Background of the Port Performance Scorecard (PPS)

The initiative started in 2012 with a series of international conferences held in cities from the TFT Port Network (Belfast, Manila, Ciawi, Valencia, and Geneva). Thereafter, the Port Performance Scorecard (PPS) has gone through tremendous changes and upgrades to respond to four main technical requests from port members. Indeed, the new pps.unctad.org website now features (1) a more user-friendly interface, (2) incorporated data consistency checks, (3) an automated past-entry function, and (4) advanced analysis tools by regions and categories with automated graphics and filters. The process captures data through annual surveys (starting with year 2010) sent to focal points in each port entity around April to report for the previous calendar year.

Key elements

  • Ports range in size from 1.5 to 80.7 million tonnes in 2019;
  • The average port handled 19.2 million tonnes per annum over the last 5 years;
  • However, the median value for the same period is 8 million tonnes illustrating the skewed nature of the data with more than 50% of ports in the small to medium categories; and
  • 25% of ports averaged less than 3.3 million tonnes over the period.

The financial analysis presented in the PPS platform dashboard, from which selected graphics are reproduced below, shows the range of values for the ports over the 5-year period to 2019. Over the period 2015-2019, the average of the annual total revenues of all participating ports was 1.97 billion USD on 417 million tonnes. The average revenue per tonne varies greatly depending on port financial profile, including port dues, port estate and other services/investment income. The figure illustrates the range of income categories for the participating ports (indicators 3, 4, 5 and 6). The analysis of revenue for ports by region shows the expected dominance of cargo related income for port entities, especially when compared with vessel related income. Thus ports generate more return on working quays for cargo and relatively less against marine assets such as dredged berths and channels.

Labour costs have recorded a stable average over the life of the PPS. Values have settled around 20-22% as a proportion of gross revenue (indicator 2). When analysed by region (Figure 3), there is a significant range across mean values. For Africa, the value is relatively high and Latin America is low. It is not clear at this level of data abstraction if this is because of rates of pay or employee numbers that in turn may reflect levels of private supply to port entities as contractors. In the case of Latin America, the average rate (indicator 10, Figure above) is lower than the global mean suggesting that ports have relatively high staffing levels. However, the analysis is less clear for Africa where labour rates are at the higher end of the range. Europe shows the highest rate per employee of 67,705 USD per annum.



The gender profile remains low in terms of female participation (indicator 12, Figure above). The category that is not very far from a gender-balanced distribution is Management and administration. However there is much to be done across the Network in order to achieve greater female participation.
The relative investment in training is also quite low (indicator 11). However, this may be partially explained by differing data capture methods across the Network.
There is definite scope for a debate on human resource strategies in modern ports. We would welcome feedback on this topic of interest to researchers for the reasons identified here and given the changes in work practices driven by digitilization and security impacts from the COVID-19 pandemic.

This figure illustrates the profile of participating ports in terms of vessel type (indicators 15.1-15.6) and cargo lot size (indicator 14). The graphics show once again that there are no two ports in the world with the same vessel and cargo mix. Both Europe and Africa have the largest average cargo tonnes per arrival or departure but arguably for different reasons given their different vessel mix.


Relating the average time in port to the varied cargo size per vessel is of interest. There is a tight range of 1.5 to 2 days in port. Therefore, the larger cargo lots are logically handled by higher output labour and equipment. With container vessels taking, on average, less time in port at 1.2 days there are higher averages in dry and wet bulks. Dry bulks stay on average 3.5 days however LNG/LPG measures do distort the global average because of a small level of data points and some very high outliers. Therefore, the data reflects the observable reality for port managers.

Waiting times in the online scorecard show little change. Figures bellows provide some insights into the efficiency of container handling operations. There is a wide range of values across the standard performance metrics of dwell time and crane lifting rates. Europe has particularly higher lifting rates that perhaps reflects equipment capacity rather than labour efficiency. Figure 8 shows the highest dwell time in days for each region. This topic requires quite sophisticated analysis to isolate the reasons for slow processing. For example: customs procedures; storage agreements; on port container stripping; multi-user facilities; and congestion in road network at or near the port.




The proportion of total capital spending (CAPEX) on average per annum on investment in environmental projects (indicator 25) averages 7.2%, with 2.3% of operating expenditures reported as dedicated to environmental requirements (indicator 26). This is a difficult number to isolate and therefore the reported benchmarks come with a note of caution. However, throughout the data collection period the recorded numbers have been consistent. It suggests a relatively low proportion of total capital spending and it will be useful to note any upward trend should new regulatory requirements be implemented as climate change effects increase.

UNCTAD’s liner shipping connectivity index (LSCI)

The chart below represent a selection of ports that are members of the TrainForTrade Port Management Programme and for which the LSCI is indicated for 2006 (inception date) and for 2020 (latest data) by port. These data refer to the ports connectivity within contaianer networks and other modes are not included.


Data Partnership

Major improvements have also been conducted in terms of data consistency checks performed by TFT team with the support of data provided by MarineTraffic an UNCTAD partner for maritime statistics. Gross tonnage and total time in port are 2 of the main set of data utilised to operate checks in the pps platform.


Port Performance Newsletter 4

This publication presents UNCTAD’s Port Performance Scorecard 2020 of the TrainForTrade Port Management Programme. 2020 Newsletter

Port Performance Newsletter 3

This publication presents UNCTAD’s Port Performance Scorecard 2019 of the TrainForTrade Port Management Programme. 2019 Newsletter

Port Performance Newsletter 2

This publication presents UNCTAD’s Port Performance Scorecard 2018 of the TrainForTrade Port Management Programme.

Port Performance Newsletter 1

This newsletter presents UNCTAD’s Port Performance Benchmarking: Linking Performance Indicators to Strategic Objectives of the TrainForTrade Port Management Programme

Presentation 2021 of the PPS to Indonesia

Introduction by Mark Assaf, Presentation by Gonzalo Ayala, UNCTAD

Presentation by Dr Joseph HINEY,Chairman Drogheda Port Company
Linking performance indicators with strategic objectives

Presentation by Juan M. Diez, Valenciaport : Strategic Planning & Innovation