Transcript The Integrated Business Statistics Program at Statistics Canada Marie Brodeur SNA seminar in the Caribbean St.

The Integrated Business
Statistics Program at
Statistics Canada
Marie Brodeur
SNA seminar in the Caribbean
St. Lucia: February 2014
Statistics Canada • Statistique Canada
Corporate Business Architecture
 Three objectives:
• Efficiency: A harvestable efficiency on ongoing
operating costs of 5% within 5 years;
• Robustness: A reduced, unduplicated set of robust
systems and processes that are properly maintained
and documented; and
• Responsiveness: Improved responsiveness in
delivery of new statistical programs
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Key Architectural Principles
 Corporately optimized decision-making:
• Governance to define and apply
 Centralization of informatics, statistical
processing, methodology support and frame
infrastructure is the corporate default
• IT resources under one management
• Centralized management of software and hardware
infrastructure
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Key Architectural Principles 2
 Mandatory use of generic corporate services
(collection, operational support, dissemination, etc.)
 Creation of new generic corporate services where
appropriate
 Maximize re-use:
• Smallest possible number of business processes
• Smallest possible number of enabling computer
systems
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Key Architectural Principles 3
 Maximize deployment of electronic data reporting
solutions
 Minimize tool kits
 Eliminate re-work
• Meta-data driven
 Manage statistical information
• Common Information Management policy
framework
• Data service centres
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IBSP Project Background
 Why IBSP?
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Aging infrastructure
Lack of Flexibility
StatCan faced financial pressures
Respondent burden
Higher than historical turnover in personnel
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Project Background 2
• Re-think the way in which we produce business
statistics
• Adopt an approach that ensures coherence from start
to finish and across the different programs that
produce business statistics
• The IBSP is an important transformational project:
 Examined from a conceptual point how we want to
function
 Operationalize the conceptual approach
 Develop infrastructure
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Objective of Project
 Develop generic model for producing business
statistics
• Improve quality, in particular the coherence aspect,
across the different programs
• Robust infrastructure
• Less expensive to maintain
• Flexible to respond to client needs
• Reduce respondent burden
 Return efficiencies to the corporation
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IBSP Pillars
 Based on the Generic Statistical Business Process
Model (GSBPM)
 Use of a common frame (BR)
 Use of tax data universe for the estimation of financial
information
 Use Electronic Data Reporting as the principal mode of
collection
 Use of common processing methodology and metadata
driven process
 Establish an earlier cut-off to improve timeliness
 Establish a Data Service Center for warehousing
statistical information
 Increase governance across all areas involved in
statistical data output
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The Generic Statistical Business Process Model
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To successfully achieve integration across
many programs and processes requires:
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Continuous support from Senior leaders
Very strong governance over life of project
Extensive collaboration across the organization
Ability to negotiate and adapt: generic solutions have
limitations
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Scope of Project
 Suite of approximately 150 existing business
surveys covering manufacturing, services, retail,
agriculture, capital expenditure, energy and
R&D ; ad-hoc surveys as well
 Covers all survey activities from frame to
dissemination
• Financial and activity based
• Establishment and enterprise
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System of
National
Accounts
Subject Matter
Areas
IBSP
Methodology
CANSIM
Enterprise Architecture Integration Platform (EAIP)
Tax
Business Register
GenSys
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Collection
Horizontal Integration
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Vertical Integration
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How to Achieve Integration - tools
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Generic processors for:
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Sampling
Edit and imputation
Estimation
Moving towards one collection platform
Common analytical tools
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Used by subject matter analysts and the System of
National Accounts analysts;
Simplifies staff mobility
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How to Achieve Integration Content – Concepts and Output
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Harmonized common content across business
surveys – it is now an enforced standard
Harmonized questions to extent possible
One mapping between tax information and
survey concepts with the Chart of Accounts
Reduced content by 20%
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Coherence Across Different
Programs
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Why coherence?
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Output from different programs integrated into the
System of National Accounts
Output from different programs compared by users
Eliminates potential overlap in coverage and helps
identify coverage gaps
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Project Management

To successfully achieve integration across
many programs and processes requires:



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Continuous support from Senior leaders
Very strong governance over life of project
Extensive collaboration across the organization
Ability to negotiate and adapt: generic solutions have
limitations
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Methodology
 Use of the Business Register
• Establishment and entreprise based
 Two-phase sampling for commodity and activity
based surveys
 For the rest Stratified Ramdom sample
• Allocation industry by geography
• Take-all strata for complex enterprises
• Take-some strata for simple establishments
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Methodology
 Focus on commodities and
activities through two-phase
strategy
• Collect key information to
Update the Business Register
And select a targeted sample
• Applicable mainly to activity and
commodity surveys
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Large
Sample
Gather information on
activity/commodity and
select target sample
Send full
questionnaire to
sub-set
Use of Tax Data and Sampling
 Population divided into two components:
• The very complex
 Census of these enterprises
 Financial and characteristics information collected
 The rest
• Tax data will be used for the financial information
• Collect characteristics information
• The large enterprises with a simple structure
• Pilot project to use tax data
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Metadata
 The backbone of all survey processes
 Developed semantic model which illustrates and
documents all survey concepts and their
properties and relationships with other concepts
within a domain of knowledge
 Developed standard nomenclature and
numbering system for survey variables, cells,
code sets
• Will be re-used for all surveys to be integrated into
IBSP
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Collection
 Develop electronic questionnaire
 Modular Approach
 Implement common editing strategy
• Active collection management
• Resolve as much as possible failed edits through
automated editing and imputation to reduce follow-up
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Collection
 Collection primarily via EDR
• Modular Approach
• Built in edits
• Spreadsheets sent via e-file channel for some large
enterprises
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Reduce the collection window
Still keep paper collection for small businesses
Around ??? Units collected
4 million $ Collection budget
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Data Processing
 Implementation of common editing strategy
 Resolve as much as possible failed edits through
automated editing and imputation to reduce follow-up
 Systems
• Common systems platform
• Improve generalized systems
• Re-use some existing systems
 Create Data Service Center
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Streamline the Survey Process –
The Rolling Estimates
 Current processing model for annual business
surveys
Sampling
Collection
Processing
Analysis
Dissemination
• Several occurrences of manual interventions through
the processes
• Estimates and quality indicators are only produced near
the end
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Streamline the Survey Process –
The Rolling Estimates 2
 Proposed processing system - iterative
• Collection, processing and analysis done in parallel
• Quality indicators used to dynamically manage collection
• Basic principle: no manual intervention inside an iteration
Collection
Dissemination
Sampling
Processing
Analysis
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Data Service Center
IBSP or
Dissemination
IBSP
IBSP or BSS-CR
CAPTURED DATA
MICRO DATA
MACRO DATA
DISSEMINATION
DATA
Processes
Processes
Processes
Processes
Quality Assurance
Macro Corrections
Data Analysis
Confidentiality
Transformations
CANSIM Load
- Quality Assurance
- Data Analysis
- Publication
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Capture Edits
Coding
Quality Assurance
Progress Reports
Transformations
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Quality Assurance
Micro Corrections
E&I
Allocation
Estimation
Aggregation
Cube Creation
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EDR
CLIENT
CUSTOMER
RESPONDENT
Paradata Repository (Data about Processes)
Metadata Repository (Data about Data)
Other Repository (BR, Tax, SNA, …)
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Conclusion
 5 year developmental project
 Generate 2.5 millions of efficencies
 Better coherence among survey programs,
SNA and administrative
 Currently in the field for collection
 Project will continue for several years
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