Companion to EFFEN_Cost_Model.xlsx. Every row below maps to a yellow cell on the model’s Inputs tab (also mirrored on the Questions tab). The model already runs on the placeholder values shown — tomorrow, just capture the real number in the “Confirm” column and overwrite the matching Inputs cell.
Base-case placeholders shown. Where a value differs by scenario it’s noted as Conservative / Base / Aggressive.
1. Growth drivers
Question
Placeholder
Confirm
Brands live today?
5
New brands over next 36 months?
4 / 6 / 8
Avg ad accounts per brand (Meta+Google+TikTok × markets)?
2.0 / 2.4 / 2.8
Monthly orders per brand today?
1,600
Ad spend RM/mo per brand today?
60,000
US: which month does it go live?
18 / 12 / 9
US: how much does it add (accounts/orders/spend)?
+30% / +40% / +50%
2. Labor being displaced — loaded RM/mo (salary + EPF/SOCSO + overhead) and the trigger to hire
Role
Loaded RM/mo
+1 hire per…
Confirm cost
Confirm ratio
Performance marketer
6,500
2.0 ad accounts
Graphic designer / creative
5,000
1.2 per brand
Social media manager
5,500
2 brands
CS agent
4,000
2,000 orders/mo
Data analyst
8,500
4 brands
Data engineer
12,000
8 brands
3. Current headcount (the flat baseline that does not grow)
Include your loaded salary as a cost line? (payback test)
No (RM18,000 if yes)
Revenue-lift % to attribute (faster iteration → ROAS)
0%
What the model says at these placeholders (Base case)
Payback: month 6.
By month 36: ~RM221k/mo of labor displaced vs ~RM13k/mo of spend → cumulative net ≈ RM3.7M.
Marginal economics: each additional brand adds ~RM609/mo of A+B+C cost against ~RM27,775/mo of labor avoided — cost is ~2% of the labor it offsets.
The tell: across all three scenarios, cumulative A+B+C spend barely moves (~RM400–425k) while cumulative labor avoided ranges RM2.3M → RM6.2M. Spend is decoupled from output — that is the lean-scaling thesis.
The one line to watch (honest finding)
The only cost lines that scale with output are Track-C usage — video/image generation (biggest), Claude API, scraping. Video gen is modelled per-brand, so it rises roughly linearly. At the placeholder rate its per-brand cost is a small fraction of labor avoided, so the thesis holds comfortably — but if creative volume per brand explodes or you lean on premium video at scale, that’s the line that could erode the gap. It’s the model’s key sensitivity (see the Dashboard).