In our kick-off Ask the Expert session, our team explains why data quality is the starting point for successful account reviews—and how to strengthen your UpKeep foundation for 2026.
We cover practical setup standards, common pitfalls that break reporting, and how NOVA can help you validate and clean up data at scale. This session also includes live Q&A and demos.
What we cover
Why a strong data foundation matters before optimization and reporting
UpKeep’s core data model: Locations → Assets → Parts → Work Orders & PMs
Common setup mistakes and how to avoid them
How to use NOVA to identify gaps and clean up data in bulk
Key takeaways
Optimization only works if your data is trustworthy. Incomplete or inconsistent data leads to unreliable reporting and reactive maintenance.
Consistency beats completeness. Choose the fields that matter and standardize how they’re filled out across the team.
Tie work to assets whenever possible. Location-only work orders limit lifecycle history and cost insights.
Log parts in structured fields—not in notes. Notes won’t deduct inventory or support accurate cost/usage reporting.
Use NOVA for ongoing data hygiene. Identify missing fields, duplicates, and reporting gaps before they become bigger problems.
Best practices at a glance
For admins and managers
Build a clear location hierarchy (site → building → area/line)
Use consistent naming conventions for assets and parts
Ensure every asset is assigned to a location and ensure work orders have assets and locations attached where applicable
Require technicians to capture key completion details (status, time, parts, closeout notes)
Use dashboards and scheduled reports to monitor data quality over time
For technicians
Create work orders from the correct asset (and location) when applicable
Update work order status as work progresses (not just open → complete)
Log time and parts used consistently
Add clear, complete closeout notes to support reporting and history
Using NOVA to validate and strengthen your setup
NOVA helps you spot gaps quickly and clean up data efficiently.
Use NOVA to:
Identify assets missing key fields (category, criticality, manufacturer details, etc.)
Find assets not tied to a location
Surface “ghost assets” (assets with no work order or PM history)
Summarize assets by location and category to catch inconsistencies
Flag incomplete work orders (e.g., closed without labor time or parts recorded)
Support bulk updates (moving assets, standardizing fields, correcting gaps)
Example NOVA prompts
“Which assets are not tied to a location?”
“Show me assets with no work order history or PM history.”
“Where is my data collection failing in work orders from the last 90 days?”
“List work orders closed without labor hours or parts logged.”
“Summarize asset counts by location and category.”