Lulu Hypermarket

Lulu Retail Holdings

AI Operating System

DeployOne
Viewing as

Operating scope

Country head

Capability

All capabilities

Active handovers

0

Outcomes written back

0

Information density is explain.

PerishablesOS · screen 04 of 05

Production to demand

Central kitchens produce to a plan. Stores sell to a curve. The gap becomes waste.

3 issues · 2 waiting on you

Issues in scope

3

3 instances across 2 places

Waiting on you

2

0 already decided in this session

Three largest

AED 27.1m–AED 78.1m

Modelled annual value, three largest only

Running without asking

0

1 armed and waiting on a threshold

Decision owner

Country head

Returns to Country head, Group

Scope

Oman

27 stores · all capabilities

Listen

Central kitchen output and timingStore sell-through by day partDelivery timingWaste by line

Process

Batch against the curve it servesIs the cause the plan or the storeWhich stores share a kitchen

Act

Batch and timing proposalRedirect between storesTo the country, not the store
Written backEvery outcome returns to the systems that produced the evidence.
KindOrder

Queue

3 issues · 2 waiting on you
Armed

Nothing notices when production and demand drift apart

Buraimi
What happened
Waste is reported as a percentage of fresh sales. Whether it is tracking demand error or production timing is not measured, so a kitchen cause looks exactly like a store cause.
Why it matters
Divergence is the only signal that separates the two, and without it a kitchen cause and a store cause look identical, and the fresh conversation starts in the wrong place.
Already done
Armed on divergence rather than on waste level, so it fires on cause rather than symptom.
Worth
AED 15.4m to AED 43.8m a yearModelledDivergence separates a kitchen cause from a store cause before the quarter closes.Stores where waste tracks the window
Then what
Threshold armed on divergenceGroupStanding, no return date
Threshold
Waste and forecast error diverging beyond tolerance at any store
Fires
Fires to the country with the kitchen, the window and the affected stores named
GroupPerishablesOSDeployOnePredictDeployOneBrain
Approve

Waste at the stores on one Oman kitchen is a kitchen decision, not a store one

Oman
What happened
Four stores share a production window they cannot influence. Each currently receives a waste action they can do nothing about.
Why it matters
Sent to four store managers this produces effort without a change, since none of them can move a central kitchen window. The decision sits with the country because the asset does.
Already done
The proposal is assembled at country level with store level evidence, sized to the kitchen rather than to any one store.
Worth
AED 6.3m to AED 18.5m a yearModelledA proposal sent to the owner of the kitchen rather than to stores that cannot change the window. Value is execution rather than acknowledgement.Actions reaching an owner who can act
Then what
Production proposal with store level evidenceCountry headReports back 30 Sept
If approved
The production proposal goes to the Oman country head with the timing evidence
If declined
Store managers keep receiving a waste action about a window they do not control
Country headPerishablesOSDeployOnePredictDeployOneBrain
Choose

Kitchen output in Oman is planned on a daily volume, not on when the day actually sells

Oman
What happened
Production runs to a daily quantity per line. Store sell-through is concentrated in specific day parts and differs materially between the stores one kitchen serves. Waste concentrates at the stores whose curve is furthest from the production window.
Why it matters
Producing the right quantity at the wrong time produces the same waste as producing too much. This is the largest single controllable cost in fresh and it is currently managed as a forecasting problem, which it is not.
Already done
Output, timing and store level curves are read together, with the waste attributed to timing rather than to volume where the evidence supports it.
Worth
AED 5.3m to AED 15.8m a yearModelledOutput planned on daily volume against stores selling on different curves. Value is the waste attributable to timing rather than quantity.Kitchen window against store curve
Then what
Chosen fix costed and scoped to the kitchenCountry headReports back 30 Sept
Country headPerishablesOSDeployOnePredictDeployOneBrain