EzyMart Group · Store Pulse

Executive view

12 real EzyMart sites (Sydney & Melbourne) · all trading figures generated for this demo

Synthetic data. Locations are real; every figure is simulated.

Period

Region Store

This period in one paragraph

Daily sales

This yearSame period last year

Store map

Dot size is sales · colour is scorecard status · click to focus

On targetWatchOff targetAct now

Store scorecard

Targets: GP ≥ 30% · labour ≤ 15% · wastage ≤ 3% · out-of-stocks on the top-200 lines ≤ 10

Store	Region	Sales	vs LY	GP %	Labour %	Wastage %	Sales / labour hr	OOS top-200	Status

Needs attention

Breaches against the scorecard targets, worst first

Sales by store

Period total · click a bar to focus

Range by velocity

Every ranged line, ranked by units per week · A = the few lines that make most of the sales

Category margin

GP % by category · label shows share of sales

Fast movers

A-band lines · reorder when days of cover falls under the supplier lead time

Line	Category	Supplier	Units / wk	GP %	Stock on hand	Days cover	Lead time	Action

Slow movers

C-band lines · capital tied up on the shelf and what to do about it

Line	Category	Supplier	Units / wk	GP %	Stock on hand	Days cover	Capital tied	Recommendation

Wastage by category

Written off in period · label shows % of that category's sales

Wastage by reason

Why stock left the shelf unsold

Most wasted lines

Days of cover longer than shelf life is the tell

Line	Wasted	% of line sales	Cover / shelf life

Roster against demand

Weekday · staff needed from foot traffic vs staff rostered · gaps are where queues form and where hours are wasted

NeededRostered

Labour % of sales by store

Period · 15% target line

Foot traffic by hour

Average transactions per hour

Time at the register

Seconds per transaction by hour, weekday · rises when queues form faster than registers open

Checkout timeRegisters open

Store staffing

Headcount, mix, productivity and where the hours go outside serving customers

Store	Headcount	Casual	Sales / labour hr	Checkout s/txn	Peak queue wait	Unload min / delivery	Shelf-fill hrs / day	Turnover (ann.)

People flags

Compliance and retention signals from rostering and time & attendance

Delivery calendar

Deliveries expected per store over the next 7 days · warehouse runs and direct-to-store combined

Supplier fill rate

Lines received ÷ lines ordered, period

Open purchase orders

Warehouse and direct-to-store, sorted by due date

PO	Supplier	Deliver to	Lines	Value	Due	Status

Suggested orders today

Lines under reorder point in this view, grouped by supplier

Supplier	Lines	Units	Est. value	Route

Receiving discrepancies

What the store signed for versus what was ordered

Store	PO	Supplier	Line	Ordered	Received	Issue	Credit

Where the money goes

Group P&L for the period, sales to EBITDA

The squeeze

Cost of goods per unit vs shelf price, indexed to 100 at week 1 · the gap is margin leaving the business

Cost per unitShelf price

P&L by store

Period · rent and other overheads allocated to the store · click a row to focus

Store	Sales	COGS	Gross profit	GP %	Labour	Rent	Other	EBITDA	EBITDA %

Cash position

Group, as at period end

Indicative value per store

Annualised EBITDA × a common multiple · the same method for every partner · illustrative only

Multiple

Store	Period EBITDA	Annualised	Indicative value	Share of group

Where the stock went

Period, at cost · opening stock + received − sold − recorded wastage = what should be on the shelf; the count says what is

Unexplained loss by store

Shrink after recorded wastage, as % of sales · 1% target

Product-level variance

Lines where the count does not match the system · pattern is inferred from the last three counts

Line	Category	Store	System	Counted	Variance	At cost	Last count	Pattern	Risk

Cycle-count coverage

Share of A-band lines counted each week, last 8 weeks · the rule is every A-line weekly, every line monthly

Count schedule & accuracy

Who counts, how often, and how right the last count was

Store	Method	A-lines	Last full count	Accuracy	Next due

Investigate

Signals that separate theft from paperwork

Demo prepared for the owners' discovery session. Store addresses cross-checked against public listings (Yelp, Tripadvisor, Waze, ASIC) in September 2026; EzyMart's own locator was unavailable at the time. EzyMart: founded 2001 in Bondi Beach, ~490 stores across NSW, VIC, QLD, SA and TAS, mixed company-owned and partner-operated. All sales, margin, labour, wastage, traffic, stock, order and financial figures on this page are simulated with a fixed seed and do not describe the real business.