1. TRILLIUM SOFTWARE 2013 CUSTOMER CONFERENCE
Proving your worth
Building the business case for Data Quality
Presented By:
Nigel Turner
VP Information
Management Strategy
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2. 2012/13 – a year of horrors

3. 2012 / 2013 – another year
of data quality horrors

4. 4

5. And it’s going to get worse…
 Big Data, Cloud Computing & Data Virtualization and other drivers
are causing the exponential growth of data:
 In total some 2.5 quintillion bytes of data are being created daily;
equivalent to 57.5 billion 32 GB iPads
 Today more digital data is being created every day than the digitized
equivalent of all the words ever spoken by human beings throughout
human history
 Data quality shortcomings are already badly hurting
organizations…

6. Trillium Software EMEA poll –
Sept 2012
QUESTION:
AS A DQ PROFESSIONAL WHAT KEEPS YOU UP AT NIGHT?

7. A paradox…
“We learn from
history that we
do not learn
from history”
7
Georg Wilhelm Friedrich Hegel
German Philosopher
1770 – 1831

8. The barriers to improving DQ…
MAKING
THE INITIAL
CASE FOR
INVESTMENT
OVERCOMING
INDIFFERENCE
& IGNORANCE
DEMONSTRATING
CONTINUED
BENEFITS
WHY DQ
VERSUS…?

9. Overcoming barriers
A BUSINESS JUSTIFICATION / CASE IS REQUIRED

10. What is a Business Case & why do
one?
A business case is an argument, usually documented,
that is intended to convince a decision maker to
approve some kind of action
WHY MAKE A BUSINESS CASE TO IMPROVE DATA
QUALITY?
Cut wasted expenditure and improve business
performance
Ensure compliance with law & regulation
Improve business process efficiency
Improve employee satisfaction and productivity
Protect & enhance brand and reputation

11. Different kinds of DQ business
cases
11
LOOKING
AHEAD
LOOKING
BACK
LOOKING
BOTH
WAYS

12. Seven steps to success
STEP 1
STEP 2
STEP 3
STEP 5
STEP 6
STEP 7
STEP 4

13. Step 1 - Identify the Issue
 Start with acknowledged issues
 Think about your company or department’s
key strategic goals
 How does data quality impact on these?
 Talk to key people across the problem area
 All grades and types – producers & consumers of
data
 Uncover and analyse / revisit DQ problem(s):
 Business problems & impact
 Potential or actual solutions
 Benefits – financial & other

14. Step 2 - Gather Evidence
 Stakeholder Workshops
 Various techniques - Systems thinking, Rapid etc.
 Must have a clear purpose, and attendees empowered to make
decisions
 Interviews
 Use a pre-prepared list of questions to ensure structured capture
and analysis
 Always try to interview in pairs and ideally face to face
 Issue / opportunity logs
 These logs may already exist
 Can be added to or revisited
 Data profiling & analysis
 Useful to do before workshop or interview sessions
 Will drive the key question – “So what?”

15. Step 3 - Quantify the costs of
failure, risks & potential benefits
 Successful business cases are always backed up with
relevant & provable facts
 Potential costs & benefits generally fall into 4 categories:
 Economic
 Customer Experience
 Legal & Regulatory Compliance
 Brand Awareness & Reputation
 Focus on current costs of failure and not on the ‘value’ of
good data
Some potential useful tools and techniques include:
Fishbone
Diagrams
Lean DQ
Approaches
Force Field
Analysis
Root Cause
Analysis
Benefits
Analysis
Net Present
Value (NPV)

16. Example – Summary
benefit analysis (partial)
16
DATA
DOMAIN
BENEFIT TYPE DESCRIPTION EXPECTED REVENUE INCREASE / COST SAVING
Year 1 Year 2 Year 3
CUSTOMER COST
REDUCTION
BONUS ABUSE
REDUCTION
£125,000 £125,000 £125,000
COST
REDUCTION
EMAIL M/K
COST REDN
£10,000 £10,000 £10,000
COST
REDUCTION
REDUCTION
IN 3RD PARTY
ADDRESS
CLEANSE
£50,000 £50,000 £50,000
SALES RISK
AVOIDANCE
AUTOMATED
REGULATORY
REPORTS
£20,000 £20,000 £20,000
REVENUE
INCREASE
CROSS-
SELLING OPPS
50,000 50,000 50,000
TOTAL £255,000 £255,000 £255,000

