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Power BI Analytics

Retail

Store, ecommerce, inventory, and margin in one hierarchy

Merchandising and finance finally share one product story — sales, stock, and margin together.

NDA-readyFixed-scope first releaseBusiness + IT handover
Store performance dashboard for retail — Power BI — showing same-store sales, gross margin, sell-through, and stockout rate
  • Operating since 2012
  • Microsoft Power BI specialists
  • NDA-ready data handling
  • Fixed-scope first releases
  • Independent — not affiliated with Microsoft

01 · Context

The situation

Specialty retail chain · Retail

A specialty retailer sold in stores and online. Inventory sat in the warehouse system. Margin lived in finance.

Each team had a report. None of them used the same product hierarchy or the same “day.” Trading meetings started with translation, not decisions.

They needed sell-through, markdown exposure, stockouts, and realized margin on one shared product tree.

02 · Solution

What we built

A retail trading BI layer: one hierarchy, channel facts, and pages for merchants and leadership.

Product hierarchy spine

One tree owned by merchandising. Store, web, warehouse, and finance all hang off it.

Trading dashboard

Sell-through, stockouts, and markdown risk in the weekly review — not three exports taped together.

Margin bridge

Realized margin from finance sits next to sales so “good sales, bad profit” is visible early.

Category trading

  • Sell-through by style
  • Stockout and ageing
  • Markdown exposure

Channel & margin

  • Store vs ecommerce
  • Margin by hierarchy node
  • Exception list for buyers

Data sources

  • POS sales
  • Shopify ecommerce orders
  • Warehouse inventory
  • Finance margin extracts

Connectors

  • SQL Server
  • Shopify connector / extracts
  • Power Query

Model design

Merchandising-owned product hierarchy; channel dimension; measures for sell-through, markdown exposure, stockouts, and margin. Import for trading packs.

03 · Process

How we delivered

From the real meeting to a live report — with checkpoints, not a big reveal at the end.

  1. 01

    Hierarchy workshop

    Froze the product tree merchandising will own — and who can change it.

  2. 02

    Connect channels

    Brought POS, Shopify, warehouse, and finance onto shared keys.

  3. 03

    Phase release

    Category pilot first, then roll to more teams once definitions stuck.

  4. 04

    Adoption check

    Measured whether buyers opened the board in the real trading meeting.

04 · Technologies

Stack and why we chose it

Tools that serve the report — not a shopping list of buzzwords.

Power BI

Trading and margin pages for merchants and leadership.

Why: Handles multi-channel filters without another Excel cube.

Shopify + POS extracts

Ecommerce and store sales into the same model.

Why: Channel truth has to meet in one place for assortment decisions.

SQL Server

Inventory and history at scale for daily Import.

Why: Trading packs need speed; warehouse systems need protection.

05 · Challenges

What got hard — and how we fixed it

Real delivery friction, not a polished success-only story.

Challenge

Web SKUs and store SKUs did not share IDs.

Resolution

Built a product bridge with merchandising as owner. Unmapped SKUs surface as a data-quality list, not silent gaps.

Challenge

Direct queries to POS during peak weekends timed out.

Resolution

Daily Import for trading packs. Peak sales stay in the POS; reporting reads the staged day.

06 · Results

What changed

  • One product hierarchy across store, web, inventory, and finance.
  • Trading meetings open on sell-through and stock risk together.
  • Margin sits next to sales — not in a separate Friday file.

Continue exploring this topic

Related pages that deepen the same subject—services, industries, integrations, and proof.

Why teams trust Power BI Analytics

Enterprise delivery with clear ownership

Power BI Analytics combines Power BI craft with business process discipline—so leaders get numbers they can act on.

14

Years building software & automation

Enterprise security practices
Microsoft Power BI specialists
Business + IT delivery model
Measurable reporting ROI

What to expect in an engagement

  • Named business sponsor and delivery ownership
  • KPI definitions validated against source totals
  • Security-aware workspace and refresh design
  • Documented handover, not a black-box model
  • First release scoped to prove value quickly
  • Response within one business day on qualified enquiries
Response within one business dayClear first-release scopeGoverned KPI definitionsSecurity-aware delivery

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