How to Model Evolving Cost Structures for Reliable Cash Runway Forecasts

The Evolution of Cost Structures in Startup Financial Models

Your first financial model was probably a masterpiece of simplicity. You took your current costs, slapped a growth percentage on them, and projected a neat, linear path to profitability. For a pre-seed company, that's often enough. But as you scale, that model starts to break. The numbers you pull from QuickBooks or Xero no longer match the straight lines in your spreadsheet. You sense that hiring one more person or landing ten more clients has a disproportionate impact on your cash burn, but your forecast doesn't explain why. This isn't a sign of failure; it’s a signal that your cost structure is evolving. Learning how to model cost structure as my startup scales is less about complex accounting and more about understanding the non-linear realities of growth, which is critical for timing hires, managing runway, and successfully fundraising.

Deconstructing Your Costs: The Foundational Split

Before we can project the future, we must understand the present. The first step is to move beyond a simple list of expenses and categorize them by their behavior. Whether you are a US company using US GAAP or a UK startup on FRS 102, the principles are the same. Look at your chart of accounts and assign each line item to one of three categories to understand your variable vs fixed expenses.

Fixed Costs

Fixed costs are expenses that do not change in the short term, regardless of how many customers you serve or products you sell. These are the costs of being in business, forming your baseline cash burn. Think of office rent, executive salaries, insurance premiums, and your core software subscriptions, like your accounting platform itself. They are predictable month to month, within a certain range of activity.

Variable Costs

Variable costs scale directly and proportionally with revenue-generating activity. For an E-commerce business on Shopify, this is your Cost of Goods Sold (COGS) and the payment processing fees from Stripe for each transaction. For a SaaS company, it's the hosting costs on AWS that increase with user activity. For a Professional Services firm, it's the hourly wages of contractors assigned to a specific client project.

Semi-Variable Costs

These costs are a hybrid, with both a fixed base and a variable component. A common example is a sales team's compensation, which includes a fixed base salary plus a variable commission based on the deals they close. Another is a utility bill with a fixed monthly service charge plus a variable fee based on usage. At this stage, the primary challenge is getting this separation right. The goal is to understand which costs you incur just to keep the lights on versus which ones are directly tied to growth.

How to Model Cost Structure as My Startup Scales: Beyond the Basics

Why don't costs just scale up in a straight line as a simple model assumes? The basic fixed versus variable split is a great start, but it doesn't capture the whole picture of scaling costs in startups. The reality for most Pre-seed to Series B companies is that costs don't move in smooth lines; they move in jumps and curves. Recognizing these patterns is the key to accurate expense forecasting for founders.

The Step-Function: Modeling When Fixed Costs Suddenly Jump

A step-function cost is a type of fixed cost that remains flat over a certain level of activity, then suddenly jumps to a new, higher level once a threshold is crossed. This is one of the most common sources of forecasting errors because it turns a predictable, "fixed" expense into a sudden cash outlay that can shorten your runway unexpectedly.

A scenario we repeatedly see is with customer support teams in SaaS startups. Imagine your startup needs one full-time support representative for every 100 active customers to maintain service levels. The annual cost for that rep is a fixed $60,000.

• From 1 to 100 customers, your support cost is fixed at $60,000.
• The moment you sign your 101st customer, you must hire a second representative. Your cost doesn't gradually increase; it instantly jumps to $120,000.
• It stays at $120,000 until you hit 201 customers, at which point it jumps again to $180,000.

This isn't a variable cost that grows with each customer, but a fixed cost that changes in large, discrete steps. Other common examples include needing to rent a larger office or warehouse once you exceed your current capacity, or upgrading to a more expensive enterprise tier of a critical software tool after crossing a user limit. Failing to model these jumps means underestimating future cash needs significantly.

To model this in a spreadsheet, you can use a formula that calculates the number of "steps" needed. Instead of a messy nested IF statement, a ROUNDUP function is cleaner and more scalable. If your customer count is in cell B2, the formula to calculate total support salary would be:

=ROUNDUP(B2/100, 0) * 60000

This formula divides the number of customers by the threshold (100), rounds the result up to the nearest whole number to get the required number of reps, and multiplies by the salary. This single line creates a much more accurate forecast for hiring-related expenses. To implement this cleanly, model this in a spreadsheet where you can separate drivers and formulas in a dedicated layout, making your assumptions easy to audit and update.

The Curve: Modeling Economies and Diseconomies of Scale

Other costs don't jump in steps but follow a curve, becoming progressively cheaper or more expensive on a per-unit basis as you scale. This is where understanding unit economics for SaaS and identifying key cost drivers in e-commerce becomes vital for reliable financial modeling for growth.

Economies of Scale: The Downward Curve

This is the positive curve every founder hopes for. As your volume increases, your per-unit cost decreases, which is a key component of operational leverage explained. The classic example is in e-commerce inventory purchasing. A supplier might offer volume discounts: the more you buy, the cheaper each unit becomes.

• 1-500 units: $10 per unit
• 501-2000 units: $9 per unit
• 2001+ units: $8 per unit

You can model this in your spreadsheet using a VLOOKUP or LOOKUP function against a small assumptions table. This allows your model to automatically adjust your COGS based on your projected sales volume, improving the accuracy of your gross margin and cash flow projections. Another example is marketing spend, where buying media in bulk may unlock lower rates.

