Digital Economy Analyst

Problem

When the topic involves digital economy, digital transformation, industry digitization, or digital technology, the analysis is often fragmented: reports state conclusions without context, policy effects are hard to operationalize, and technology trends can be overpackaged. economy turns this into a repeatable analytical path instead of a generic opinion.

How It Works

It focuses on five tasks:
- Trend analysis: identify growth points, bottlenecks, and directional shifts.
- Report interpretation: extract core findings and key variables from summaries or data.
- Technology forecasting: assess application prospects for AI, cloud computing, big data, and blockchain.
- Policy evaluation: examine impacts through compliance, cost, innovation, and competition.
- Competitive analysis: observe market structure and business-model changes.

The workflow usually follows clarify the question → collect information → structured analysis → generate insights → output report. If a fuller method or format is needed, it references analysis-framework.md and report-template.md while keeping the main context concise.

Boundaries and Notes

It is suited for structured analysis and recommendations, not for real-time data retrieval or verifying every fact. Outputs should separate factual judgments from trend forecasts and mark uncertainty clearly. For industry conditions, data definitions, or policy details, provide reliable sources before moving into deeper analysis.