Real-world examples of expense forecasting for business plans

Examples of expense forecasting example for different business models

The fastest way to understand forecasting is to study real examples. So instead of starting with definitions, let’s look at how different types of companies actually build an expense forecast inside a business plan.

SaaS startup: examples of expense forecasting example by department

Take a seed‑stage SaaS startup with $50,000 in monthly recurring revenue and a plan to triple ARR in 18 months. The finance lead breaks the expense forecast into a few core buckets: people, software, marketing, and overhead.

People costs are forecasted headcount by role and start date. For instance, they might plan:

• 3 new engineers starting in March at $130,000 per year each
• 1 sales rep in May at $90,000 base plus 10% commission
• 1 customer success manager in July at $80,000

Instead of a flat number, this example of an expense forecast layers in:

• Salary start dates (partial months when someone joins mid‑month)
• Payroll taxes at, say, 8–10% of gross payroll (using IRS guidance as a reference point: https://www.irs.gov/businesses/small-businesses-self-employed/employment-taxes)
• Benefits at a fixed cost per employee, such as $700 per month for health insurance

Software and tools are forecasted as a mix of per‑seat and flat‑rate subscriptions. Examples include:

• Developer tools at $60 per user per month, scaling with every new engineer
• CRM at $50 per user per month, scaling with sales and success hires
• Cloud hosting at 10–15% of revenue, increasing as customers grow usage

This is one of the best examples of expense forecasting example in a SaaS plan because it connects cost drivers directly to growth: more users and more employees automatically push software and hosting costs higher in the model.

E‑commerce brand: examples include variable costs tied to orders

For an e‑commerce brand, the most important examples of expense forecasting example revolve around variable costs per order. Instead of starting with salaries, they start with:

• Cost of goods sold (COGS) per unit
• Shipping and fulfillment per order
• Payment processing fees as a percentage of sales

Suppose the brand sells a $60 product. Their forecast might assume:

• COGS of $18 per unit
• Shipping of $7 per order (using current carrier rate tables from USPS or UPS)
• Payment processing of 2.9% + $0.30 per transaction

If the marketing team plans to grow from 2,000 to 5,000 orders per month over 12 months, the forecast multiplies those unit costs by forecasted order volume. This gives a granular example of how expenses scale with revenue, not just over time.

On top of that, fixed expenses like warehouse rent, a flat Shopify subscription, and a 3‑person operations team are layered in. The real examples that investors like to see show:

• A clear split between variable and fixed expenses
• Sensitivity to shipping rate changes or supplier price increases
• Seasonality (e.g., Q4 spikes in marketing and fulfillment labor)

Brick‑and‑mortar retail: example of location‑driven expense forecasting

A physical retail store offers another strong example of examples of expense forecasting example, because location drives most of the cost structure. When preparing a business plan, the owner might forecast:

• Rent based on square footage and local market comps
• Utilities using historical averages from similar properties
• Insurance and property taxes using local government data

For instance, a 2,000‑square‑foot store in a mid‑tier U.S. city might budget:

• Rent at \(32 per square foot per year → about \)5,333 per month
• Utilities at \(1.50 per square foot per year → about \)250 per month
• Insurance at $300 per month, based on quotes

Labor is forecasted using store hours and staffing patterns. If the store plans to be open 70 hours a week, the owner might forecast:

• 1 manager at 40 hours/week, $22/hour
• 2 part‑time associates at 20 hours/week each, $16/hour

The model then applies overtime rules, payroll taxes, and expected annual raises. This example of forecasting shows how regulations and local wage trends matter. When you’re writing your plan, referencing official sources such as the U.S. Bureau of Labor Statistics for wage data (https://www.bls.gov) adds credibility.

