Creating Pivot Tables with Frame and a 3D Viewer

Why pivot tables still win for takeoffs

Most teams already trust Excel for cost checks and scope reviews. The problem is speed: exporting schedules, cleaning columns, then re-running everything after each model update. A pivot table fixes the analysis layer, but you still need a clean, model-linked dataset and a fast way to verify results.

That is where the Frame for Excel add-in helps. It creates the model-linked tables directly in Excel with stable element IDs, and it can generate both:

• Flat tables (one row per element) for detailed QA and filtering.
• Pivot tables for fast summaries by level, type, phase, or material.

From there, you can click a row and see the exact elements highlighted in a live 3D viewer. You get familiar Excel analysis without losing traceability back to the model.

Build the flat table with the Frame for Excel add-in

Start by creating a flat table in Excel from the add-in. Keep one row per model element and include only the fields you plan to group, filter, or validate.

Recommended columns

• Element ID (externalId)
• Category
• Family
• Type
• Level
• Phase
• Material
• Quantity fields (Area, Volume, Length, Count)
• Cost or unit rate if available

If your model has naming drift, add a normalized field (for example, a cleaned Type name) in the add-in output before analysis. That keeps your pivot groups tight and reduces rework.

Build the pivot table with the same add-in data (fast, repeatable)

To create a pivot table with the Frame for Excel add-in, use the add-in menu in Excel:

1. Open the add-in and click Export Options.
2. Choose Export Pivot table to current sheet or Export Pivot table to a new sheet.
3. Confirm the export and start with the generated pivot table.
4. Create a baseline view: Drag Category and Type into Rows, and Area or Count into Values.
5. Add a cost check: If you have Unit Cost, add a calculated field for Total Cost.
6. Slice by level or phase: Drop Level or Phase into Filters or Columns to isolate work packages.
7. Keep it readable: Turn off subtotals you do not need and format values with units.

Example: wall takeoff by level

A common check is wall area by level. Here is a simple layout:

• Rows: Level → Type
• Values: Sum of Area
• Filters: Phase = New

This view gives you quick totals per level, and it also exposes outliers. If one level spikes, you can drill in by Type and then cross-check in 3D.

Validate the numbers with the 3D viewer

Pivot tables are fast, but they are only as good as the input. Use the viewer to prove the totals.

A practical validation flow

• Select a pivot row (for example, Level 03, Type W-201).
• Filter your dataset to those rows.
• Sync that selection to the 3D viewer.
• Visually confirm the elements belong to that level and type.

This is where element IDs matter. If your viewer selection does not match the pivot row, you have a data mapping issue, not an Excel issue.

Common pitfalls and how to avoid them

• Duplicate types: Standardize Type names before exporting.
• Mixed units: Verify that area and volume are consistent across categories.
• Phasing overlap: Lock your pivot to a single phase when reviewing scope.
• Missing elements: Filter for null values in key fields (Level, Type, Material) and fix them at the source.

Turning pivots into a repeatable workflow

Once your pivot is stable, the rest is just refresh and verify:

• Keep the same column order in every export.
• Replace the data table, then Refresh All.
• Re-run your 3D validation on any category that changes by more than a set threshold.

Over time, you can turn this into a clean audit trail: the pivot shows the numbers, and the viewer proves the scope.

Next step

If you want to build this workflow for your team, we can set up a pilot with your models and a ready-to-use export template.

CTA: Book a pilot.