# Car Wash Roll-Up Model A 5-year express car-wash roll-up that scales from 10 sites to 40+ on membership-led unit economics - per-site membership, retail-wash, and ancillary revenue, platform EBITDA after corporate overhead, an initial-platform-plus-acquisitions capital schedule with PIK debt, and a sponsor equity IRR / MOIC on a five-year exit. - Canonical: https://finamodel.com/templates/car-wash - Excel download: https://finamodel.com/templates/car-wash.xlsx - Category: Consumer - Model type: Operating model - Difficulty: Intermediate - Audiences: PE & buy-side, Founders & operators, PE associates and partners, Car-wash platform CFOs, M&A bankers, Acquisition lenders - Tags: car wash, roll-up, membership, private equity, multi-site ## Overview A car-wash roll-up model captures the five-year arc of an express car-wash platform - the PE thesis of acquiring single-site express tunnels at a low single-digit EBITDA multiple, converting pay-per-wash customers to unlimited monthly membership plans, running them through a shared platform (Mister Car Wash, Driven Brands, ZIPS, Whistle Express, GO Car Wash), and exiting at a premium multiple. The workbook runs across eight sheets - Cover, Assumptions, Site_Count, Revenue, P&L, Capital, Returns, Dashboard - plus the shared Disclaimer. Every input is a named-range cell and every formula is one or two operations long. The Site_Count sheet builds the panel roll-forward: opening sites carry from prior closing, acquired sites from the per-year input, closed sites from a small attrition rate, and closing sites fall out as opening + acquired - closed. Average site count drives the per-site revenue and cost lines so a mid-year acquisition is not double-counted. The Revenue sheet runs three streams off the average site count: membership (members x plan price x 12 x sites), retail wash (washes per day x operating days x ticket x sites), and ancillary (a percent of wash revenue for vacuums and vending), each growing at the per-site growth rate. The P&L sheet is the cost stack diligence cares about: site labour, utilities, land lease, and repairs & maintenance are per-site costs scaled by average sites; chemicals & water and marketing are percent-of-revenue lines; corporate overhead is a base plus per-site add-on. EBITDA, D&A, EBIT, tax on positive EBIT, and net income flow out with margins and a P&L identity check. The Capital sheet buys the starting platform at Year 0 and then deploys annual acquisitions at trailing EBITDA x purchase multiple, splitting each into sponsor equity and acquisition debt that accrues PIK interest into a cumulative balance. The Returns sheet runs the sponsor's IRR stream - a Year 0 platform-equity outflow, per-year acquisition-equity outflows, and a Year 5 exit inflow equal to enterprise value (Y5 EBITDA x exit multiple) less cumulative debt - and reports sponsor IRR, MOIC, blended entry multiple, and the entry-vs-exit multiple arbitrage that is the headline value driver. The Dashboard collapses Y5 revenue, EBITDA, EBITDA margin, site count, IRR, MOIC, exit enterprise value, and a revenue mix by stream, with traffic-light status flags against user-set thresholds. The defaults reflect a realistic mid-size roll-up (10 starting sites, ~6 acquisitions per year, ~$1.0M revenue per site, mid-30s mature EBITDA margin, 8.0x entry multiple, 11.5x exit multiple) producing ~27% sponsor IRR and ~2.0x MOIC - flex the inputs to model a specific target portfolio. ## What's included - Site-count roll-forward (opening + acquired - closed) with average sites driving revenue and cost - Per-site revenue by stream: membership, retail wash, and ancillary, with annual growth - P&L to platform EBITDA after site labour, chemicals, utilities, lease, R&M, marketing, and corporate overhead - Capital sheet: initial platform purchase plus annual acquisitions at trailing-EBITDA multiples with PIK debt - Returns with sponsor IRR, MOIC, blended entry multiple, and exit multiple arbitrage - Dashboard with Y5 headline metrics, revenue mix, and traffic-light status against thresholds - P&L from revenue through site labour, chemicals, utilities, lease, R&M, marketing, and corporate