Data collection tool for producing accurate forecasts of the total supply in the UK’s natural gas market.
Goal
Client asked me to fix 3 resource drains:
- Time drain. Time consuming data collection.
- Money drain. Manually collected data was used in the natural gas demand forecasting process. Poor data quality and insufficient data collection frequency resulted in suboptimal forecasting results and significant revenue loss.
- Stress. Unlock new time for more rewarding work and reduce human stress.
Role
I automated tedious data processes with python (retrieval, harmonization, reformatting, sharing), saving 2 FTE hours per day, improving forecasting accuracy, maximizing company revenue, and creating more time for rewarding work.
Capability
I delivered 3 benefits for the client:
- Time gain. 2 hours (1 FTE equivalent) of time savings per day;
- Money gain. Better data quality, higher frequency and faster collection process significantly improved demand forecasting deliverables and protected key revenue stream.
- Reduced human stress. New time for more rewarding work unlocked / stress reduced.
Preview
Tech Stack
Python, API development, Database design, Data pipelines, ETL, Web scraping, Data quality automation.
Year
2019