Presented by: Charles King

Date:15th March 2006

QAS data quality research

Agenda

Two views

Why is research valuable?

Global research

Public Sector specific

Common themes

Value Ownership

Investment Data Strategy

Responsibility

Two views

“Lies, damn lies and statistics.”

Mark Twain

“98% of statistics are made up on the spot.”

Anonymous

Why have we done the research?

Every day there are:18,000 movers

1,600 deaths

820 marriages

410 divorces

50,000 telephone number changes

Data is dynamic

Understanding and responsibilities

Marketplace

Education

Methodology

In June 2005, 550 private and public organisations from across the globe were surveyed in order to establish the integrity of their customer data.

The respondents were a mixture of CEO’s MD’s and senior managers.

Is it important?

All industry types rate enhanced customer satisfaction as one of their top 3 drivers to improve data accuracy

July 2005 white paper figure 3

*Dynamic Markets research 2005

Cost of poor data

75% admit poor data quality leads to lost revenue through missed opportunities.

73% believe inaccurate data costs them money on wasted resources, lost productivity, wasted marketing spend, reworking, etc.

On average 6% of revenue is perceived to be lost through incomplete or inaccurate data.

Impacts the efficiency and costs of your business.

Financial issue.

*Dynamic Markets research 2005

A case in point…

“Clean data – that is my biggest, biggest, biggest, biggest challenge. If I could get the data clean in our organisations so that many millions of people have not got multiple entries, we can do much less reworking. Reworking is a real killer.”*

Steve Lamey, CIO, HMRCs

*31st May, 2005

Barriers to maintaining accurate databases

Key data accuracy challenges

Figure 4 July 2005 white paper

Clear strategy

Only 34% have a Board member who takes ownership of the data

Only 19% say it has been discussed in the last 3 years

Communicate

27% have an organisation wide documented strategy

*Dynamic Markets research 2005

The data quality strategy

So why is a strategy so important?

“If you do not have a focussed data quality strategy in place, you have to assume that you have a data quality problem”

• It’s a strategic issue• It can impact new IT initiatives• It’s all about people

Public SectorSpecific Research

Who participated?

Contributors by sector

350 respondents from across the UK

How is data perceived

99% of respondents view it as a key organisational asset

15% strongly agree, 43% agree

Data strategy ownership by function

Who owns data strategy?

IT responsible for but do not have ownership

Low strategic prioritisation

Strategy must come from the top

Confidence in data quality

How accurate is your data?

High degree of confidence

Don’t know

90%

70-89%

50-69%

<50%

How often is your data cleaned?

Over 50% rarely clean their data, or don’t know how often, if at all, it is cleaned.

Data decay

Data sharing can be problematic

Avoid ‘boom and bust’

The benefits of accurate data

Benefits clearly recognised

Legacy systems / Budget allocation

51% of organisations are planning to invest in better data management practices in the next 12 months.

*Dynamic Markets research 2005

Outdated Data Quality Systems

Only 62% of organisations have a database manager or alternative that looks after data quality.

79% said 3 or more people have responsibility in the organisation.

*Dynamic Markets research 2005

Lack of best practice/ Strategic prioritisation

Ownership of data

Head of IT / IT Managers 60%

Primary users

Are they best placed to maximise data?

Can they get the buy in to a data quality strategy?

Organisational asset

Visibility

The principal barriers to data accuracy

Key data accuracy challenges

Considerations for data migration

The most important data

What 3 things would you most like to improve?

Inaccuracies

Duplicates

Ability to share information

How is the Public Sector different?

More public sector organisations than any other industry sector (36%) said they have an organisation-wide data strategy in place. (Finance - 24%, Telecoms - 18%, Utilities - 21%, Retail –27%)

More public sector organisations (62%) have a dedicated database manager than any commercial sector (which averaged 42%)

How is the Public Sector different?

More Public Sector organisations (27%) have a single champion for data quality (compared to 18% in Finance and Telecoms,15% in Retail, and 21% in Utilities

Fewer Public Sector organisations (25%) are planning on investing in data management over the next 12 months compared to those in all other sectors – 59-64%

Research summary

Progress is being made!Data deteriorates rapidly through timeThe value of data is being recognisedA data quality strategy must be

OwnedRecognisedCommunicatedSupportedContinuousConsistent

Data quality directly impacts service delivery and the bottom line

Consequences…

Negative publicity

IT project risk

“30 million tax letters a year go astray”

“Between now and 2007, over half of all […] CRM implementations will fail due to a lack of attention to data quality issues”

Customer interactions

Front-line morale

Wasted money

Sensitive information astray

Fraud

Thank you for listening

Any Questions?