This document discusses data protection challenges in a big data world. It provides examples showing that personal data can be used to accurately identify individuals and deduce sensitive personal details. 72 countries now have data privacy laws aligned with EU standards. Privacy concerns led to a $100 million project by inBloom being shut down. If Google breaches forthcoming EU privacy regulations, it could cost $0.85 billion. The document advocates developing a deep understanding of customer experiences and valuing privacy to build trust and meet privacy obligations. It links data protection, information governance and information quality as important capabilities.

1. DATA PROTECTION IN A
BIG DATA WORLD
Understanding privacy as a quality
characteristic of information, and how to
deliver it as a value proposition

2. Some Numbers
80%
Users can be identified by when
and how movies are rated.
(Narayaan & Shmatikov, 2008)

3. Some Numbers
Analysis of anonymous Facebook Likes…
Discriminated between homosexual and heterosexual men
88%
Distinguished between African Americans and Caucasian
Americans
95%
85%
Identified Republican vs Democrat
All categories of “Sensitive Personal Data” under EU law and Privacy
laws of other regions…
(Research by Cambridge University & Microsoft)
http://dx.doi.org/10.1073/pnas.1218772110

4. Some Numbers
72
http://dlapiperdataprotection.com/#handbook/world-map-section
Number of countries currently with a general Data Privacy/Data Protection
law mapped to EU or OECD standards
Note: EU Data Protection Regulation will require non EU organisations processing
data about EU Citizens to comply with EU rules.

5. Some Numbers
$100 million
The amount of seed funding given by Bill & Melinda
Gates Foundation to inBloom, which is shutting down
over privacy concerns
http://bits.blogs.nytimes.com/2014/04/21/inbloom-
student-data-repository-to-close

6. Some Numbers
$0.85 Billion
Potential cost to Google of a single breach of forthcoming
EU Data Protection Regulation (5% of Global turnover)

7. Three ways organisations innovate
Internally Driven
This is what we do and
we’re great!
We can do this and it will be
AWESOME!
Focus on finding/countering
objections to product
Customer Compelled
Ask the customer what will
make them happy
Ask what features they want
and what price they’ll pay
Exploring Experiences
Develop deep understanding
of what they do (or can’t) and
why
Creatively infer what
experiences/outcomes would
be most valuable
“OK, we’ll tweak it a bit”
“If we build it they will come” Consistently meeting expectations

8. A Value Delivery System Strategy
..We have a crack team of Big
Data analysts looking at it right
now..

9. Privacy as a Key Resulting Experience
The “Surprised Customer” Test

10. A Value Delivery System Strategy
Choose a Value
Proposition
Provide it Communicate it
Analyse the
market
Pick Key
Resulting
Outcomes
(a complete Value
Proposition)
For each Resulting Outcome how will we,
with others, cause customers to:
Actually experience it
Understand it & why
to believe it
Capabilities that will therefore be needed
Total Revenue and Cost  Profit, Business Case
Indirect Impacts (Other businesses, departments, project
timeframes etc.)
Privacy versus what?
How will privacy be
ensured in the
processing?
Data Governance,
information quality, data
masking, training,
“human factors”, infosec
Communication,
transparency, user
education, demonstrating
value
Business case for
organisation: cost and risk
of getting it wrong (brand
damage/penalties)

11. Linking DP, IQ, and IG
Data
Protection
Information
Governance
Information
Quality

12. A Value Delivery System Strategy
Choose a Value
Proposition
Provide it Communicate it
Analyse the
market
Pick Key
Resulting
Outcomes
(a complete Value
Proposition)
For each Resulting Outcome how will we,
with others, cause customers to:
Actually experience it
Understand it & why
to believe it
Capabilities that will therefore be needed
Total Revenue and Cost  Profit, Business Case
Indirect Impacts (Other businesses, departments, project
timeframes etc.)