The second data source is used as back-up in case
information was not available in the leading data
source. Further, it must be considered that the data
analysis does not make a distinction between freight
building 1 and 3, as this is not possible in the leading
data source. However, the designed process is
focused on freight building 3.
4 CONCLUSIONS
This research found that without a Late Show process,
there is no difference in the physical handling of a
shipment in the acceptance process of KLM Cargo in
case the shipment is delivered late. This means that
the shipment is always accepted, and the Received
from Shipper (RCS) message is always sent,
indicating the carrier considers the shipment as ready
for carriage. As a result, it is often tried to still build
up a late shipment and let it depart on the planned
flight, even though there is sometimes not much time
left for this process. This research shows that 13% of
the Late Shows do not depart on the planned flight at
RCS meaning the commitment to the customer is not
met, which deteriorates the quality of the process.
Based on this research, it is concluded that the
design of a standard Late Show process must consider
specific Late Show characteristics. It is important to
consider the product types requiring a different design
because of specific operational processes in the
warehouse. Further, the design of the process should
include a check on whether the shipment was
delivered on time, before acceptance of the shipment
and thus the sending of the RCS message. Then, in
case the shipment is late, it should be checked
whether the planned flight is still operationally
achievable. When this is not possible, the Late Show
first has to be rebooked to another flight before the
RCS message is sent. By following this decision-
making process while the shipment is stored in the
FOH-buffer located in the receiving area of the
warehouse, and thus before the shipment is driven to
the buildup buffer, it is assured that the Late Show
will be on time at the buildup buffer for the booked
flight.
The research recommends to also include at least
the product with the second largest number of Late
Shows in the Late Show policy, as this product also
has a large operational impact caused by the Late
Shows. This means further research must be
conducted into mainly the storage requirements of
this product, and how a Late Show process for this
product should look like. Further, it is recommended
to further research the predictability of the Late
Shows in more detail, as this research shows the
number of Late Shows is currently difficult to predict.
A more detailed analysis can lead to even better
insights into the characteristics of the Late Shows and
can help to decide on future improvements for the
process. In addition, it is recommended to validate the
data from the two data sources used in this research,
after the identified issues that caused the differences
between the two sources are solved
ACKNOWLEDGEMENTS
This research is conducted in the context of a
graduation internship for the study Aviation
Operations at the Amsterdam University of Applied
Sciences at the request of internship company KLM
Cargo.
REFERENCES
Blonk, M. (2017). Dock & Yard Management at KLM
Cargo. Master Thesis. Eindhoven University of
Technology. The Netherlands.
Henriksson, F. T., & Petersson, J. (2019). Mapping of the
Air Freight Handling at Stockholm Arlanda Airport.
Bachelors Thesis. Linköping University.
IATA. (2019). IATA Master Operating Plan Glossary.
IATA/ Cargo iQ. Retrieved March 8, 2021
Recker, J., Rosemann, M., Indulska, M., & Green, P.
(2009). Business Process Modeling- A Comparative
Analysis. Journal of the Association for Information
Systems, 10(4), 333-363. doi:10.17705/1jais.00193
Slack, N., Brandon-Jones, A., & Johnston, R. (2016).
Operations Management (8th ed.). Pearson.
White, S. A. (2004, July 6). Introduction to BPMN. Retrieved
from BPTrends: https://www.bptrends.com/bpt/wp-
content/publicationfiles/07-04%20WP%20Intro%20to%
20BPMN%20-%20White.pdf