TECHNOLOGY & DESIGN
RETAIL & COMMERCE / OVERVIEW
Connect stores, e-commerce, inventory and advertising to inform margin and stock decisions. Start with SKU-level data and build toward forecasting and campaign evaluation.
Explore the delivery scope ↓Conceptual data-to-operation flow, adapted to the agreed project scope.
Channels introduce different product identifiers and revenue cutoffs. Distinguish sales growth from contribution after discounts, returns and fulfilment costs.
For these teamsPlanning, merchandising, e-commerce, marketing and IT
01 / INPUTS
02 / CONTEXT
Align scope and time, preserving the path to source records.
03 / WORKFLOWS
Decide buying and promotion
PRIORITY WORKFLOWS
01 / CAPABILITY
Order, shipment, store sale and accounting dates may differ. Define which event drives each management metric.
Align channels by product, store and period to compare contribution and stock. Show the effects of returns and discounts that sales rankings can conceal.
Explore data, evaluation and scope ↗02 / CAPABILITY
Zero sales can indicate no demand or unavailable stock. Distinguish availability from demand before training on sales counts.
Evaluate forecasts using sales, stockouts, promotions and lead times. Show uncertainty and retain the reasons for buyer adjustments.
Explore data, evaluation and scope ↗Before adding systems, identify sources, access methods and refresh owners. CSV and existing reports can establish value before committing to integrations.
Separate orders, line items and returns. Align when shipping, discounts and cancellations enter revenue.
Check sellable inventory by SKU, store and date; distinguish stockouts and closures from zero-demand days.
Capture promotion dates, included products and price changes, using only information available at prediction time.
Confirm refresh schedules and API constraints for commerce, POS and stock systems. Retain history for cancellations, returns and product merges.
Architecture principles ↗A WORKFLOW IN PRACTICE
This is an illustrative engagement, not a client case study or a claim of results.
If store and e-commerce totals disagree, begin with reconciliation rather than forecasting. Select one category and agree with sales and finance whether the view uses order, shipment or return dates.
Prototype product-level sales, discounts, returns and sellable inventory with a path back to line items. Check whether the evidence can separate unavailable stock from weaker demand.
Reconcile against existing reports at the same cutoff and explain differences at line-item level. Agree how later returns affect figures before extending into purchasing or forecasting.
The set does not need to be complete; discovery can establish missing inputs and access conditions.
DISCOVER → PROVE → BUILD
Select one category and channel for reporting or weekly forecasting.
Use only promotions and prices known at the historical forecast date.
Compare results with explicit treatment of unavailable periods.
Compare current and proposed orders under lead-time, pack-size and workload constraints.
QUESTIONS BEFORE YOU START
We assess product identifiers, returns and available fields; CSV exports can be a starting point.
Limited observations make evaluation unstable. Compare category-level forecasts, replenishment rules and buyer judgement.
RELATED FIELD GUIDE
RETAIL & COMMERCE / GUIDE
Sales history alone does not make a forecast useful for buying. Distinguish why sales were absent, what was known at prediction time and the constraints of ordering.
Read the guide ↗YOUR OPERATION / OUR STARTING POINT
Tell us about the workflow, systems and reporting or documents that need attention. We will define a suitable phase, deliverables and assumptions.
Retail and e-commerce — discuss your project How scope and estimates work ↗