Operating Expense Breakdown

COGS vs OPEX: Know the Difference? 📊💰 Looking at financial statements, there's always confusion around expense classifications. Let me break it down once and for all! Your P&L tells a STORY about your business, and how you classify expenses completely changes that narrative. ➡️ COST OF GOODS SOLD (COGS) COGS represents the direct costs tied to producing your goods or services. Without these costs, you simply couldn't deliver what you sell. Manufacturing companies? Think direct materials, labor costs for production workers, and manufacturing overhead. SaaS companies? Think web hosting, servers, and customer support directly related to delivering your product. The PROS of COGS: - Directly tied to revenue generation - Often areas where supplier negotiations can reduce costs - Clearly shows the efficiency of your production process The CONS of COGS: - Fluctuates with production volume (making forecasting harder) - High COGS squeezes your gross profit margins - Sometimes hard to classify consistently ➡️ OPERATING EXPENSES (OPEX) These are your day-to-day expenses not directly tied to production. This is where most businesses spend the bulk of their money. Common examples include office rent, utilities, marketing costs, admin salaries, and professional fees. The PROS of OPEX: - Generally more stable and predictable month-to-month - Strategic investments here (like marketing) can drive growth - Easier to forecast in many cases The CONS of OPEX: - Doesn't vary with sales volume (fixed costs hurt more when revenue drops) - Can quickly balloon without proper controls - Your largest expense (usually payroll) is often the hardest to adjust quickly WATCH OUT FOR THIS: Many businesses misclassify expenses between COGS and OPEX. Development costs for your product should NOT be in COGS - they belong in OPEX or might need to be capitalized on your balance sheet! Want to really understand your business? Track your gross profit margin over time (Revenue - COGS). This single metric tells you more about operational efficiency than almost anything else. === Getting these classifications right should be step one in any financial strategy. The insights that appear once expenses are properly categorized can completely change how you view your business performance. What expense do you find hardest to classify correctly? Comment below with your toughest example! 👇

"Why are you raising money?" It's easily my most asked question, and to be honest I usually know the answer before I've asked it, but it's great hearing the responses. If you’ve ever wondered where the money REALLY goes between pre-seed and Series A, here’s the breakdown, based on real data across Europe. 1. People dominate the budget Salaries, hiring, and recruitment costs eat up 50%+ of early funding. The founders often pay themselves modestly, but key hires (engineering, product, and leadership roles) make this the single biggest expense. 2. Building product is next 30–40% of funding goes into product development and R&D — especially for deep tech and SaaS companies. This includes dev work, design, infrastructure, prototyping, and testing. I wonder how low this will go over next few years due to AI? 3. Marketing is where things shift At seed, most startups spend very little on marketing. But by Series A, 20–30% of the round can go straight into customer acquisition. Startups are expected to scale growth quickly — so this is where paid ads, content, CRM tools, sales hires, and GTM strategies show up. 4. Operations and Infrastructure Think cloud hosting, SaaS tools, dev software, IT setup. Thanks to startup credits and modern tooling, most startups keep this lean — around 5–15% of total spend depending on complexity. 5. Legal, Compliance, Admin This includes legal fees, accounting, insurance, data protection, and any regulatory requirements. These costs spike during fundraising or contract negotiation, but typically stay in the 5–10% range overall. 6. Office and admin overhead is shrinking Pre-2020, rent was the #2 cost. Now? It’s closer to 3–5%, with remote work, coworking spaces, and lean ops setups being the norm across Europe. → Your budget isn’t infinite — treat marketing and hiring like high-leverage investments, not default checkboxes. → Get clear on your business model before scaling spend. → Make sure your burn reflects your actual stage — not what others are doing. → A great product still needs great distribution — spend accordingly. → Keep legal, admin, and ops tight — they matter, but they shouldn't steal runway. This is how funding gets spent...whether you plan for it or not. So plan for it.

