Financial Analysis Techniques

Forecasting is hard. Finding analysts who do it well is even harder. Too often, I see forecasting either: 1. Overcomplicated: Applying complex ML models just to predict a moving average (?!), or 2. Oversimplified: Running regressions without understanding what the coefficients even mean. I personally use 4 forecasting methods to model a range of outcomes, from conservative to aggressive: 1. ARIMA - Smooths time series data, w/o seasonality adjustment. 2. SARIMAX -  Like ARIMA, but accounts for seasonality. Likely to be the safest and conservative forecast. 3. Prophet -  Captures non-linear trends and seasonality. Often the most accurate. My favorite model for growth forecasts. 4. Manual Projection – aka Olga's secret, overly complicated manual projection. I plot every available metric’s historical D/D, W/W, M/M, and Y/Y % change and analyze their: (a) correlations and relationships (b) seasonal thresholds. It takes ages to complete, but it delivers the most precise forecast. If done right. If I can account for everything the teams are doing. Which is rarely the case. 😬 When reporting, I typically present only Prophet alongside my Projection, keeping ARIMA and its variations for myself as checks. There are many time series models out there: MA, AR, ARMA, ARIMA, SARIMA, Exponential Smoothing, VAR, and more. Forecasts are fun.

The COMPLETE guide to forecasting every account on your financial statements 👇 The financial forecast is your company's roadmap for success, but most forecasts I see miss crucial details in how they approach individual accounts. I want to share my methodology for forecasting the most critical accounts👇 ➡️ PROFIT & LOSS 📈 REVENUE FORECASTING 1️⃣ Renewals & Expansion → Renewal rate × renewal likelihood × Expansion % This is the foundation of your revenue forecast and typically the most predictable revenue stream For example, if you have $100,000 in current MRR, a 90% renewal rate, and 10% expansion from existing customers: $100,000 × 90% × 110% = $99,000 in monthly recurring revenue Common mistakes to avoid: - Using a flat renewal rate across all customer segments - Ignoring seasonal patterns in expansion - Not factoring in price increases 2️⃣ New Customer Acquisition → Break down by acquisition channel with specific metrics For Sales Reps: - Factor in ramp time (typically 3-6 months to full productivity) - Use realistic quota attainment (industry average is 60-70%) Real example with 3 new sales reps, each with a $500K quota and 60% attainment: - Q1: Minimal contribution - Q2: 25% of full productivity = $62,500 - Q3: 75% of full productivity = $187,500 - Q4: 100% of full productivity = $250,000 Total annual contribution: $500,000 (vs $1.5M if you ignored ramp time and attainment) ➡️ COST OF GOODS SOLD 💰 COGS → Calculate as a percentage of revenue for most businesses Perfect for software companies and service businesses where costs scale relatively linearly with revenue. Implementation tips: - Calculate your 12-month historical COGS percentage - Adjust for any known future changes in your cost structure - Create separate percentages for different product lines Example: If your SaaS platform has historically run at 22% COGS/Revenue, but you're investing in better infrastructure that will reduce costs by 2%, forecast at 20% going forward. ➡️ OPERATING EXPENSES 💼 Headcount-Based Expenses → Build position-by-position with specific hiring dates and fully-loaded costs Example for a Marketing Manager with $100,000 salary + 25% additional costs: - Annual cost: $125,000 - Q2-Q4 cost (9 months): $93,750 Contract-Based Expenses → Review existing contracts and renewal dates with expected increases === Creating a detailed financial forecast takes time, but the accuracy gained from using these account-specific methodologies will transform your company's financial planning. Funny enough, today my community kicks off the FP&A Season with Financial Modeling Fundamentals - perfect timing for this post! We'll be building on these concepts with dedicated sessions on Revenue Forecasting , P&L Forecasting, and Balance Sheet Forecasting. You can find more details about the community here: https://lnkd.in/eU4b8ARA What account do you find most challenging to forecast accurately? Share your thoughts in the comments below 👇

