Integrated Statistical Systems: Data collection, Processing and - - PowerPoint PPT Presentation

Arab Conference Transformative Agenda for Official Statistics 5-7 April, Ankara Turkey

Integrated Statistical Systems: Data collection, Processing and Dissemination of Integrated Statistics

An Integrated Statistics Approach

Challenges

• Fast technological developments
• Sharp increase in rate of data availability
• Greater demand for more (& quicker)

information

• Decreasing budgets and improving cost

efficiency

• Demands to decrease response burden

Responds to challenges

• Through modernization programmes for

integrated statistics.

• Characterized by:

– technical and managerial specializations of staff – modernization of the IT-environment – harmonization/centralization of statistical production processes - GSBPM – repositioning the legal and regulatory environment of the statistical organizations.

• Business as usual will not be enough.

Traditional approach

Agriculture

Meta data and standards Registers and frames Surveys and admin sources Processing Analysis Dissemination IT processes etc.,

Industry Household Income and Expenditures Education Jobs

etc.

Environment Statistical Domains economic, environment and social statistics

New Approach

grated statistical production process and

Integrated statistics programme

Integrated business and international trade statistics programme (IBIS)

Economic dimensions Environment dimensions Social dimensions

Integrated household and social statistics programme (IHSP)

Economic dimensions Environment dimensions Social dimensions

Integrated Statistics Programme

• Meta data driven statistical production process
• Meta data catalogue of variables
• Survey repository
• Guidelines

– GSBPM based register based survey design – Multi source and multi mode collections – Micro data linking – Dissemination and visualisation

• Software (micro data cataloguing, disclosure

control

Integrated statistics approach

Institutional arrangements Institutional setting Management and internal policy Information, Communication Technology (ICT) Standards and methods

Statistical infrastructure

Data collection Data processing Data integration Registers and frames Surveys/Admin data Inputs Macroeconomic accounts Household and demographic statistics Economic & environmental statistics Outputs / Dissemination Statistical

• perations

Benefits of integrated systems

• Statistical business and information architecture governs common

statistical production process and centralized statistical services over time and across countries.

• Corporate, centralized services allow for statistical professionalization,

project management and coordination.

• Meet policy demands: covering business and household statistics, labor

statistics, short term statistics, national accounts and international statistics.

• Cost effectiveness.
• Improved quality: coordinated output; reduction of human factor;

improved reproducibility.

• Reduction of response burden on business and household respondents.
• Offer collaboration in the development and application of common

methods and IT tools.

• Robust and flexible and a stable platform for facing new developments.

Cost/Investments

• Expertise (subject-matter specialists,

projectmanagers, methodologists, IT specialists)

• Training (new) personnel in change/project

management and integration methods and process management

• IT-environment using standards-based

modules and dissemination platforms

• Reorganisations

General Organizational Principles

• 1. Use corporate business and information

architecture—blue print for process development

• 2. Adopt legal mandates based on fundamental

principles for official statistics

• 3. Mainstream standards and metadata
• 4. Optimize use of administrative data
• 5. Maximize multi-use of data

General Organizational Principles (2)

• 6. Top down editing and imputation
• 7. Develop modular IT applications across

statistical domains

• 8. Initiate methodological innovation and

modernization

• 9. Establish quality culture

10.Manage development and change

I. Project portfolio and portfolio management II. Planning and prioritisation

• III. Centralization and chain management

Phase 1 Common needs assessment Phase 2 Common design Phase 3 Common build Phase 4 Common collection Phase 5 Common processing Phase 6 Common analysis Phase 7 Common dissemination Phase 8 Common evaluation Input data Disseminated data Output data Macro and sector statistics Micro data

Total Cycle of Official Statistics Production (GSBPM)

Corporate services

• 2. Data

collection and processing

• 3. Dissemination
• 4. Methodology

and process development

• 6. Project

management

• 1. Population

and business registers and frames

• 5. IT-services

14

Economic Statistics

IT processes etc. Dissemina-tion Analysis Processing Surveys and Admin sources Registers and frames Meta-Data and Standards

Social Statistics

IT processes etc. Dissemina-tion Analysis Processing Surveys and Admin sources Registers and frames Meta-Data and Standards

Environm ent statistics

IT processes etc. Dissemina-tion Analysis Processing Surveys and Admin sources Registers and frames Meta-Data and Standards

Accounts and Indicators Methodology Data Processing (IT) Data Collection

Economic Statistics Social Statistics

Environment

Statistics

Statistical Infrastructure Standards and methods, SBR, Legislative mandates, etc.

Specialized corporate services

Integrated Statistics Architecture

NSI 1

Collec t Proce ss

Analys e Disse minat e

Survey A Survey B

Historically statistical organisations have produced specialised business processes and IT systems

The problem we are trying to solve

How does Architecture help?

• Many statistical organisations are modernising

and transforming using Enterprise Architecture

• Enterprise Architecture shows what the

business needs are and where the

• rganisation wants to be, then aligns efforts

accordingly

• It can help to remove silos and improve

collaboration across an organisation

NSI 1

Coll ect Pro ces s

Ana lyse

Survey A Survey B Survey C

Enterprise Architecture helps you get to this

Dissemin ate

…but if each statistical

• rganisation works by

themselves…..

Canada

Coll ect Proc ess

Anal yse Disse mina te

Sweden

…we get this….

Canada

Coll ect Proc ess

Anal yse Disse mina te

Sweden

? ?

This makes it hard to share and reuse!

…but if statistical

• rganisations work

together?

Colle ct Proc ess

Analy se Disse minat e

? ?

Sweden Canada

This makes it easier to share and reuse!