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Cost of Poor Quality

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mohammad aarabi

on 2 May 2013

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Transcript of Cost of Poor Quality

1.China Incident "Where There's data smoke,
there's Business Fire" Academic View! Scenarios Problem Most managers dont believe that bad data will hurt their company. Every company, small or big, and every department can be impacted by the Data Quality issues. The most common of these are ..... Methods & Strategies General awareness of the "cost of poor data" can be spread among the employees by small workshops or banners through the company
For Retail & chain stores COPDQ model is recommended because faults can be found much easier, and Decision Making is based on reliable data. Also Standardization is recommended.
For Insurance companies and big corporates Standardization is a better choice (like SunLife) for better database search like Names, Addresses .... . Cost of Poor Quality Why poor data will hurt you! Big mistakes were made Dirty Dozen Seven common data Quality Issues The methods and strategies can vary in specific COPDQ model can be named,...... Meta Data NEXT STEP China incident The cia selected only one bombing target during the entire kosovo war. But an incorrect map led it to pinpoint the Chinese embassy rather than the Headquarters of the Yugoslav Federal Directorate for supply and Procurement. The suspected presence of weapons of mass destruction was the reason.
Another Example is National Intelligence Estimate on nuclear weapons in Iran changes completely an earlier Assessment The quantifiable cost was $27 million the USA paid.
The real problem is the relation setback between the countries that cannot be described numerically. 2.Mortgages Meltdown Mortgages Meltdown The meltdown has its roots in two financial innovations in 2007:
New mortgage product with low introductry rates
Collaterized Debt Obligations ( CDO's)
Because of several problems like: Incorrect data from applicants
Decreased Accuracy of Credit Scores
Complexity of CDO's for people The lenders couldn't get the loans back, and after a year ,because of this problem. many families lost their homes, many people lose their jobs, several companies declares banktrupcy.
Even now we can see its impact around the world.(mostly Enrope) There are bigger ones Like.... Meta Data Why Is it important?! Meta data or Often called Data-Resource-Data.
Data Definitions
Technical Details of their physical Storage
Details for gaining access
Their original source
Who is eligible to use? imagine there is no DDS and ISBN search system in NYU-Poly library when you want to find a book Without Meta Data systems, Information would become impossible to find in a reasonable time manner. Frustrated
Manager Hidden Cost
gonna catch you! They can become this big! Common Issues Ranked! 1.Can't Find the data they need 2.Incorrect data 4.Too much Data 3.Data privacy/security 40% unsuccessful in intranet
50% unsuccessful in Internet
30% of their time 10% to 25% inaccuracy in data records Risk of Identity Theft
You can buy US Army critical data on USB drives in Afghanistan Bazaars! Half of data never used
Uncontrolled redundancy The cost of poor data quality Tactics/Decision Making Operations Strategy Harder to set and execute strategy
Fewer options to derive value from data
Harder to align organization
Distracts management attention Lower trust between orgs
Lost scales
Poorer decisions
Increased technology risk
Harder to manage risk Higher operating cost
Lower employee morale
Lower customer satisfaction Time spent on searching add costs.
Inaccurate data add costs to operations. Process Driven Data Driven Strategies In general Important notes: Acquisition of new data: Replace data with new better quality data
Standardization: Standard formatting is applied to current databases
Source Trustworthy: Data mined is categorized based on their resources reliability
Error Localization: Identify & eliminate data by detecting errors Check and control Procedures:
1.When new data is created
2.When data sets are uploaded
3.When new data is accessed by process
Process Redesign:
process are redesigned in order to remove the causes of poor data quality and introduce new activities Data Quality Characteristics:
our suggestions are base on these characteristics 3.The 2000 Election

4.Mars Spacecraft

5.Fort Monmouth Closing

6.Trader assistant's error

9.Dep. Veteran Affair laptop

10.9/11 Intelligence problem

11.The 2000 census

12.Financial Reporting 7.Misgraded SATs

8.Jésica Santillán
Poor data definition
Data inconsistency
Organizational Confusion The other 3 Issues are:
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