Warehouse Stock Management with Stock Dispatched Tracking
Budget: ₹600 – ₹1,500 INR
Our day-to-day operations throw off plenty of raw data—process logs, production metrics, turnaround times—and I need a clear, evidence-based narrative that pinpoints where things break down and why. The brief is straightforward: take my operational data, run a thorough analysis, and translate the findings into concrete problem-solving steps that my team can act on immediately.
Data access
I will supply exported CSV files plus a live connection to our SQL warehouse. If additional data shaping is required, let me know early so we can arrange secure access.
Scope of work
• Clean and structure the data so it is analysis-ready (Python/pandas or SQL is fine).
• Explore the dataset to surface anomalies, bottlenecks, or recurring failure points.
• Apply appropriate statistical or machine-learning techniques—anything from control-chart analysis to clustering—so the root causes are indisputable.
• Visualize key insights in a concise dashboard (Power BI, Tableau, or an interactive Jupyter notebook).
• Deliver a short, plain-language brief that maps each finding to an actionable recommendation.
Acceptance criteria
1. All code/scripts are executable on my end without modification.
2. Visualizations clearly highlight at least three priority issues and their impact on uptime, cost, or throughput.
3. Final report includes a ranked action list and the metrics we should track to confirm improvements.
If you already have sample work that shows similar operational problem-solving, pointing me to it will speed up onboarding. I’m ready to share the data as soon as we agree on milestones and timelines.
Data access
I will supply exported CSV files plus a live connection to our SQL warehouse. If additional data shaping is required, let me know early so we can arrange secure access.
Scope of work
• Clean and structure the data so it is analysis-ready (Python/pandas or SQL is fine).
• Explore the dataset to surface anomalies, bottlenecks, or recurring failure points.
• Apply appropriate statistical or machine-learning techniques—anything from control-chart analysis to clustering—so the root causes are indisputable.
• Visualize key insights in a concise dashboard (Power BI, Tableau, or an interactive Jupyter notebook).
• Deliver a short, plain-language brief that maps each finding to an actionable recommendation.
Acceptance criteria
1. All code/scripts are executable on my end without modification.
2. Visualizations clearly highlight at least three priority issues and their impact on uptime, cost, or throughput.
3. Final report includes a ranked action list and the metrics we should track to confirm improvements.
If you already have sample work that shows similar operational problem-solving, pointing me to it will speed up onboarding. I’m ready to share the data as soon as we agree on milestones and timelines.