overhead to EBITDA - Returns sheet with sponsor equity IRR, MOIC, blended entry multiple, and exit multiple arbitrage - Dashboard with Y5 headline metrics, revenue mix, and traffic-light status against user-set thresholds ## Car Wash Roll-Up Model: A Five-Year Operating and Returns Template The Car Wash Roll-Up Model is a five-year operating template for an express car-wash platform that scales from 10 to over 40 sites via acquisitions and membership conversion. It builds site count, revenue, EBITDA after corporate overhead, acquisition capital with PIK debt and a cash sweep, and sponsor equity IRR and MOIC on a five-year exit. ### How the Site Panel and Membership Ramp Drive Revenue The operating engine starts with the site panel: opening sites plus acquisitions less closures define the annual average site count used across revenue and cost lines. Per-site revenue flows from three streams: membership (members per site times monthly plan price times twelve), retail washes (washes per day times operating days times ticket), and ancillary revenue as a percentage of wash revenue. - Per-site revenue grows at a compounded rate. A vintage-weighted membership ramp factor holds new sites below mature penetration for a set period, reflecting the time needed to convert pay-per-wash customers. - The model's illustrative defaults include 4–8 annual acquisitions, 1,800 members per site at $25 per month, 85 daily washes at $13, 8% ancillary, and 3% per-site growth. ### From Revenue to EBITDA: Cost Structure and Platform Overhead Revenue builds by stream feed a P&L where site-level costs include labour, chemicals and water as a percentage of revenue, utilities, land lease, repairs and maintenance, and marketing as a percentage of revenue. Corporate overhead is modelled as a base amount plus a per-site add-on, capturing the shared platform drag as the panel grows. - EBITDA is revenue less total operating expenses, and the model also deducts depreciation and amortisation, interest, and tax on positive EBIT only. Illustrative defaults show a thin initial EBITDA margin that expands as the membership base matures and the fixed corporate base spreads over more sites. - The model includes a P&L identity check and tracks EBITDA margin and net margin. ### Capital Deployment, Debt Schedule and the Membership Arbitrage Thesis Capital deployment starts with the initial platform purchase at Year 0: starting sites times trailing EBITDA times the entry multiple, split into platform equity and platform debt. Each year, acquisitions are funded by sponsor equity and acquisition debt. - Interest accrues via PIK on the opening debt balance, and a cash sweep uses a percentage of platform free cash flow to pay down debt, capped so the balance cannot go negative. Cumulative equity is seeded from platform equity and grows with each acquisition. - The model's illustrative defaults include an 8.0x entry multiple, $320k trailing EBITDA per acquired site, 50% sponsor equity, a 7% debt rate, and a 50% cash sweep. This structure underpins the multiple arbitrage thesis of buying single sites and exiting a scaled platform at 11.5x. ### Returns and Dashboard: Sponsor IRR, MOIC and Exit Value The returns view builds a sponsor equity cash flow: a Year 0 outflow for platform equity, annual acquisition equity outflows, platform free cash flow, and a Year 5 exit inflow. Exit enterprise value equals Year 5 EBITDA times the exit multiple. - Net debt at exit is cumulative debt after the cash sweep, and equity proceeds are exit EV less net debt. The model calculates sponsor IRR, MOIC, blended entry multiple, and multiple arbitrage. - The dashboard surfaces Year 5 revenue, EBITDA, EBITDA margin, site count, sponsor IRR, MOIC, exit enterprise value, and revenue mix by stream, with traffic-light formatting on margin and IRR KPI cards against assumed thresholds. Illustrative defaults show about 32% IRR and 2.3x MOIC, but these are model outputs, not market benchmarks. Calculation summary: ```text Exit enterprise value = Year 5 EBITDA × the exit multiple ``` ## Built for platform underwriting The roll-up question is not one site forecast but whether buying sites at a low