Title

Proceedings of the Eighth International Conference on Information Quality (ICIQ-03)

8th International Conference on Information Quality (IQ-2002)

8th International Conference on Information Quality (IQ-2003)

Executive Summary/Abstract

Most IT systems cannot measure the accuracy of outputs

Does the system work and where is the evidence?

Are business decisions based on garbage?

Barclays Bank Case Study:

Small data quality flaws at the start of a project magnify into

inexplicable defects in end user outputs. Objectives cannot be

translated into measurable performance indicators and nobody

knows why.

Barclays1 used artificial intelligence to audit trail the history of

each data record at sub field, field and record level from the

source system to the warehouse. Audit trails made the workings

of the IT system transparent and end users were able to validate

output, identify errors and track back to fix them.

Using Artificial Intelligence to Benchmark

Organizational Data Flow Quality

Adrian McKeon

Infoshare Limited

amckeon@infoshare-is.com

1

McKeon, A. J. “Basel II Compliance: Can You Prove It?” A Barclays Bank plc Case Study, November 2002, www.infoshare-is.com

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8th International Conference on Information Quality (IQ-2003)

8th International Conference on Information Quality (IQ-2003)

Which Comes First: Data or Technology?

Why Measuring Data Quality is Important

Data links policy to operations i.e. it translates

objectives into measurable performance indicators

Why measuring data quality is important

What happens when you can’t measure it

Output measurements reconcile silos of data from

disparate agencies and link it to objectives

Barclays Bank Case Study

Decisions made on fragmented or inaccurate data

are invariably bad making partnerships ineffective.

What did Barclays Achieve?

How did Barclays Achieve it?

Analysis tools are useless if they do not provide

accurate, measurable intelligence for action,

monitoring and evaluation

Conclusions

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