United Nations Economic Commission for Europe Statistical Division Enhanced Generic Models to Support the Standardisation of Statistical Production Steven Vale UNECE

Introducing UNECE Statistics

Challenges Increasing cost & difficulty of acquiring data New competitors & changing expectations Rapid changes in the environment Competition for skilled resources Reducing budget Riding the big data wave

Using common standards, statistics can be produced more efficiently No domain is special! Do new methods and tools support this vision, or do they reinforce a stove-pipe mentality?

Standards-based Modernisaton % 43% 34,600

Introducing the GSBPM

Why do we need the GSBPM?  To define and describe statistical processes in a coherent way  To compare and benchmark processes within and between organisations  To make better decisions on production systems and organisation of resources

Key features  Not a linear model  Sub-processes are not followed in a strict order  It is a matrix, through which there are many possible paths

The GSBPM is used by more than 50 statistical organisations worldwide

What is GSIM?  A reference framework of information objects  It sets out definitions, attributes and relationships of information objects  It aligns with relevant standards such as DDI and SDMX

GSIM and GSBPM  GSIM describes the information objects and flows within the statistical business process.

Outcomes GSBPM v5.0

Main Changes  Phase 8 (Archive) removed Archiving can happen at any stage in the statistical production process  New sub-process "Build or enhance dissemination components"  Clearer distinction between detection and treatment of errors  Sub-processes re-named to improve clarity  Descriptions of sub-processes improved  Terminology is less survey-centric

Outcomes Version 1.1 Simplified information objects Incorporates revised Neuchâtel Model of classification terminology Better aligned with other standards, particularly DDI

Mappings Fundamental Principles of Official Statistics

Governance

More Information  HLG Wiki: www1.unece.org/stat/platform/display/hlgbas  LinkedIn group: “Business architecture in statistics”