Key Metrics to Include in Financial Models

Ever spent hours perfecting an Excel formula, only to realize… no one cared (at all)? Here’s what your boss actually cares about 👇 - Do we have enough cash to get through our slow season? - What happens if gross margin drops by two points? - Are we in covenant compliance next quarter? - Is our EBITDA defensible? Despite all the advances in technology (which, yes, are definitely helpful), I've found most conversations boil down to the same four things: 1. Revenue 2. Gross Margin 3. EBITDA 4. Cash And honestly, this should be a 𝘳𝘦𝘭𝘪𝘦𝘧. Technology comes and goes, but business acumen will 𝘢𝘭𝘸𝘢𝘺𝘴 matter. 𝗧𝗵𝗲 𝗥𝗲𝗮𝗹 𝗣𝘂𝗿𝗽𝗼𝘀𝗲 𝗼𝗳 𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 We’ve all been there — chasing the “perfect” model: - Auto-updating - Efficient formulas - Amazing formatting - A financial masterpiece ✨👌 But here’s the truth: 𝗼𝘂𝗿 𝗷𝗼𝗯 𝗶𝘀𝗻’𝘁 𝘁𝗼 𝗰𝗿𝗲𝗮𝘁𝗲 𝗮𝗿𝘁. The real purpose of financial modeling is 𝘁𝗼 𝘁𝗲𝗹𝗹 𝘁𝗵𝗲 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 𝗧𝗲𝗮𝗺 𝘄𝗵𝗮𝘁 𝘁𝗼 𝗱𝗼 𝗻𝗲𝘅𝘁. The model is just an abstract representation of what 𝘮𝘪𝘨𝘩𝘵 happen. Real people have to act on it to make the projections a reality. That’s the purpose. 𝘖𝘶𝘵𝘴𝘪𝘥𝘦 𝘵𝘩𝘦 𝘴𝘱𝘳𝘦𝘢𝘥𝘴𝘩𝘦𝘦𝘵. 𝗧𝗵𝗲 "𝗕𝗮𝗱 𝗠𝗼𝗱𝗲𝗹" 𝗧𝗵𝗮𝘁 𝗪𝗼𝗿𝗸𝘀 As someone who teaches financial modeling, I hold myself to a high standard when building client models. But one of the models I use every week is "not that great": - 30+ minutes of prep - A few hardcodes - Manual updates - Basic lookups Yet, it’s excellent at one thing: 𝗵𝗲𝗹𝗽𝗶𝗻𝗴 𝘁𝗵𝗲 𝗢𝗽𝘀 𝘁𝗲𝗮𝗺 𝗻𝗮𝘃𝗶𝗴𝗮𝘁𝗲 𝗮 𝗰𝗮𝘀𝗵 𝗰𝗿𝘂𝗻𝗰𝗵. It tells them: - Which customers to call for collections - Which vendors to push - How to make payroll Do they care that I used SUMPRODUCT to build the summary? Hasn't come up once. The “bad model” does its job. And that’s all that matters. (Even if the Excel nerd in me wants to rebuild it) 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂 𝗖𝗮𝗻 𝗗𝗼 𝗧𝗼𝗱𝗮𝘆 Business acumen will 𝘢𝘭𝘸𝘢𝘺𝘴 outrank Excel skills. That’s why so many CFOs who “aren’t that good with Excel anymore” still sit in the Board room — they bring insight, not formulas. So, start with the model you’re working on right now: - Who’s the audience? - What do they truly care about? - Does your model help them make decisions and take 𝗮𝗰𝘁𝗶𝗼𝗻? Don’t get stuck in the pursuit of perfection. Direct link if you have to — or (gasp 😬) hardcode something. Don't get me wrong: Excel skills are an essential toolkit for every modeler, but the big picture is 𝗵𝗲𝗹𝗽𝗶𝗻𝗴 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝘀𝘂𝗰𝗰𝗲𝗲𝗱. 📌𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝗬𝗼𝘂: What’s the best “bad” model you’ve ever built that helped your team? 𝗔𝗯𝗼𝘂𝘁 𝗠𝗲 𝗶𝗻 𝟯.𝟳 𝗦𝗲𝗰𝗼𝗻𝗱𝘀: 👋 Hey, I’m Chris Reilly—I’ve spent my career building Financial Models (FP&A and Private Equity). 📍 Learn not just "how" to build Financial Models, but WHY 👉 https://lnkd.in/e6B7y9yk