Professional services: examples include utilization‑based forecasts

Consulting firms, agencies, and law practices are great real examples of expense forecasting where people’s time is the main cost driver. A small marketing agency may forecast expenses based on billable utilization:

• Each strategist is expected to bill 70% of their time
• Each designer is expected to bill 75% of their time

Expenses are then forecasted by:

• Salaries and benefits for all billable staff
• A load factor for non‑billable staff (admins, finance, leadership)
• Office and software costs allocated per employee

For example, if the agency plans to hire 3 new designers next year, the expense forecast doesn’t just add salaries. It also adds:

• Extra Adobe licenses
• Higher project management tool costs
• A proportional share of rent and utilities

This is one of the best examples of expense forecasting example for service businesses because it shows how each new hire affects both direct and overhead costs.

Manufacturing: examples of fixed vs. variable production expenses

Manufacturers must forecast both fixed plant costs and variable production costs. A small electronics manufacturer might break expenses into:

• Direct materials per unit
• Direct labor per unit
• Factory overhead

Suppose a device costs \(40 in materials and \)10 in direct labor per unit at current volumes. The plant lease, equipment depreciation, and maintenance are mostly fixed. The expense forecast then tests what happens if:

• Volume doubles (spreading fixed costs over more units)
• Component prices rise 8% (not unusual in certain supply cycles)
• Overtime is needed to meet seasonal demand

These real examples of forecasting let management test different production scenarios. Citing industry or trade association data, or U.S. Census manufacturing statistics (https://www.census.gov/programs-surveys/asm.html), can help anchor assumptions.

Building a monthly expense forecast: a practical example of structure

Across all these examples of expense forecasting example, the structure of the model matters as much as the numbers. A solid monthly forecast usually has:

1. Clear categories
Rather than a long, unorganized list of line items, you group expenses into:

• Cost of goods or direct costs
• Payroll and benefits
• Marketing and sales
• General and administrative (G&A)
• Facilities and equipment

Each category has its own drivers. Payroll is driven by headcount and salaries. Marketing might be driven by a percentage of revenue or a fixed media plan. Facilities are often driven by square footage and local prices.

2. Time‑based logic
Good real examples of expense forecasting show how costs change month to month, not just annually. For instance:

• Rent might increase 3% on lease renewal in month 13
• Health insurance might jump 6% at the start of each calendar year, reflecting recent trends in employer health costs reported by sources like the Kaiser Family Foundation (https://www.kff.org)
• Marketing spend might spike during key sales periods (e.g., back‑to‑school, Black Friday)

3. Cash vs. accrual thinking
An underappreciated example of expense forecasting nuance is the difference between when an expense is incurred and when cash leaves the bank. A SaaS company might pay an annual software contract upfront in January but amortize it monthly in the P&L. Your forecast can show both views:

• The P&L view: $1,200 per month for software
• The cash view: $14,400 outflow in January

That single modeling choice can change whether your cash runway looks like 18 months or 12.

2024–2025 trends that should shape your expense forecasts

If you want your business plan to feel current, your examples of expense forecasting example should reflect real‑world 2024–2025 conditions.

Wage inflation and labor shortages
Many industries in the U.S. are still dealing with elevated wage pressures, especially in healthcare, hospitality, logistics, and tech. Forecasts that assume flat wages for three years look naive. Better examples include:

• Annual wage increases of 3–5% for most roles
• Higher starting wages in competitive markets
• Extra recruiting and retention costs (sign‑on bonuses, referral programs)

You can support your assumptions with data from the Bureau of Labor Statistics Employment Cost Index (https://www.bls.gov/eci/).

Remote and hybrid work
Post‑pandemic, a lot of startups and knowledge‑based businesses are rethinking office footprints. Expense forecasts now often show:

• Lower office rent but higher spending on home office stipends
• Increased SaaS costs for collaboration tools
• Travel budgets that rebound as teams meet in person a few times a year

This creates an interesting example of expense forecasting where you trade fixed rent for more flexible, usage‑based costs.

Cloud and AI costs
In 2024–2025, more companies are experimenting with AI tools and heavier cloud usage. Best examples of expense forecasting example in tech now include:

• Separate line items for AI‑related APIs or GPU compute
• Cloud cost forecasts tied to user growth or data processed
• A buffer for unexpected overages as usage patterns evolve

Investors have seen too many models that underestimate these costs, so realistic, data‑backed assumptions matter.

