Challenge
International Monetary Fund was looking for a solution that is capable to cover all stages of GSBPM with the primary focus on data collection, processing, analysis, and dissemination.
The goal of the exercise was to standardize terminology, document statistical processes, establish a standard framework for benchmarking and facilitate use common tools and methodologies.
Issue 1: Quality of Input Data
- No standardization of data submission format
- No standardization of data quality (units of measurement, seasonal adjustment)
- Lack of metadata and transparency
Issue 2. Work Inefficiency
- A large variety of applications needed to, separately, process data, create metadata, produce reports and more
- Significant labor resources required (and a higher likelihood of human errors)
Issue 3. Business Risk and Response Time
- Business continuity risk: Large complex programming, based on statistical packaged, are used to generate data output
- Slow response time to analyzing global economic changes
- Difficulty in protection of confidential forecast data
Issue 4. Limitation on Publication Diversity
- A lot of effort and time is required to revise/add data output (including tables, charts, maps)
- Potential dependency and time lag on drawing IT department’s assistance in producing new publication output (e.g. web reports)