Two Core Business Models to Master 🎯 If you can forecast these, you can forecast almost anything. Most finance professionals get thrown off when they switch between industries...but once you understand these two models, everything clicks. ➡️ SAAS (SOFTWARE AS A SERVICE) This is the recurring revenue goldmine. Monthly recurring revenue (MRR) and annual recurring revenue (ARR) become your best friends. High margins, low cost of goods sold...because once you build the software, serving additional customers costs almost nothing. Deferred revenue shows up everywhere because customers pay upfront but you earn it monthly. Often B2B with longer sales cycles, which means your pipeline matters more than daily sales. The metrics that matter: MRR/ARR → Predictable recurring income (this is your lifeline) CAC → Cost to acquire a new customer (how much you spend to get them) Churn → Customers lost (the number that keeps you up at night) Expansion → Customers increasing spend (your growth engine) Contraction → Customers reducing spend but not leaving (still revenue, just less) The MRR waterfall becomes your monthly obsession: New customers minus churn plus expansion equals net MRR growth. ➡️ CONSUMER-PRICED GOODS This one's completely different. One-time or repeat transactions instead of recurring revenue. Physical logistics take over your life...inventory, shipping, returns. Lower pricing with faster sales cycles means volume becomes everything. Digital marketing and ads drive most of your growth, so ROAS (return on ad spend) becomes critical. The metrics that matter: Conversion Rate → Percentage of users who actually buy (usually low, but that's normal) AOV → Average order value (how much each customer spends) Inventory Turns → How fast you sell through stock (cash flow killer if you get this wrong) Return Rate → Percentage of orders returned (especially brutal for fashion and electronics) ROAS → Return on ad spend (if this goes negative, you're in trouble fast) The e-commerce funnel becomes your roadmap: Traffic converts to revenue, but each step has massive drop-off. Cash vs revenue recognition gets tricky because you collect payment immediately but might have returns, chargebacks, or refunds later. ➡️ WHY THIS MATTERS FOR FORECASTING Each model requires completely different assumptions. SaaS forecasting focuses on cohort analysis, retention curves, and expansion patterns. Consumer goods forecasting centers on seasonality, inventory cycles, and marketing spend efficiency. Miss the fundamentals of either model and your forecast becomes useless. But master both? You can walk into any company and build a solid forecast within weeks. === Understanding these two models has saved me countless hours when building forecasts for different industries. Which business model do you work with most? What metrics do you find trickiest to forecast? Share your experience in the comments below 👇

My post on formatting SaaS financials has received almost 200k impressions as of today. It seems I am not the only person frustrated with inconsistent reporting, metrics overload, and lack of visibility into what actually matters. My post failed to explain why you should track the metrics that I selected, so I'll explain that here. In reality, only a few metrics in business REALLY (hello CASH) matter. Everything else is just derivative. So here are the questions I am trying to answer with each metric: ARR: How much revenue are we generating? Growth Rate: Is the revenue growing or shrinking? How fast? Average Revenue per Account and Customer Count: What’s the breakdown of our revenue in terms of average account size and customer count? How is it trending? Gross Revenue Retention and Net Effective Retention Rate: How long do our customers stick around and do they typically upgrade or downgrade? CAC: How much does it cost to acquire a customer? Gross Margins: How much does it cost to service a customer? CAC Payback Period: How quickly do we make our money back after acquiring a customer? R&D Spend: How much are we investing in long-term growth? When do we expect to start generating money from these long-term investments? What’s our expected ROI? G&A Spend: How much do we spend on overhead to support all of this? ARR per FTE: Are we efficient? Cash Flow Statement: What’s driving the increase/decrease in our cash? Months Burn: Do we need more outside money either in the short-term or long-term? And to simplify things even further, what I am really trying to answer as a CFO is the following: What's our cash look like in the short-term and the long-term? KISS: Keep it Simple Stupid #SaaS #Startups #Finance #founders #Bootstrapping