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Data Analytics And Artificial Intelligence For Effective Logistics

Our world today is surrounded with the ever-changing modern technologies and endless data exploration within our reach. On this constant development and the revolution of big data are evolving the human race on Artificial Intelligent (A.I.) dependence for a better managed environment and the convenience in life.

A.I. is the key driver of the fourth industrial revolution of new technologies that bridge the physical, digital and biological worlds. With the enormous explosion of data that powering this rapid growth rate of A.I. in recent decades, it will have a continuous increased impact on the economy and society to drive the business transformation in coming years.

Connectivity – Intelligent Analytics – Automation

Like many other industries that have already successfully adopting A.I. into their everyday businesses, now is the best time for the logistics sector shifting its traditional operating model to a new class of intelligent assets and operational paradigms.

There is a massive flow of cargoes handled by logistics providers creating vast data base across the globe. Millions of daily shipments movement from different origin to various destinations, different contents in different sizes and weight are traced through the delivery networks of individual businesses.

All this data collection built around time can be use with the prevailing technology of analytics platform to assist the logistics companies to rethink, reinvent and reconnect in having a better insight on their existing business.

With the combinations of A.I, this business systems are able to learn and extract all the insights from the unstructured data to execute well-structured inputs giving a real time overviews, making decisions and minimising mistake on behalf of human workers.

There are numerous opportunities for A.I. to be applied in logistics by leveraging the right set of digital tools in building a truly effective supply chain to save time, reduce costs and increase productivity with cognitive automation, predictive studies on demand and intelligent logistics assets (IoT / autonomous).

Robotics with A.I. are supplementing and augmenting human roles in knowledge-intensive areas such as supply chain planning, customer order management and inventory management. The picture below shows a robot with inbuilt intelligent sensors examining the products in a warehouse.

Connectivity - Intelligent Analytics
Picture extracted from http://en.yibada.com

The ultimate goal is to create a seamless collaboration and connectivity among all involved parties treating the value chain as a whole, externally and internally, providing end-to-end visibility. The organisations have to ensure they have the capabilities to analyse from the collection of the bigger data, using it to improve their operational efficiency and facilitate to implement new innovated services, like last-mile delivery.

For logistics as the network-based nature industry with the shared real-time information through leveraging analytics intelligently, cognitive equipment and smart apps implementation, will positively amplify and improvise the human components of decision making and forecasting accuracy.

From the environmental point of view, the equipped capabilities can assist to monitor and reduce the harmful waste with clean tech, green tech & eco-friendly technology in preserving the environment through energy efficiency and obtaining a more sustainable product life cycle.

A.I. can ultimately assist the logistics business to redefine clients’ present behaviours and best practices, taking operations from reactive to proactive, planning from forecast to prediction, processes from manual to autonomous, and services from standardised to personalised.

The diagram below shows network effect of future logistics and supply chain utilising artificial intelligence.


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References

Alvin Tan. SIPMM. (2017). “Key Strategies to Implement a Digital Supply Chain”. Retrieved from: https://publication.sipmm.edu.sg/key-strategies-implement-digital-supply-chain/, accessed 10 Jun 2018.

Ben G., Steve J., Dirk M. (2018). “Artificial Intelligence in Logistics”. Retrieved from: https://www.logistics.dhl/content/dam/dhl/global/core/documents/pdf/glo-ai-in-logistics-white-paper.pdf, accessed 11 Jun 2018.

Jason Tan. SIPMM. (2017). “Artificial Intelligence on Digital Supply Chain
Retrieved from: https://publication.sipmm.edu.sg/application-impact-artificial-intelligence-digital-supply-chain/, accessed 11 Jun 2018.

Pieter T. (2017). “Digital Supply Chain: How to Unlock the Real Value of Digital”. Retrieved from: http://prod.accenture-insights.be/en-us/articles/digital-supply-chain-how-to-unlock-the-real-value-of-digital-1, accessed 10 Jun 2018.

Skilton, M. (2017). “The Impact of Artificial Intelligence on Business”. Retrieved from: https://warwick.ac.uk/fac/soc/impact/policybriefings/impact_of_ai_on_business_policybrief_final.pdf, accessed 10 Jun 2018.

Michael Eng Tien Wah
Michael Eng Tien Wah
Michael Eng has more than 15 years of experience specifically in the logistics sector. He is currently Head of Sales for a global freight forwarding and logistics service provider, a company with expertise in intelligent logistics. He holds the WSQ Diploma and is a qualified member of the Singapore Institute of Purchasing and Materials Management (SIPMM). He completed the Advanced Diploma in Logistics and Supply Management (ADLSM) course on July 2018 at SIPMM Institute.
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