Reports: TugIO
Job Level Data
Most fleet and performance assessments stop at the vessel level, but real optimisation starts at the job level. The Job-Level Data module within TugIO gives tug operators, port authorities, and planners access to granular insights on every tug operation. From timestamps and tug specs to fuel burn and idle times, this module enables fact-based comparisons across vessels, operators, and ports. Job-Level Data transforms operational complexity into actionable intelligence.
Ports Explored
Worldwide Annual Cost Savings
KGs of CO2 saved
Report overview
How the Job-Level Data Report can help your business
This report highlights how LionRock’s Job-Level Data delivers detailed insights on every ship assist operation: vessel by vessel, job by job. The dashboard captures full job records including tug and vessel specifications, timestamps, sailed distances, fuel consumption (both measured and estimated), waiting time, and emissions impact.
Crucially, the dataset includes not only your own fleet’s activities but also comparative job data from competitor operations within the same port environment. This enables side-by-side benchmarking of job execution quality, fuel efficiency, and service availability. With visibility into both actual fuel use and model-based estimations, Job-Level Data supports smarter planning, transparent reporting, and continuous operational improvement.
Insight 1
Tug Specs and Operator
This insight shows the specifications of the tug assigned to each job, such as bollard pull, tug type, and power class, along with the responsible operator. It supports performance comparisons across different tug types and operators and helps identify mismatches between tug deployment and job requirements.
Insight 2
Job Timestamps
Job Timestamps give precise records for each phase of the job, arrival, first line, job start, job complete, and departure. These time markers are essential for duration tracking, delay analysis, and benchmarking response or execution speed across jobs or operators.
Insight 3
Distance Sailed
This metric captures the total distance covered by the tug during each individual job, including approach, assistance, and return. It supports fuel and time efficiency analysis, especially when comparing different tugs or routes for similar operations.
Insight 4
Waiting and Idling Time
Understand how long a tug remains idle or waiting before, during, or after a job. This is critical for identifying inefficiencies in job planning and can be directly tied to cost and emissions waste.
Insight 5
Fuel Consumption
Gain insight into actual or estimated fuel usage for each job. When sensor data is available, actual fuel consumption is displayed; otherwise, a machine learning model provides an estimation based on tug specs, job conditions, and job duration. This dual approach enables comprehensive fuel benchmarking even where data availability varies.
Included Reports
Insights we provide:
- Tugspecs and operator
- Vessel specs
- Job timestamps
- Distance sailed
- Waiting and idling time
- Fuel consumption
We Have Answers
Frequently Asked Questions
What makes Job-Level Data different from vessel-level reports?
Job-Level Data drills down into each individual assist operation, capturing critical details like timestamps, distance, fuel use, and waiting time, offering far more granularity than vessel-level averages.
Can I view job data from other tug operators?
Yes. The platform includes comparative job data from competitor tugs operating in the same port, helping you benchmark performance and efficiency beyond your own fleet.
Is fuel consumption based on sensors or estimates?
Both. Where onboard sensors are available, we use actual measured fuel use. Where they’re not, we estimate fuel based on our machine learning model using job specs, tug type, and job conditions.
How accurate are the job timestamps?
Timestamps are sourced from AIS and other operational tracking systems, offering high-resolution data for job duration, delays, and dispatch response times.