Unlock better decision-making with this easy-to-use dashboard

👋 Introduction: Why Forecast Accuracy Matters

Ever spent hours building forecasts only to discover huge gaps between expectations and reality? You’re not alone.

Whether you’re in sales, supply chain, or business analytics, forecasting is essential—but rarely perfect. Inaccurate forecasts can lead to excess inventory, missed opportunities, or poor planning decisions. That’s where a forecast accuracy dashboard can be a game-changer.

In today’s post, I’ll walk you through a simple yet powerful Excel model that helps you measure and improve your forecast accuracy—no expensive tools required.

🎯 What You’ll Learn in This Tutorial

In this video (and now in this blog post), I share a step-by-step guide to create a forecast accuracy dashboard using:

• Dummy sales and forecast data across 6 US regions
• KPIs like MAPE, Normalized MAPE, and Bias
• Top 10 items with the biggest forecast errors
• A detailed report to drill down into item-level performance
• A dynamic dashboard with slicers and pivot tables

Why it matters:
This tool is great for supply chain professionals, sales planners, and analysts who need a quick and visual way to track how well their forecasts match reality—so they can pivot fast and improve future planning.

📺 Watch the full video for a hands-on walkthrough :

📊 Dashboard Overview

Let’s break down what’s included in the template.

🔢 1. Sample Data Setup

• Regions: 6 fake US regions
• Sales Reps: Assigned randomly
• Models: Top 30+ selling cars
• Timeline: 2 years of monthly data
• Randomized forecasts vs. actuals to simulate real-world scenarios

Everything’s calculated using simple Excel formulas and VLOOKUP, then values are pasted for use in analysis.

📈 2. Key Metrics & Pivot Tables

We calculate three main KPIs:

• Gap – Difference between forecast and actual
• Normalized MAPE (nMAPE) – How accurate your forecast was, scaled for impact
• Bias – Are you over-forecasting or under-forecasting?

✅ Normalized MAPE uses the maximum of forecast or sales to normalize the gap—providing a more realistic view of accuracy.
✅ Bias shows whether you’re consistently off in one direction (over or under).

These are added as calculated fields in your pivot table, which means they’re dynamic—adjusting automatically as you filter or slice the data.

📉 3. Top 10 Forecast Errors

A pivot table lists the Top 10 models with the highest absolute gaps, helping you pinpoint which products consistently miss the mark.

This view is crucial for prioritizing action—maybe it’s time to dig deeper into why those models are underperforming.

📃 4. Detailed Data Report

Want to see the raw numbers?
A clean, flat view includes:

• Date
• Country / Region
• Model
• Sales
• Forecast
• All calculated metrics

This allows you to audit and drill down without having to dig through different reports or tabs.

📊 5. Dashboard Charts

• Clean combo charts show trends over time
• Dynamic slicers let you filter by region, model, or sales rep
• KPIs update automatically as you explore the data

The visuals are simple, but effective—perfect for presenting in meetings or sharing with your team.

📥 Get the Template

Want to try it out yourself?
💡 Download the Forecast Accuracy Dashboard Template and start optimizing your forecasting today.

🙌 Final Thoughts

Forecasting doesn’t have to be a mystery. With this Excel model, you can see exactly where your predictions are going wrong—and take action to fix them.

This dashboard is perfect for:

• Sales & Operations Planning (S&OP)
• Demand Planners
• Supply Chain Analysts
• Anyone working with forecast data

Thanks for reading, and happy forecasting!
– Elad