Industry — Retail
Retail
Retail businesses need to understand sales, margin, inventory, customer activity and store performance quickly. JBI helps turn disconnected sales and inventory data into clearer decisions.
In Ricky's Words
Why I enjoy working in retail
Retail gives you daily feedback whether you want it or not. Sales, stock and margin move constantly, and the decisions are made by people on the floor as much as in the office. I like the pace, and I like that good reporting in retail is immediately useful: it tells a store manager what to do this week, not just what happened last quarter.
Common Challenges
What we see most often
- Poor sales visibility
- Inventory issues
- Margin leakage
- Manual reporting
- Disconnected POS and finance systems
- Store performance inconsistency
- Poor customer insights
- Slow reporting cycles
Capability 01
Business Intelligence and Reporting
Retail is a margin and availability business. Reporting connects sales, stock and labour so you can see which lines, stores and hours actually make money.
Examples
- Sales, margin and mix by store, category and line
- Stock on hand, cover and availability against lost sales
- Labour cost as a percentage of sales by trading hour
- Promotion performance measured on incremental margin, not volume
- One trading pack refreshed daily for the leadership meeting
KPIs that matter
KPI reference for retail
The measures we most often build for this industry, why each one matters, how it is calculated and the bands we benchmark against.
| KPI | Why it matters | How to measure | World class | Benchmark | Typical |
|---|---|---|---|---|---|
| Gross margin % | Are we selling profitably? | (Sales − COGS) ÷ sales. | Above category benchmark | At benchmark | Below benchmark |
| On shelf availability % | Can customers buy it? | Lines available ÷ lines ranged. | ≥98% | 94–97% | 88–94% |
| Sales per labour hour | Is labour productive? | Net sales ÷ paid labour hours. | Top quartile | Median | Bottom quartile |
| Stock turn | Is capital working? | COGS ÷ average inventory. | Category top quartile | Median | Slow |
| Shrink % | What are we losing? | Shrink value ÷ sales. | ≤0.5% | 1–2% | 3%+ |
Capability 02
Data Engineering, Fabric and AI Readiness
POS, inventory and rostering data need to be joined before you can see a true store P&L. We build that foundation.
Examples
- Join POS, inventory, supplier and rostering data in one model
- Standardise product hierarchy, store and supplier structures
- Automate daily sales and stock movement loads
- Data quality checks on negative stock, unmapped SKUs and price errors
- History that supports demand forecasting and range decisions
Capability 03
Power Platform and Business Applications
Store teams still ring, email and text the office. We give them apps that record it properly the first time.
Examples
- Stock count and adjustment capture in store
- Markdown, waste and damage recording with approval
- Store checklist, compliance and opening routines
- Maintenance and IT request raising from the floor
- Automated exception alerts on availability and shrink
Capability 04
Continuous Improvement and Business Process Improvement
Store labour is the biggest lever most retailers have. We map the routine and put the hours where the trade is.
Examples
- Map the store day and match labour to trading pattern
- Simplify replenishment and back-of-house handling
- Standard work for opening, close and stock routines
- Reduce shrink by fixing the process behind it
- Improvement register measured in margin per labour hour
What we work on here
- Poor sales visibility
- Inventory issues
- Margin leakage
- Manual reporting
- Disconnected POS and finance systems
- Store performance inconsistency
What changes for you
- Better inventory management
- Better customer insights
- Faster decisions
- Stronger margin visibility
- Improved store performance