OICT Smart Waste Management

Context

OICT (Prague's municipal technology organization) runs technology projects for the city. I worked on analytics around smart waste management - turning sensor and operations data into reporting that city stakeholders could use for decisions, not only archival exports.

Problem

Waste operations generate continuous data - routes, fill levels, collection patterns - but public-sector stakeholders need clarity, not raw tables. Without trustworthy reporting, "smart" infrastructure does not change how anyone plans or allocates resources.

My role

Data and business analyst: building operational analytics and waste-management reporting used by city-side stakeholders.

Constraints

• Public-sector pace: Requirements evolve with political and operational reality, not sprint boards.
• Data quality: Field hardware and legacy processes do not arrive perfectly labeled.
• Audience mix: Technical operators and non-technical decision-makers in the same conversation.

What I did

• Translated operational waste data into reporting views stakeholders could review regularly.
• Worked through data quality and definition issues so metrics meant the same thing week to week.
• Supported conversations between technical teams and city users about what the numbers could and could not prove.

Key decisions

• Operational truth first: Reports had to match what crews saw on the ground, or adoption died.
• Simple cuts before fancy models: Reliable weekly views beat ambitious dashboards nobody opened.

Result

Waste-management analytics landed in regular use by city stakeholders - a practical link between smart-city instrumentation and day-to-day municipal operations.

What this shows

Analytics in messy operational environments where the end user is not a product manager with a Mixpanel login - and where trust in the number matters as much as the chart design.