modernising official statistics

United Nations Economic Commission for EuropeStatistical DivisionUnited Nations Economic Commission for EuropeStatistical Division

Introduction to the Initiative

Steven ValeUNECE

steven.vale@unece.org

Introducing UNECE Statistics

UNECE Statistics: Priorities

Population censuses, migration, gender Globalisation, National Accounts,

employment, business registers Sustainable development,

environmental accounts, climate change

Modernisation

Introducing the HLG-MOS

High-level Group for the Modernisation of Official StatisticsCreated by the CES Bureau in 2010Strategic vision endorsed by CES in 2011/2012Annual projects in priority areasActivities are voluntary and demand driven

Who are the HLG-MOS members?

Ireland - Chair Australia Canada Italy Netherlands New Zealand Republic of Korea Slovenia

Eurostat OECD UNECE

Why is the HLG-MOS needed?

Before the HLG-MOS Now

Many expert groups Clear vision

Little coordination Agreed priorities

No overall strategy Strategic leadership

Limited impact Real progress

• Launched in 2016• Open to all statistical organisations

who endorse “Statement of Intent”• No fee, but expectation to contribute• Partners benefit from collaboration

and sharing• Four main principles:

− Openness− Flexibility− Participation− Pragmatism

Statistical Modernization Community

The Challenges

These challenges are too big for statistical organisations to

tackle on their own

We need to work together

Using common standards, statistics can be produced

more efficiently

No domain is special!

Do new methods and toolssupport this vision, or do they

reinforce a stove-pipe mentality?

HLG-MOS

Expert Groups

Projects

The story so far - 2011

The story so far - 2013

The story so far - 2015

CSPA

GSBPM

GAMSO

The GSBPM

What is the GSBPM?

Generic Statistical Business Process Model It shows the different steps needed to

produce official statistics It provides standard terminology to help

statistical organisations• Modernise statistical production processes• Share methods and components

Why do we need the GSBPM?

To define and describe statistical processes in a coherent way

To compare and benchmark processes within and between organisations

To make better decisions on production systems and organisation of resources

What will this mean for resources?

Applicability (1)

All activities undertaken by producers of official statistics which result in data outputs

All statistical domains National and international statistical

organisations

Applicability (2)

Development and maintenance of statistical registers

All types of data source:• Surveys / censuses• Administrative sources / register-based

statistics• Mixed sources• “Big Data”

Structure of the Model (1)Process

Phases

Sub-processes

(Descriptions)

Key features

Not a linear model Sub-processes are not followed in a strict

order It is a matrix, through which there are

many possible paths

The GSBPM is used by more than50 statistical organisations

worldwide

KSBPM – Republic of Korea

Beyond statistics: Data archivesGeneric Longitudinal Business Process Model

Uses of the GSBPM

Managing statistical programmes Cost / resource allocation Documenting statistical processes Framework for quality assessment Sharing statistical software

The GAMSO

What is the GAMSO?

Generic Activity Model for Statistical Organisations

It extends and complements the GSBPM by adding other activities needed to support statistical production

Background

In the GSBPM, activities not directly part of statistical production are referred to as over-arching processes, and are listed, but not elaborated in detail

There have been several calls to expand the GSBPM to better cover these activities. The GAMSO was developed to meet these needs

Who created the GAMSO? The business activity model developed by

the Statistical Network provides the basis for over 70% of the content of GAMSO.

The Modernisation Committee on Standards further developed GAMSO, taking account of comments from a public consultation

GAMSO v1.0 was approved by HLG in March 2015.

Level 1 of the GAMSO

Capabilities A capability is an ability that an organisation,

person, or system possesses

Methods People

Standards and

Frameworks

Processes Technology

Uses of GAMSO

Resource planning Measuring costs Assessing readiness to implement

different aspects of modernisation  Supporting risk management systems Implementing enterprise architecture Measuring and communicating the value

of statistical modernisation activities

Maintaining GSBPM & GAMSO

Owner = High-Level Group Maintenance is delegated to the

Modernisation Committee on Standards Discussion forums to gather feedback Importance of stability over time

• Reviews every 5 years• Revisions only if really needed

What is the GSIM? A reference framework of information

objects:• Definitions• Attributes• Relationships

It gives us standard terminology GSIM aligns with relevant standards such

as DDI and SDMX

GSIM and GSBPM

GSIM describes the information objects and flows within the statistical business process.

110 information objects!

Clickable GSIM

Other relevant standards

DDI SDMX

GSIMConceptual model

Implementationstandards

the Future of Statistical ProductionCSPA

What is the CSPA?

• A template architecture for official statistics

• A set of standard specifications for new statistical components(services) that can beused in a modular way

• A new way of developing statistical tools, with sharability as a design feature, not an afterthought

Problem statement:Specialised business processes, methods and IT systems for each survey / output

Applying Enterprise Architecture

Disseminate

... but if each statistical organisation works by themselves ...

... we get this ...

.. which makes it hard toshare and reuse!

… but if statistical organisations work together to define a common

statistical production architecture ...

... sharing is easier!

We all have to modernise our statistical production systems

The marginal cost of doing this in a way that supports collaboration and complies with CSPA is relatively low, but the potential savings from such a standard approach are high

Key Message

Get involved!Anyone is welcome to contribute!

More Information HLG-MOS Wiki: www1.unece.org/stat/platform/display/hlgbasLinkedIn group:“Modernising official statistics”