entry multiple and exiting a scaled platform at a premium clears the equity hurdle. This model makes that arbitrage explicit. ## Designed around membership economics Express car-wash value is driven by unlimited monthly membership penetration, which smooths weather seasonality and lifts per-site EBITDA. Members per site and plan price are first-class inputs. ## Audit-friendly mechanics Every input is a named range, every formula is one or two operations, and the workbook passes static-value, self-reference, dead-assumption, and unused-named-range scans. ## Built for platform underwriting The roll-up question is not one site forecast but whether buying sites at a low entry multiple and exiting a scaled platform at a premium clears the equity hurdle. This model makes that arbitrage explicit. ## Designed around membership economics Express car-wash value is driven by unlimited monthly membership penetration, which smooths weather seasonality and lifts per-site EBITDA. Members per site and plan price are first-class inputs. ## Audit-friendly mechanics Every input is a named range, every formula is one or two operations, and the workbook passes static-value, self-reference, dead-assumption, and unused-named-range scans. ## Workbook structure ### Cover Workbook overview, sheet legend, and tab-colour key for navigation. - Title and scope framing - Sheet-by-sheet purpose summary - Tab-colour legend ### Assumptions Every driver in one sheet: site panel, per-site revenue, cost structure, M&A inputs, and dashboard thresholds. - Starting sites, annual acquisitions, closure rate - Members per site, plan price, retail washes, ticket, ancillary % - Site labour, chemicals, utilities, lease, R&M, marketing, corporate overhead - Purchase multiple, trailing EBITDA per site, sponsor equity %, exit multiple, debt rate ### Site_Count Panel roll-forward with opening, acquired, closed, closing, and average sites. - Opening carries from prior closing - Acquired from per-year input, closed from attrition rate - Closing = opening + acquired - closed - Average (open/close mean) drives revenue and cost ### Revenue Per-site revenue by stream multiplied across the panel. - Membership = members x plan price x 12 x sites - Retail wash = washes/day x operating days x ticket x sites - Ancillary = percent of wash revenue - Total revenue and revenue per site ### P&L Revenue to net income with margins. - Per-site labour, utilities, lease, and R&M scaled by average sites - Chemicals & water and marketing as percent of revenue - Corporate overhead base plus per-site add-on - EBITDA, D&A, EBIT, tax on positive EBIT, net income, and margins ### Capital Initial platform purchase plus annual acquisition deployment. - Year-0 platform spend split into equity and debt - Annual acquisition spend = sites x trailing EBITDA x purchase multiple - Sponsor equity and acquisition debt per year - Cumulative equity and cumulative debt with PIK interest ### Returns Sponsor equity IRR and MOIC on a five-year hold. - Equity cashflow: Year-0 platform equity, per-year acquisition equity, Year-5 exit inflow - Exit EV = Y5 EBITDA x exit multiple, less cumulative debt - Sponsor IRR, MOIC, equity invested, equity proceeds - Blended entry multiple and exit multiple arbitrage ### Dashboard Y5 headline metrics and revenue mix with status flags. - Y5 revenue, EBITDA, EBITDA margin, site count - Sponsor IRR, MOIC, exit enterprise value, multiple arbitrage - Y5 revenue mix by stream - Traffic-light status against user-set thresholds ### Cover Workbook overview, sheet legend, and tab-colour key for navigation. - Title and scope framing - Sheet-by-sheet purpose summary - Tab-colour legend ### Assumptions Every driver in one sheet: site panel, per-site revenue, cost structure, M&A inputs, and dashboard thresholds. - Starting sites, annual acquisitions, closure rate - Members per site, plan price, retail washes, ticket, ancillary % - Site labour, chemicals, utilities, lease, R&M, marketing, corporate overhead - Purchase multiple, trailing EBITDA per site, sponsor equity %, exit multiple, debt rate ### Site_Count Panel roll-forward with opening, acquired, closed, closing, and average