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Integrated Business Statistics Program (IBSP) Introduction PowerPoint PPT Presentation


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Integrated Business Statistics Program (IBSP) Introduction. Daniela Ravindra Director, Enterprise Statistics Division November 9th, 2010. Overview. What is the IBSP? Drivers for change Building on an existing model Objectives of the initiative Project plan. What is the IBSP?.

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Integrated Business Statistics Program (IBSP) Introduction

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Integrated Business

Statistics Program (IBSP)

Introduction

Daniela Ravindra

Director, Enterprise Statistics Division

November 9th, 2010


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Overview

  • What is the IBSP?

  • Drivers for change

  • Building on an existing model

  • Objectives of the initiative

  • Project plan

Statistics Canada • Statistique Canada


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What is the IBSP?

  • General model for producing business data

    • Covers all aspects of survey

    • Modular approach

    • Accommodate most business surveys

    • Uses as much as possible already existing approaches and generalized systems

Statistics Canada • Statistique Canada


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IT infrastructure

rusted out systems

proliferation of systems

lack of robustness

Lack of responsiveness to clients’ needs

Many commonalities between business surveys

Maintain relevance/Corporate Business Architecture

Need to develop more efficient approaches

Drivers For Change

Statistics Canada • Statistique Canada


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Building On An Existing Model

  • Based on the existing UES model

  • Incorporate lessons learned

    • Need to streamline

    • Need to consolidate different processing models

    • Introduce and support stronger governance model

  • Incorporate new methodologies

  • Introduce more flexibility into the system to respond to changing clients’ needs

Statistics Canada • Statistique Canada


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Reduce development and maintenance costs

maximize the use of generalized systems for survey production

Develop a modular system

Simplify processes, reduce the learning curve and improve timeliness

establish a common editing strategy for automated and manual editing

High Level Objectives

Statistics Canada • Statistique Canada


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Modernization of processes

multi-modal collection with Electronic Data Collection as the principal mode of collection

Reduce response burden and realize efficiencies

maximize the use of tax data for the estimation

of financial information

active collection management

Integration

promote the full use of the Business Register as

the frame for all business surveys

High Level Objectives (continued)

Statistics Canada • Statistique Canada


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Integrating New Surveys - Schedule

Statistics Canada • Statistique Canada


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Challenges With Respect To Integration

  • Integrate both annual and sub-annual surveys

  • Some surveys have particularities: balancing systems

  • Scope creep

  • Standardize methods and processes across so many programs

Statistique Canada • Statistics Canada


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Frame

  • Hook all surveys to the Business Register

Statistique Canada • Statistics Canada


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Sampling

  • Objectives:

    • Target commodities and characteristics

    • Designed for both industry and activity based and surveys

  • Work to date:

    • Tested one and two phase sample approaches

    • Examined pro and cons of each approach

  • Challenges:

    • Operationalize the two-phase approach (need to test)

    • Minimize response burden

    • Determine sampling variables allowing for targeting commodities and/or characteristics

Statistique Canada • Statistics Canada


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Content

  • Objective:

    • standardize and harmonize content

    • produce a modular questionnaire

    • Maximize use of tax data

  • Work to date:

    • Reviewed all UES and CAPEX content

    • Tested all new CAPEX concepts

    • Produced draft questionnaires

  • Challenges:

    • Determine frequency of collection

    • Determine tax replacement

Statistique Canada • Statistics Canada


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Collection

  • Objective:

    • Use electronic questionnaire as primary mode of collection

    • Focus on collecting characteristics and commodities

    • Active collection management for a more efficient process

      • Use quality indicators to prioritize

  • Work to date:

    • Produced process model for active collection management

    • Plan for parallel run from June to September 2011

    • Evaluated existing questionnaire development tool

  • Challenges:

    • Harvest efficiencies while maintaining data quality

    • Manage collection workload

    • Keep process simple

Statistique Canada • Statistics Canada


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Post-Collection Processing

  • Objective:

    • Use of a common editing strategy

    • Integrate subject-matter and SNA needs

  • Work to date:

    • Proposal for new process flow

      • Implement an iterative rather than a linear process

    • Evaluated different existing tools

  • Challenges:

    • Keep edits to minimum required

    • Optimize manual editing

    • Design efficient process that allows for processing of large number of surveys

Statistique Canada • Statistics Canada


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Analysis

  • Objective:

    • Standardize analytical process

    • Integrate subject-matter and SNA needs

  • Work to date:

    • Conducted consultations and proposed approach

    • Evaluated different existing analytical tools

  • Challenges:

    • Meet vast array of requirements

    • Re-use existing tools

    • Deal with break in series

Statistique Canada • Statistics Canada


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