Healthcare and benefits
Health insurance premiums in the U.S. have tended to rise faster than general inflation. When you build your plan, it’s reasonable to model mid‑single‑digit annual increases based on recent trend data published by organizations like the Kaiser Family Foundation. That gives your examples of expense forecasting example more credibility than simply copying last year’s rate.

Turning examples into your own expense forecast

Studying examples of examples of expense forecasting example is helpful, but the real value comes when you adapt them to your business. A few practical tips:

Anchor big assumptions in external data
If you’re forecasting rent, reference local commercial real estate listings. If you’re forecasting salaries, use published ranges from job boards or data from BLS. When your plan cites real sources, it stops looking like wishful thinking and starts looking like a serious financial projection.

Tie expenses to drivers, not just time
The strongest real examples don’t just say “marketing: $20,000 per month.” They say:

• Marketing spend equals 12% of revenue, with a floor of $15,000 per month
• Customer support headcount equals 1 FTE per 400 active customers
• Cloud hosting equals 8% of subscription revenue

That way, when revenue changes, your forecasted expenses change logically with it.

Model best‑case and worst‑case scenarios
Any example of expense forecast that only shows a single path is fragile. For a more convincing plan, show:

• A base case where wage increases and rent escalations follow current trends
• A downside case with higher interest rates, slower hiring, or supplier price spikes
• An upside case where economies of scale lower per‑unit costs faster than expected

This is where the best examples of expense forecasting example stand out: they’re not just precise, they’re flexible.

Keep an eye on cash runway
Most founders use their expense forecast to answer one question: how long until we run out of money? By layering in:

• Starting cash balance
• Timing of new investment or loan draws
• Realistic collection periods for receivables

…you can turn your expense model into a cash runway view. That’s often the single page investors study most closely.

FAQ: examples of expense forecasting in real business plans

Q: What are some simple examples of expense forecasting for a very early‑stage startup?
A: For a pre‑revenue startup, the cleanest examples include a 12‑ to 18‑month runway model with just a few categories: founder salaries (or stipends), 1–3 key hires, basic software stack, legal and accounting, and minimal marketing. You can forecast each hire’s start date, apply a flat percentage for payroll taxes and benefits, and then add a small buffer (often 5–10%) for unexpected costs.

Q: Can you give an example of tying expenses directly to revenue?
A: An e‑commerce brand might forecast marketing as 15% of projected revenue, payment processing at 3% of revenue, and customer support at 1 full‑time employee per 800 orders per month. As revenue grows in the model, those expense lines automatically scale. This is a clear example of expense forecasting that investors like because it shows how profitable growth depends on managing those ratios.

Q: How detailed should my expense forecast be in a business plan?
A: For external audiences, you usually show summarized categories, but behind the scenes you should have more detailed line items. Real examples from successful fundraising decks tend to show 8–15 high‑level categories, supported by a spreadsheet that breaks those down further. The goal is to be detailed enough to be credible without burying readers in minutiae.

Q: How often should I update my expense forecast?
A: Most growing companies revisit their forecast monthly or quarterly. In volatile periods—rapid hiring, supply chain shocks, or new product launches—monthly updates are common. A living forecast that is updated regularly is far more useful than a perfect one you only build once a year.

Q: Where can I find data to support my own examples of expense forecasting?
A: For U.S. businesses, the Bureau of Labor Statistics (https://www.bls.gov) is helpful for wage data, the IRS site (https://www.irs.gov) covers tax rules and rates, and organizations like the Kaiser Family Foundation (https://www.kff.org) publish health cost trends. Industry associations, trade groups, and large public competitors’ filings can also inform realistic assumptions.

By studying and adapting these real examples of expense forecasting example, you can turn your business plan from a rough guess into a thoughtful financial roadmap that stands up to investor questions and helps you make better decisions in 2024 and beyond.