Getting demand planning right can make or break your supply chain. If you’re using Forecastpro or thinking about it, you want workflows that are accurate, efficient, and not a nightmare to maintain. This guide is for planners, analysts, and supply chain folks who want a straightforward, real-world approach. No buzzwords. Just what works—and what you can skip.
1. Start With Clean, Usable Data
Let’s be blunt: if your data’s a mess, your forecasts will be too. No fancy algorithm or shiny dashboard will fix bad inputs.
Checklist for your data: - Historical sales: At least 18–24 months if possible. More is better. - Consistent units: Don’t mix cases, pallets, and eaches unless you’re sure you want to. - Granularity: Decide if you’re forecasting by item, SKU, region, or customer. Don’t overcomplicate it. - Missing values: Fill gaps or explain them. Zero sales in a pandemic month? Flag it.
Pro tip: Don’t waste weeks cleaning data that doesn’t matter. Focus on your top-selling products and locations first.
2. Define What “Good Enough” Looks Like
Forecastpro has tons of options—don’t try to use them all. Before setting up workflows, get clear on: - What accuracy do you actually need? 80% might be fine for some products, while others need more precision. - How often do you need updates? Monthly is typical, but some teams do weekly or even daily. Don’t overdo it. - Who’s using the forecast? Finance might want one number, operations another. Get everyone on the same page.
What to ignore: Fancy models for low-impact products. Focus effort where it matters.
3. Map Out Your Basic Workflow First
You don’t need a 20-step process to start. Here’s a simple core workflow that works for most teams:
- Import and clean data
- Use Forecastpro’s data import tools (Excel, CSV, or direct database pulls).
- Set up recurring imports if possible—manual uploads get old fast.
- Run baseline statistical forecasts
- Stick with Forecastpro’s automatic model selection at first. It’s usually good enough.
- Save overrides and custom tweaks for truly weird items.
- Review exceptions
- Let the system flag big variances or anomalies.
- Prioritize review time on items with high forecast error or high business impact.
- Collaborate and adjust
- Pull in sales or marketing only when needed—don’t make it a committee sport.
- Document overrides. If you’re changing numbers, say why.
- Finalize and publish forecasts
- Export back to your ERP or planning system.
- Archive a “snapshot” for later accuracy checks.
Pro tip: Automate as much as you can. Manual steps are where errors and burnout happen.
4. Build in Exception Management (Don’t Chase Every Error)
Most demand planners burn out chasing small errors. Instead:
- Set reasonable thresholds—review only outliers (e.g., forecast error > 30% or items with big dollar impact).
- Use Forecastpro’s exception reporting to focus attention.
- Accept that some products will always be unpredictable. Don’t lose sleep over them.
What doesn’t work: Trying to “fix” every forecast. It’s a waste of time and rarely improves the overall plan.
5. Bring in Human Judgment—But Sparingly
Forecastpro is powerful, but no software understands your business quirks perfectly. Human tweaks can help, but don’t overdo it.
When to override: - Promotions, price changes, or known supply issues - One-off events (e.g., a customer suddenly drops off) - New product launches without history
When not to: - Just because you “feel” the number is off - To hit a budget target (tempting, but risky)
Honest take: The more overrides you do, the less you trust your process. If you’re constantly tweaking, rethink your setup.
6. Track Performance and Learn
If you don’t measure how your workflow’s working, you’re just guessing.
- Use Forecastpro’s tracking reports to see forecast accuracy by item, family, or region.
- Look at both bias (are you always over/under?) and error (by how much).
- Share results with the team—good and bad.
Don’t get obsessed with perfect accuracy. If your forecast is close enough to support good business decisions, that’s a win.
7. Iterate—But Don’t Overcomplicate
Demand planning is never “done.” Expect to tweak things, but avoid the trap of endless tinkering.
- Start simple. Add complexity only if you have a clear reason.
- Review your workflow quarterly, not weekly.
- Ask yourself: Is this step helping, or just making things look busy?
What to ignore: Every new feature or statistical model Forecastpro releases. Most teams use only a fraction of what’s available—and that’s fine.
Pro Tips for Forecastpro Users
- Templates are your friend: Set up workflow templates for repeatability.
- User permissions: Don’t give edit rights to everyone. Too many cooks spoil the forecast.
- Documentation: Even a quick comment log beats tribal knowledge.
- Integrations: If your data lives in other systems, automate the sync. Manual handoffs are error-prone.
- Support: Forecastpro’s own helpdesk is decent, but real-world user forums often have better answers.
What to Watch Out For
- Overfitting: If your forecast looks perfect on paper but stinks in reality, you’re probably overfitting. Simpler models are usually more robust.
- Analysis paralysis: Don’t wait for perfect data or models. Get something working, then improve it.
- Workflow sprawl: Every exception, override, or new step adds complexity. Be ruthless about what actually adds value.
Summary: Keep It Simple, Keep It Honest
Don’t let tool complexity or “best practice” hype distract you. Solid demand planning in Forecastpro is about: - Good enough data - Clear, documented steps - Focusing on what matters - Iterating based on real results
Most of all, keep your workflow simple and your process honest. The best teams are the ones who keep things moving, learn as they go, and don’t get bogged down chasing perfection. Start simple, keep tuning, and don’t be afraid to ignore what isn’t working for you.