Lost Time Injury Frequency

Goal of the analysis:

Measure how often work-related injuries or illnesses result in at least one day away from work, diagnose underlying risks, and implement controls that prevent recurrence. Lost Time Injury Frequency (LTIF/LTIFR or LTIR) focuses on the most consequential, productivity-impacting events, normalized by exposure hours, so leaders can compare performance across sites and periods. Executives use this analysis to protect people, ensure regulatory compliance, reduce legal and insurance costs, minimize production disruption, and prioritize engineering and operational changes (guarding, ergonomics, pedestrian–PIT separation, LOTO discipline, fatigue management) that sustainably reduce serious harm.

Data required:

• Incident and case data (EHS/OSHA logs):
  • Case details: date/time, site/department/line, shift, employee vs contractor, tenure band, job/role.
  • Classification: lost-time case (days away ≥1), days away count, DART status (days away/restricted/transfer), recordable criteria narratives, SIF potential flags.
  • Injury details: event type (slip/trip/fall, overexertion, struck-by, caught-in/between), body part, equipment/task involved.
• Exposure hours and workforce (HRIS/Payroll):
  • Total hours worked by site/department/shift; split employees, temps, and contractors; overtime hours; headcount and tenure.
• Operational context (MES/Operations):
  • Throughput, changeovers, unplanned downtime, rush order frequency; PIT traffic intensity; maintenance/shutdowns.
• Training and compliance (LMS/EHS):
  • Completion status for LOTO, PIT/forklift, working at height, ergonomics, contractor orientation; procedure availability (JSAs/SOPs).
• Leading indicators and audits:
  • Near-miss and hazard reports, safety observations, corrective action closures/lead time, guarding/LOTO audits, housekeeping/5S scores.
• Environment and PPE:
  • Heat/cold stress indicators, lighting/noise, PPE issuance and compliance records.
• Policy and regulatory references:
  • Definition of “lost-time case” for your jurisdiction, inclusion of contractors, method and base for frequency (per 200,000 hours vs per 1,000,000 hours), counting rules for days away.

Detailed step-by-step instruction on how to conduct the analysis:

1. Define metrics and scope.
   • LTIFR (per 1,000,000 hours) = (Lost-time cases × 1,000,000) ÷ Total hours worked. In OSHA contexts, LTIR (per 200,000 hours) = (Lost-time cases × 200,000) ÷ Hours.
   • Severity Rate = (Days away × base) ÷ Hours; Median/P90 days away per case; DART Rate for context (includes restricted/transfer).
   • Scope: employees and supervised contractors; choose monthly and rolling 12‑month views; define site/department/shift granularity.
2. Assemble and validate data.
   • Extract incident logs and OSHA/EHS case files; join to payroll hours by site/shift and contractor hours if included.
   • Validate “lost-time” classification (beyond first aid, ≥1 day away), deduplicate cases, align case dates with hours periods; document exceptions.
3. Compute rates and severity.
   • Calculate LTIFR/LTIR by site/department/shift and by workforce type (employee vs contractor); include counts with rates to avoid small-denominator bias.
   • Compute Severity Rate and distribution of days away (median/P90) to distinguish frequency vs seriousness.
4. Segment patterns and hotspots.
   • Slice by injury type, body part, SIF potential, tenure (<6 months vs experienced), overtime bands, time of day, day of week, equipment/task.
   • Identify top 10 departments/lines contributing 80% of lost-time cases; compare employee vs contractor rates.
5. Pareto and root-cause analysis.
   • Pareto lost-time cases by event (e.g., manual handling, slip/trip/fall, PIT, LOTO violations, working at height); overlay days away to weight severity.
   • For top categories, run 5‑Why/fishbone; verify control gaps (engineering, administrative, PPE) and systemic contributors (fatigue, layout, training).
6. Link to operating conditions and leading indicators.
   • Correlate LTIFR/LTIR with overtime, unplanned downtime, changeover spikes, rush orders; check whether poor housekeeping/5S or low observation rates precede incidents.
   • Assess PM compliance on safety‑critical assets; review guarding/LOTO audit findings at hotspots.
7. Trend and control.
   • Plot monthly and rolling 12‑month LTIFR/LTIR and Severity with control limits; annotate major changes (layout, new lines, seasonal peaks).
   • Use p‑charts for incident proportion where exposure hours vary widely.
8. Scenario and what‑if.
   • Model reductions from engineering controls (pedestrian–PIT separation, guards), ergonomic redesign, slip‑resistant flooring, PIT telematics/speed limits, enhanced LOTO/permit-to-work, and fatigue management.
   • Estimate avoided cases and days away, productivity gains, and insurance/legal cost avoidance; prioritize by SIF potential.
9. Integrity checks.
   • Ensure contractor cases are included only if their hours are included; keep base consistent (200k vs 1M hours) across all views.
   • Track near‑miss and first‑aid rates to detect under‑reporting; audit a sample of cases against medical records and OSHA 300/301.