sites. - Opening carries from prior closing - Acquired from per-year input, closed from attrition rate - Closing = opening + acquired - closed - Average (open/close mean) drives revenue and cost ### Revenue Per-site revenue by stream multiplied across the panel. - Membership = members x plan price x 12 x sites - Retail wash = washes/day x operating days x ticket x sites - Ancillary = percent of wash revenue - Total revenue and revenue per site ### P&L Revenue to net income with margins. - Per-site labour, utilities, lease, and R&M scaled by average sites - Chemicals & water and marketing as percent of revenue - Corporate overhead base plus per-site add-on - EBITDA, D&A, EBIT, tax on positive EBIT, net income, and margins ### Capital Initial platform purchase plus annual acquisition deployment. - Year-0 platform spend split into equity and debt - Annual acquisition spend = sites x trailing EBITDA x purchase multiple - Sponsor equity and acquisition debt per year - Cumulative equity and cumulative debt with PIK interest ### Returns Sponsor equity IRR and MOIC on a five-year hold. - Equity cashflow: Year-0 platform equity, per-year acquisition equity, Year-5 exit inflow - Exit EV = Y5 EBITDA x exit multiple, less cumulative debt - Sponsor IRR, MOIC, equity invested, equity proceeds - Blended entry multiple and exit multiple arbitrage ### Dashboard Y5 headline metrics and revenue mix with status flags. - Y5 revenue, EBITDA, EBITDA margin, site count - Sponsor IRR, MOIC, exit enterprise value, multiple arbitrage - Y5 revenue mix by stream - Traffic-light status against user-set thresholds ## Features - **Membership-led unit economics:** Revenue builds from members per site and monthly plan price alongside retail throughput, so the subscription and pay-per-wash mix is explicit and flexable. - **Multiple arbitrage made visible:** Buy single sites at a low entry multiple and exit a scaled platform at a premium; the entry-vs-exit spread is a headline dashboard metric. - **Honest roll-up returns:** The sponsor buys the starting platform at Year 0, so the initial sites carry real equity and leverage rather than landing in the exit for free. ## Use cases - **Platform underwriting:** Flex acquisition pace, membership penetration, and the exit multiple to test whether a car-wash platform clears the equity hurdle. - **Acquisition debt sizing:** Lenders use the per-site trailing EBITDA and cumulative debt schedule to size facilities against forward platform cash flow. - **Board and IC reviews:** Hand the Dashboard to the investment committee or board as a single-page snapshot of EBITDA, margin, site count, IRR, and MOIC. ## Frequently asked questions ### What is a car-wash roll-up model? It is a model that captures the economics of acquiring multiple express car-wash sites, converting customers to monthly memberships, running them through a shared platform, and exiting the scaled portfolio at a premium EBITDA multiple. ### How is car-wash revenue built? Per site, membership = members x monthly plan price x 12, retail wash = washes per day x operating days x ticket, and ancillary is a percent of wash revenue. Each scales by average site count and a per-site growth rate. ### Why buy the starting platform at Year 0? Without an initial platform purchase the starting sites would contribute to the exit value for free and overstate returns. The model buys them at Year 0 so they carry real equity and opening debt. ### What entry and exit multiples are realistic? Single express car-wash sites typically trade around 7-9x EBITDA; scaled platforms exit nearer 11-15x. The defaults use 8.0x entry and 11.5x exit, a 3.5x multiple arbitrage. ### How is the sponsor IRR calculated? The Returns sheet builds an equity cashflow stream - a Year-0 platform-equity outflow, per-year acquisition-equity outflows, and a Year-5 inflow equal to exit enterprise value less cumulative debt - and IRR and MOIC fall out. ## Related templates - [Pet Care Roll-Up Model](https://finamodel.com/templates/pet-care) - [Leveraged Buyout Model](https://finamodel.com/templates/lbo-model) - [Unit Economics Dashboard](https://finamodel.com/templates/unit-economics-model)