Diseconomies of Scale: The Upward Curve

More challenging, and often overlooked, is the upward curve, where unit costs increase as you scale. This is a trap that catches many scaling startups. The most common driver of this is Customer Acquisition Cost (CAC) saturation. Your first customers are often the cheapest to acquire through your most efficient marketing channels. To get the next wave of customers, you have to spend more, either by bidding more on competitive keywords, moving to less efficient channels, or hiring a more expensive sales team. This means your marginal CAC increases.

The pattern across high-growth startups is consistent: the cost to acquire the 10,000th customer is almost always higher than the cost to acquire the 1,000th. This isn't just a theory. A 2021 ProfitWell study of over 2,500 SaaS companies found that Customer Acquisition Cost (CAC) has increased by over 60% in the five years prior. Assuming your CAC will remain flat is one of the fastest ways to build an unreliable forecast and run out of cash sooner than expected.

Other diseconomies can include increased management overhead, as you need more managers who don't directly generate revenue. Operational complexity can also rise, requiring more expensive systems, compliance staff, or specialized finance teams to manage the business, pushing general and administrative costs up as a percentage of revenue.

Putting It Into Practice: Building a Dynamic Forecast

How do you translate these concepts into your spreadsheet without creating an unmanageable mess? The key is to build a drivers-based forecast. Instead of typing in fixed numbers for your expenses each month, you create a dedicated 'Assumptions' tab in your Google Sheet or Excel file. This tab becomes the engine of your model.

1. Identify Key Business Drivers: On your Assumptions tab, list the core metrics that drive your business. For a SaaS company, this might be new customers, total active customers, and churn rate. For an E-commerce business, it could be website sessions, conversion rate, and average order value.
2. Define Cost Relationships: For each expense line item, define its relationship to a driver. This is where you will house your step-function thresholds (e.g., 1 support rep per 100 customers) and your VLOOKUP tables for economies of scale (e.g., COGS volume discounts). Define your marginal CAC assumptions here as well, perhaps with tiers based on total customer count.
3. Model Your P&L with Formulas: In your main financial statement tabs, replace hard-coded expense values with formulas that reference your Assumptions tab. For example, your 'Salaries - Support' line will now be driven by the ROUNDUP formula which is, in turn, driven by your projected customer count. Your marketing spend will be driven by your new customer target and your tiered CAC assumptions.

This approach separates your assumptions from your outputs, making your financial model dynamic. It allows you to easily test scenarios, which is where the value of a drivers-based model becomes obvious. What happens to my runway if CAC increases by 20%? Test scenarios and sensitivity analysis to find out. How many months of cash do we gain if we can handle 120 customers per support rep instead of 100? This conversion of changing unit economics into a reliable cash-flow forecast is exactly what investors want to see and what you need to manage the business effectively.

Common Mistakes in Modeling Scaling Costs in Startups

As you build a more sophisticated model, be wary of common pitfalls that can undermine its accuracy. Avoiding these mistakes is as important as implementing the right techniques.

• Applying a Universal Growth Rate: The most common error is applying a single growth percentage (e.g., 10% month-over-month) to all expense lines. This ignores the different behaviors of fixed, variable, and step-costs, leading to a fundamentally flawed projection.
• Assuming Flat Unit Economics: Another frequent mistake is assuming your COGS per unit or CAC will remain constant forever. This misses both the positive impact of economies of scale and the dangerous negative impact of diseconomies.
• Forgetting People Thresholds: Founders often neglect to model the large cash jumps required for new hires, especially in non-revenue generating roles like operations, HR, or finance. These hires are step-costs that must be anticipated.
• Ignoring the Cash Impact of Growth: It's possible to build a perfect accrual-based P&L but forget that hiring, inventory purchases, and annual software prepayments are cash events. These activities impact your runway immediately, a fact that a pure P&L model can hide.

Practical Takeaways for a More Reliable Forecast

The transition from a simple, static financial model to a dynamic one is a sign of operational maturity. It reflects a deeper understanding of how your business actually works. The goal isn't to create an impossibly complex spreadsheet, but to build a more realistic tool for decision-making and cash management.

Start small. Pick one or two costs that you know do not behave linearly, like customer support hiring or inventory costs, and model them dynamically first. This small change will immediately improve the reliability of your forecast. What founders find actually works is incrementally adding complexity only where it matters most, focusing on the largest and most volatile expense lines.

By embracing the reality of step-functions and cost curves, you move from simply reporting on the past to intelligently anticipating the future. This gives you a clearer view of your operational leverage, improves conversations with investors, and most importantly, helps you manage your cash runway with far greater confidence. For more frameworks, see the Building Financial Forecasts hub.

Frequently Asked Questions

Q: At what stage does this level of detail in cost modeling become critical?
A: Generally, this becomes crucial around the Seed to Series A stage. When you begin scaling your team and customer base rapidly, linear projections break down. Investors at this stage will expect a drivers-based model that reflects a nuanced understanding of your unit economics and scaling costs.

Q: How often should I update the assumptions in my cost model?
A: Your financial model should be a living document. Review and update your core assumptions at least quarterly, or whenever a significant event occurs, such as a major price change from a supplier, a new marketing channel performing differently than expected, or a change in your hiring plan.

Q: How should I model G&A costs like finance and HR that don't scale with a single driver?
A: These costs are often best modeled as step-functions. For example, you might decide you need to hire a full-time finance manager when you reach 50 employees or a dedicated HR person at 75 employees. You can use these employee count thresholds as the drivers for these specific hiring step-costs.