Most founders don’t know where their money is going. They see revenue growing. They see expenses rising. But they don’t really understand why cash is tighter every month. I’ve made this mistake. Even while growing multiple profitable businesses. Even while acquiring companies doing millions in ARR. Here’s what I wish someone told me earlier: There isn’t just one type of cost. There are 4. And they each require a different decision. Let’s break it down: 1) Operating Expenses (OpEx) – the obvious one → Salaries, software, support, AWS, office → What you pay every single month → If it’s bloated, you’re burning → If it’s too lean, you’re stuck doing everything yourself At lemlist, we kept OpEx low by default. That’s why we could stay profitable, even while growing fast. 2) Capital Expenses (CapEx) – the bets → One-time costs: rebuilding onboarding, buying a tool, acquiring a company → If you get it right, it pays off for years → If not, you’ve just set money on fire Buying Taplio & TweetHunter was CapEx. But we had the cash because OpEx was under control. Most founders don’t plan for CapEx, they react to it. That’s why they’re always scrambling when an opportunity shows up. 3) Revenue Expenses (RevEx) – the sneaky one → Payment fees, affiliate cuts, partner revenue shares → The more you sell, the more you lose, unless you optimize this 4) Financial Expenses (FinEx) – the silent killer → Loan interest, venture debt, equity dilution, broken payment terms → Founders ignore it until it’s too late I’ve invested in 20+ startups. You’d be surprised how many raise money with bad terms, poor capital structure, and no understanding of dilution mechanics. They celebrate the fundraise, then spend the next 3 years trying to fix it. Here’s the shift: Don’t ask, “Can we afford this?” Ask, “What kind of cost is this and what’s the long-term tradeoff?” That one question has saved me millions.

Here's how you operate with 50 basis points of sales expense, 150 basis points of comp, and beat the market. I had a loan officer ask me yesterday: "Rich, how are you getting your sales expenses down to 50 basis points? That seems impossible." So I pulled one of our April P&Ls. Real numbers. Not a pro forma. Not a projection. Here's the actual breakdown for an originator who closed 7 loans: • Loan Level Expenses: $465 per loan (16 bps) • Processing: $500 per loan (17 bps) • Marketing & Expenses: $102 per loan (3 bps) • Technology: $82 per loan (3 bps) • Occupancy: $129 per loan (4 bps) • Benefits and Payroll Taxes: $311 per loan (10 bps) • Total Non-Commission Expense: $1,588 per loan (54 basis points) This originator made 150 basis points in commission and had better rates than most of his competitors. Here's what most people get wrong: They think you need to cut services to cut costs. But look at those numbers again. Processing is $500 per loan. That's full-service processing, underwriting support, and a seamless experience for the borrower. Technology is $82 per loan. We're not running on spreadsheets and prayer. The magic isn't in what we don't provide. It's in what we don't waste. Every dollar goes toward actually manufacturing the loan. Processing, underwriting, technology, compliance—the things that directly impact the borrower's experience. The math is simple: When your non-commission expenses are 54 basis points instead of 100+ basis points, you can either: • Offer rates that are 50 basis points better, or • Pay yourself an extra 50 basis points in comp, or • Split the difference and do both This is how you win more loans. This is how you make more money. This is how your borrowers get better rates. It's not magic. It's math. Your costs equal your rates. Productivity is the biggest driver of costs. Most loan officers have no idea what their real expenses are because their companies won't show them. They think in basis points on loan amount instead of thinking about actual dollars spent to manufacture each loan. Here's what I'm still figuring out: How do you get loan officers to care about their cost structure when most companies actively hide this information from them? Because once you see these numbers, you can't unsee them. Once you understand that every dollar of waste comes out of either your pocket or your borrower's pocket, everything changes. Want to find out how to calculate your non-commission expenses per loan? DM me and we'll go over it together.

$56K annually on dripper replacement alone. The facility had no idea until we calculated it. One of our local Facility Advisor’s flagged a leaking Dosatron during a prospect visit last week. Hadn’t been cleaned in four years. Massive salt buildup from backflow contamination between concentrates. They were using a traditional ag salt company. The kind that works great for tomatoes. Not so much for controlled environment cannabis at scale. This got me thinking: how many facilities actually track maintenance burden? Here’s a simple exercise that might reveal a blindspot in your operations: Pull your last 90 days of maintenance logs. Calculate total labor hours spent on irrigation system maintenance. Drippers, valves, line cleaning, component replacement. Now divide by your total cultivation labor hours. If that percentage is above 15%, you’ve got an input problem disguised as a maintenance issue. One facility we visited is replacing 5,000 drippers per room twice a year. That’s 224 labor hours per room annually. Just for dripper replacement. Not including cleaning, not including Dosatron servicing, not including unplanned downtime and definitely not including the new hardware. At $25/hour fully loaded, that’s $5,600 per room in replacement labor alone. Multiply that across 10 rooms. You’re spending $56K annually on a task that shouldn’t exist at that frequency. Here are the warning signs you might have the same issue: - Weekly cleaning schedules for injection equipment instead of monthly - Soft irrigation replacement cycles under 12 months - Visible salt buildup on emitters between irrigation cycles - Backflow between concentrate tanks creating deposits - Team spending more than 10 hours per week on irrigation maintenance The fix isn’t just switching inputs. It’s understanding your total operational cost. Track maintenance hours. Calculate replacement cycles. Measure downtime impact. Because if your cultivation team is spending 20% of their time maintaining equipment, you don’t have an efficiency problem. You have a capacity problem. And capacity costs way more than inputs.

