English Version
INTERNATIONAL LECTURE
“PREDICTIVE ANALYTICS IN LOGISTICS AND SUPPLY CHAIN FOR
SUSTAINABILITY & COMPETITIVE ADVANTAGE”
Speaker: Dr. Noorul Syaiful Fitri Bin Abdul Rahman -
University of Doha for Science and Technology (UDST), Doha, Qatar
Reviewer: Prof. Dr. Ir. Agus Purnomo, M.T., CMILT. (Professor
of Supply Chain Management - Master of Logistics Management Department –
Universitas Logistik Dan Bisnis Intenasional – ULBI)
Introduction
Imagine a logistics world where 41% of the
total supply chain cost is absorbed by the “last-mile,” where deliveries from
warehouses to consumers become a trap of expenses and emissions. What if you
could predict where delays, overstock, or surges in demand would occur before
the cost disaster unfolds — would that not change the game? “Without big data analytics, you are blind and deaf and in the
middle of a freeway,” remarked Geoffrey Moore, highlighting the
critical role of data and prediction in modern operations.
Amid accelerating trends in digitalization, sustainability, and
intensifying global competition, the topic Predictive Analytics in
Logistics and Supply Chain for Sustainability & Competitive Advantage is no longer an optional add-on — it has
become a strategic necessity. In the context of higher education and
Indonesia’s logistics industry, particularly within the Master of Logistics
Management program at ULBI, the international lecture delivered by Dr. Noorul Syaiful Fitri Bin Abdul Rahman from the
University of Doha for Science and Technology (UDST) represents a crucial moment to reflect on
how predictive analytics can bridge operational efficiency, environmental
impact, and competitive advantage.
Summary of
Key Themes
In
the international lecture delivered by Dr. Noorul Syaiful Fitri Bin Abdul
Rahman, the central theme highlighted was how predictive analytics has become a
vital pillar in transforming the face of logistics and supply chains from
merely reactive to proactive and predictive. By leveraging big data, machine
learning, and artificial intelligence, companies are able to forecast demand,
optimize distribution routes, manage inventory intelligently, and even detect
potential supply chain disruptions before they occur.
Two case studies
reinforced this relevance: Amazon, which successfully integrated predictive
analytics into product recommendations and stock management, and Walmart, which
developed a supply chain resilience platform to address market dynamics and
global risks. The key message from this lecture is clear: data is not merely a
record of the past but a roadmap to the future.
Analysis
& Discussion
The
implications of predictive analytics adoption are far-reaching for both
industry and education. For industry, it offers cost efficiency, faster service
delivery, and a competitive edge in the global marketplace. For education,
particularly in the field of logistics, it opens opportunities to integrate
analytical technologies into the curriculum, enabling students not only to
understand supply chain theory but also to acquire the digital skills essential
in the era of Industry 4.0.
In the Indonesian
context, the adoption of predictive analytics still faces challenges, such as
limited data infrastructure, human capital quality, and relatively high
technology investment costs. Yet behind these challenges lies a tremendous
opportunity: with its rapidly growing e-commerce market, Indonesia urgently
requires predictive solutions to reduce persistently high logistics costs and
to strengthen the resilience of its national supply chain.
Relevance
to ULBI’s Vision and Mission
For
Universitas Logistik dan Bisnis Internasional (ULBI), this topic is not merely
an academic insight but an integral part of its strategy to strengthen
scientific capacity and innovation. By hosting international lectures such as
this, students of the Master of Logistics Management program are introduced to
state-of-the-art technologies that support sustainable practices and industrial
competitiveness.
This initiative aligns
with ULBI’s vision to become a World Class Entrepreneurial University in
logistics and international business by 2047. Predictive analytics can serve as
a foundation for flagship research, the development of a digitally driven
curriculum, and international collaboration. Furthermore, such initiatives
reinforce ULBI’s positioning as a knowledge hub that not only follows global
developments but also acts as a driving force for innovation in Indonesia’s
logistics ecosystem.
Conclusion
This
international lecture reaffirmed that predictive analytics is not merely a
technological trend but a vital strategy capable of delivering efficiency,
sustainability, and competitive advantage in modern supply chains. Adopting and
further exploring this topic is imperative, particularly for universities,
industries, and policymakers in Indonesia who are striving to reduce logistics
costs and enhance global competitiveness. For the ULBI academic
community—students, faculty, and practitioners—this is a pivotal moment to not
only understand the concept but also to implement the knowledge in research,
innovation, and tangible collaboration with industry. It is time for us to
collectively embrace predictive analytics as a strategic tool in building a
logistics future that is more resilient, greener, and globally competitive.
Indonesian Version
INTERNATIONAL LECTURE
“Predictive Analytics In Logistics and Supply Chain for
Sustainability & Competitive Advantage”
Pembicara: Dr. Noorul Syaiful Fitri Bin Abdul Rahman - University
of Doha for Science and Technology (UDST), Doha, Qatar
Pengulas: Prof. Dr. Ir. Agus Purnomo, M.T., CMILT. (Guru Besar
Supply Chain Management - Master of Logistics Management Department –
Universitas Logistik Dan Bisnis Intenasional – ULBI)
Pendahuluan:
Bayangkan sebuah dunia
logistik di mana 41% dari biaya total rantai pasok tersedot hanya pada
trayek “last-mile”, di mana pengiriman dari gudang ke konsumen menjadi jebakan
biaya dan emisi. Bagaimana jika Anda
bisa memprediksi di manakah delay, kelebihan stok, atau intensitas permintaan
sebelum bencana biaya muncul — bukankah itu akan mengubah game? “Without big data analytics, you are blind and deaf and
in the middle of a freeway,” kata Geoffrey Moore, yang
menggambarkan betapa gentingnya peran data dan prediksi dalam operasional
modern.