Format of the output of analysis:

• Executive scorecard: LTIFR/LTIR, Severity Rate, counts, median/P90 days away, employee vs contractor split, current vs rolling 12 months, target gap.
• Heatmaps: LTIFR/LTIR by site × department/shift; tenure band; PIT zones vs non‑PIT areas.
• Pareto charts: lost-time cases and days away by event type, task/equipment, and body part; SIF potential overlay.
• Trend charts: monthly LTIFR/LTIR and Severity with control limits; leading indicators (observations, hazard closures, 5S scores) in parallel.
• Corrective action register: top risks, owners, due dates, status, verification of effectiveness (pre/post metrics).

How to interpret results:

• High LTIFR with high Severity: Frequent and serious incidents—urgent need for engineering controls and critical risk management (LOTO, PIT, falls).
• Low LTIFR but high Severity: Few incidents but severe outcomes—focus on SIF exposures and permit‑to‑work rigor; audits should target critical tasks.
• Contractor LTIFR > employee LTIFR: Gaps in onboarding/supervision or permit controls—tighten contractor prequalification, orientation, and oversight.
• Tenure <6 months overrepresented: Onboarding/mentoring and procedure usability issues—strengthen training, supervision, and job hazard analyses.
• Spikes coincide with overtime/changeovers: Fatigue and rushed states elevate risk—cap sustained OT, adjust staffing, and reinforce standards during transitions.
• Leading indicators weak at hotspots: Low observations or slow hazard closures predict higher LTIs—raise leading activity and close hazards faster.

Steps a company can take to improve on this measure:

• Engineering and layout controls:
  • Separate pedestrians and PITs (barriers, marked walkways, right‑of‑way rules); install machine guarding/interlocks; deploy ergonomic aids (lift assists, adjustable fixtures).
  • Improve walking surfaces (anti‑slip, drainage), lighting, and housekeeping to prevent slips/trips/falls.
• Critical procedures and permits:
  • Strengthen LOTO, confined space, hot work, working at height programs; use pre‑job briefs and clear permit‑to‑work workflows; audit compliance.
• Operations stability and fatigue management:
  • Reduce rush/chaos via frozen windows and SMED; manage overtime thresholds and breaks; rotate tasks to reduce overexertion.
• Training and competency:
  • Targeted onboarding for new hires/temps; periodic refreshers for PIT/LOTO/ergonomics; contractor orientation; mentor programs for first 90 days.
• Inspection, maintenance, and 5S:
  • PM on safety‑critical assets; pre‑shift PIT/tool inspections; 5S with fast abatement of hazards; routine guarding and walkway audits.
• Digital and analytics:
  • PIT telematics (speed/impact), near‑miss mobile capture, hazard closure dashboards; integrate EHS–HRIS–MES for exposure and context.
• Governance and culture:
  • Daily safety huddles and leader gemba; encourage reporting (no‑blame); enforce stop‑work authority; verify corrective action effectiveness.
• Example scenarios:
  • If LTIR is 1.6 per 200k hours with 40% PIT‑related, implement pedestrian segregation, PIT speed/impact monitoring, and refresher training; target LTIR ≤0.8 in 2 quarters.
  • If manual handling drives 50% of days away, add lift assists and redesign work heights; expect ≥30% reduction in related LTIs and shorter average days away.
  • If new hires (<6 months) account for 3× the LTI rate, strengthen onboarding, assign mentors, and pace complex tasks; reduce tenure‑related LTIs by ≥40% within a quarter.

Benchmark comparisons:

General benchmarks (directional):

• Manufacturing sites often target LTIR (per 200,000 hours) below ~1.0–1.5; top‑quartile programs trend toward ≤1.0 with steady severity reduction.
• Many global reports cite LTIFR per 1,000,000 hours; directional targets in mature programs are in the low single digits, moving toward ≤1–2 for best performers.
• Severity should decline alongside frequency; high Severity with low LTIFR signals focus on SIF controls.

Constructing internal benchmarks:

• Track monthly and rolling 12‑month LTIFR/LTIR by site/department/shift and workforce type; set guardrails (e.g., above internal P75 or any SIF triggers executive review).
• Benchmark tenure, PIT zones, and high‑risk tasks across sites; codify best practices (barriers, speeds, ergonomics, LOTO verification).
• Set leading indicator targets (e.g., ≥10 safety observations per 10,000 hours; ≥90% hazard closures within 14 days) and validate relationship to lagging rate improvement.
• Rebaseline after layout/equipment changes or major policy updates; periodically calibrate against industry/association data recognizing different bases (200k vs 1M hours) and activity mix.