A preliminary insight into the new Container Port Performance Index

The World Bank in collaboration with IHS Markit have recently published their inaugural edition of the Container Port Performance Index (CPPI). The CPPI is a welcomed addition to a growing list of indices on container-port performance (JOC's Berth Productivity Index, WEF's Quality of Port Infrastructure Index, DNV/GL's Container Terminal Quality Index, UNCTAD's new stats on port connectivity and time in ports, etc.). However, as with any index or performance metric, the CCPI must be judged on what it tries to measure, the approach it uses for performance measurement and benchmarking, and the interpretations and implications of its scores and rankings of container ports and terminals.

Unlike previous indices, the CPPI is constructed using two different approaches: (i) an 'administrative approach' where the CPPI team uses expert judgement to assess ship's arrival and berth hours then indexes them as performance scores, and (ii) a statistical approach where factor analysis is used to reduce a large dataset of port variables, including 5 ship-size groups, 10 call-size bands and a two-part berth information (port to berth and on-berth), into a single weighted CPPI ranking score. The assumption is that latent (non-observed) port performance variables can be inferred from the two measured (observed) berth variables namely call-size bands and berth/port-to-berth.

This is the inaugural edition of the CPPI and understandably it is a work in progress. By its own admission, the CPPI team outlines several limitations and one could list other analytical and practical anomalies. For instance, the empirical data underpinning the CPPI is drawn from the IHS port performance program used by the JOC productivity index (JOC was acquired by IHS in 2014), which questions the need for developing two potentially symmetrical and converging indices. Analytically, the weights assigned to the index still rely on 'subjective' expert judgement including for ship size/call categories but those are often uncontrollable factors and fall outside the decision making remit of terminal operators. Similarly, factor analysis could be further expanded to test relationships within and between latent and observed variables, for instance by using techniques such as structural equation modelling. Some independent or additional review may also be required to clean the sample dataset (for instance London has 2 independent container ports while Batumi has little or no container traffic), steer the CPPI towards a productivity index and ultimately an efficiency benchmark, and make sense of some of the CPPI outlying scores and results (for instance on why Beirut is ranked 11th under the statistical approach but only makes it to 63rd place under the administrative approach).

Yet, the main shortcoming of the CPPI and other similar indices stems from their unidimensional view of container-port performance:

• On the one hand, the CPPI is a snapshot metric rather than a productivity index let alone an efficiency one, i.e. relative to an underlying technology or reference benchmark. As such, the CPPI does not assess the ability of a port to use and allocate its resources in an economic and efficient way. This is a fundamental principle in productive efficiency because a port that unnecessarily throws extra capacity resources to improve berth performance may not necessarily be efficient, yet it could end up achieving a high score under the CPPI. No wonder that the top 50 ranked CPPI ports are dominated by deep-sea hub ports with ample spare capacity in East Asia and the MENA regions. Container-port performance must be seen as a balancing act between the needs of customers and users and the constraints placed on port planning, capacity and investment, including such aspects as the lumpiness and indivisibility of many port assets and infrastructure.
• On the other hand, the CPPI is exclusively focused on waterside and berth performance which is unfairly skewed towards the interests of one set of port customers (shipping lines and ship operators) and does not address the needs of cargo interests nor covers land-side and hinterland sources of port congestion and inefficiency. This could explain the ranking prominence under the CPPI of ports with a high transhipment incidence, the latter require little or no inland and hinterland efficiency.
• Last but not least, since the CPPI ranks ports rather than container terminals while at the same time focusing on berth and waterside performance, it would be difficult to properly interpret the results of the rankings or make sound operational strategy and policy recommendations. Many ports around the world follow a landlord model where nautical and marine services are managed and operated by port authorities or by specialised companies other than terminal operators. A single CPPI score would not be able to pinpoint the sources of delays and congestion in a multi-institutional port setting especially where many terminal operators are already bound by performance requirements in their PPP and concession contracts or as part of Service Level Agreements (SLAs) they often sign with various stakeholders.

The above outlines the background of the new CCPI. Despite its shortcomings, the index can provide, if read and understood properly, some indication on how a port's waterside and berth performance compares to that of regional and global peers. However, there is a real danger of misreading and/or misinterpreting the CPPI ranking and the authors should put enough caveats and disclaimers so that no blind interpretation of the scores or rankings is made. There are already many misleading reviews and misguided commentary across port and trade publications, in particular those blindly praising or damning regional and country ports based exclusively on their CPPI scores and rankings.

The subject of container-port performance and benchmarking has always been difficult to address, especially where attempts were made to establish a global reference point or performance index. Some of the difficulties and limitations are outlined in the following papers (1, 2) but as I found out throughout my humble formal and consulting careers, no two container terminals depict similar features in their operating arrangements, market conditions or institutional and regulatory structures.

Back in 2006/7 and drawing on professional contacts and successful experiences in other transport settings such as airports and railway metros and buses, I tried (and failed!) to build up a port benchmarking group, first at Imperial College London and later between GPRA members. Unfortunately, and after several attempts, it became clear that unlike airports and urban railways, container ports and terminal operators compete directly and indirectly with each other. As such, they were not willing to share detailed and confidential data which can be used against them in SLAs and tariff negotiations or even encourage shipping lines' footloose behaviour. Furthermore, many operators who already report performance data either as part of concession performance requirements or due to incentive-based regulations felt that this would add an unnecessary layer of reporting complexity.

Even when (a few years later) I successfully landed my 1st port benchmarking project for two large international terminal operators (ITOs), it was impossible to establish a reference efficiency benchmark even among the container terminals operated by the same ITO. This is because the differences in terminal design, technological configurations and operating conditions are so wide and dynamically changing across world ports that a single reference benchmark is impossible to establish. Instead, technical efficiency benchmarks were estimated for each local container terminal or, where possible, for homogenous groups of terminals.

My work since then has expanded to other ports and operators but I remain of the view that the search of a single performance index for container ports is not justified and may not be achievable. The new CPPI has re(opened) this debate and its inaugural work may evolve in many ways. One option that could be put forward is to move towards measuring productive efficiency(ies) so as to benchmark technical efficiencies while also detecting potential shifts in production technology over time. Another trail that World Bank colleagues could pursue is to complement the CPPI with perception-based surveys of local port users across missing areas and dimensions of port performance. After all, it is those users who can provide informed and honest judgements about the cost and service quality of the port they use and the World Bank has already an excellent track record in structuring and managing similar surveys most notably the highly respected Logistics Performance Index.