Clothing Inventory Optimization Analysis
Budget: ₹750 – ₹1,250 INR
I’m handing over two years of point-of-sale inventory data from my clothing shop, already sitting in a single Excel workbook, and I need it turned into clear insight that will let me optimise inventory control. The end goal is practical: cut overstock and stock-outs while quickly spotting slow-moving lines so I can react before cash is tied up on the rack.
Here’s what the work looks like on my side. First, the raw data needs a thorough wash—duplicates removed, SKUs standardised, missing values flagged, and dates aligned—so every formula and PivotTable you build rests on solid ground. From there I’d like monthly and yearly views of stock movement, best and worst sellers, seasonal demand swings, and turnover rates. Once the numbers speak, translate them into specific actions I can take in-store, all wrapped up inside the same workbook.
Deliverables I expect
• A cleaned, fully validated dataset in Excel (no stray blanks or mismatched codes)
• An analytics dashboard: PivotTables, slicers and charts that tell the story at a glance
• A tab dedicated to actionable recommendations laid out as bulleted tasks with KPIs, so I can implement them without cross-referencing another document
• A one-page executive summary inside the workbook for quick sharing with my team
Advanced Excel skills—Power Query, PivotTables, nested formulas, perhaps Power Pivot for DAX calculations—will make this job easier, and a background with retail or inventory data will help you interpret the numbers quickly.
I’d like to see a first draft of the dashboard and recommendations within 7 days so we can tighten anything that needs it before sign-off.
Here’s what the work looks like on my side. First, the raw data needs a thorough wash—duplicates removed, SKUs standardised, missing values flagged, and dates aligned—so every formula and PivotTable you build rests on solid ground. From there I’d like monthly and yearly views of stock movement, best and worst sellers, seasonal demand swings, and turnover rates. Once the numbers speak, translate them into specific actions I can take in-store, all wrapped up inside the same workbook.
Deliverables I expect
• A cleaned, fully validated dataset in Excel (no stray blanks or mismatched codes)
• An analytics dashboard: PivotTables, slicers and charts that tell the story at a glance
• A tab dedicated to actionable recommendations laid out as bulleted tasks with KPIs, so I can implement them without cross-referencing another document
• A one-page executive summary inside the workbook for quick sharing with my team
Advanced Excel skills—Power Query, PivotTables, nested formulas, perhaps Power Pivot for DAX calculations—will make this job easier, and a background with retail or inventory data will help you interpret the numbers quickly.
I’d like to see a first draft of the dashboard and recommendations within 7 days so we can tighten anything that needs it before sign-off.