Developing and applying business process models in

practice

Statistics Norway

Jenny Linnerud and Anne Gro Hustoft

Business Process Model (BPM)for Statistics Norway

Project within our programme on improvement andstandardisation of statistical production (FOSS)

Progress• BMP project started in March 2008 and ended

mid-August 2008

Resources• 520 man-hours were used

BPM project group

The project group consisted of 9 members

of the FOSS coordination group, who

represent different professional areas within

the process:

management support, data processing, IT

industry, labour market statistics, registers

IT development, metadata, sample surveys,

population statistics and statistical methods.

Statistics Norway’s Business Process Model

Kvalitetssikre - evaluere og t ilbakef øre

8Q uality assurance - evaluate and f eedback

Develop and

design 2

Build

3

Collect

4

Process

5

Analyse

6

Disseminate

7

Specify needs

1

S upport and inf rastructure

9

Business Process ModelSpecify needs

1

Develop and design

2

Build

3

Collect

4

Process

5

Analyse

6

Disseminate

7

Consult and confirm need

1.2

Check dataavailability

1.4

Establish output objectives

1.3

Prepare business case

1.5

Prepare data for dissemination

database7.1

Produce product

7.2

Release and promote product

7.3

Classify and code

5.1

Micro-edit

5.2

Macro-control

5.3

Impute for partial non-response

5.4

Interpret and explain

statistics6.4

Establish frame and registers, select sample

4.1

Set up collection

4.2

Run collection

4.3

Finalise collection

4.4

Outputs

2.1

Data collection methodology

2.3

Process and analysis

methodology 2.4

Production system

2.5

Integrate production system with

other systems3.2

Test production system

3.3

Finalise production

system 3.4

Acquire domain intelligence

6.1

Produce statistics

6.2

Prepare statistics for dissemination

6.5

Finalise content

6.6

Frame, register and sample

methodology 2.2

Determine need for information

1.1

Manage user queries

7.4

Calculate weights and derive variables

5.5

Quality assure statistics

6.3

Build and enhance process

components3.1

Phase 5. Process

Classify and code

5.1

Micro- edit

5.2

Macro- control

5.3

Imputation for partial non-response

5.4

Calculate weights and derive variables 5.5

Code and store

micro-data 5.1.3

Prepare derived

variables 5.5.4

Link data sources and establish

statistical registers 5.1.1

Evaluate imputations

5.4.2

Perform manual editing

5.2.2

Identify and investigate outliers and critical values

5.3.1

Perform controls at macro-level

5.3.2

Calculate weights

5.5.2

Run automated control and

correction routines 5.2.1

Identify and establish

statistical units 5.1.2

Run imputation routines for partial

non-response 5.4.1

Supplement statistical registers

5.5.3

Imputefor unit

non-response5.5.1

Store micro-data

5.5.5

Data ready for

processing

Data ready for analysis

Comparison with

Generic Statistical Business Process modelSpecify

needs

1

Develop and design

2

Build

3

Collect

4

Process

5

Analyse

6

Disseminate

7

Consult and confirm need

1.2

Check dataavailability

1.4

Establish output objectives

1.3

Prepare business case

1.5

Prepare data for dissemination

databaseUpdate output

systems7.1

Produce products

7.2

Release, 7.3market and

promote product 7.47.3

Classify and code

5.3

Micro-edit

5.2

Macro-control

5.3

Impute for partial non-response

5.4

Interpret and explain

statistics6.4

Establish frame and registers, select sample

4.1

Set up collection

4.2

Run collection

4.3

Finalise collection

Load data into processing

environment4.4

Outputs

2.1

Data collection methodology

2.3

Process and analysis

methodology 2.4

Production systemProcessing systems

and workflow2.5

Integrate production system with

other systemsConfigure workflows

3.3

Test production system

3.4

Finalise production

systems 3.5

Acquire domain intelligence

6.1

Produce statisticsPrepare

draft outputs6.2

Prepare statistics for dissemination

Disclosure control6.5

Finalise contentoutputs for

dissemination6.6

Frame, register and sample

methodology 2.2

Determine need for information

1.1

Manage user customer queries

7.5

Calculate weights 5.6and derive new

variables5.5

Quality assure statistics

Verify outputs 6.3

Build and enhance process

components3.2

Data collectioninstyument

3.1

Standardiseand anonymise

5.1

Integrate data

5,.2

Calculate aggregates

5.7

Edit andimpute

5.4

This process is associated with, among other things:

- Quality control in every processes

- Identify and propose process-related improvements

- Collection, follow-up and analysis of process data

- Identify and propose product-related improvements

- Collection, follow-up and analysis of user and customer feedback

- Quality indicators

Q uality management- evaluate and f eedback

8

Examples of resources under this:

Legal acts

Control documents e.g. IT-strategy

Systems and associated documentation

Templates, guidelines and handbooks

Committees, fora, expert groups

Support processes, e.g. ITIL (IT Infrastucture Library)

Data storage and administration

Population administration

Cross cutting:

Security

International activities

Financial matters

Competence and development

Last but not least:

Business Process Model

S upport and inf rastructure

9

Recommendations from the BPM development project

• The business process model will need to be reviewed and updated to ensure that it reflects the real state of affairs at any time.

• The model originally in Norwegian was translated into English for international use.

• A process guide for the model should be made available on Statistics Norway’s intranet.

Case study

- Description of the production process for Price index for legal services with emphasis on the use of metadata throughout the process. – Description of the process for a new statistic

and for future publishing of the same statistic. – Creation of a metadata checklist that can be

used whenever this type of statistics is produced.

- 7 participants: statistics, IT, metadata

- 435 man-hours used.

Result 1 – New statisticProcess Activities Actors

1 Specify needs

Statistics division, Eurostat, National accounts, Branch organisation, businesses, Justice department

1.1 Consult and confirm need

Discuss need for price index with national accounts & branch organisation

Result 2 – Metadata checklist

Process Metadata checklist

1 Specify needs

1.1 Consult and confirm need

Update product register, make resource estimates and project description.

1.2 Establish output objectives

Check for existing variables and classifications and update if necessary.

Process Create Use Update

 6.5 Prepare statistics for dissemination

New classifications for new statistics, if necessary

Existing classifications

Classifications for established statistics

  New variables for new statistics, if necessary

 Existing variables

Variables for established statistics

Result 3 – Metadata overview

Specify needs

Develop & design

Build Collect Process Analyse Disseminate

Variables X X X

Classifications X X X X

File descriptions

X X

Questionnaires X X

Rules X X X

About the statistics

X X

About the data collection

X

Metadata

portalX

Metadata systems & Statistics Norways Statistical Business Process Model

Specify needs

Develop & design

Build Collect Process Analyse Disseminate

Eurostat X X

Branch organisations

X X X

Businesses X X X X

Justice department

X

Director general

X X

Head of department

X X

Head of division

X X X X X

Resp. statistics X X X X X X X

Different actors & Statistics Norways Statistical Business Process Model

Conclusions - case study

- Process improvements were suggested and made

- Include metadata documentation and linking of metadata in formal approval procedure

- Suggestions for improved functionality in systems were identified and improvements made.

Conclusions – BP model

- The method of documenting a statistic based on the Statistical Business Process Model, can be used for other statistics.

- Documentation of new and established statistics is useful for training new employees and for rotation of current employees

Conclusions – BP model – cont.

-The business process model is an important tool in planning, standardising and improvingwork processes in statistical production, and for training purposes.

-The business process model is also a communication tool for standardisation and cooperation between statistical agenciesand government departments.