Smart decision-making and collaborative alignment
How often do we experience that decisions are being made on the basis of static information? Picture a printed document listing expected arrival and departure times for the ships visiting a port, or a list of reservations made for berths and other infrastructure. From the moment that it is printed, the information in the document may be out of date.
As digital innovations are adopted ever more widely, opportunities to explore the results of access to real-time data will challenge traditional patterns of behaviour. The success of tomorrow’s company is not just about making smarter decisions; it is also about challenging the traditional roles and processes adopted by the many engaged actors within the emerging – and increasingly necessary – collaborative environment.
Fail to collaborate, prepare to fail
As in many other industries, opportunities are now arising for empowered decision-making based on an increasing access to digital data streams. Everything is claimed to have become smarter, such as smart ships, smart ports, smart containers etc.
Different parties have begun to join forces in establishing local and/or horizontal information sharing communities in order to stay up to date. However, one does need to question whether engagement in such communities aims to empower the capability to make smarter decisions, or whether the engagement is based on incentives of true collaboration in the joint co-creation of maritime transport services providing value to the clients of maritime sector.
There is no doubt that the technology is available – standards for messaging and interfaces are increasingly in place – but do we really have the right perspective on why we engage in digital collaboration?
As we will argue in this short article, optimisation, synchronisation, greater efficiency and improved service delivery in maritime transport will not happen if the actors involved do not establish processes for the continual alignment of their plans based on outcomes and disruptions further up the value chain, and by providing better information services on predictability as is increasingly desired by the clients of maritime transport.
To do this, the actors must learn to continually share data and be convinced that this behaviour is a virtuous circle that will benefit all parties. It is now a call for collaborative alignment based on digital data sharing among engaged actors.
The maritime industry is often conceived as a self-organised ecosystem. It is composed of a multitude of actors being mostly in competition, but at the same time part of alliances for specific markets or trades.
By contrast with the coordination processes across different actors adopted in the aviation industry, maritime lacks an overarching coordination body. This creates the necessity for actors to voluntarily share data with each other to ensure that the total value brought from the co-production of digital services is achieved.
Digital data sharing between engaged actors in a pre-defined way is what has been conceived as ‘digital collaboration’. For a modern, efficient and dependable maritime supply chain to operate in a satisfactory manner, the dependency between the involved actors requiring each of them to inform the other about progress and disruptions in order to synchronise their plans must be acknowledged.
Historically, due to the lack of information and the complexity of planning, many operators have adopted a rule of first-come, first-served – which is inherently inefficient, unpredictable and not cost effective. The installed base of IT systems in the maritime sector also reflects this situation, where many lack connectivity to systems outside the control of the organisation that the system is serving.
Fragmented and unrealistic situational awareness in operators’ decision-making leads to underutilised or wasteful use of resources. However, for those systems that are aiming to connect actors together in sub communities, such as port community systems (PCS), community systems for supply chain visibility, etc., strong voices are then raised that enable standardised data sharing that go beyond manufacturer-specific solutions.
Actors in self-organised ecosystems make decisions based on their perceived situational awareness. This includes data acquired from operations beyond the scope of what is generated by the organisation itself.
Situational awareness is thus essential to fulfilling the task at hand. Situational awareness can be defined simply as ‘knowing what is going on around us’, or – more technically – as “the perception of the elements in the environment within a volume of time and space, the comprehension of their meaning and the projection of their status in the near future.”
As maritime operations are continuously adapting to new situations (as part of their DNA) there is a need to make decisions on when to set aside infrastructure and resources to serve others. This should be based on the latest possible information which can be continuously updated to reflect new and changing circumstances.
Importantly, independent of whether the information is acquired in a direct peer-to-peer interaction or from information based on complementary sources of data, engaged actors will base their decisions on the best data at hand.
What has become clear is that many IT systems are not being updated with the latest information on such things as arrival and departure times for ships or when operations are planned to be conducted. This jeopardises the smoothness of the port call process. Utilising multiple sources of information to cross-check the data upon which the actor is basing their decision is key to assuring timely operations.
In the model below we elaborate on how engagement in information sharing communities can act as an example of a collaborative environment, allowing collaborative alignment and providing a foundation for making smart decisions.
As the growth in connected devices, such as e.g. smart containers, continues in the maritime sector and is expected to boost the accessibility to additional and complementary data sources, the foundational support for smart decisions is increasing substantially. This, combined with the capture of data in systems of production, will provide the essential components needed for optimisation and predictability along the maritime transport chain, as well as the transport chain across several modes of transport.
The situation might apply to a just-in-time arrival and departure to/from a port or a passage through confined or restricted waterways. The overall need is based upon the desire to coordinate and satisfy the supply of e.g. port call services demanded by multiple clients, particularly when the demand is for the same services at the same time or the same location.
While there may be individual initiatives to predict events, there is untapped potential in a predictive supply chain. Many actors are working on increasing the accuracy of predictions, and then acting when the actual event happens, as opposed to acting on the prediction to visualise alternative options and re-plan the future. This is where collaborative alignment on standards and accessibility are a prerequisite to release the true value of this process.
The future will require smart long-term and short-term decisions to be made within a collaborative setting. We have learned in recent years that it is extremely hard in maritime to forecast when a particular movement or operation will take place. There is thus a continual need for updates on plans and progress as the initial plans that were established do not transpire.
Attempts have been made to overcome this by utilising historical data in artificial intelligence applications, such as big data analytics and machine learning. An unresolved quest however is whether this is going to be enough to reach the optimum infrastructure and resource utilisation desired by the many engaged actors of the maritime industry.
It is also unlikely that such efforts can provide adequate reliability for the clients of maritime transport, such as the cargo owners and other supporting modes of transport. There is thus a need to establish data sharing environments where those that know something share that knowledge with the rest of the community engaged in the same environment.
The potential in exposing, accessing and using predictive data in smart decision making is not yet driving processes. Participating in this new landscape of digital opportunities will require upgrading of processes and the introduction of new roles by many of the organisations that have a long history of operating in the maritime industry.
Editor’s note: This article is an abridged version of a longer paper by the authors, which includes further details on the projects and use cases mentioned above, as well as a full list of references. The full paper can be downloaded here.