Contractor Capability Scorecard
Sample: Northline Roofing
Fictional Minnesota residential roofing contractor · direct to homeowners · 12 employees · roof replacement projects
Fictional example — not a real company, customer result, or benchmark. No scores or measured outcomes are implied.
What is supplied, illustrative, and still to validate
- Supplied by the fictional business
- Trade, direct-to-homeowner model, employee count, roof replacement project type, and the current-process descriptions in this example are fictional intake details.
- Illustrative larger-company practices
- These are examples of operational approaches, not sourced peer research or claims about what every larger roofing company does.
- Assumptions to validate
- Confirm the actual job and approval tools, subcontractor requirements, customer follow-up process, and staff responsibilities with the business.
Capability comparison
The comparison focuses on relevant work practices, not on assuming every larger-company process fits a smaller roofing contractor. AI supports defined tasks; people remain responsible for decisions and outcomes.
Estimating and bid review
- How your business handles it today
- Fictional intake: The owner reviews measurements and prepares most residential reroof quotes from a shared template.
- How larger peers typically handle it
- Illustrative practice: A repeatable estimating workflow connects takeoff, scope checklist, pricing inputs, and a second review for exceptions.
- Your capability gap
- Pricing and scope checks rely heavily on the owner's individual review.
- How AI could help
- Organize project details and flag missing scope items against an approved checklist.
- What requires people or other improvements
- A qualified estimator verifies measurements, material choices, exclusions, and final price. Improve the checklist and cost data.
Field documentation
- How your business handles it today
- Fictional intake: Crews send job photos and completion notes to the office by text.
- How larger peers typically handle it
- Illustrative practice: Job records use consistent photo categories, closeout notes, and a named reviewer.
- Your capability gap
- Photos and notes may be difficult to find by job or confirm as complete.
- How AI could help
- Sort submitted notes and photos into a job record and flag missing closeout details.
- What requires people or other improvements
- A crew lead captures accurate evidence; office staff verify quality and completion. Agree on a simple capture standard.
Change-order management
- How your business handles it today
- Fictional intake: Extra work is discussed by phone or text; documentation varies by job.
- How larger peers typically handle it
- Illustrative practice: Requests have an owner and are tracked from description and price through customer approval and billing.
- Your capability gap
- Consistent capture, ownership, approval status, and billing handoff.
- How AI could help
- Organize field notes, draft a change description, flag missing details, and prepare follow-up reminders.
- What requires people or other improvements
- Confirm scope, set pricing, authorize work, and approve billing. Establish a clear approval rule and record.
Project visibility
- How your business handles it today
- Fictional intake: The office checks progress by calling the crew lead and updating a shared calendar.
- How larger peers typically handle it
- Illustrative practice: A job list shows owner, next milestone, blockers, and last update in a shared view.
- Your capability gap
- Progress and blockers are not visible in one consistent place.
- How AI could help
- Summarize approved job updates and highlight records that may need a status check.
- What requires people or other improvements
- Crew leads report status and a coordinator resolves blockers. Set useful milestones and keep the job list current.
Billing and collections
- How your business handles it today
- Fictional intake: The office prepares invoices from completed-job notes and follows up from a calendar reminder.
- How larger peers typically handle it
- Illustrative practice: Closeout evidence, invoice status, due dates, and follow-up responsibility are tracked together.
- Your capability gap
- A completed job can wait while details are gathered or follow-up ownership is unclear.
- How AI could help
- Assemble a draft invoice packet from approved job records and create reminders for staff review.
- What requires people or other improvements
- Verify the work, contract terms, invoice amount, and customer communication. Improve the closeout checklist and ownership.
Subcontractor paperwork
- How your business handles it today
- Fictional intake: Insurance and job documents are requested by email when needed.
- How larger peers typically handle it
- Illustrative practice: Required documents, review status, and renewal dates are kept in a shared vendor record.
- Your capability gap
- Document completeness and renewal status may depend on memory and inbox searches.
- How AI could help
- Sort documents, extract dates for review, and remind the assigned person about upcoming checks.
- What requires people or other improvements
- Verify the document, coverage, and contractual requirements. Define required records and who may approve them.
Customer follow-up
- How your business handles it today
- Fictional intake: The owner handles estimate follow-up when time permits.
- How larger peers typically handle it
- Illustrative practice: Estimates and customer questions have a recorded next step and assigned follow-up owner.
- Your capability gap
- Follow-up can be delayed when the owner is focused on field and office work.
- How AI could help
- Prepare a draft response or reminder from the estimate and conversation history.
- What requires people or other improvements
- Choose the right timing, review the message, answer customer questions, and maintain a respectful contact policy.
AI use and governance
- How your business handles it today
- Fictional intake: A few staff have tried public AI tools; no written company guidance is reported.
- How larger peers typically handle it
- Illustrative practice: Approved tools, data rules, and human review expectations are communicated to staff.
- Your capability gap
- Staff may not know what customer or company information is appropriate to enter.
- How AI could help
- Help draft internal guidance and summarize approved, non-sensitive material within reviewed workflows.
- What requires people or other improvements
- Leaders select tools, set data and access rules, train staff, and review output before use.
Each capability card includes the six comparison fields shown in the full table.
Three practical priorities to validate
These are discussion priorities for the fictional example, selected for cross-team usefulness and practical first steps—not promised savings or results.
Make field closeout information easier to find.
- Why it matters
- Photos and completion notes support customer updates, change documentation, and invoice preparation, so improving capture can help several handoffs.
- Practical measurement
- Track the share of completed jobs with the agreed photo set and closeout note recorded before invoicing.
- Human responsibility
- A crew lead captures the information; an office coordinator checks completeness and improves the checklist.
Record extra work from request through billing.
- Why it matters
- A consistent record can reduce missed handoffs and clarify whether work is described, priced, approved, and ready to bill.
- Practical measurement
- Review the share of change requests recorded before work begins, plus time from request to a complete invoice handoff.
- Human responsibility
- The estimator confirms scope and price; the authorized person approves work; office staff update status and billing.
Create clear, safe rules for AI use.
- Why it matters
- Simple guidance helps staff use suitable tools without exposing customer information or treating generated text as verified fact.
- Practical measurement
- Record whether staff have received the policy and periodically review which tools and workflows are in use.
- Human responsibility
- A business leader approves tools and data rules; staff follow them and check every AI-assisted output.
Find the capability gaps in your own business.
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