Overview

 This is a general 5-year financial model with dynamic assumptions for opening up (developing or acquiring) and operating up to 25 retail locations. The revenue growth drivers make it easy to show your strategy for cash generation and re-investment. Each location has separate assumptions for:

  • Initial Investment
  • Average Item/Service Price (3 slots)
  • Maximum Sales per Day
  • Percentage of Sales that fall into each item slot
  • Percentage of capacity attained in first 12 months (variable by month)
  • Labor Headcount in first 12 months (average labor rate and increase therein)
  • Average labor hours per week per head
  • Average cost of goods sold and inventory purchasing schedule (if not relevant the user can enter a 1 on this input)

The idea behind this assumption architecture is that it can fit any type of business broadly speaking and there are enough variables in the drivers to tweak the numbers so it is able to fit any strategy. The main global assumption is that the locations become stabilized within 12 months although there is an input that allows the maximum capacity to grow in each of the 5 years.
There are also general operating costs to account for district managers, corporate overheads, marketing, and other on-going expenses that don’t fall into labor or cost of goods sold as well as a few catch-all costs that can be defined as a percentage of total revenues.
General output summaries include:

  • 5-year monthly and annual P&L Detail
  • 5-year annual contribution/distribution summary
  • 5-year DCF Analysis (project/investor/operator)
  • Dynamic visualizations (16)

There are some global assumptions that determine start year, exit year and exit multiple if applicable, funding sources (debt and/or equity) as well as a corporate tax rate. Separate schedules also exist for one-off startup costs and other capex items not already accounted for.
All the assumptions are taken into consideration and flow nicely to the same 5-year monthly and annual model timeline so it is easy to see how the operation scales up to ‘n’ locations and what the cash flow looks like within that.

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