Tania Scenario Planner

Baseline: validated five-year simulation · Reference 30 June 2026
This page answers one question for Tania's network: if sales come in differently than forecast, or we choose to push the lines harder, do we still have enough storage and production capacity to keep up? Move the controls below and watch the story change.

Scenario Controls

Direction matters here. Positive means actual sales are running ahead of forecast — product is selling through faster than what was produced for it, so it clears space in the warehouse. Negative means sales are falling short — product made for demand that didn't show up piles up and adds pressure on storage.
This is a real push strategy now, not just a capacity dial. Dragging this up means deliberately running the lines harder to use more of the available hours — exactly what a push strategy does. The direct trade-off: extra output that demand hasn't caught up to yet has nowhere to go but the warehouse, so pushing production up also pushes Storage Needed up. Drag it down and the opposite happens — leaner production, less builds up.
A planned expansion or reduction applied evenly across all three plants.
Disposing of or reworking old/delisted FG frees this much of the space it currently occupies.
Default of 83 units/pallet blends several pack sizes (200ml-1.5L); refine per item once exact pack data for these older codes is confirmed.

System Status

Storage utilisation, worst month
How this is calculated, and a known limitation. This is the average pallet level actually held in inventory over the worst month in the simulation, combining Factory and DC stock for each plant — not total monthly demand or production volume, which would be a much larger number. It comes from averaging the day-by-day ending-stock balance the detailed simulation computed for every day in that month.

This figure is likely understated. The underlying simulation has not yet been corrected for minimum production run lengths (a 4-day minimum batch for Riyadh PET, daily for the 5-gallon line). Until that's fixed, production happens in smaller, more frequent batches than reality, which understates how much stock builds up between runs. Confirmed open item, not a guess — treat this number as a floor, not a ceiling.
Production headroom before lines become the constraint
Shown as headroom rather than a bare "% of hours used" because production runs in concentrated batches, not continuously through the month — a line can be entirely on-plan and still show a tiny fraction of monthly hours used. The number above answers "how much demand growth could the lines absorb," which is what matters for a capacity decision.

Plant BreakdownStorage by location

"Storage Needed" below is how full each warehouse actually runs day to day — not how much is sold or made in a month, which would be a far bigger number. Selling fast drains it; producing ahead of demand fills it up.

PlantBase CapacityDead StockEffective CapacityStorage NeededUtilisationStatus
System Total

Division BreakdownStorage by location + division

Dammam is verified Gallon-only — it carries no PET SKUs at all in the detailed model, so its split below is certain, not estimated. Riyadh and Jeddah are estimated splits, flagged below — both plants run many PET SKUs alongside Gallon and the exact pallet-level breakdown for the worst month hasn't been pulled from the detailed model yet. Adjust the % split inputs once the real numbers are available.

Dead & Obsolete StockOld and delisted FG currently occupying space

194,433
total units across all locations
estimated pallets at current assumption
months in storage, oldest to most recent item
IdentityItem CodePackYear / Month Jeddah (F)Al KharjRiyadh HeetJeddah (W)Dammam QassimTotal
Note on scope. Al Kharj, Heet and Qassim are not part of the three-plant production capacity model above, so their dead stock is shown here for completeness but is not deducted from the Plant Breakdown capacity figures. Jeddah (F) and Jeddah (W) are combined into the single Jeddah figure used there.