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Activity Number: 419 - Contributed Poster Presentations: Government Statistics Section
Type: Contributed
Date/Time: Tuesday, July 30, 2019 : 2:00 PM to 3:50 PM
Sponsor: Government Statistics Section
Abstract #308005
Title: Data Analytics for Better Statistics
Author(s): Jeremy Heng*
Companies: Ministry of Manpower

Modern technology has revolutionized the way official statistics is produced and consumed. With large amounts of data available, Singapore’s Ministry of Manpower seeks to tap on data analytics to improve the quality of statistics produced. Data analytics is used in three areas to aid in the statistical production process: (1) automated-classification system, (2) sentiment analysis and (3) predictive modelling.

An automated-classification system is developed to automate the conversion of raw occupation and industry data into standard occupation and industry codes. It ensures consistency among interviewers and respondents who may have their own understanding of occupation and industry definitions. A speech-to-text analytics tool facilitates sentiment analysis to provide insights into the behaviour of interviewers and respondents by analysing telephone conversations. Lastly, a fieldwork predictive model is used to predict the optimal dates and times to conduct survey interviews with various demographics of respondents, thereby reducing the likelihood of non-response cases.

Through these initiatives, the Ministry is able to improve operational efficiency and data quality.

Authors who are presenting talks have a * after their name.

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