Di tengah tren percepatan
digitalisasi, keberlanjutan, dan persaingan yang makin ketat di pasar global,
topik Predictive Analytics in Logistics and
Supply Chain for Sustainability & Competitive Advantage bukan lagi opsi tambahan — melainkan kebutuhan
strategis. Dalam konteks pendidikan tinggi dan industri logistik Indonesia,
terutama di program Magister Manajemen Logistik ULBI, kuliah internasional oleh
Dr. Noorul Syaiful Fitri Bin Abdul Rahman dari University of Doha for
Science and Technology (UDST) menjadi momen krusial untuk merefleksikan
bagaimana predictive analytics bisa menjembatani efisiensi operasional, dampak
lingkungan, dan keunggulan kompetitif.
Ringkasan
Isi/Tema Utama
Dalam
kuliah internasional yang disampaikan oleh Dr. Noorul Syaiful Fitri Bin Abdul
Rahman, topik utama yang diangkat adalah bagaimana predictive analytics
menjadi pilar penting dalam mengubah wajah logistik dan supply chain dari
sekadar reaktif menuju proaktif dan prediktif. Dengan memanfaatkan big data,
machine learning, dan kecerdasan buatan, perusahaan mampu memperkirakan
permintaan, mengoptimalkan rute distribusi, mengelola inventori secara cerdas,
dan bahkan mendeteksi potensi gangguan rantai pasok sebelum terjadi.
Dua studi
kasus yang disajikan memperkuat relevansi ini: Amazon yang berhasil
mengintegrasikan predictive analytics untuk rekomendasi produk dan
manajemen stok, serta Walmart yang membangun platform resiliensi rantai pasok
untuk menghadapi dinamika pasar dan risiko global. Pesan utama dari paparan ini
jelas: data bukan hanya catatan masa lalu, melainkan peta masa depan.
Analisis
& Diskusi
Implikasi
dari penerapan predictive analytics sangat luas bagi dunia industri
maupun pendidikan. Industri memperoleh efisiensi biaya, peningkatan kecepatan
layanan, dan keunggulan kompetitif dalam menghadapi persaingan global.
Pendidikan, khususnya di bidang logistik, mendapat peluang untuk mengintegrasikan
teknologi analitik ke dalam kurikulum, sehingga mahasiswa tidak hanya memahami
teori rantai pasok, tetapi juga menguasai keterampilan digital yang dibutuhkan
di era industri 4.0.
Dalam lingkup Indonesia, adopsi predictive analytics
masih menghadapi tantangan: keterbatasan infrastruktur data, kualitas SDM,
serta biaya investasi teknologi yang relatif tinggi. Namun, di balik tantangan
ini tersimpan peluang besar: Indonesia dengan pasar e-commerce yang tumbuh
pesat membutuhkan solusi prediktif untuk menekan biaya logistik yang masih
tinggi dan memperkuat ketahanan rantai pasok nasional.
Kaitan
dengan Visi & Misi ULBI
Bagi
Universitas Logistik dan Bisnis Internasional (ULBI), topik ini bukan sekadar
wawasan akademik, melainkan bagian dari strategi membangun kapasitas keilmuan
dan inovasi. Dengan menghadirkan kuliah internasional seperti ini, mahasiswa
Magister Manajemen Logistik diperkenalkan pada state-of-the-art
teknologi yang mendukung praktik berkelanjutan dan daya saing industri.
Hal ini
sejalan dengan visi ULBI untuk menjadi World Class Entrepreneurial
University di bidang logistik dan bisnis internasional pada 2047. Predictive
analytics dapat menjadi salah satu fondasi riset unggulan, pengembangan
kurikulum berbasis teknologi digital, dan kerja sama internasional. Lebih jauh
lagi, inisiatif seperti ini memperkuat positioning ULBI sebagai pusat keilmuan
yang tidak hanya mengikuti perkembangan global, tetapi juga menjadi motor
penggerak inovasi di ekosistem logistik Indonesia.
Penutup
Kuliah
internasional ini menegaskan bahwa predictive analytics bukan sekadar
tren teknologi, melainkan strategi vital yang mampu menghadirkan efisiensi,
keberlanjutan, dan keunggulan kompetitif dalam rantai pasok modern. Mengadopsi
dan meneliti lebih jauh topik ini menjadi keharusan, terutama bagi perguruan
tinggi, industri, dan pembuat kebijakan di Indonesia yang sedang berjuang
menurunkan biaya logistik dan meningkatkan daya saing global.
Bagi sivitas
akademika ULBI—mahasiswa, dosen, maupun praktisi—ini adalah momentum untuk
tidak hanya memahami konsep, tetapi juga mengimplementasikan pengetahuan dalam
riset, inovasi, dan kolaborasi nyata dengan industri. Saatnya kita bersama-sama
menjadikan predictive analytics sebagai alat strategis dalam membangun
masa depan logistik yang lebih tangguh, hijau, dan berdaya saing.
"LET'S
JOIN ULBI"
Magister Manajemen
Logistik - “Shaping Future Leaders in Global Logistics”
Learn more by visiting :
https://admission.ulbi.ac.id/s2-magister-manajemen-logistik/
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Management; #predictive
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