Integrated Business Integrated Business

Statistics Program (IBSP)Statistics Program (IBSP)

IntroductionIntroduction

Daniela RavindraDirector, 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

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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

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Drivers For Change

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

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

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High Level Objectives

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

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High Level Objectives (continued)

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

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PH

AS

E 1

Program Fiscal Year to Start Integration

58 Existing UES surveys 2013

CAPEX surveys (actual, preliminary and intentions) – 2 survey periods

2013

PH

AS

E 2

22 Energy surveys (13 annual, 2 quarterly and 7 monthly)

2014

3 Transportation surveys (Annual and quarterly Trucking Financial and Passenger Bus)

2014

RDCI (Research & Development in Canadian Industries)

2014

PH

AS

E 3

30 Agriculture surveys 2015

1 IOFD program (Enterprise Financial Statistics made up of 3 surveys - Quarterly Survey of Financial Statements, Annual Financial and Taxation Statistics and Survey of Suppliers of Business Financing)

2015

Integrating New Surveys - Schedule

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

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Frame

Hook all surveys to the Business Register

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Business Register Integration

Program Year of Integration

CAPEX 2011-2012

Energy 2010-2011

Transport 2010-2011

Farm Register 2012-2013

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 characteristicsStatistique Canada • Statistics Canada11

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

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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

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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

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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

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