If you’re buried in spreadsheets, second-guessing your sales forecasts, and sick of “magic” AI promises, you’re in the right place. This guide is for sales analysts, supply planners, and anyone who wants real, practical steps for using Forecastpro to turn historical sales data into forecasts you can actually trust. No fluff—just what works, what doesn’t, and how to avoid classic mistakes.
Step 1: Get Your Sales Data Ready
Before you even open Forecastpro, set yourself up for success. Garbage in, garbage out is painfully true here.
What you need: - A clean, consistent set of historical sales data (ideally 18–36 months, but more is better). - Data at the level you want to forecast (item, SKU, customer, region, etc.). - No missing dates, wild outliers, or weird formatting.
Tips: - If you have gaps or outliers (like a pandemic spike), mark them now. Forecastpro can handle them, but only if you’re honest about what’s real and what’s a fluke. - Don’t overcomplicate things. Start with your top-selling products or regions before trying to forecast everything.
What to skip:
Don’t bother importing every column from your ERP “just in case.” Stick to what matters: date, item, and sales quantity (or revenue, if that’s how you plan).
Step 2: Import Your Data into Forecastpro
Now, fire up Forecastpro and get your data in. The software accepts Excel, CSV, and direct database connections.
How to do it: 1. Open Forecastpro and start a new project. 2. Choose “Import Data” and select your file or database. 3. Map your columns (date, item ID, sales, etc.)—double-check that dates are recognized correctly.
Pro tip:
If your file structure changes often, set up a template import. Saves headaches down the line.
What can go wrong:
- Date formats (US vs. European) can trip you up.
- If you see a wall of errors, check for blank rows or merged cells in your spreadsheet.
Step 3: Visualize and Explore Your Data
Don’t trust the numbers blindly. Use Forecastpro’s built-in charts and summaries to get a feel for your data.
What to look for: - Trends: Is sales volume growing, flat, or declining? - Seasonality: Do you see regular spikes or dips? - Outliers: Any months way above or below the average?
How to do it: - Use the “Graph” or “Plot” feature for a bird’s-eye view. - Drill into individual products or regions that look odd.
Honest take:
If your data looks chaotic or random, no amount of fancy modeling is going to save you. Focus on cleaning and understanding it first.
Step 4: Choose a Forecasting Model (Don’t Overthink It)
Forecastpro offers automatic model selection—ARIMA, exponential smoothing, seasonal models, and more. For most people, letting the software pick is fine.
Let Forecastpro suggest a model: - Select “Automatic Model Selection” for each item or group. - Review the model it chooses. The software shows you fit statistics (MAPE, RMSE, etc.).
Manual override:
If you know your business has quirks (like hockey-stick growth or sudden drops), you can pick or tweak models. Just don’t kid yourself—complex doesn’t always mean better.
What to ignore:
Don’t obsess over getting the absolute lowest error metric. Consistency and simplicity usually win in the real world.
Step 5: Handle Promotions, One-Offs, and Special Events
No forecasting tool can read your mind. If you ran a big promo, had a supply chain meltdown, or saw a weird spike, tell Forecastpro about it.
How: - Use the “Event” or “Outlier Adjustment” tools. - Mark the dates and specify if they’re one-time or recurring. - Adjust the history, not the future. Don’t fudge future forecasts to “make the boss happy.”
Pro tip:
Keep a log of all adjustments. If next year someone asks why April 2023 looks weird, you’ll have an answer.
Step 6: Generate and Review Your Forecast
Click “Generate Forecast.” Now the real work starts: reviewing and making sense of the output.
What to check: - Does the forecast line up with what you know about your business? - Are seasonal patterns being picked up, or is it just a straight line? - Are there any wild swings or drops that don’t make sense?
What works:
Forecastpro’s visual tools make it easy to spot weirdness. Trust your gut—if something looks off, dig in.
What doesn’t:
Blindly accepting the first forecast. Always sanity-check against your own knowledge and recent trends.
Step 7: Export, Share, and Document
Don’t let your forecast live and die inside the software. Get it into a format your team can use.
How: - Export forecasts to Excel or CSV. - Include charts for context (people love pictures). - Write a quick summary of what you did—models used, adjustments made, what to watch for.
Pro tip:
Keep your documentation short and to the point. “Used automatic model; adjusted for Black Friday in Nov 2023; data through April 2024.” That’s it.
Step 8: Iterate and Improve
Forecasting isn’t “set and forget.” The best teams revisit their process every month or quarter.
What to do: - Compare forecasts to actuals. Where did you miss? Why? - Update your data and rerun the process. - Don’t be afraid to drop overly complex models if they aren’t adding value.
What to ignore:
You don’t need to chase every new feature or buzzword. Solid process beats shiny tools.
What Works, What Doesn’t, and What to Skip
- Works: Letting Forecastpro automate the boring stuff, but keeping a close human eye on the results.
- Doesn’t: Expecting perfect accuracy. Forecasts are always wrong; the goal is to be less wrong.
- Skip: Over-engineering. A clean process with clear documentation beats a stack of mysterious tweaks.
Keep It Simple, Stay Curious
Sales forecasting isn’t magic. With a clean dataset, honest adjustments, and regular reviews, Forecastpro can be a solid workhorse—not a miracle. Start small, learn as you go, and don’t get distracted by hype. Simple, clear forecasts beat complicated guesses every time.