Statistical Organization and Management : Information Technology Stefan Schweinfest, UNSD

1. Statistical Organization and Management:Information TechnologyStefan Schweinfest, UNSD Workshop for SADC Member States, Luanda, December 2006

2. Rapid IT developments advance capacities of statistical agencies • Powerful, cost-effective computers • User-friendly software • Computer networking • Intranet/Internet (WWW) technology

3. Managing Information Technology • General objectives: • support of core function: producing and disseminating official statistics • meet the needs of substantive users • cost effective • avoid information anarchy • Two principal models: • Highly centralized informatics organization • “Federation of solutions”

4. Some critical elements for efficient IT management • Build on customized software or off-the-shelf products wherever possible • Leave hardware infrastructure in hands of specialist group • Promote training activities as integral part of IT development strategy • Emphasize the importance of documentation • Learn from past performance and experience of other similar organizations

5. Why (and when) outsourcing • Best solution when commercial products and services can be adapted to the mission requirements • Market competition brings innovation and reduces costs • Specialized skills found among vendors are difficult to maintain “in-house” • Risks shared with vendors

6. Outsourcing challenges • Do not jeopardize core functions or confidentiality of information • Maintain healthy business relationship with commercial vendors • Balance risk sharing vs. rewards sharing (incentives/penalties) • Develop necessary management skills for outsourcing

7. ‘IT pressure points’ for Chief Statisticians • Continually new and different IT capabilities and products (facts or claims) • Lobbying by internal staff for a product • Pressure to reduce costs and improve delivery of products

8. IT Project management: Good practices (I) • Involve top-level management • Employ effective risk analysis in guiding direction • Avoid untried leading-edge technologies • Opt for small projects • Involve end users in project formulation

9. IT Project management: Good practices (II) • Formulate explicit and detailed IT project plans: • analyze return on investment • identify risks and mitigation strategies • ensure modular development to avoid large-scale failures • provide for oversight and review at crucial steps along the way

10. IT Project management: Good practices (III) • When purchasing IT products • avoid new or immature technologies • assess results of others who have applied the product • determine product compatibility with existing IT architecture of the organization • assess risks and price/performance of the product

11. Conclusions • Key challenge: Balance management discipline with drive for innovation in the application of IT • Strategies for reducing risk of failure • Involve top-level management • Employ effective risk analysis • Avoid leading-edge technologies • Opt for small projects • Involve end-users in project formulation