HR & Contractor Workforce Analytics

Contractor labour hours audit fails when muster, subcontractor SOV, and gate logs disagree on the same day and the same package. Without hour-level reconciliation, clients overpay for idle or ghost strength while honest vendors absorb schedule shocks silently.

FireAI ingests daily or shift-level attendance, site gate transactions where available, and certified work quantities so you can compare billed or claimed man-hours to physical progress and contract norms. Real estate hr contractor analytics flags variance by trade, floor, and contractor with drill-down to the shift pattern that caused it.

How FireAI solves the problem: It maps your vendor and internal codes once, matches attendance to work front and rate contract rules, and refreshes as RA and muster data land so contractor labour hours audit is repeatable for internal audit and main contractor reviews.

What FireAI tracks:

• Present strength versus planned and versus billed hours
• Overtime and double-shift concentration by package
• Idle hours against weather, material, or hold reasons when logged
• Trend versus prior months for the same site phase

What you can ask FireAI:

• "Which contractor claimed more man-hours per sqm of slab pour than peer packages this month?"
• "Show contractor labour hours audit variance for MEP in Tower C"

Site supervisor performance tracking is subjective when it relies on anecdote, WhatsApp groups, and monthly ratings without a link to safety, quality, and schedule outcomes on that supervisor’s patch. High-risk zones need coverage data, not only seniority on the org chart.

FireAI ties walk-around logs, toolbox attendance, incident and near-miss location, and sub-contractor scorecards to supervisor or engineer IDs where your systems support it. Real estate hr contractor analytics shows coverage versus plan, first-response time to holds, and trends in repeat issues on a supervisor’s area.

How FireAI solves the problem: It standardizes performance dimensions you already capture, adds time-on-front where mobile or access data exists, and makes site supervisor performance discussable in weekly reviews with evidence.

What FireAI tracks:

• Planned versus actual site walks and toolbox talks
• Incident and high-severity near-miss density by zone owner
• Certification and quality hold closure speed when attributed
• Sub-contractor NPS or score trends by supervisor (if you collect them)

What you can ask FireAI:

• "Which shift reported the most uncorrected high-risk observations for Supervisor Zone B?"
• "Compare site supervisor performance for two sample towers on coverage and close rate"

Safety incident frequency analysis breaks down when LTI, MTI, and near-miss data sit in EHS software that does not connect to trade mix, headcount, or training expiry for the same week. Project boards see counts without a fair denominator or root-cause pattern.

FireAI classifies incidents by type, body part, trade, and shift, then normalizes with hours-on-site or man-days where data exists. Real estate hr contractor analytics shows frequency rate trends, repeat mechanisms (falls from height, struck-by, electrical), and contractor packages that need targeted intervention.

How FireAI solves the problem: It joins incident registers to muster and training lists with consistent IDs, so safety incident analysis highlights leading indicators before a lost-time event repeats the same story.

What FireAI tracks:

• LTI, MTI, and first-aid case frequency and severity mix
• Near-miss to incident ratios by trade and contractor
• Training or induction gaps correlated with high-risk work orders
• Stop-work and permit breach counts when logged digitally

What you can ask FireAI:

• "Did incident frequency rise after the new façade contractor doubled headcount?"
• "Show safety incident frequency for electrical work in the last 90 days"

Headcount vs project milestone is misaligned when the schedule accelerates a slab or envelope trade while procurement still releases steel or glass, leaving crews idle or undermanned in the same month. Manpower plans in Excel rarely re-tie to the latest baseline after every revision.

FireAI links revised milestone dates, float, and resource-loaded tasks from your planning tool or import files to on-site muster and contractor commitments. Real estate hr contractor analytics shows overhang or shortfall of key trades versus the next 30 and 60 days of critical work.

How FireAI solves the problem: It projects required crew curves from the milestone view you trust, compares to submitted manpower plans, and flags headcount versus project milestone gaps for procurement and contracts to act early.

What FireAI tracks:

• Planned strength by trade versus recommended band from schedule logic
• Milestone slippage impact on next-month crew need
• Surge and ramp-down cost exposure when you model rates
• Dependency on single subcontractor for a bottleneck trade

What you can ask FireAI:

• "If Tower D slab moves two weeks, how does headcount for shuttering need to change?"
• "Show headcount vs project milestone for façade against the current programme"