Statistical Organization and Management: Information Technology Stefan Schweinfest, UNSD

1
Statistical Organization and ManagementInformat
ion 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

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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