Stop looking at financial modeling as only your job. It should involve many other smart people too. Here's how to involve them and lighten your load. 𝗦𝗮𝗹𝗲𝘀 Sales is a primary driver of the P&L. The P&L is a primary driver of cash flows. Variable costs are heavily dependent on the sales projections which means that the forecast better be reliable. The sales manager should update the sales forecast every week or month with the assistance of the sales team and CRM. The analyst should challenge the numbers but it’s the sales team that is ultimately responsible. 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 Ops bases their decisions on anticipated future activity. Operations tend not to base their decisions on cash flow, unless liquidity is an issue. This requires coordination with sales, not just finance, for planning, purchasing and production. When the volume forecasts change, or requires recalibration, that’s a sales and ops discussion. FP&A may help with facilitating. 𝗛𝘂𝗺𝗮𝗻 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 Hiring is usually driven by strategic planning and resource needs. Hiring is usually not a cash flow decision, despite major implications of human resources decisions on finance. The coordination may take place among sales, ops, HR, and the CFO before it ever makes its way into the cash flow forecast. 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 Marketing is responsible for the marketing budget, which has direct implications for finance and cash flow. But the marketing initiatives are usually tied to strategic and sales planning. Once those activities are clear, the marketing team budgets for must-haves and nice-to-haves. 𝗖𝗮𝗽𝗲𝘅 The CFO or COO may take ownership of capex planning, depending on the needs and activities forecast by department heads. Timing and magnitude may be contractual obligations with supporting schedules updated periodically. 𝗚𝗲𝘁 𝗼𝘁𝗵𝗲𝗿𝘀 𝗶𝗻𝘃𝗼𝗹𝘃𝗲𝗱: A financial analyst’s responsibilities are to coordinate and facilitate the forecasting process, not owning every dimension of planning. 90% of the process should involve sales, ops, HR, and other business partners. Empowering them and supporting them makes them responsible for their zones of influence. Finance is responsible for putting the pieces together. When you delegate, the forecasting process is better and easier.

Many companies don’t struggle because of profits. They struggle because of cash flow. Entirely preventable, but here’s the kicker: Too many leaders rely on historical metrics—net income, EBITDA, last quarter’s revenue—thinking they reflect financial health. They don’t. Because profit tells you where you’ve been. Cash flow tells you where you’re going. ➡️ Learn to analyze a cash flow statement in 10 steps and never miss another red flag again: https://lnkd.in/e2JXiUK6 ✔ Profit is a historical number. It tells you how the business performed—not whether it can navigate through what’s coming next. ✔ Cash flow is real-time financial health. It shows how money moves in and out, revealing whether you can meet obligations today. ✔ Forecasted cash flow is future strength. Because past performance doesn’t guarantee future liquidity. If you don’t know what’s coming, you’re flying blind. Here's why companies get this wrong: 1️⃣ They trust EBITDA instead of tracking real cash. → EBITDA strips out expenses like interest and taxes, but those bills still need to be paid. 2️⃣ They assume profit = cash in the bank. → Profit looks good on paper, but if revenue is tied up in receivables, you have no liquidity. 3️⃣ They don’t forecast future capital needs. → It’s not enough to know what happened last quarter—cash planning must include future payment obligations, growth investment plans, and economic shifts. Here's the right way to measure financial strength: 1. Operating Cash Flow → Are you generating real cash, or just showing paper profits? 2. Real Free Cash Flow → After investments, do you have excess cash, or are you overextending? 3. Cash Conversion Cycle → How long does it take to turn revenue into usable cash? 4. Debt-to-Cash Flow Ratio → Can you service obligations, or is debt outpacing liquidity? 5. Rolling 16-Week Cash Flow Forecast → Are you prepared for short-term risks, or just hoping for the best? The Bottom Line: ↳ Historical profit tells you where you’ve been. ↳ Current cash flow tells you where you are. ↳ Cash flow forecasts tells you your future. 📌 Make 2025 your best year yet and master financial leadership ↴ ▷ Enroll in my 5 on-demand video courses and save 50%+ with the bundle: https://bit.ly/4bTdu8T ▷ Join the April cohort waitlist for my 6-week Financial Intelligence Program: https://bit.ly/3ZCI0kr ♻️ Like, Comment, Repost if this was helpful. And follow Oana Labes, MBA, CPA for more.

✨Need some liquid courage while pouring over your budget? ✨ It’s Hard to Predict—But Is It Really? Every year around this time, we work with clients to forecast the next 12 months. Their biggest hesitation? They feel it’s pointless to try and predict the future. It’s challenging for them to think about what’s possible because it doesn’t feel real or tangible. It can seem like the numbers are random—but there are ways to make an educated guess about the future. Here are some of the steps my CFO leads and I take to help clients move through the uncertainty: 1️⃣ Financial Statements We look at the past year or two of financial performance by month. We review the income statement, balance sheet, and cash flows over the past 12–24 months. This gives us a starting point to see if there’s any seasonality, any trends, and an idea of general operating costs. It gives us a chance to look at past revenue sources—what products or services sold the best—and to spot customer patterns, including any former customers who haven’t purchased in a while or new potential customer segments. 2️⃣ Collaborate with the CPA We speak to the CPA to check for any upcoming changes in tax laws that may impact financials. We talk about any potential changes in the industry or economic environment that might affect the company’s future revenue. 3️⃣ Evaluate Staffing and Major Purchases We review the current employee list, their salaries, and benefits to determine if there are any hiring needs. Then, we discuss any new major purchases that need to happen, whether in technology, software, professional development, or conferences. And all of this revolves around the CEO’s higher-level goals for the company for at least the next 3 years. These are just a few of the ways we help make the future feel more tangible for our clients. Do you have similar hesitations when it comes to financial forecasting? If so, come to my next CFO Hours on 11/20—sign up at the link in the comments! #SmallBusinessFinance #ProfitabilityTips #ScalingYourBusiness #FinancialPlanning

