Backorders are not just an inventory issue, they create missed installs, rescheduled service calls, idle techs, and frustrated customers. In this lesson, you’ll learn how to track Backorder Rate % over time, spot problem suppliers fast with a heat map, and use a changing target so your team can instantly see what’s above your acceptable threshold.
Download the Excel file used in this tutorial:
Make sure your dataset includes:
These are the only fields needed to calculate Backorder Rate %.
This allows structured references and dynamic expansion.
To group orders by month:
This allows you to bucket all transactions into January, February, etc.
Backorder Quantity is calculated at the row level:
Fill the calculation down the table.
These months will form the rows of your matrix.
Now you have:
To build the matrix:
Copy and paste across the entire matrix after locking the proper references.
This gives total Backorder Rate % per supplier.
This gives total Backorder Rate % per month.
This gives your dataset-wide Backorder Rate %.
This will serve as your changing target value.
Now anything above your target automatically highlights.
If you want the cell to display something like “Target: 4.0%”:
This keeps the cell numeric while displaying a clear label.
Q1. What is Backorder Rate % in inventory management?
Backorder Rate % measures how often ordered items are not fully shipped, resulting in backordered quantity. It’s a key inventory KPI because higher backorders often lead to delays, rescheduling, and operational instability.
Q2. Why does Backorder Rate % matter beyond the warehouse?
Because backorders create downstream problems: missed installs, delayed projects, repeat scheduling work, idle technicians, and unhappy customers. Tracking this KPI helps operations teams reduce friction and protect service capacity.
Q3. What will I learn in this video tutorial?
You’ll learn how to organize inventory data into monthly buckets, calculate Backorder Rate % by month and supplier, and build a heat map that highlights where performance is above your target so you can quickly spot inefficiencies.
Q4. Why use a heat map for Backorder Rate %?
A heat map makes issues obvious at a glance. Instead of scanning rows of numbers, you can immediately see which suppliers or months are driving the most backorders and prioritize follow-up or process changes.
Q5. What is a “changing target cell” and why is it useful?
A changing target lets you set a threshold (like 3% or 4%) and automatically highlight any supplier-month results above that level. It makes the dashboard easier to share because users can adjust the target and instantly see what’s out of bounds.
Q6. Do I need a specific dataset to follow along?
It helps. This lesson uses a structured inventory export with common fields (order date, supplier, quantities, etc.). You can download the sample file linked near the video (or request it) to replicate the same view step by step.