You think your burn rate is $20K/mo. It’s actually $80K/mo — and you’re sleepwalking into death. Most first-time founders think burn rate is just what hits their bank account. Nope. That’s your cash burn. Your real burn—the one that kills startups—is total monthly obligation. And I’ll show you exactly how most founders lie to themselves: Here’s what founders usually count: → $12K on salaries → $5K on tools & infra → $3K on rent + ops = “We’re burning $20K/mo.” Wrong. Here’s what they forget (but will still bleed you out): → Founders not paying themselves = deferred compensation → ESOP grants = future dilution cost → Unused marketing budget = future ramp-up delays → SaaS trials = hidden conversion bombs → Legal/CA filings = annualized spikes → Hiring plans = committed spend once term sheets land Add all that? You’re functionally burning $60K–$80K/mo even if only $20K exits your account. Burn rate ≠ cash out. Burn rate = how fast you’re moving toward needing more money. Big difference. This is why founders get blindsided: → You raise $300K. Think you have 15 months of runway at $20K/mo. → But reality hits. Hiring ramps. Ads start. Tools convert. Legal bills land. → Real burn = $60K. Actual runway = 5 months. You’re now default dead, not default alive. And you didn’t even see it coming. Want to never get blindsided? Use this simple model: 📌 Total Burn Rate Formula = Monthly Cash Out + Accrued Founder Salary (market rate) + Committed Future Spend + ESOP Value Cost (dilution impact × future valuation) + Deferred Operational Costs (e.g. SaaS, legal, infra ramp-up) Build this into your investor updates. Build this into your planning. If you don’t track it, you can’t survive it. ✅ Pro tip: Your job as a founder isn’t to “manage expenses.” It’s to know your runway with ruthless accuracy—and then extend it or raise before the panic window opens. Because panic rounds are where cap tables die and desperation leads to bad deals. Want brutal clarity on your startup? Skip years of wasted effort and stop making expensive mistakes. Get direct advice on your deck, fundraising, GTM, or founder challenges. Book a no-BS 1:1 call with me here: https://lnkd.in/gWV8DT56 ♻ Repost to spread the reminder. 🔔 Follow Anshuman Sinha for more Startup insights. #Startups #Entrepreneurship #AngelInvesting #VentureCapital #LeanStartups

Most underwriting models just plug in a flat percent of Gross Rent for every line item. That’s a mistake. Let’s say you have two nearly identical properties:  • One near transit and nightlife, commanding high rents  • One at the city’s edge with more modest rents. Should operating costs really scale 1 to 1 with rent? We ran the numbers. And here’s what actually works, based on real-world data and variance analysis: 𝗪𝗵𝗮𝘁 𝗧𝗿𝗮𝗰𝗸𝘀 𝗕𝗲𝘀𝘁 𝗳𝗼𝗿 𝗘𝗮𝗰𝗵 𝗘𝘅𝗽𝗲𝗻𝘀𝗲 𝗟𝗶𝗻𝗲 𝗜𝘁𝗲𝗺: 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 & 𝗟𝗲𝗮𝘀𝗶𝗻𝗴 = 𝗣𝗲𝗿𝗰𝗲𝗻𝘁 𝗼𝗳 𝗥𝗲𝗻𝘁 This one holds. Turnover is rent-dependent. Leasing commissions are typically about one month’s rent. 𝗨𝘁𝗶𝗹𝗶𝘁𝗶𝗲𝘀 = 𝗗𝗼𝗹𝗹𝗮𝗿𝘀 𝗽𝗲𝗿 𝗦𝗾𝘂𝗮𝗿𝗲 𝗙𝗼𝗼𝘁 (𝗼𝗿 𝗽𝗲𝗿 𝗕𝗲𝗱𝗿𝗼𝗼𝗺 𝗶𝗳 𝘀𝗾𝘂𝗮𝗿𝗲 𝗳𝗼𝗼𝘁𝗮𝗴𝗲 𝗶𝘀 𝗺𝗶𝘀𝘀𝗶𝗻𝗴) Tenants don’t use more water just because they pay more rent. Utility bills follow space and usage, not revenue. 𝗥𝗲𝗽𝗮𝗶𝗿𝘀 & 𝗠𝗮𝗶𝗻𝘁𝗲𝗻𝗮𝗻𝗰𝗲 = 𝗗𝗼𝗹𝗹𝗮𝗿𝘀 𝗽𝗲𝗿 𝗦𝗾𝘂𝗮𝗿𝗲 𝗙𝗼𝗼𝘁 Dollars per bedroom is a good backup. Our internal regression model confirms this is directionally reliable. 𝗧𝗿𝗮𝘀𝗵 = 𝗗𝗼𝗹𝗹𝗮𝗿𝘀 𝗽𝗲𝗿 𝗕𝗲𝗱𝗿𝗼𝗼𝗺 More people equals more garbage. Simple. 𝗜𝗻𝘀𝘂𝗿𝗮𝗻𝗰𝗲 = 𝗗𝗼𝗹𝗹𝗮𝗿𝘀 𝗽𝗲𝗿 𝗨𝗻𝗶𝘁 Based on replacement cost, not rent. We didn’t guess. We tested for what shows the least variance across deals. 𝗛𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆: Use the metric that reflects how the cost behaves. Don’t treat every line the same. Be wary. Percent of Rent looks clean, but it lies. Still modeling everything as a percent of rent? You might be mispricing risk and missing upside. Want to compare notes or rethink your model? Drop a comment or DM me.

