing into the processes.
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Addresses a holistic approach to managing Information Quality and that is based on proven Quality Management Systems (QMS).
E.g. Deming, Juran, Crosby, Imai (Kaizen), the Baldrige Criteria, and Six Sigma.
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to provide a means for organizations, whether in the private or public sector, whether large or small, to accomplish their missions efficiently and effectively to delight their Customers by eliminating process failure, recovery from failure, Information Scrap and Rework or waste of resources caused by poor quality information
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Assessment: Measure Information Quality capability and information processes to identify process capability (degree of defects)
Betterment: Continually improve processes
Culture Transformation: Transform the culture of the Enterprise to value "Information Customers" and empower "Information Producers,"
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Quality of "Information Product Specification" data (data definition, valid values, business rule specifications, information model correctness, and database design stability, flexibility, and reuse)
Quality of Information Content (accurate and complete)
Quality of Information Presentation (relevant, objective, intuitive)
Quality Culture transformation to sustain Business Performance Excellence through Information Excellence as a result of Continuous Information Process Improvement
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Data Name: Represents an attribute or characteristic about a real-world object or event the enterprise needs to know.
Data Definition: A clear definition of the characteristic of the real-world object or event
Valid Value Set: The complete set of discrete values for the attribute
Data Value Format: The structure of the value, such as NNN-NN-NNNN for a U.S. Social Security number
Business Rules: Clear and correct specification of rules that govern integrity of the valid values
Derived Data Calculation Formula: The correct algorithm or formula used to calculate a fact of derived data
Information Model: Represents the objects and events and the attributes — or facts — that the enterprise needs to know in order to be successful and accomplish its mission.
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Data Content Quality is equivalent to the Quality of Raw Materials in manufacturing.
Defects in the content cause defects in the Information Presented to Knowledge Workers or in applications that use the defects in their calculations or processing, causing them to fail
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relevant information must be accessible, available, and presented in a timely, intuitive, and un-biased way, enabling
Knowledge Workers to understand the significance in the Information, so they can take the right action or make the right decision.
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IQ is quality of data in databases
IQ is "data cleansing."
IQ is data profiling or data measurement
IQ is "fitness for use" or "fitness for purpose."
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The Quality of Information is needed to build system and maintenace the business
TIQM is about quality of people. "A company able to build quality into its people is already halfway toward producing Quality [Information] Products
TIQM is Quality System that values the information Customer in term presentation, content, and data