in a changing environment Beijing, 2004, session 2 Nico Heerschap The role of the Business Register in a changing environment at Statistics Netherlands

Content: Old / current situation - changing environment 2/14 Content: Old / current situation - changing environment Ideal situation Strategy for the short and medium term The role of the Business Register 25 min.

Organisation of SN: Business statistics (BES) Social statistics (SRS) Macro economic statistics (MSP) Technology and facilities (TNF) Two distant locations

Types of statistics in the Division of Business Statistics: Production (mainly for NA) Short term (mainly turnover) Investments International trade Thematical Energy, Technology, Environment, Health, Agriculture, Transport, Crime, Culture, Tourism Business Register / Baseline

         Old situation: Output Throughput Input Statistic 1 Product view Old situation:     Output CR3 CR2 CR1 CRx Throughput Input BR Statistic 1 Statistic 2 Statistic 3 Statistic x ESB     

Changing environment: Changing needs of customers: more integrated, coherent and quicker. New theme’s emerge Growing competition in the market place Pressure to reduce the survey burden on enterprises Smaller budget: pressure to be more efficient: less staff but same or more output New developments in IT and methodology ESB

Disadvantages current situation: 4/14 Disadvantages current situation: No co-ordination between statistics / separate worlds No integration of the data overall (quality and consistency) Sometimes different figures for the same phenomenon Overlapping customer bases Same data suppliers approached by different statistics Little documentation of processes / hardly any mobility Inefficient processes (e.g. not invented here syndrome) / high business costs Conclusion: The situation within SN is not in line anymore with a changing environment ESB

Main goals of SN: consistent, quicker, flexibility, one window 5/14 Main goals of SN: Strengthen the relationship with the customer: integrated, consistent, quicker, flexibility, one window New position in the market place: integrating crossroad on the information highway, knowlegde institute (networks) Reducing the survey burden by: - Optimising the use of secondary sources - Approaching the respondent in its own environment More efficiency by redesigning the processes and applying new IT and methodology Adapt the organisational structure, culture and skills (7S model of McKinsey) ESB

better and quicker output lower input costs (SN / Enterprises) In business terms: better and quicker output lower input costs (SN / Enterprises) and lower process costs (higher productivity) Meaning: another way of making statistics with less but more professional staff ESB

Old situation Desired situation P I S C U S T O M E R A Unanswered Survey B needs burden burden Unanswered Survey needs Desired situation E N T R P I S C U O M A B

  Output Throughput Input Merge Theme 1 Theme 2 Theme 3 Theme x ESB One window for data dissemination services Merge Output Throughput Input Theme 1 Theme 2 Theme 3 Theme x  One window for data-collection services ESB

 One window for all output services L Customers / data-users Output for customer Internal analists Information development Data production factory Knowledge institute (integrated) publication information development customer base W O R K F L M A N G E T M E T A D S Y Output driven process L Output Making of data-marts (selection, aggregation etc.) Transactional dbase Data repository CBR B A C K O N E S Transfer data to Data warehouse Checking, editing and micro-inte- gration Coupling data to the backbone(s) Throughput External SBR Input One window for all data-collection All input, primary and secondary  ESB

Dimensions of the data repository: 7/14 Dimensions of the data repository: (3) TIME (2) VARIABLES Administrative sources Administrative sources Administra- tive sources Survey- data (1) B A C K O N E S (BR)

Main advantages, business case (1): 8/14 Main advantages, business case (1): A uniform and consistent archive and output database for all business statistics (one window) with: - standardised definitions and concepts / structured metadata - all data in one database, micro-data, aggregates, historical data - data manipulation / output facilities (StatLine, Eurostat etc.) - flexible, reproducible and better accessibility data users Knowledge base for expert groups (tools for analysis, production) Integration frame - optimal use of secondary sources - quality - coordinated - less and smaller surveys - quicker output ESB

Main advantages, business case (2): 8/14 Main advantages, business case (2): Tool for analysis: - longitudinal research - timeseries - follow big enterprises or a panel of enterprises - consistency micro-data and corresponding aggregates Documented Basis for an output driven process In line with organisational developments (hybrid organisation) Reduced survey burden Customer database Efficient process (in potentie groot, lange en korte termijn) - IT / methodology - Organisational ESB

10/14 Bottlenecks: Little experience with integration / very complex process of checking, editing, imputation and micro-integration No coordinated backbones Still limited use of administrative sources No centralised meta-data systems No real experience with consistent weighing of data-marts Controle of data disclosure No experience with new technologies like dataware houses Is it possible to control the total process? Already made investments in short term process improve- ments (input driven) / quick results

Strategy for the short and medium term: A step-by-step approach gaining insight optimal situation as point on the horizon using already existing improvement projects as the starting point no cathedral building avoided. Strategy one centralised BR for (the maintenance of ) all backbones / populations (coordination) one contact centre for all input activities (coordination) as less production lines as possible as much standardisation and generic tools and solutions as possible one output data warehouse for all business statistics the optimal use of administrative sources at the cost of surveys one centralised metadata – infrastructure

Customers BR Baseline Registrations Enterprises SBR Publication layer Determine Statistical needs ESB-Basis Metasystem Information development Publication layer (incl. statistical disclosure control Process meta system Data manipulation layer Data repository layer Integration layer BR Statistical Backbones SBR Input layer Clean (micro) data (meta) Approach companies Multi-channel Institutional statistics (Impect) Approach regis- tration holders Baseline (secundair) Functional Enterprises Registrations

The (changing?) role of the BR Determination and derivation of statistical backbones / populations Sampling and weighting frame for all business statistics Matching frame (e.g. micro-integration) The bridge between administrative and statistical data A benchmark Source for economic demography Information source

Old situation Desired situation Mainly a sampling frame Existence of decentralised BRs No overall coordination Processing mainly within SN No units of functional statistics No metadata and quality indic. Basis economic demography Survey burden Less accessible Crucial role in coordination / unam- bigious backbones / no decentralised BRs Matching frame. Integration Information to follow businesses over time (longitidinal / transversal) Attention bigger businesses Regional aspects A bridge between adminstrative and statistical data Processing also outside SN (SBR) Units functional statistics included Metadata and quality indicators User friendly access Basis economic demography Survey burden

Thank you for your attention Open questions: Timeliness of updates of the BR Inclusion of functional statistics The connection between BR and CPR Thank you for your attention