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Results-Based Management for Statistics projects

Results-Based Management for Statistics projects. 7 October 2010 Robert Backlund robert.backlund@sida.se. Efficiency and Transparency. Efficiency Decentralised decisions Performance is monitored, evaluated and reported Transparency Use of tax payers money Democratic accountability.

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Results-Based Management for Statistics projects

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  1. Results-Based Managementfor Statistics projects 7 October 2010 Robert Backlund robert.backlund@sida.se

  2. Efficiency and Transparency • Efficiency • Decentralised decisions • Performance is monitored, evaluated and reported • Transparency • Use of tax payers money • Democratic accountability

  3. Inputs Activities Outputs The chain of results: Sphere of interest = social, economical, environmental factors Sphere of control = operational environment Sphere of influence = relationships & interactions Outcomes / result areas Impacts ACTION PLAN STRATEGY POLICY

  4. Project Project Project Project Project oriented Programme oriented → Unity Fragmented

  5. Activities and outputs Impact Input Outcome What is a result? Improved economic policies Better control of inflation Improved energy production Published reports on CPI Output price index Publication of Energy Balances Formats for business survey Compilation of data Surveys Processes to produce services Money Staff Systems Computers

  6. SMART S Specific M Measurable A Attainable R Realistic T Time bound

  7. Whatnot to accept • Objectives that have no defined time span • Expected result is too lofty • Developmental process has no benchmarks • Project does not inform on the resources needed • Same objectives appear unchanged in different programmes • Lack of analysis of possible impact

  8. Politicians’ management of the different policy areas Management within an agency Results Based Management Programme and project management for external funding For the public to know what to expect

  9. RBM in an IPA perspective • Regional cooperation motivated • EU and Eurostat applies known quality standards for well defined statistical production areas • All PARs in favour of RBM • Closeness regarding geopolitical realities • Key staff from all NSI’s has similar learning needs

  10. Threats to RBM • Structures and procedures rigid – not freedom to manage for results • NSI’s underresourced and unflexible whilst functioning in a dynamic environment • Unclear expectations from political level

  11. Issues for the future • Support to Statistical Master Plan with an RBM connection • Find synergy effects between NSI’s own development, IPA support and donor support • Communication and dissemination key to build trust • More emphasis on institutional and management development

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