Brief presentation evaluation of the fleet economic performance

Programa de Atualização Profissional

Evaluation of the Fleet Economic Performance

methodology summary

by Gláucio Bastos, M.B.A., Ch.E.


abstract

target: vessels fleet productivity definition from relevant economic data whatever the vessels chacracteristics or their activity and location

due to the difficulty of obtaining complete data on costs, revenues, employment and activity of the entire fleet, we set a representative and otpimized sample from the total number of vessels for this survey which allows to calculate the revenues by ship according to its characteristics and its activity

statistical analysis to define a model for fleet’s gross revenue allows to asses its activity level


data collection

annual surveys are conducted to update the collection of the following data:

activity (objective, areas of operation, duration and number of trips)

diversification of activities (besides the main one) ship (physical characteristics, purchase price, insurance

value, as is estimated value) major equipment (description and cost of acquisition

and maintenance of essential parts for the main activity)


data collection annual surveys are conducted to update the collection of

the following data :

other onboard equipment (motor, electronic, mechanical, for storage)

revenues and costs (transaction value, operating costs - fuel, oil, food, dockage, insurance premiums, repairs, maintenance, etc).

crew (quantity, functions, salaries)

vessels are grouped into segments each with common characteristic bands


sampling

for obtaining reliable economic indicators covering the entire fleet, the sampling plan is optimized

fundamental to a minimum accuracy level of economic indicators

the minimum (best) sample is estimated for each segment so that in at least 80% of the measurements, the range of variation (precision) around vessels average revenue is 40% with 95% certainty (as required by the regulator)


sampling

vessels are selected for an interview according to a systematic random sampling procedure

it is applied within each segment to ensure location and vessel length representativity


gross revenue model

each segment has its linear model data parameters with significance are (costs are not

significant for the revenue): ship length crew number annual operation months number (least significant at

25%) held life cycle

accuracy is good mainly due to there is a specific model for each fleet segment


gross revenue model there is a correlation between the following parameters:

length and crew number operation months number and crew number crew number and lifecycle (least significant at 15%)

e.g. in the case of segment “TrawlerNex length<12m.”: population size: 237 minimum size of the representative sample : 6 Gross_Revenue = -7.03 - 19.1 x Length – 11.7 x Crew – - 103 x Months – 15.4 x LfCycl + 8.63 x Crew x Length + + 48.4 x Crew x Months + 4.34 x Crew x LfCycl(Revenue in $, Length in meters, LfCycl in years)


results* evaluation of the sampling distribution algorithm*

comparison of the distribution between sample and population by region [SRG,AQ,...,PL,SB] and by length [12 – 23 meters]

e.g. for the fleet segment “DemTrawl 12-24m“:

is good the length representation and excellent the spatial representativeness


results

model of the overall revenue is used to assess the total income of the fleet segments

cost data allows assessment of the overall and segment gross profit and the direct employment level of the fleet


results the model of the gross revenue allows definition of each fleet

segment contribution for total gross income and total gross profit economic data allow assessment of the intermediate costs for a

significant sample of vessels covering the full range of activities

Brief presentation evaluation of the fleet economic performance

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