17. Example – hotel chain
enterprise DQ summary case
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 STRATEGIC GOAL 1 - Increase revenues by 20%
 Our data will not identify our most profitable customers so limits
targeted marketing opportunities
 Poor DQ has caused us brand damage so will discourage new bookings
 Parking revenues are not been accurately recorded so losing revenues >
$2.5 million pa
 STRATEGIC GOAL 2 - Cut operating costs by 15%
 Returned mailings & duplicates due to poor DQ in marketing systems
cost us $420k pa (197,000 direct mailings returned in 2012)
 Emergency supply orders to hotels cost $21.7m pa (20% above
standard orders), costing group $3.6m pa. Caused by poor ordering /
inventory data management
 STRATEGIC GOAL 3 - Introduce customer loyalty scheme
 Our current customer data contains duplicates, inaccuracies & missing
data, e.g. 37% of customer records have no zip code
 Impact is that launch of scheme will be 31% more expensive if no action
taken to improve the data

18. Step 4 – Identify Stakeholders
 Develop a stakeholder map
 Use this to:
 Identify a potential senior executive champion
 Identify other key stakeholders to be involved
 Start to gain cross-organizational support
 Engage stakeholders who represent all affected
areas – both managers and front line people
 Tap into existing organisations and structures in
the business and try to use them, e.g. process
improvement forums, programme boards etc.

19. Step 5 - Draft the Case
 Ensure you comply with your company
standards for business cases / case studies
 Where possible obtain copies of other
successful cases and emulate their style
 Use business language and avoid technical
jargon
 If DQ improvements have already been made
instead produce internal case studies and
disseminate
 Use your stakeholders to review the draft
business case / case study

20. Step 6 – Socialise the Case
 Data quality improvement is a collaborative
process so socialisation of data quality business
cases is critical
 The best cases for Data Quality improvement are
usually better driven “bottom up”
 Secure support from those who will implement
improvements BEFORE approaching senior managers
and seeking their support
 Use these supporters to help socialise and sell the case
and break down potential barriers and blockers

21. Step 7 – Finalise and present
the case / case study
“If you cannot SELL your business case in seven PowerPoint
slides and in under 20 minutes or less you don’t have a case”
(CEO of Global Manufacturing Company)
 Ensure that final cases are:
 Short, simple, visual and impactful
 Capable of delivery across the organization
 Focused on business benefits and not technical features
 Before presenting:
 Practise and memorise your key points
 Think about potential objections
 When presenting:
 Show personal passion, confidence & commitment
 If you don’t believe in it, they won’t!

22. The barriers to improving DQ…
MAKING
THE INITIAL
CASE FOR
INVESTMENT
OVERCOMING
INDIFFERENCE
& IGNORANCE
DEMONSTRATING
CONTINUED
BENEFITS
WHY DQ
VERSUS…?

23. Making the initial case –
further tips
23
Include
Market
/ Competitor
perspective
Get expert
help
Include
‘Do nothing’
option
Seek
Incremental
funding

24. Proving continued value –
further tips
24
(Re) engage
with business
beneficiaries
Spread the
good news…
past, present
& future
Identify
further
DQ issues
Use their
words,
not yours

25. Overcoming indifference
- further tips
25
Do
stakeholder
analysis
Develop
2 / 10 / 30
minute
pitches
Educate
& re-
educate
See the
world as
they see it

26. Prioritising DQ over other cases
- further tips
26
Be patient
Seek
quick
wins
Keep it
simple
Must show
RoI and / or
unacceptable
risk

27. 27
Proving your worth – keeping it simple
“You have to work
hard to get your
thinking clean to
make it simple. But
it's worth it in the
end because once
you get there, you
can move
mountains.” Steve Jobs
1955 - 2011

28. Questions
Proving your worth
Making the business case for data quality
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