One of the fastest ways to break an FP&A forecast? Treat every operating expense like it behaves the same way. In reality, expenses don’t move together. Some scale with the business. Some barely move at all. And some sit somewhere in between. When FP&A models ignore this, forecasts quickly fall apart once volumes change. That’s why high-quality operating expense models separate fixed and variable cost behavior from the start. Not just for accuracy. For decision-making. A strong Opex model isn’t built around historical averages. It’s built around assumptions that explain how costs behave as the business grows or shrinks. Instead of forecasting “Marketing Expense = last year + 5%”, structure expenses like this: Variable cost formula Variable Expense = Driver × Variable Rate Example: Units Sold × Commission % or Revenue × Marketing % Fixed cost formula Fixed Expense = Base Monthly Cost Example: • Salaries • Software subscriptions • Office leases In Excel, your total expense structure becomes simple: Total Opex = Fixed Costs + (Driver × Variable Rate) Now your model adjusts automatically when business drivers change. That’s where the real forecasting power comes from. A practical Opex model usually includes: • Driver selection Link expenses to operational metrics (revenue, headcount, units, customers). • Cost classification Split accounts into: Fixed Variable Semi-variable • Assumption layer Store rates, growth assumptions, and cost drivers in one centralized assumptions sheet. • Transparency Use clear formulas like: =Units * Cost_per_Unit Avoid hidden hard-coded numbers. • Scenario flexibility When drivers change, your entire cost forecast updates instantly. This turns your model from a static forecast into a decision engine. Quick question for fellow FP&A professionals: When you forecast operating expenses, do you model cost behavior or mostly rely on historical trend percentages? Both approaches exist in the wild. Curious where people land. I regularly help finance teams redesign Excel models so costs respond to operational drivers instead of static assumptions. If your current forecast struggles when volumes change, rebuilding the Opex structure is often the fastest fix.

Revenue doesn't mean profit. You could be bleeding cash without realising. Nothing kills momentum faster than reaching $1M revenue...   Only to realise you are haemorrhaging $1,000s every week.  That's why you need to know OpEx vs CapEx vs RevEx vs FinEx: OpEx → The recurring costs to keep your business running. CapEx → Long-term investments that create future value. RevEx → Costs that scale directly with revenue. FinEx → The cost of capital and your financial structure. Here's a clear breakdown of all four: (See the cheat sheet to get the full picture of each ↓) 💸 OpEx: Operating Expenditure ↳ The day-to-day costs required to keep the business running.  How It Works ↳ Expensed immediately through the P&L in the period incurred ↳ Directly reduces operating profit ↳ Creates no long-term asset or future balance sheet value Key Examples ✅ Salaries and contractors ✅ Rent, utilities, and admin costs ✅ SaaS subscriptions ⏳ CapEx: Capital Expenditure ↳ Investment in long-term assets designed to create value long-term. How It Works ↳ Recorded on the balance sheet, not expensed immediately ↳ Depreciated over the asset’s useful life ↳ Improves future capability rather than short-term profit Key Examples ✅ Core technology platforms ✅ Equipment and machinery ✅ Proprietary internal software 📈 RevEx: Revenue Expenditure ↳ Costs that scale directly with generating and delivering revenue. How It Works ↳ Moves in line with sales volume ↳ Impacts gross margin, not operating margin ↳ Determines how profitable growth actually is Key Examples ✅ Cost of goods sold ✅ Fulfilment and logistics ✅ Sales commissions 💵 FinEx: Financial Expenditure ↳ The cost of capital and decisions that shape your financial structure. How It Works ↳ Affects cash flow rather than daily operations ↳ Driven by leverage, risk, and timing ↳ Often tax deductible depending on structure Key Examples ✅ Loan and debt interest ✅ Credit facility fees ✅ Investor and legal transaction costs If you don't understand these four types of expenditures,  You simply can't build a profitable business. Even if your revenue looks impressive,  It doesn't guarantee long-term profitability. Learn these to align revenue growth with actual progress. Are you measuring OpEx, CapEx, RevEx, and FinEx?  Or are they completely new to you? Share your questions/concerns in the comments. And if you want to continue to dominate search results while you scale...   Searchable handles SEO and AEO automatically so you can focus on building. Learn more and get started for free:   https://lnkd.in/epgXyFmi  ---- 📌 If you want a high-res PDF of this sheet: 1. Follow Chris Donnelly. 2. Like the post. 3. Repost to your network. 4. Subscribe to: https://lnkd.in/eUTCQTWb

