Overview
INNERGY’s Regression Analysis tool helps you estimate labor hours by product type using real data from your own shop floor. By tagging shipment items with standardized regression types and pairing them with actual tracked labor hours, INNERGY calculates the best-fit model for your production — giving you a data-driven foundation for labor standards and estimating.
Before you begin: Regression Analysis requires that your shipment items are tagged with regression types. If your items are untagged, complete the tagging process first. See Step 1 below.
How It Works
INNERGY uses regression analysis to find the statistical relationship between the types and quantities of items you ship and the labor hours it takes to build them. The result is a set of estimated hours-per-unit for each product type — calculated from your historical work order data.
Two key statistics tell you how reliable your model is:
R-squared measures how well the model explains your data. It ranges from 0 to 1. A value close to 1 indicates a strong, reliable model. Values above 0.90 are generally considered excellent in a shop environment.
P-value measures whether the relationships in your data are statistically significant. A p-value below 0.05 means the pattern is real — not the result of random variation.
Both statistics are available in the Advanced Statistics toggle inside the regression results view.
Step 1 — Tag Your Shipment Items
Regression type tagging is required. Items without a regression type are excluded from the analysis, and work orders with less than 80% of items tagged will trigger a data quality warning.
Navigate to: Manufacturing MES > Shipping > Shipment Items Grid
Recommended Saved View
Create a saved view with these four columns to support tagging work:
Column | Purpose |
Project Name | Identifies the project |
Work Order Number | Links to the work order |
Shipment Item Name | Identifies the item to tag |
Regression Type | Shows current tag or blank if untagged |
Filter by blank Regression Type to see all items that still need tagging.
How to Assign Regression Types
Regression types can be assigned in three ways:
• Manually — Inline editing in the Shipment Items Grid
• Engineering sync setup — Configured during engineering sync
• Integration — Automatically assigned through CAD/design integrations including MicroVellum, Mosaic, Ajax, and CAD/MAVISION
Standard Regression Type List
INNERGY uses a standardized list of regression types. Users must select from these built-in options:
Category | Available Types |
Base Cabinets | Base cabinets, Base cabinets with doors, Base cabinets with drawers, Base cabinets with doors and drawers |
Upper Cabinets | Wall cabinets, Upper open, Microwave cabinets |
Tall Cabinets | Tall cabinets |
Countertops | Plastic laminate, Solid surface, Solid surface loose backsplash, No backsplash, Loose backsplash |
Other Products | Die wall products, Paneling products |
Note: Some product types (such as trim) do not yet have regression types. INNERGY is actively expanding the list.
Step 2 — Select Work Orders
Navigate to: Work Order Grid
Use a saved view called Regression Analysis to display work orders alongside their shipment item counts.
Important: Only select work orders that have shipment items. Work orders with zero items will cause an error. Sort by shipment item count to bring populated work orders to the top before making your selection.
Select the work orders you want to include, then click Regression Analysis to open the configuration page.
Step 3 — Configure and Run
On the configuration page, choose your labor scope:
Option | Use When |
All labor hours | You want a total production picture |
Specific labor item (e.g., Case Good Assembly) | You want to isolate a particular operation |
Data Quality Warning
INNERGY will display a warning if any selected work order has less than 80% of its shipment items tagged. Work orders in this state can skew your results. It is recommended to either complete tagging on those work orders or exclude them from the analysis before proceeding.
Click Next to run the analysis and view results.
Step 4 — Read Your Results
The regression output displays estimated hours per unit for each tagged product type. Example output:
Product Type | Estimated Hours per Unit |
Base cabinet with doors | ~4.7 hours |
Wall cabinet | ~0.96 hours |
Tall cabinet | ~3.1 hours |
These estimates are derived from your actual labor-tracked work orders — not industry defaults.
Advanced Statistics
Toggle on Advanced Statistics to view:
• R-squared — How well the model fits your data (target: close to 1.0)
• P-value — Whether the results are statistically significant (target: below 0.05)
If the system is unable to calculate statistics, it is typically a sign that tagging is incomplete or the dataset is too small to produce a reliable model.
Tips for Better Results
• Tag shipment items consistently across all projects, not just recent ones. More data improves model accuracy.
• Run regression analysis periodically as you add new completed work orders to your dataset.
• If your R-squared is low, use the Shipment Items Grid to find and fix gaps in tagging before re-running.
• Narrow your labor scope to a specific labor item (such as Case Good Assembly) for more targeted estimates.
Limitations and Known Constraints
Limitation | Detail |
No custom regression type names | Users must choose from INNERGY’s standard list |
No operation-level inputs (yet) | Currently limited to labor-item-level data; operation-level inputs are in development |
Some product types not yet supported | Trim and certain specialty items do not have regression types yet |
Empty work orders cause errors | Always verify shipment item count before running |
Related Articles
• Setting Up Engineering Sync
• Tracking Labor Hours in Work Orders
• Using Saved Views in the Work Order Grid
• Shipment Items Grid Overview