1 / 10

Methodology vs Quality: synergies and gaps

From Knowledge to Quality: Contribution of Methodology Francisco FERNANDEZ FERNANDEZ Jean Marc MUSEUX Se ssion 1. Methodology vs Quality: synergies and gaps. Does ESS integration create new opportunities to use process harmonisation/standardisation as an additional way to improve quality?

Download Presentation

Methodology vs Quality: synergies and gaps

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. From Knowledge to Quality: Contribution of MethodologyFrancisco FERNANDEZ FERNANDEZJean Marc MUSEUXSession 1 Q 2010 Conference. Helsinki, 3 – 6 of May 2010

  2. Methodology vs Quality: synergies and gaps • Does ESS integration create new opportunitiesto use process harmonisation/standardisationas an additional way to improve quality? • An inventory of factors determining quality; • What possibilities in a complex ESS? • A cartography of ESS generic processes; • Discussion on test cases and formalisation.

  3. The constraints of integrated complex systems • No clear causality link between input and outputs; • Impossible to define clearly traceable processes; • Use of generic processes models and adjustment. boundary conditions ? a b c d a b c d BACK * Not yet active * Not yet active

  4. The place of Methodology in system building Identified Needs Looking for the best way to go: « Methodology » Quality Delivery * Not yet active * Not yet active

  5. Incorporation resources Knowledge Generation (R&D/innovation) Knowledge Formalisation(LDF) Competence Building Build-up Formalise Customisation Manage Test Valorise Good-practiceGeneration (ESSnets) Operational Governance extend facilitate output input Methodology Build-in Ensure Design Implementation Production Quality & Tools (IT) Strategy (CVD) Help Provide products A cartography of ESS generic processes 1. Multidimensional processing to integrate parallel unidimensional processes 2. Collaborational Methodology to complement Methodological Collaboration BACK

  6. Tracking back SDC developments Tracking back Seasonal Adjustment works input Knowledge Generation (R&D/innovation) Knowledge Formalisation(LDF) Competence & Capacity Building 2 3 3 1 2 2 Good-practiceGeneration (ESSnets) Methodology Operational gouvernance 3 4 4 2 3 RESOURCES 1 2 PRODUCTS 4 Production Strategy (CVD) Implementation 3 4 2 4 1 Quality & Tools (IT) output 1: 1997-2004 : CASC FP5 research project 2: 2004-2006 : CENEX project 3: 2007-2009 : ESSnet SDC II

  7. input GRANT Knowledge Generation (R&D/innovation) Knowledge Formalisation(LDF) Competence & Capacity Building 1 FPA Good-practiceGeneration (ESSnets) Methodology Rationalisation of Production 2 RESOURCES PRODUCTS 3 8 4 ESSnets 7 5 6 Production Strategy (CVD) Implementation Quality & Tools (IT) MARKET CONSULTATION output Positioning ESSnets components in the scheme

  8. Identifying niches for Methodology in Quality improvement BACK * Not yet active * Not yet active

  9. Main directions to move forward • More deterministic representation of change processes • Qualitative analysis to determine dimensions of quality and their inter/correlations and their link to methodology (hard and soft) and to other determinants • Formalisation of the correlations for error propagation and sensitivity analysis to help decision making on appropriate deployment of resources. • Improve conceptualisation. Deepening exploration of indicators and benchmarks • identification of additional/different set of dimensions for analysis • re-designing the refined map • Improve formalisation * Not yet active * Not yet active

  10. Conclusions • Conceptual model provides a framework allowing a meaningful representation of complete statistical projects and innovation processes • Pave the way for a first level of harmonisation over a wide range of actions covering the improvement of production from a generic perspective • Possibility to refine the model • systematic description of any improvement' steps • identify synergies among actions * Not yet active * Not yet active

More Related