Cost of Production in a Gold Mine The global average AISC ranges between USD 1,100 – 1,700 per ounce. - 🔶 1. Capital Costs (Capex) These are one-time upfront investments before production begins. a) Mine Development Capex Mine design & feasibility studies 5 – 20 million Land acquisition & permits 2 – 10 million Overburden removal (pre-stripping) 20 – 200 million Development drives, shafts (UG) 50 – 500 million Tailings storage facility 30 – 150 million b) Plant & Infrastructure Capex Item Cost Crushing, grinding plant 50 – 200 million CIL/CIP processing plant 60 – 300 million Power supply (Grid/Diesel) 10 – 80 million Water supply, workshop, offices 10 – 50 million Camp, housing, transport 5 – 40 million Typical Total CAPEX: USD 200 – 900 million for a medium gold mine. 2. Operating Costs (Opex) These are day-to-day costs of mining and processing gold. A) Mining Costs Cost depends on strip ratio, depth, and equipment. Open-Pit Mining Cost USD 2.0 – 4.5 per tonne of material mined Major cost drivers: diesel, explosives, labor, tires, maintenance Underground Mining Cost USD 40 – 120 per tonne of ore mined Higher due to support, ventilation, drilling/blasting cycles. B) Processing/Plant Costs Gold processing (CIL/CIP) is often USD 15 – 40 per tonne ore. Breakdown: Crushing/grinding: USD 3 – 10/t Leaching tank farm: USD 4 – 12/t Reagents (cyanide, lime, carbon): USD 2 – 6/t Tailings handling: USD 1 – 3/t Power: USD 5 – 9/t C) General & Administrative (G&A) Costs USD 5 – 15 per tonne ore Includes: Management, salaries Security Camp & catering Laboratory & environment compliance CSR & regulatory reporting 3. Refining & Transport Costs USD 5 – 12 per ounce Includes smelting, transport security, insurance. 4. Royalties, Taxes, & Government Charges 2% – 10% royalty depending on country Corporate tax: 25% – 35% Environmental bonds Local infrastructure payments Key Industry Metrics A) Cash Cost (C1 Cost) Includes: Mining cost Processing cost G&A Smelting & refining Typical Cash Cost: USD 800 – 1,200 per ounce B) All-In Sustaining Cost (AISC) Includes Cash Cost + Sustaining capital Tailings dam raise Rehabilitation Exploration for reserve replacement Typical AISC: ▶ USD 1,100 – 1,700 per ounce (global average) Higher in deep underground mines: USD 1,700 – 2,200 per ounce Example Calculation: Medium-Scale Open-Pit Gold Mine Assume: Ore grade: 1.5 g/t Recovery: 92% Throughput: 3 million t/yr 1. Production 1.5 g/t × 3,000,000 t = 4,500,000 g 4,500,000 g ÷ 31.104 g/oz = 144,700 oz/year 2. Operating Cost Mining: 3 million t × USD 3/t = USD 9M Processing: 3 million t × USD 25/t = USD 75M G&A: 3 million t × USD 8/t = USD 24M Smelting: 144,700 oz × USD 6 = USD 0.86M Total Opex = USD 108M/year 3. Cash Cost per ounce 108M ÷ 144,700 oz = USD 746/oz (Realistic numbers usually fall USD 800 – 1,200/oz) 🟢 Final Summary Capital Cost: USD 200 – 900 million Cash Cost: USD 800 – 1,200 per ounce AISC Cost: USD 1,100 – 1,700 per ounce