Digitalization and new developments in the field of artificial intelligence, blockchain, IoT and automation are becoming increasingly relevant for maritime transport. They help streamline existing processes, create new business opportunities, and transform supply chains and trade geography. Despite the potential, opportunities and benefits offered by these technologies, they also entail risks and potential costs for maritime actors in developing countries. Thus, it is necessary to create a level playing field. This policy brief discusses the role of interoperability and global standards, the importance of driving technological innovation while avoiding monopolistic outcomes, and the need to ensure that digitalization works towards the Sustainable Development Goals.
The impact of digitalization on maritime transport can be divided into the following five stages:
1. Examine your current state
Study the datasets used carefully. What types of data do you collect from your organization? Who uses this data and what does it serve? How is data managed throughout its life - how is it collected, verified, cleaned, distributed to downstream systems, protected and verified? With a thorough analysis of the data on which you make decisions and how they do it, you can begin to outline the data architecture that will be the starting point for your digital transformation.
2. Explore your future state
What do you want to do with your data in the ideal future? Where can this data bring the most value to your business? How could this support your organizational goals? Perhaps the data will help you demonstrate greater transparency in the face of increasing supply chain volatility. You may be planning aggressive business growth through increased bandwidth, customer acquisition, or infrastructure projects. Perhaps this data will help you improve the quality of service and achieve greater customer loyalty in a highly competitive market. Start with your organization's goals and work backwards to prioritize data.
3. Create a framework
«efore starting a digital transformation initiative, focus on master data management (as defined above). Create a structure that manages all of your datasets to ensure that data is accurate, validated, consistent, and ready to support automation and analytics across different user groups. There is a valuable lesson to be learned from the first wave of industries that embarked on digital transformation, many of which skipped this foundational step and found that without the right data governance model, their data-driven initiatives were not delivering the expected value.
4. Embrace data as an asset
Organizations moving from manual to digital operations often find data management a burden. This approach leads to missed opportunities, inefficiency and unnecessary risk. With a structured data governance structure and a digital repository of trusted data, your organization can begin to use data to reduce risk, improve service delivery, and drive growth through efficiency, innovation, and continuous optimization. But first, you must accept data as an asset in your organizational culture. The understanding that data is an asset must be done from the top down by stakeholders who have both an impact on the organization and an understanding of the value that data brings to the organization.
5. Be realistic about your capabilities
For the maritime industry, data requirements are quickly becoming more complex than in-house development systems can meet. For many, maintaining these capabilities internally is challenging, time-consuming, and distracting from the core business. Outsourced data management can provide the best of both worlds by allowing users to access the data they need to get their jobs done, while facilitating the effort required to manage the underlying tools and technologies that consume, cleanse, aggregate, and distribute that data for adoption. solutions.