A presentation of my PhD dissertation's longitudinal case: The Basic Data Program

1. Thorhildur Jetzek
Analyst and Industrial PhD Fellow
KMD and CBS
A STRATEGY FOR THE FUTURE
OF PUBLIC SECTOR DATA
MANAGEMENT

2.  The challenge
 Desired future state
 The path from data to value:
OR
 Governing complexity and crossing boundaries
 Finding the balance – from tensions to synergies
2
OVERVIEW

3. 3
DENMARK AT A GLANCE 2014
Denmark
OECD
average
2012
2014
Life satisfaction

4. 4
SOCIETAL CHALLENGES
• Demographic development
• Fiscal constraints
• Low productivity growth
• More people in need of public
service
• Rising expectations regarding
levels of public service

5. 5
HOW CAN DANISH AUTHORITIES PROTECT THE
WELFARE STATE?
Growth, jobs and competitiveness
2020 Goals: Economic growth, 150.000 new private
sector jobs, sustainable public finances
Improving
framework
conditions for
businesses
Contribution to
growth towards
2020
EUR 2.7 billion
Increasing levels
of education and
employment
Contribution to
growth towards
2020
EUR 2.7 billion
Reforms of the
public sector and
sustainable public
finances
Contribution to
growth towards
2020
EUR 1.6 billion

6. 6
DIGIGAL SERVICES ARE THE WAY FORWARD
 People appreciate the flexibility and freedom provided by
digital services – but…
 …they do not appreciate service delivery silos
 Service needs are always changing  AGILITY is needed
 People want smarter services
 H2H instead of B2C or G2C

7. 7

8. “Forget the old debates about public/private and central/local
delivery. We must build the foundations of a shared economy
of public services, powered by a new digital civic infrastructure
of shared digital capabilities, shared digital platforms and
standard approaches to using and protecting data. In doing
so we save billions and deliver much better services.”
(GovernUp, 2015)
8
WHAT NEEDS TO BE DONE
We need to be able to bring basic data into
play with greater stability and capacity than
we can at the moment. This means finding
an efficient way to distribute data across
the public and private sectors using a
shared infrastructure.”
(Digitization Strategy 2011-2015).

9.  Services that are designed around the needs and behaviors of
citizens, rather than the needs and structures of government.
 Empowering citizens to be more independent and self reliant.
 Using funds efficiently to offer world class help to those who
really need it.
 A foundation for such a state is the ability to share
data and information across boundaries
9
A DESIRED FUTURE STATE FOCUSED ON:

10. Current situation in Denmark
10
Use of Basic Data is limited by multiple
distribution platforms, double registration and
shadow registers

11. • There is an increasing pressure on registers due to increasing
demand for data
• Today, problems with gaps and redundancy in the data sets used
across public administration, means that many keep their own
shadow registers of the information required to deliver the service
requested
• Differences in semantic understanding of core concepts make it
difficult to link data together
• Today, there is a great number of individual systems for
distributing basic data about individuals, businesses, addresses,
etc.
• Many distribution solutions are technically obsolete, and as a
consequence not capable of delivering the desired data as fast as
needed or in the necessary formats
11
DATA COLLECTION AND DISTRIBUTION IN PUBLIC SECTOR

12. 12
CURRENT SITUATION IN DENMARK

13. Future state – from silos to
platforms
13
Basic Data is distributed via single high-
performance platform and mashed up with other
sources of data to create citizen-centric servies
“Platforms” are components that provide
access and can be used by many services

14. • Master data management ensures uniformity, accuracy,
stewardship, semantic consistency and accountability of basic
data
• Each register can operate independently, focusing on their
professional tasks as shared data models prescribe how data
should be prepared and disseminated
• Each register is accountable for their own data but adhers to
common standards
• No need for continuous coordination or shadow registers as
shared conceptual foundations ensure transparency and
consistency and common understanding of core concepts
14
ROLE OF MASTER DATA MANAGEMENT

15.  An average of 550.000 queries pr. municipality pr. year can be
optimized
 An average of 55.000 errors or data reroutes can be alleviated
pr. municipality.
 This is supposed to lead to efficiency gains estimated as worth of
26,5 million DKK pr. year.
 Having all data hosted only in the original registry instead of
running shadow registers will save around 190.000 DKK pr.
Municipality pr year, or 18,6 million DKK total.
 Finally, estimated gains from more efficient processes are
estimated as 36 million DKK pr. year.
 This is a total of 81,6 million potential savings for the
municipalities.
Source: http://www.frederiksberg.dk/~/media/eDoc/2/2/9/2295002-2543404-1-pdf.ashx
15
EXAMPLE: ADDRESS DATA

