I've done a bunch of financial models for clients that need to understand the monthly cash flow effects of opening physical locations over time. There are a few different approaches to this, which I'll discuss below. Most of the industry-specific models I have are for bottom-up assumptions of a single location and planning all the economics of that, but I also have a few broad-based models that can plan 12 to 25 locations. For clients, I've done them for arbitrarily large scaling plans.
Relevant Templates:
Factors to Consider:
- Let's say we want to model opening up an arbitrarily large number of new car washes over time.
- First, we need to know if it makes sense to categorize the new locations. For example, there could be low volume, mid volume, and high-volume locations and each one has its own key variables.
- Then, we need to know what makes sense to configure for each location, such as:
- Development costs or acquisition costs (Is this cost incurred at the start month, or evenly spread over a period, or a % that defines the total development cost that is spent over a defined start/end month relative to the start month of the given location) If it is an acquisition, that cost would typically be incurred at the start month.
- The start month of revenue relative to the start month of development (or acquisition)
- The expected revenue growth rate (is it annual, is it custom for the first 12 or 24 months and then has a normalized growth)?
- The starting revenue and how is that derived i.e. are you just going to input a single high-level number or have bottom-up assumptions for each location type that drive the expected revenue. For large scaling plans, usually a single starting revenue figure is just defined.
- Debt / equity assumptions for each location type for example, what percentage of the acquisition / development costs are going to come from investors vs. traditional loans and what are the terms on the loans.
- You need to know the variable costs associated with each location or location type. This could be the average cost of goods sold and anything else that makes sense to define as a percentage of revenue.
- There could also be fixed costs for each location type, such as property taxes, wages, and other things that don't make sense to define as a percentage of revenue but do need an input for and an annualized growth input for.
- Once you have all the variables you want to configure for each location, you've got to come up with a way to make all the things that were just discussed flow into a financial statement format dynamically and on the same timeline. Usually, I like to use a matrix style cohort modeling approach.
- This style will tell the user how much it costs on an aggregate basis to acquire and/or develop retail locations over time, and account for all the revenue timing nuances.
Article found in General Industry.
