Census Processing Baku Training Module.  Discuss:  Processing Strategies  Processing operations  Quality Assurance for processing  Technology Issues.

Slides:



Advertisements
Similar presentations
Testing Relational Database
Advertisements

1 of 18 Information Dissemination New Digital Opportunities IMARK Investing in Information for Development Information Dissemination New Digital Opportunities.
Leverage MarkITS for agile solutions delivery that balances strategic thinking with tactical execution for “Business & Technology Convergence” MarkITS.
Software Quality Assurance Plan
Enhancing Data Quality of Distributive Trade Statistics Workshop for African countries on the Implementation of International Recommendations for Distributive.
Quality assurance -Population and Housing Census Alma Kondi, INSTAT, Albania.
Monitoring and Control
Infrastructure Projects Facility in the Western Balkans Part of the Western Balkans Investment Framework Facility funded by the European Union TA-ALB-10.
Pertemuan 16 Matakuliah: A0214/Audit Sistem Informasi Tahun: 2007.
Auditing A Risk-Based Approach To Conducting A Quality Audit
Introduction of Internet Survey Methodology to the Emirate of Abu Dhabi Andrew Ward, Maitha Al Junaibi and Dragica Sarich.
Design, Implementation and Maintenance
Improving the Quality of Tax Statistics: Recent Innovations in Editing and Imputation Techniques at the Statistics of Income Division of the U.S. Internal.
UNSD Regional Workshop on Census Data Processing for the English speaking African Countries: Contemporary technologies for data capture, methodology and.
Introduction to Computer Technology
Enterprise Architecture
Welcome ISO9001:2000 Foundation Workshop.
Project Human Resource Management
Today’s Lecture application controls audit methodology.
Copyright 2010, The World Bank Group. All Rights Reserved. Agricultural Coding and Data Processing Section B 1.
UNSD-ESCWA Regional Workshop on Census Data Processing in the ESCWA region: Contemporary technologies for data capture, methodology and practice of data.
Information Systems Security Computer System Life Cycle Security.
The Health Roundtable 4-4c_HRT1215-Session_CLARK_PCHosp_QLD TPCH: Using Data to Improve Performance – The Clinical Dashboard Presenter: Kevin Clark The.
Project Evaluation UNIT 2 Software Project Management.
Slide 1 D2.TCS.CL5.04. Subject Elements This unit comprises five Elements: 1.Define the need for tourism product research 2.Develop the research to be.
United Nations Economic Commission for Europe Statistical Division Field Operations Distribution and Return of Material Angela Me, Chief Social and Demographic.
Regional Workshop on the 2010 World Programme on Population and Housing Censuses: International standards, contemporary technologies for census mapping.
Certificate IV in Project Management Introduction to Project Management Course Number Qualification Code BSB41507.
[Hayes, Dassen, Schilder and Wallage, Principles of Auditing An Introduction to ISAs, edition 2.1] © Pearson Education Limited 2007 Slide 8.1 Control Risk,
Computerised Air Traffic Management Tools - Benefits and Limitations OMAR BASHIR (March 2005)
Service Transition & Planning Service Validation & Testing
Getting Started Conservation Coaches Network New Coach Training.
Data Capture Overview United Nations Statistics Division
Guest Cycle A division of the flow of business through a hotel that identifies the physical contacts and financial exchanges between guests and hotel employees.
AADAPT Workshop South Asia Goa, December 17-21, 2009 Maria Isabel Beltran 1.
Overall Quality Assurance, Selecting and managing external consultants and outsourcing Baku Training Module.
European Conference on Quality in Official Statistics Session 26: Quality Issues in Census « Rome, 10 July 2008 « Quality Assurance and Control Programme.
Uganda – October 2009 Census Data Collection & Processing John Gomersall.
Test and Review chapter State the differences between archive and back-up data. Answer: Archive data is a copy of data which is no longer in regular.
Census Quality: another dimension! Paper for Q2008 conference, Rome Louisa Blackwell Quality Assurance Manager, 2011 Census.
Use of Administrative Data Seminar on Developing a Programme on Integrated Statistics in support of the Implementation of the SNA for CARICOM countries.
Quality Assurance Programme of the Canadian Census of Population Expert Group Meeting on Population and Housing Censuses Geneva July 7-9, 2010.
Statistical Expertise for Sound Decision Making Quality Assurance for Census Data Processing Jean-Michel Durr 28/1/20111Fourth meeting of the TCG - Lubjana.
Lessons from Programme Evaluation in Romania First Annual Conference on Evaluation Bucharest 18 February 2008.
McGraw-Hill/Irwin © 2003 The McGraw-Hill Companies, Inc., All Rights Reserved. 6-1 Chapter 6 CHAPTER 6 INTERNAL CONTROL IN A FINANCIAL STATEMENT AUDIT.
United Nations Oslo City Group on Energy Statistics OG7, Helsinki, Finland October 2012 ESCM Chapter 8: Data Quality and Meta Data 1.
The Implementation of BPR Pertemuan 9 Matakuliah: M0734-Business Process Reenginering Tahun: 2010.
Project management Topic 8 Quality Review. Overview of processes Prepare for Quality Review Questions list Meeting Agenda Review Meeting Sign-off Product.
E-MARKING Isabel Millar e-marking at SQA Benefits of e-marking What you can do to assist Q & A Aims.
Oman College of Management and Technology Course – MM Topic 7 Production and Distribution of Multimedia Titles CS/MIS Department.
Regional Workshop on the 2010 World Programme on Population and Housing Censuses: International standards, contemporary technologies for census mapping.
UNSD-ESCWA Regional Workshop on Census Data Processing in the ESCWA region: Contemporary technologies for data capture, methodology and practice of data.
An Overview of Editing and Imputation Methods for the next Italian Censuses Gianpiero Bianchi, Antonia Manzari, Alessandra Reale UNECE-Eurostat Meeting.
Exercising, Maintaining and Reviewing BCM Arrangements ERMAN TASKIN
Session 6: Data Flow, Data Management, and Data Quality.
ISO 9001:2015 Subject: Quality Management System Clause 8 - Operation
A Training Course for the Analysis and Reporting of Data from Education Management Information Systems (EMIS)
Welcome. Contents: 1.Organization’s Policies & Procedure 2.Internal Controls 3.Manager’s Financial Role 4.Procurement Process 5.Monthly Financial Report.
LRC Network Planning for Records Management improvement Kathryn Dan, GM University Records and Policy.
MANAGEMENT INFORMATION SYSTEM
National Population Commission (NPopC)
Software Project Configuration Management
Managing the Project Lifecycle
Survey phases, survey errors and quality control system
Egypt’s Population, Housing & Establishments e-Census, 2017
Survey phases, survey errors and quality control system
Quality Assurance in Population and Housing Censuses
AUDIT TESTS.
Internal Control Internal control is the process designed and affected by owners, management, and other personnel. It is implemented to address business.
Presentation transcript:

