Objective To implement an AI-driven system that converts operational retail data into clear insights and actionable tasks, improving decision-making and execution across the business. Scope The project will integrate existing data sources: Retail performance systems (sales, margin, transactions) Staffing and hours data ClickUp (task management) Using AI tools (ChatGPT / Claude and Openclaw), the system will: Analyse structured operational data Generate concise, action-focused reports Translate insights into prioritised tasks Assign and track execution via ClickUp Key Outputs Weekly performance reports (AI-generated) Exception / “red flag” reports Trend analysis (e.g. margin, volume, staffing efficiency) Structured task lists linked to operational issues Success Criteria Clear link between data → insight → action → outcome Reduction in manual reporting and decision effort Improved operational performance (e.g. margin, labour efficiency) Consistent execution through task tracking Approach Use existing reports and datasets (no rebuild of core systems) Layer AI analysis and workflow automation on top Start with manual processes → move to automation over time Outcome A scalable “operating system” for the business that: Identifies issues early Drives consistent action Enhances performance without increasing management overhead
I am open to engaging over a longer period of time to help monitor and I improve the system. Please outline in your response what experience you have completing a similar project.
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