New Store Expansion Model
This use case explains how to build a new store expansion model in Model Reef for retail businesses.
You will use branches to represent existing and planned stores, capex and pre opening costs for new locations, store specific revenue and cost drivers, and valuation outputs to assess the economics of expansion.
When to use this pattern
Use this pattern when:
You are planning to open one or more new stores in an existing retail network.
You want to understand how new stores affect group P&L, cash and funding needs.
You need to compare different rollout speeds or location strategies.
This pattern builds on Store Level P&L Modelling and Inventory and Replenishment Planning.
Architecture overview
The expansion model includes:
Branch structure
Existing stores.
New store branches for planned openings.
Head office or group branch.
New store drivers
Ramp up for traffic, conversion and basket size.
Store specific cost and staffing assumptions.
Capex and pre opening expenses.
Outputs and evaluation
Store level and group P&L.
Cashflow and funding requirements.
Store level and network level IRR and payback.
Steps
Start from an existing store-level model
Begin with a working store level model as described in Store Level P&L Modelling:
Existing store branches with revenue, COGS, Opex and staff.
Head office and central costs in a separate branch.
Inventory purchasing and timing where relevant.
Clone this model to create a dedicated expansion planning model, for example:
Retail - Expansion Plan Model.
This keeps your planning scenarios separate from day to day operational models.
Add branches for planned new stores
In the expansion model, add branches for each new store, for example:
Group.Store 01(existing).Store 02(existing).New Store A.New Store B.
For each new store branch:
Copy the variable structure from an existing store that is similar in format.
Clear or adjust assumptions so they represent a new store rather than a mature store.
This gives you a consistent starting point for each planned location.
Model new store capex and pre opening costs
For each new store branch, add Asset and Opex variables to represent:
Fitout and build costs as Assets with depreciation schedules.
Equipment and fixtures.
Pre opening marketing and training as Opex.
Any lease incentives or landlord contributions if material.
Use timing and delays to align spending with the planned opening date, for example:
Fitout capex over the three to six months before opening.
Pre opening marketing in the one or two months before opening.
This allows the Cashflow Statement and Cash Waterfall to show the investment phase clearly.
Build new store revenue ramp up
New stores rarely trade at steady state from day one. For each new store branch:
Define ramp up drivers in the Data Library, for example:
Ramp - Store A - Footfall.Ramp - Store A - Conversion.Ramp - Store A - Average Basket.
Set the ramp so that:
Early months have lower volumes or conversion.
The store reaches a target steady state after a defined period (for example 12 to 24 months).
Use these drivers in store revenue variables, combining with base assumptions for mature stores where appropriate.
You can calibrate ramp patterns using historical data from previous new store openings.
Set new store staffing and operating costs
For each new store, configure Staff and Opex variables to reflect:
Pre opening staff build up.
Full staffing levels after opening.
Fixed and variable components of store operating costs.
Be explicit about:
Store manager and core staff.
Casual or part time staff that scale with traffic or sales.
Rent and occupancy costs based on the specific lease.
This ensures that store level P&L shows both ramp up losses and later profitability.
Evaluate store and network level economics
With branches configured, use Model Reef outputs to assess:
Store level P&L and cash contributions over time.
Network level P&L and cash including existing stores and new stores.
Peak funding requirement caused by capex and early operating losses.
Store specific metrics such as:
Time to break even.
Cash payback period for store level capex.
Use the valuation engine to compute store or network level IRR and Money Multiple if needed, by treating capex as investments and store contributions as returns.
Explore rollout scenarios
To compare different expansion strategies:
Create separate models for alternative scenarios, for example:
Expansion Plan - Slow Rollout.Expansion Plan - Base Rollout.Expansion Plan - Fast Rollout.
Vary:
Number of new stores.
Opening dates.
Capex per store.
Ramp assumptions.
Compare outcomes for:
Peak and cumulative funding requirements.
Network profitability timelines.
Store level economics.
This helps management choose a rollout strategy that matches capital availability and risk appetite.
Check your work
New store branches are clearly identifiable and separate from existing stores.
Capex, pre opening costs and ramp assumptions align with realistic timelines.
Group P&L and cashflow clearly show the impact of expansion on performance and funding.
Results are easy to explain to non modelling stakeholders.
Troubleshooting
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