👥 Who it’s for: Chief Estimators, Precon Managers, Executives
🗓 When to use it: When you decide whether to pursue a job, or before you lock your number
Is this bid in line with what you've built before? Muro finds your most similar past projects in Procore and BuildingConnected, matched by type, size and location, and shows how this bid compares on value and cost per square foot.
At a glance
🔌 Connect | Your project management tool and bid management tool (e.g., Procore, BuildingConnected) |
📁 Add these files | Optional: your estimate, if the bid isn't in your tools yet |
📄 You get | A side-by-side table of your most similar past projects, history stats (average and median value, cost per square foot, range), a short analysis and a list of data gaps, as Excel and PDF |
⏱ Takes about | A few minutes |
What to ask
1. Run the benchmark:
Benchmark the Medical Office project against similar past projects in Procore and BuildingConnected.
2. Narrow the comparison:
Only compare healthcare projects over 30,000 SF from the last five years.
3. Summarize it for the go/no-go meeting:
Summarize where this bid sits against our history, and what explains the difference.
Go further:
Pull our historical unit costs for Division 03 from Procore job costs.
Score this opportunity for go/no-go.
Tips & best practices
✅ Connect both tools first. Procore has the jobs you built, and BuildingConnected has the jobs you bid. Together they give the best match.
💡 Keep project details filled in. Muro reads the value, type, size and location from each project's details. Projects with missing values still show up, flagged as data gaps.
💡 Check the match, not just the average. Each past project gets a match score. Look at the closest few before you draw conclusions.
✅ Run it early. Use it next to your go/no-go score, before anyone starts a takeoff.
Good to know
Muro only reads from your tools. It doesn't change anything in Procore or BuildingConnected.
The comparison is only as good as your project records. Muro lists anything it couldn't find under Data gaps.