16. 16
Public
Sector
Public
and
private
sector
FUTURE STATE
Master data
management
Distribution
Value-added
products
Corereg.Shadowreg.
• Master data management cover maintenance
and development of registers containing public
basic data and private core data
• There is an increasing pressure on registers due to
increasing demand for data
• Today, problems with gaps and redundancy in the
data sets used across public administration, means
that many keep their own shadow registers of the
information required to deliver the service
requested
Standardized value added services
based on multiple sources of data
A common distribution platform -
Datafordeleren
CompaniesPeople Real Estate
Adresses,
Roads etc.
Maps and
Geography
Sensor data
Social data
Proprietary
data
Buying property
Staying healthy
Avoiding traffic

17.  Danish commuters spent around 128.000
hours in their cars trapped in traffic in
2010, an increase of 33% from 2001.
 These lost hours can cost the Danish
economy 8,5 mia DKK pr. year
 Besides the monetary impact, the
increased levels of stress, the time taken
away from family and the resulting
pollution each stand as convincing
arguments on their own – traffic
congestion reduces sustainable value.
17
EXAMPLE TRAFFIC APPS

18. 18
So… is it really this simple?

19. No! But it is doable
Hvannadalshnjúkur

20. 20
 Challenge:
The need to keep people informed and coordinated and giving key players
a voice in how the program evolves, without suffocating in administrative
tasks and bureaucracy
 Solution: SoS governance
 Basic Data program has seven subprograms (sub-systems) and 38
individual projects
 Make sure all sub-systems share the same overall mission and goals
(regarding data sharing in this case)
 Allow autonomy but ensure high standardizations of deliverables and
removal of barriers that prohibit cooperation (for instance economic
barriers)
 Encourage communication and enforce interoperability
 Create multi-stakeholder collaboration forums and establish rules of
behavior
1. SOLVE GOVERNANCE CHALLENGES – REMOVE SILO
THINKING

21. 21
2. REMOVE BARRIERS TO USE THROUGH OPEN LIQUID
DATA
Open by default. All
kinds of data (excluding
person sensitive) are
open
Price of data should
not be a barrier to
use
Open licenses allow for
reuse for all possible
purposes
Data should be
easy to interact
with, discover and
access (platforms)
Data should be easy to
understand out of
context and published
in a conceptually
organized way so that
they can be used in a
variety of systems and
be linked to other data

22. 22
3. IMPROVE DATA QUALITY – REMOVE NEED FOR SHADOW
REGISTERS
Attribute Description
Accuracy
Accuracy means that data that are correct,
precise, and reliable and errors can be easily
identified (Wang and Strong, 1996).
Completeness
Completeness can be defined as the extent to
which the information contained in the data is of
sufficient breadth, depth and scope for the task
at hand (Wang and Strong, 1996).
Representational
consistency
Consistency means that data are continuously
presented in the same format, consistently
represented, consistently formatted and
compatible with previous data (Wang and
Strong, 1996).
Timeliness
The timeliness attribute reflects whether the
data are available when expected and needed.

23. 23
3. VIEW DATA AS A STRATEGIC RESOURCE – REMOVE
SPLIT BETWEEN POLICY, DELIVERY AND USE

24. Exploitation – focus on
using openness to drive
good governance
Exploration – focus on
using openness to drive
new ideas
EconomicfocusSocialfocus
∆ Transparency ∆ Collective impact
∆ Efficiency ∆ Innovation
24
4. CONVERT TENSIONS TO SYNERGIES – FOCUS ON
OVERALL GAINS
Tension/
synergy

25.  A national data infrastructure that allows flexible configuration
of individual modules and use of data across boundaries
 Platforms where public and private parties can collaboratively
turn data into information
 TO CONSIDER:
 Trust in sustainability and quality of data
 Trust in the legal framework (privacy, security, terms of use)
 Skills
 Technical infrastructure – connectivity
 How to protect autonomy and expertise while enforcing
interoperability – lowest common denominator or golden standard?
25
THE FUTURE?

26. 26
SHOWCASING THE POWER OF OPEN ACCESS,
CROWDSOURCING AND HIGH QUALITY DATA
OSM in Haiti before 2010 earthquake
OSM in Haiti 2 days after earthquake

27. 27
WHERE GOOD DATA MANAGEMENT CAN LEAD

28. 28
I would love to network on LinkedIn:
dk.linkedin.com/in/thorhildur
Twitter feed or current insights on all things data:
https://twitter.com/HildaJetzek