The future of air cargo

Design of a solution to use sensor-based data to improve efficiency, transparency and communication for KLM Cargo’s employees and customers

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Abstract

Assignment - This report describes the design of solutions that enable KLM Cargo to add more value for its employees and customers using data generated by new technological opportunities. The scope for this report is on pharmaceutical shipments passing through KLM Cargo’s Schiphol hub, from acceptance to delivery, and focuses on addressing the needs of warehouse employees, customer service agents, and pharmaceutical customers. Problem - KLM Cargo’s current cargo handling process is a manual, labour-intensive process suffering from problems for warehouse and customer service employees in terms of efficiency, workload, and quality, caused by missing and inaccurate data. It is therefore necessary to improve the amount, accuracy, and availability of condition, location, timing, and activity data, because these data categories have the biggest impact on KLM Cargo’s service delivery. Interviews show that pharmaceutical customers want to feel safe that KLM Cargo will deliver pharmaceutical shipments on time, in good order, and according to regulations, most importantly by controlling the temperature throughout the transport. Customers also want to be kept informed in real-time about their shipment’s status, temperature, location, and activities, and expect KLM Cargo intervene and communicate in case problems occur. Market trends will require and enable technological, digital, and data-driven innovations for the airline industry at an accelerating speed. Rapid technological progress drives the cost of computations, data collection and storage down, and enables a low-cost, low-power data collection infrastructure, combined with effective storage and analytics methods. To keep up with these developments KLM Cargo should develop technological, innovative solutions that are able to deal with a continuous, high volume, high velocity data flow and can transform data into actionable insights. Results - These insights can be combined in a design scenario for 2030, in which KLM Cargo operates in a competitive air cargo market that pushes airlines to compete on digital initiatives that use intelligent, connected cargo assets that generate and use a real time flow of data in order to enable an intelligent, efficient, reliable, and transparent logistical process for the transport of high-impact, high-value goods. In this future, KLM Cargo should aim to improve the quality of its pharmaceutical solutions through data-driven solutions. These solutions should help warehouse employees to work more efficiently, improve transparency for customers, and improve communication by customer service agents. The data framework presented in this report provides KLM Cargo with a common language and structure, while five data enablers outline the foundation for its actual data use. First, smart, sensor-equipped cargo assets and other systems connected to a common data sharing platform allow KLM to collect large flows of real-time data about its cargo process. Next, this data should be transformed into insights and actions through descriptive, predictive, and prescriptive analytics, one of which is defined as the ability to automatically prescribe required actions. Finally, data and insights are delivered to stakeholders via the digital tools presented in this report, that allow KLM Cargo to achieve quality improvements. Warehouse employees are provided with tablets, mobile apps, and large screens that enable them to work more efficiently, through automatic incident monitoring, data collection, and notifications. Transparency towards customers is increased, through online access to real-time shipment condition, location, and activity information. Finally, customer service agents get a tool that gives them access to the same accurate, real-time shipment data, so customers and customer service agents will benefit from improved, proactive communication.

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