streamlining the data compilation and dissemination at ilo department of statistics lessons learned...

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ILO Department of Statistics Edgardo Greising [email protected]

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In May 2012, during MSIS 2012 meeting in Washington, DC, I made a presentation about the rationale behind the streamlining processes we had started at the ILO Department of Statistics, and made a brief description of the project to redesign the department’s approach that included not only the development of new applications using updated and appropriate tools to achieve the required functionality, but also changes in the procedures for data compilation. The new process for data compilation and dissemination has been built based on four main ideas: - The broadening of the ways of interaction with the countries for data collection; - The full automation of computerized procedures, so as to enable Statistical Assistants to engage more efficiently in non-computerized activities; - The systematization of the consistency and correction procedure regardless of the way the data was received; and - The ability to know when and why (or why not) data from the countries is arriving, thus knowing how much information is to be included in a publication. The new ILOSTAT database compilation procedures aims to have a better response rate from the countries, to reduce the delay of the information received and to improve the overall quality of the data published. After one year, and with more than 80% of the project completed, we have some experiences and lessons learned in the process regarding the implementation of changes in the procedures, IT applications developed, development tools, the reality of data providers, etc., that we would like to share.

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Page 1: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

ILO Department of Statistics

Edgardo Greising

[email protected]

Page 2: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

◦ MSIS 2012

Page 3: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

◦ MSIS 2012

Page 4: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

Lessons LearnedChanging the procedures

Application development

Current status

Page 5: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

From Topic- to Country-centric approach

«Country specialists» assigned based on language and cultural affinity

Coverage increased compared to last 5 yearsEven with 72 indicators from 17 topics

Training needed, specially on new topics

CS requesting improvements in contacts management tool

Page 6: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

Towards timely and comparable dataTimeliness has to be improved. What

was wrong?New questionnaire, broader and bigger

New topics

New IT tools, some under development

Comparability improvedAdhering to suggested breakdowns

Coded notes

Data quality improved thanks to extensive consistency checking

Page 7: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

Towards timely and comparable dataFor next collection:Some indicators to be simplified

Some breakdowns to be simplified

New data channels available

Increase technical assistance to countries

Increase response rate

Page 8: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

“The size of the accomplishment can be measured by

the obstacles you have to overcome to reach your

goals” – Booker T. Washington

Conceptual design of new collection took too long and put high pressure on development

An agile iterative-incremental development model was adopted to provide “ready-to-work” basic versions of the tools

Early adoption of a new software platform in the ILO was the cause of several delays

Page 9: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

“Vamos más despacio, Sancho, que estoy apurado” –Don Quijote de la Mancha (Let’s go slower, Sancho, I’m in a hurry).

Some modules of the initial project were deferred because:eQuestionnaire: We privileged backoffice editing

tools aiming to efficiency and data quality

SDMX and csv upload: Many developing countries lack a repository of indicators as to easily generate the files in the format requested.

Page 10: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

Knowing how it goes.

The Workflow Control Subsystem was misunderstood by the CS as a tool for controlling their work

After some time, they started to understand the usefulness of having real time information of contacts made and data status

Now they are providing feedback on improvements for the workflow dashboard reports

Task1

Page 11: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

To BI or not to BI?

Page 12: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

To BI or not to BI?ILOSTAT is based on Oracle technology platform (ILO

standard)

Dissemination based on WebCenter portal manager with OBI-EE for building the reports (Original idea)

Standard BI reports were not able to handle breakdown’s labels and footnotes properly

Star-schema datawarehouse did not provide any added value to the solution

Switched to ad-hoc reporting solution using ADF and a “flat” materialized view for dissemination

Valuable help from the official statistics community in sharing experiences

Page 13: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

All you need is data…

Fully metadata driven website

Every navigation menu is contextual and is built dynamically

Avoid duplication of efforts in editing web pages

Minimize errors due to missed updates

Page 14: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

Increased coverage

Improved timeliness

Improved quality

Reduced overburden

Standards based

Metadata driven

General purpose

Page 15: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

29

1749

71

137165

4271,657

7,71930,121

78,916364,524~5,000,000

Page 16: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

E-mail:[email protected]

Skype:egreising

Twitter: egreising

LinkedIn: http://www.linkedin.com/in/egreising

Page 17: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

E-mail:[email protected]

Skype:egreising

Twitter: egreising

LinkedIn: http://www.linkedin.com/in/egreising

Page 18: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

From Topic- to Country-centric approach

Page 19: STREAMLINING THE DATA COMPILATION AND DISSEMINATION AT ILO DEPARTMENT OF STATISTICS  LESSONS LEARNED AND CURRENT STATUS

Knowing how it goes.

E-mail

(country + user)

Qtable

(country + indic + survey)