Fashion brands and manufacturers
ADVISORY AND ANALYTICS · 05
Analytics: merchandise, capital and forecast
A governed sales, buying, stock, budget and forecasting system, from data review to a ready web platform.
Decision Control inventory capital and forecast demand.
For fashion brands, retailers, department stores and distributors: a complete management analytics engagement.
Who benefits
Department stores, shops and retail networks
Wholesalers, distributors and digital channels
Problems addressed
- ERP, POS, WMS and spreadsheets disagree on sales and stock.
- Buying budgets and plan-versus-actual reporting are prepared manually.
- Capital is locked in stock without a reliable diagnostic.
- Reported margins do not reconcile to returns and actual costs.
- Teams cannot analyse profitability at SKU, size and store level.
- Demand forecasts are not validated on historical out-of-sample periods.
- Management spends more time preparing reports than making decisions.
Scope and capabilities
Sales and profitability
- Plan versus actual, returns, margin and channel contribution.
- Company → store → brand → category → SKU → size.
Purchasing and supply
- Open orders, inbound receipts, lead times and supplier exposure.
- OTB limits, commitments and buying budgets.
Inventory and working capital
- Stock at cost, ageing, WOS, GMROI and sell-through.
- Excess stock, size gaps and stock transfers.
Budgets and forecasting
- Seasonal budgets by brand, store and assortment group.
- Demand and arrival forecasts with backtesting and scenarios.
Systems and data quality
- 1C, ERP, POS, WMS and spreadsheet reconciliation.
- Access management, monitoring and governed update cycles.
Work delivered
- Agree confidentiality terms, scope, data permissions and ownership.
- Audit source transactions, master data, costs, returns and stock snapshots.
- Define and reconcile sales, profit, GMROI, WOS, OTB and sell-through KPIs.
- Build drill-down reporting from company and channel to SKU and size.
- Introduce buying budgets, plan/actual scenarios and backtested forecasts.
- Establish data quality controls, access rules and update schedules.
- Where contracted, deliver an integrated web application with training and handover.
Deliverables
- Data inventory, reconciliation report and controlled KPI dictionary.
- Management reporting for sales, buying, inventory and profitability.
- OTB and budgeting models, forecast scenarios and measured accuracy.
- Action list for excess stock, loss-making SKUs and preventable shortages.
- Optional web platform, integrations, training and support as separately agreed.
Ways of working together
- Diagnostic and issue map.
- One-off management analytics review.
- Recurring reports, buying budgets and planning models.
- Integrated web platform with handover and support.
Engagement stages
- Confidentiality, management objectives and data-access permissions.
- Audit source history, master data and transaction quality.
- Agree KPI formulas and reconcile a reporting prototype.
- Select the engagement: diagnostic, reporting, recurring operating cycle or full web platform.
- Pilot on approved data, test acceptance, document and train.
- Optional forecasting refinement, support and transfer.
What we need
- A named management owner and a data owner.
- Authorized ERP/1C exports for sales, inventory, costs and budgets.
- Style, SKU, size, store, season and counterparty reference tables.
- Policies for VAT, currency, cost allocation and returns.
Scope and limits. Timing, fees and scope are agreed after discovery. Forecast error is measured. Do not send confidential customer datasets through the public contact form.
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