Trust must exist between the CEO, CFO, and CRO to be aligned on the company budget and forecast. How can this be achieved? 1️⃣ All three must agree on the data and assumptions used for the 1, 3, and 5-year plans. Data will guide what can happen based on past performance. While assumptions can be used for goals that are above and beyond historical performance. (More on assumptions later) 2️⃣ The CRO needs the company goals far in advance of their planning. The longer the hiring time & rep ramp-up time to revenue, the more warning they need to ensure they have the coverage necessary to achieve those goals. 3️⃣ The CFO and CRO must agree on how deals are forecasted. Ideally, they will have created this forecast together, even shared high, medium, and low ranges, and then take that to the CEO as a joint document. 4️⃣ The CEO must give the CFO the Board's expectations on growth, investment, and where the growth should come from, and then update the team regularly on changes to these. The CEO should also guide the Board on how quickly the team can adjust to meet changes to their expectations. 5️⃣ The annual budgeting process usually starts with the CFO doing a top-down version that is created with the Board and CEO. While, or before this, the CRO should be doing their bottom-up revenue forecast too. These two versions rarely are the same - so the assumptions in each analysis now become critical. What I have seen work well is when the CRO and the CFO use the same assumptions data for the budget. Then the gaps between the top-down and bottom-up versions can be addressed with these assumptions. As the year goes on and results get posted, the results based on assumptions can be shared back with the Board to show them where there are gaps or overperformance. If these three senior leaders are aligned and have hard discussions together, it is much easier for the company to execute. If trust does not exist, or if each leader operates in a silo, the entire company's goals will most assuredly be at risk. What process have you seen work for how these three leaders agree on "the plan?"

What would you do if your projections suddenly faced a reality check? In financial modelling, assumptions shape the story. But what happens when the plot takes an unexpected twist, and the numbers don’t align with ideal scenarios? Let’s unpack this. Imagine: You're reviewing an income statement. Sales growth is slowing not dramatically, but enough to make you pause. Instead of the expected 2.5%, it’s now projected at 1.75%. The story unfolds further: supply chain pressures pinch the gross margin, nudging it down to 21.5%. Operating expenses creep up, now at 12% of revenue instead of 11%. Depreciation, influenced by rising capital assets, moves from 4% to 5%. These aren't just numbers on a spreadsheet. They reflect a company’s adaptability under pressure pricing power, demand shifts, operational efficiencies, and workforce dynamics. And here’s where lenders and decision-makers must tread carefully. Adjusting assumptions based on industry benchmarks and external challenges isn't just prudent it’s essential. According to a report by Deloitte, 82% of financial leaders believe scenario planning improves decision-making. By crafting downside cases, businesses and lenders can navigate uncertainty with more confidence. Adjusting variables like loan-to-value ratios, amortization periods, or maintaining steady interest rates becomes less about reacting and more about preparing. But what does this mean in practical terms? It’s about balance recognising potential risks while not stifling growth. A small shift in one variable can ripple across the entire financial picture. Thoughtful adjustments now can save time and resources later, ensuring a company remains resilient, even when the numbers tell a different story. Have you had to rethink financial assumptions in your work? How did you approach it? what did you learn? Let’s discuss this in the comments.

