Transcript United Nations Economic Commission for Europe Statistical Division The Generic Statistical Business Process Model Steven Vale, UNECE METIS Workshop, Lisbon, 11-13 March 2009

United Nations Economic Commission for Europe
Statistical Division
The Generic Statistical
Business Process Model
Steven Vale, UNECE
METIS Workshop, Lisbon, 11-13 March 2009
Aim of Session 1
To finalize the model
Contents
•
•
•
•
•
Presentation of the model
Wider context
National implementations
Detailed discussions
Summary and conclusions
Steven Vale - UNECE Statistical Division
Slide 2
Background

Defining and mapping business
processes in statistical organisations
started at least 10 years ago
“Statistical value chain”
• “Survey life-cycle”
• “Statistical process cycle”
• “Business process model”
•
Steven Vale - UNECE Statistical Division
Slide 3
Background

Defining and mapping business
processes in statistical organisations
started at least 10 years ago
“Statistical value chain”
• “Survey life-cycle”
• “Statistical process cycle”
• “Business process model”
•
X
X
X
X
Generic Statistical Business
Process Model
Steven Vale - UNECE Statistical Division
Slide 4
Why do we need a model?





To define, describe and map statistical
processes in a coherent way
To standardize process terminology
To compare / benchmark processes within
and between organizations
To identify synergies between processes
To inform decisions on systems
architectures and organization of resources
Steven Vale - UNECE Statistical Division
Slide 5
History of the Current Model


Based on the business process model
developed by Statistics New Zealand
Added phases for:
•
Archive (inspired by Statistics Canada)
• Evaluate (Australia and others)



Three rounds of comments
Terminology and descriptions made
more generic
Wider applicability?
Steven Vale - UNECE Statistical Division
Slide 6
Applicability (1)



All activities undertaken by producers of
official statistics which result in data outputs
National and international statistical
organizations
Independent of data source, can be used for:
•
Surveys / censuses
• Administrative sources / register-based statistics
• Mixed sources
Steven Vale - UNECE Statistical Division
Slide 7
Applicability (2)



Producing statistics from raw data
(micro or macro-data)
Revision of existing data / re-calculation
of time-series
Development and maintenance of
statistical registers
Steven Vale - UNECE Statistical Division
Slide 8
Structure of the Model (1)
Process
Phases
Subprocesses
(Descriptions)
Steven Vale - UNECE Statistical Division
Slide 9
Structure of the Model (2)


National implementations may need
additional levels
Over-arching processes
•
•
•
•
•
Quality management
Metadata management
Statistical framework management
Statistical programme management
........ (8 more – see paper)
Steven Vale - UNECE Statistical Division
Slide 10
Key features (1)




Not a linear model
Sub-processes do not have to be followed
in a strict order
It is a matrix, through which there are many
possible paths, including iterative loops
within and between phases
Some iterations of a regular process may
skip certain sub-processes
Steven Vale - UNECE Statistical Division
Slide 12
Key Features (2)

In theory the model is
circular:
•

Evaluation can lead to
modified needs and design
In practice it is more like
a multiple helix:
•
There may be several
iterations of a process
underway at any point in
time
Steven Vale - UNECE Statistical Division
Slide 14
Mapping
to Other
Models
Remainder of This Session


Wider uses of the model – IT architecture
and statistical software sharing
National applications of the model
•
Norway
• New Zealand

Your input – parallel sessions
Steven Vale - UNECE Statistical Division
Slide 16
Parallel Sessions

Aim – to review in detail three phases of the
model in each parallel session:
•
Session 1a: Phases 1-3 (Specify needs, Design,
Build) - Facilitator: Alice Born
• Session 1b: Phases 4-6 (Collect, Process,
Analyse) - Facilitator: Jenny Linnerud
• Session 1c: Phases 7-9 (Disseminate, Archive,
Evaluate) - Facilitator: Jessica Gardner

Start 14.00, End 16.45, short plenary session
Steven Vale - UNECE Statistical Division
Slide 17