FutureFlo

challenge

Challenge 4

brief

FutureFlo delivered FutureFlo, a data‑quality‑led schedule forecasting solution that combines structured data cleansing, feature analysis and Power BI visualisation to highlight drivers of project slippage and forecast future delivery risk.

Please be aware that this content was generated follwing an automated review so may not be perfectly accurate; refer to the original challenge brief and team files for authoritative information

key outcomes

Expected to improve forecast reliability by addressing underlying data quality issues, reduce time spent manually reconciling schedule data, and enable earlier intervention on projects trending towards delay.

important files

• readme.docx: Overview of the FutureFlo solution, datasets, data quality approach, and forecasting artefacts.
• Futureflo.pbix: Power BI dashboard visualising schedule slippage trends, key influencing features, and forecast insights.
• slippages_combined: Combined dataset used to analyse schedule slippage drivers and feed forecasting visuals.

details

team: FutureFlo members: tbc topics: solution-centre, hack25, challenge4, power-bi, excel, python, chatgpt, data-modelling, schedule-forecasting, data-quality, predictive-analytics, project-controls, data-visualisation, delivery-performance technologies: Power BI, Excel, Python, ChatGPT, Data Modelling