1. ESS Vision 2020 LDF and HRM Working Group

2. Why does the ESS need a strategic debate on its future today?
"Information and knowledge are fundamental building blocks for all modern societies"
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"Official statistics offer an information infrastructure and a public good that responds to the needs of many categories of users - citizens, decision makers, researchers and journalists"
"Official statistics have always strived to adapt to major developments in society and the economy"

3. Four main drivers Data revolution New metrics Price of statistics
Future of Europe
Digital transformation
Globalisation
Quality vs. resources
Enhanced economic governance
New data sources
Complex reality
Reduced budgets
Evidence based policy making
Competition among data providers
Geo-details
Cutting
the red tape
Objectives, thresholds, quality requirements

4. A further important step in the development of European statistics
COM (2009)404 Vision
COM
(2009)433
GDP and beyond
(2011)211 Robust quality
ESSC Nov.2012 ESS.VIP Programme
Reg.
99/2013 ESP
ESS Vision 2020
"The ESS provide the EU, the world and the public with independent high quality information on the economy and society on European, national and regional levels and make the information available to everyone for decision-making purposes, research and debate."
Reg. 223/2009
ESS

5. Five priority areas Users Quality New data sources Production process
better understand and address user needs
be a global partner and leader for innovation
build strategic alliances with public and private partners
Users
abide with the European Statistics Code of Practice
apply fit-for-purpose tools to enhance quality assurance
assess the usability and quality of source data
Quality
exploit potential of new data sources
invest in new IT tools and methodology
continue to improve existing data collection methods
New data sources
adopt a new dissemination and communication strategy
create a data pool of European statistics
optimise ESS portfolio of products and services
promote European statistics as a brand
Dissemination
further intensify the collaborative partnership of the ESS
further identify and implement standards for statistical production
adopt enterprise architecture as a common reference framework
advance in sharing IT services and infrastructure
benefit from exchange of (micro)data, while fully respecting statistical confidentiality
Production process

6. Guiding principles in the implementation of ESS Vision 2020
Acknowledge diversity
Respect the key EU principles of subsidiarity and proportionality
Ensure satisfaction of European, national and regional needs simultaneously
Avoid duplication of work where possible
Abide with the European Statistics Code of Practice and the UN Fundamental Principles of Official Statistics
Adhere to the general quality management principles
Optimise value for money and burden on respondents

7. ESSC agreement – 15 May 2014 The ESSC:
Came to an agreement on the ESS Vision 2020 as the guiding frame for the ESS development during the years up to 2020
Endorsed the PG Chair's proposal for working arrangements and a roadmap leading up to the 2014 September DGINS meeting in Riga
Agreed to align the ESS.VIP Programme with the ESS Vision 2020
Welcomed the roadmap for the extension of the European Statistical Programme for the period on the basis of the ESS Vision 2020

8. An inclusive approach
GEMS – Generic Enterprise Model for Statistics
Users
Quality
Production Processes
New data sources
Portfolio
Enterprise Architecture principles
Dissemination
Portfolio of activities to implement the ESS Vision 2020 in the 5 key areas

9. Strategic aims USERS QUALITY NEW DATA SOURCES STATISTICAL PROCESSES
agile and responsive attitude to users’ needs
response to user groups
partner and a leader for innovation
strategic alliances public and private
CoP and ESS Quality Assurance Framework
quality assurance tools fit for purpose
usability and quality of source data
sound methodology and effective quality assurance mechanism
improving existing data collection methods
exploiting the potential on new data sources
establishing alliances and partnership with data owners
new IT tools and methodological development
organisational changes
partnership of the ESS
enterprise architecture
standards
common methods and tools
sharing IT services and infrastructures
(micro) data exchange and statistical confidentiality
experts working together
dissemination and communication strategy
pool of European statistics
portfolio of dissemination products and services
European statistics brand
USERS
QUALITY
NEW DATA SOURCES
STATISTICAL PROCESSES
DISSEMINATION

10. Objectives USERS QUALITY NEW DATA SOURCES STATISTICAL PROCESSES
data requirements
customise end-user products
data warehouses
target users and products
active role of users in planning European statistics production
use of existing databases and multiple data sources
quality assurance tools for indicators for direct policy use
assessment of usability and quality of new data sources
of user- oriented quality assurance mechanisms
exploitation of both administrative and innovative sources
associated challenges (relations with providers, legal and financial issues, etc.)
investment in methodology and IT infrastructure
reference ESS Enterprise Architecture model
statistical process harmonisation
sharing of data and services in a few high level use cases
EU data pool to different users segments
data services that allow navigation, reuse and visualisation
data warehouse architecture
single Entry Point for European statistics (open data portal)
tailored products and services
USERS
QUALITY
NEW DATA SOURCES
STATISTICAL PROCESSES
DISSEMINATION

11. ESS Vision 2020 implementation
through:
Projects
Programs
Other actions
…to achieving Vision goals

12. ESS Vision 2020 implementation

13. Portfolio prioritisation
Criteria drawn from the High Level PG Task Force
complemented by others that are normal good practice in project, programme and portfolio management
Attractiveness
Strategic fit; architectural fit; perceived benefits; product enhancement potential
Achievability
Degree of challenge; capability to deliver
Affordability
Whole life cost of the project

14. Portfolio attractiveness

15. The initial portfolio minibus
ESS Vision 2020
FRAMEWORKS
SIMSTAT
BIGD
ADMIN
REDESIGN
ESSC
DIGICOM
ESDEN
VALIDATION
UA/IPROD
SERV
ESBRs
Our journey to the modernisation of the ESS!

16. Frameworks in ESS Vision 2020
Legal framework
Financing mechanisms

17. Modernisation of the ESS
ESS Vision 2020
FRIBS
Social Statistics
Agricultural Statistics
FRAMEWORKS
ESSC
Modernisation
Programmes

18. The ESS Vision 2020 portfolio:
…is an initial portfolio that will be tailored on a continuous basis as new developments arise;
…covers all five key areas of the Vision;
…focuses on cross-sectional and infrastructure issues that will create foundations for modernisation in different statistical domains.

19. Governance – how it works
Portfolio Management Bureau (PMB)

20. From adoption to the implementation of the ESS Vision 2020
From now on…
February 2015
May 2014

21. People and skills in the Vision
Training and learning together
European Statisticians Training Programme
Cooperation with Universities (e.g. EMOS)
Promote mobility of staff
Know-how to ensure sustainability of project results
generated know-how will be used in giving consultancy, providing training courses and producing pedagogical material

22. ESS Vision 2020 challenges for HRM and LDF
New operational way of working
Synergies, matrix organisation, …
Project, programme and portfolio managers
New profiles
enterprise architects, business process analysts and quality managers
New skills
E.g. experts in big data, visualisation tools, …
Multidisciplinary and multinational teams
Collaborative projects
Centres of excellence
Multidisciplinary teams – e.g. IT, methodology and thematic area experts

23. Thank you for your attention!