Supply Chain Sustainability using Artificial Intelligence
by Charles H.W. Edwards, Vice President at SASI World
Sustainability is defined as “meeting the needs of the present without compromising the ability of future generations to meet their own needs.” There are three core dimensions of sustainability. They include:
Economic – Supporting long-term economic growth without negatively impacting social or environmental aspects,
Environmental – Preserving natural resources, reducing pollution, and protecting ecosystems, and
Social – Ensuring equity, human rights, and access to basic needs like education, healthcare, and community development.
Supply chains are being challenged to deliver consistent, fully transparent, high-quality and compliant services under price pressures, while simultaneously addressing external and internal issues related to long-term sustainability.
Responding to and anticipating the numerous disruptions which challenge supply chain operations and structure requires an innovative approach that employs new tools for managers and teams. This paper focuses on economic sustainability and the use of appropriate digital systems, including AI, by the worldwide air cargo logistics industry.
The challenge of embracing any new approach can be summarised by three hurdles [ii].
Bias issues – Change is always tough. Overcoming the bias against change and perceived threats to individual roles and employment or to the impact on customers’ requirements.
Integration challenges – Integrating changes into legacy systems requires thoughtful education of team members, customers and vendors. The focus must be on the collaborative benefits for all.
Scalability and Regulatory Concerns – Any change must be vetted to ensure that the new systems and processes are compliant with legal and regulatory requirements. The changes must be readily scalable without undue additional cost.
Developing a vision and strategy that addresses these hurdles is the first step. The next step is to confront additional concerns, which include:
Data Quality and Availability – Every member of the worldwide air cargo logistics industry possesses a wealth of information and data. The challenge is multifold when making changes that will alter internal processes as well as external connections. Is the information accurate? How can it be protected? How can it be used for short-term applications and long-term strategies? These and many other questions must be addressed in a thoughtful, respectful, and detailed process.
Identifying Appropriate Technologies – The rush to adopt and apply new technologies can create numerous problems. Identifying the appropriate technologies must be grounded on the individual company’s goals as well as its relationships with customers and vendors. Purchasing a new I.T. system that is not modified to the unique needs and processes of the company can, and has in the past, put the buyer in financial peril.
Recognising and formalising strategies to respond to the concerns listed above will significantly increase the probability of success. Identifying and addressing all the likely problems upfront is key to creating a project management plan that will be completed on time and on budget. This homework lays the foundation to develop a vision and strategy to implement changes to structures, systems and processes.
There are seven primary applications of Artificial Intelligence (A.I.) in supply chain operations and management. The following summarises each use and its application [iii], [iv]. The applications for the worldwide air cargo logistics industry reflect the current uses of AI in other industries.
Airport cargo community systems (ACCS) linked to AI tools are the suggested way forward for all members of the worldwide air cargo logistics industry to adopt and use digital tools and ensure long-term sustainability in an era of constant and varied disruptions. The power of these platforms is magnified exponentially when ACCS platforms are linked via Digital Logistics Corridors [v].
In conclusion, all members of the worldwide air cargo logistics industry must collaborate. The strengths of small and mid-sized companies are the bedrock of the industry. At the same time, a race to adopt new technologies, including artificial intelligence, must be measured and address all internal and external concerns. Just as the tortoise beats the hare over a long distance, it is not the speed at the start that wins the race. Rather, it is the preparation and the attention to detail in the vision and strategy that are needed to adopt AI and reap the associated benefits.
Charles Edwards
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