Census Processing Baku Training Module

 Discuss:  Processing Strategies  Processing operations  Quality Assurance for processing  Technology Issues for processing  Questions Overview

 Strategic directions need to be established early in the census cycle.  Single most important decision is deciding upon the processing system to be used and the technologies that will be adopted.  These decision needs to be made early enough to enable sufficient time for testing and implementation. Census Processing

Data Processing Cycle

 Receipt and Registration  as enumeration area materials arrive, they are checked for completeness and "marked in"  close coordination with Field processes  Preliminary Checking  forms are groomed for later processes, e.g. transcribed if not suitable for later processes  Coding and Data Capture  information is captured off the forms and converted into the classification

Data Processing Cycle  Balancing  computer records are checked against the forms to ensure a record has been created for each person and dwelling enumerated  Validation  checks the data to ensure it meets minimum agreed standards  Quality Assurance and Editing  Editing used to make responses consistent with the form/sequence rules/classifications  Imputation used to correct non-response

Controlling the workflow  monitoring and controlling work flows needs close attention  Each activity depends on the quality and quantity of the output from previous activities.  Critical that each activity is meeting production targets to ensure that the following activity has sufficient work.  Delays in one activity can lead to costly lost production in the following activities.  Changes in procedures to raise production will have to be carefully considered to ensure that the quality of the data is not adversely affected.

Management Information Systems  An essential tool for managers at a processing centre is a Management Information System  The general requirements of a MIS are as follows :  to allow access to information to all managers  to ensure all information is timely and as detailed as possible  to forecast and report on outcomes for future activity within the processing centre  ensure information acquired in one Census, can be utilized for planning in future Censuses

 What to collect :  production rates  flow control  staffing  quality assurance  automatic edits  What to report :  production  automatic edits  quality assurance  feedback to individuals Management Information Systems

Quality Assurance  Quality of Census data is defined as multi-dimensional, involving elements of :  data accuracy  budget  timeliness  relevance

Quality Assurance  Quality Management Framework  Processing of census data is complex - each process relies on the quality of the preceding process.  To assist in obtaining the highest possible data quality a framework incorporating the following components can be established at a processing centre:  quality management system;  quality assurance points for each process;  continuous quality improvement processes;  validation of data.

Continuous Quality Improvement  Continuous Quality Improvement (CQI) is a core component of the Total Quality Management philosophy.  CQI aims to continue to improve the quality of the output of a project throughout the life of that project.  A continuous quality improvement approach can be implemented in the following ways :  using teams of processing staff to identify and resolve quality problems;  using quantitative measures of quality, based on discrepancies in the output of the process; and  giving priority to identifying and addressing the root causes of these discrepancies

Measuring quality Identify root cause Identify most important quality problem Measure Quality Implement corrective action  Quality Assurance Circle (or Continuous Quality Improvement)

Validation  The purpose of validating census data is to identify system problems and ensure data quality for final output.  Final check to ensure that the data produced by the processing system meets the specifications of the editing program and output requirements.  Validating the data before it leaves the processing centre ensures that errors that are significant and considered important can be corrected in the final file  Validating as you process ensures the issues found can be fed into improving the process as you go.

 The successful introduction of technology into the processing phase will have a large impact on the overall success of the census.  The nature of census processing (ie the capture and manipulation of large amounts of data) is ideally suited to computerised technology.  Use of technology like imaging and Intelligent Character Recognition (ICR) offers great potential and associated benefits for census processing.  BUT be aware of the lead times and technology infrastructure required for successful implementation of ICR. Technology Issues

 Data- capture methods  key entry  optical mark recognition  digital imaging/intelligent character recognition  electronic lodgment of forms (eg; Internet)  Coding  clerical/computer assisted  automatic coding Technology Options

Technology Issues  Data Management - issues to consider  networks and infrastructure  data storage  data backups  data security

Questions?

Working Group Exercise  Working in groups, answer the following:  What issues can reduce the quality of the information processed?  What can be put in place to reduce the impact of these issues?