Sales Growth Projections

(FMCG Blueprint) Sales forecasting in FMCG is both an art and a science. Let’s break it down using some basic matrices with a relatable example. Imagine we’re working for a brand that sells a spicy instant noodle, “HotBowl Ramen”. 1. Historical Sales Data (Your Crystal Ball) The first step is to look at past sales. For example: Month Sales (Units) January 10,000 February 11,000 March 10,500 April 12,000 Now, let’s assume you notice a 5% growth trend every month. For May, you might forecast: May Sales = April Sales * (1 + Growth Rate) = 12000 * (1 + 0.05) = 12600 Tip: This works well unless your sales suddenly nosedive because people discovered a new health fad: “No-Spice Life!” 2. Seasonality (Your FMCG Calendar) People eat more noodles in winter because “cozy food” vibes. Let’s adjust for seasonality: • Winter months: Add 10% • Summer months: Subtract 15% If your May forecast is 12,600 units but May is peak summer, adjust like this: Adjusted Sales = Base Sales * (1 - 0.15) = 12600*0.85 = 10,710 Reality Check: Your product is spicy. Some brave souls will still eat it even in May, sweating like they’re in a sauna. 3. Market Dynamics (Your Frenemy) Suppose your competitor, “MildBowl Ramen,” launches a huge promotion in May. You estimate a 10% impact on your sales. Final Sales Forecast = Adjusted Sales * (1 - 0.1) = 10710*0.9 = 9,639 4. Promotional Impact (Buy One, Cry One Free?) Now, your marketing team swoops in with a “Buy 1 Get 1 Free” promo. Promotions can boost sales by 20%, so: Promo Adjusted Sale = 9639*1.2 =11,566.8 Realistic Case Summary Step Forecasted Sales Base Sales Forecast 12,600 Seasonality Adjustment 10,710 Competitor Impact 9,639 Promo Impact 11,566 Funny Perspective Imagine your boss: • Before Forecast: “We need 15,000 units this month!” • After Your Analysis: “Hmm… okay, but let’s add another promo to reach 12,000 at least!” Your real hero? The customer who eats your spicy noodles even in May, sweating but happy. Moral: Forecasting is like cooking ramen—balance your ingredients (data) and adjust for taste (market trends)!

Most companies are flying blind when it comes to revenue 📊 "Some months we're closing deals left and right, other months it's crickets. I never know what's coming next month." Every month I meet with business owners who tell me exactly this. Revenue unpredictability kills everything. You can't plan hiring, you can't forecast growth, and you definitely can't sleep well at night wondering where next month's revenue is coming from. Well here's the thing...it doesn't have to be this way. ➡️ THE SOLUTION: PIPELINE DRIVEN FORECASTING Stop guessing at your revenue and start building forecasts based on actual pipeline data. Think about that difference. Instead of hoping deals close, you're working with real data from real prospects. STEP 1️⃣ → STRUCTURE YOUR CRM Track each deal by stage, amount, and expected close date in your CRM system. See every deal needs to move through defined stages that actually reflect how your sales process works. You can't just throw deals in there and hope for the best. STEP 2️⃣ → EXPORT PIPELINE DATA Export your CRM data to Excel for revenue forecasting and analysis. You know what's amazing about this? You get complete control over how you manipulate and model your data. Plus Excel gives you that flexibility that most CRM reporting just can't match. STEP 3️⃣ → FORECAST REVENUE Use weighted pipeline data to predict future revenue with confidence. Apply probability percentages to each stage and calculate realistic monthly projections. That's pretty powerful when you think about it. ➡️ RECOMMENDED CRM TOOLS 🔵 Salesforce → Enterprise grade pipeline management for larger companies 🔴 HubSpot → All in one sales & marketing platform ⚫ Pipedrive → Simple, visual pipeline management for smaller teams Now you may be thinking which one should I choose? Well that depends on your company size and complexity, but any of these will work better than spreadsheets alone. ➡️ BEST PRACTICES FOR PIPELINE MANAGEMENT 📅 Keep data updated weekly 📊 Track conversion rates by stage 📋 Define clear stage criteria 📝 Review forecasts monthly ⚙️ Set up CRM automations 🗓️ Set realistic close dates The key is to export pipeline data monthly to maintain accurate revenue forecasts. This monthly ritual will completely change how you plan and operate your business. === I've seen this transform companies from reactive revenue planning to predictable growth patterns. Instead of crossing your fingers each month, you'll know exactly what's coming and can make strategic decisions accordingly. What's your experience been with pipeline management? Are you still flying blind or do you have a system that works?

Because with a bad forecast everything else will fail... This infographic contains 7 steps to create and improve a forecast: ✅ Step 1 - Start with Historical Data Collection & Cleaning 👉 gather and clean past sales data (ideally 3 years) 👉 remove outliers, fill in gaps, and ensure data accuracy before analysis ✅ Step 2 - Segment Your Demand 👉 break down your demand into segments to create more granular forecasts 👉 examples: volume, value, product categories, customer types, regions ✅ Step 3 - Generate a Baseline Statistical Forecast 👉 as starting point, generate a baseline forecast using statistical methods like time series analysis ✅ Step 4 - Apply Seasonality and Trend Adjustments 👉 use historical seasonal patterns and emerging trends to fine-tune your forecast for upcoming periods ✅ Step 5 - Collaborate & Fine-tune in S&OP Meetings 👉 collaborate with sales, marketing, finance, and operations to align on one consensus forecast ✅ Step 6 - Adjust for Market Intelligence 👉 incorporate insights from sales teams, marketing campaigns, external research, and product launches to adjust your baseline forecast ✅ Step 7 - Incorporate Forecasts into S&OE (Sales & Operations Execution) 👉 drive actionability in the short term based on this aligned forecast, helping the team respond quickly to deviations 💥 Bonus Step: Build a Continuous Feedback Loop 👉 track forecast accuracy by comparing actual sales to forecasted figures, and regularly update your model based on this feedback Any other steps to consider? #supplychain #salesandoperationsplanning #integratedbusinessplanning #procurement