My Third Post

Tags: data-analytics , customs , policy-research , indonesia

In my work as a customs officer, I’ve come to appreciate how powerful structured data can be — not just for operational efficiency, but for shaping better policy.

This post outlines a simple framework I used to analyze import data from bonded zones and how it helped flag potential risks before they turned into revenue loss.

The Challenge

Indonesia’s bonded zone facilities are crucial for supporting our industrial ecosystem. However, without proper data pipelines, it’s difficult to ensure compliance or assess the long-term economic sustainability of the participating firms.

The Approach

I used a combination of:

• Python scripts to extract and clean customs data,
• Tableau dashboards to visualize compliance behavior over time, and
• A basic scoring model to flag companies with declining economic indicators.

The result? We caught anomalies earlier and secured an additional Rp 747 million in revenue. More importantly, this became a regional model for risk-based monitoring.

Reflections

This experience affirmed that data isn’t just a technical tool — it’s a strategic asset. And with the right frameworks, even limited resources can yield high-impact insights.