A poor demand forecast destroys profits and cash. This infographic shows 7 forecasting techniques, pros, cons, & when to use: 1️⃣ Moving Average ↳ Averages historical demand over a specified period to smooth out trends ↳ Pros: simple to calculate and understand  ↳ Cons: lag effect; may not respond well to rapid changes ↳ When: short-term forecasting where trends are relatively stable 2️⃣ Exponential Smoothing ↳ Weights recent demand more heavily than older data ↳ Pros: responds faster to recent changes; easy to implement ↳ Cons: requires selection of a smoothing constant ↳ When: when recent data is more relevant than older data 3️⃣ Triple Exponential Smoothing  ↳ Adds components for trend & seasonality ↳ Pros: handles data with both trend and seasonal patterns ↳ Cons: requires careful parameter tuning ↳ When: when data has both trend and seasonal variations 4️⃣ Linear Regression ↳ Models the relationship between dependent and independent variables ↳ Pros: provides a clear mathematical relationship ↳ Cons: assumes a linear relationship ↳ When: when the relationship between variables is linear 5️⃣ ARIMA ↳ Combines autoregression, differencing, and moving averages ↳ Pros: versatile; handles a variety of time series data patterns ↳ Cons: complex; requires parameter tuning and expertise ↳ When: when data exhibits autocorrelation and non-stationarity 6️⃣ Delphi Method ↳ Expert consensus is gathered and refined through multiple rounds ↳ Pros: leverages expert knowledge; useful for long-term forecasting ↳ Cons: time-consuming; subjective and may introduce bias ↳ When: historical data is limited or unavailable, low predictability 7️⃣ Neural Networks ↳ Uses AI to model complex relationships in data ↳ Pros: can capture nonlinear relationships; adaptive and flexible ↳ Cons: requires large data sets; can be a "black box" with less interpretability ↳ When: for complex, non-linear data patterns and large data sets Any others to add?

Most startup financial models are beautiful lies. I’ve reviewed hundreds of early-stage models. And the pattern is clear: → CAC magically drops over time → Churn is “estimated” but never tracked → LTV isn’t calculated or worse, inflated → Headcount costs are wildly optimistic → There’s a “Misc” tab with $1.2M in it Why does this happen? Because founders treat models like investor theatre. Built to impress. Not to operate. The cost? → You raise capital with zero visibility on runway → You overhire and miss your margin targets → You make roadmap bets you can't actually afford → And worst of all? You realize too late that the business model doesn’t work Your model isn’t a pitch prop. It’s your decision engine. A good one should answer: → What happens if CAC jumps 25% next quarter? → Can we delay the next hire and still hit targets? → What’s real runway after expansion churn? If you can’t get those answers, you don’t have a model. You have a spreadsheet in a blazer. Here’s how to build one that actually works: 1/ Start with a clear purpose → What decisions should this model help you make? Hiring plan, pricing strategy, runway clarity? Be specific from day one. 2/ Ground it in real systems → Pull actuals from your CRM, accounting, and payroll. Your model is only as useful as the data it’s built on. 3/ Link your core financials → P&L, Balance Sheet, and Cash Flow should speak to each other. If they don’t, your forecast can’t be trusted. 4/ Segment revenue realistically → Break revenue down by product, customer type, or geography. Model retention, expansion, and churn by cohort — not hope. 5/ Reflect costs with accuracy → Include real team ramp times, founder comp, tech debt, and overlooked ops costs. This is where most risk hides. 6/ Run scenarios, add sensitivity → Best case, worst case, base case. Play with CAC, churn, and pricing levers. Your model should answer “what if?” 7/ Use and update it regularly → If your model isn’t revisited monthly, it’s already outdated. It should evolve with your business — not collect dust post-fundraise. Bottom line? If your model looks polished but doesn’t drive decisions.. Rebuild it. Your business depends on it. PS: Curious, what’s the one metric you check first when you open your model? ——— Need help making the numbers make sense? I’m Mariya. Fractional CFO for SaaS startups. I help founders get clear on what the numbers are really saying. 📩 DM me if your model doesn’t match your reality.

Years ago now, I was running FP&A for a fast-growing company that still clung to its annual budget like it was gospel. We’d spend six weeks building it. Five weeks defending it. And by Q2, it was already irrelevant. But leadership still treated it like a blueprint. Every variance felt like a crime scene. Every adjustment needed a postmortem. Meanwhile, our actual operating reality? Evolving by the week. So I built a rolling forecast—off to the side at first, just for sanity. No approval chain. No formal process. Just a model that actually reflected what was happening. And it changed everything. Because it taught me two lessons I’ll never forget: Budgets are about control. Forecasts are about clarity. A good budget keeps spending in check. A good forecast helps you see around corners. High-performing teams use both—but they lead with the forecast. You can’t steer using old data. If your plan can’t adapt to changes in hiring, sales cycles, or macro shifts—you’re not planning, you’re guessing. We eventually convinced leadership to make the rolling forecast our primary tool. The budget stayed—mostly for optics. But decision-making? That shifted to real time. If your finance team is still tethered to an annual plan that died in February, I see you. You’re not behind. You’re just ready to forecast like it’s actually 2024.