Big Data x Logistic x Globalization
‘Big data’ promises business benefits in terms of timely insights from data, real-time monitoring and forecasting of events, more fact-based decisions, and improved management of performance and risk. It has already had a considerable impact and changed the competitive landscape in many industries, for example, our targeted industry: logistic. We are going to focus on different functions of big data applied in different sub-industries under logistic: prediction on maritime shipping, real time monitoring on cold chain, decision making on logistic infrastructure, operational efficiency on supply chain. In our case, big data does help by implementing ‘intelligent operation’. The purpose of our group project is to establish a framework for identifying impact of globalization on logistic industry, understand how big data can contribute to make logistic industries safer and more sustainable under the age of globalization.
‘Big data’ promises business benefits in terms of timely insights from data, real-time monitoring and forecasting of events, more fact-based decisions, and improved management of performance and risk. It has already had a considerable impact and changed the competitive landscape in many industries, for example, our targeted industry: logistic. We are going to focus on different functions of big data applied in different sub-industries under logistic: prediction on maritime shipping, real time monitoring on cold chain, decision making on logistic infrastructure, operational efficiency on supply chain. In our case, big data does help by implementing ‘intelligent operation’. The purpose of our group project is to establish a framework for identifying impact of globalization on logistic industry, understand how big data can contribute to make logistic industries safer and more sustainable under the age of globalization.
Big Data and maritime shipping.
In global trading and logistic aspect, big data provides free real-time information to the public, about ship movements and ports, mainly across the coast-lines of many countries around the world and thus lead to emerging innovation management practices. The initial data collection is based on the Automatic Identification System (AIS). As from December 2004, the International Maritime Organization (IMO) requires all vessels over 299GT to carry an AIS transponder on board, which transmits their position, speed and course, among some other static information, such as vessel’s name, dimensions and voyage details and share the data of their area in order to cover more areas and ports around the world. AIS is initially intended to help ships avoid collisions, as well as assisting port authorities to better control sea traffic. AIS transponders on board vessels include a GPS (Global Positioning System) receiver, which collects position and movement details. Messages include the following three basic types:
1. Dynamic Information, such as
vessel’s position, speed, current status, course and rate of turn.
2. Static Information, such as
vessel’ name, IMO number, MMSI number, dimensions.
3. Voyage-specific Information, such as destination, ETA and draught.
An
increasing demand of daily products, vegetables, fruits as well as the needs of
pharmaceutical drugs boosted the cold chain market where the logistics was attached
with more importance on the control and stabilize of temperature and humidity
in the vehicles and containers, and the cold chain monitoring platform in use
of big data technology has come into the market. The M2M (machine to machine)
communication requires the sensors for temperature and humidity which has been
expected in the vehicles and containers that they carry, and this would help
generate data during the transport which can be transmitted via mobile means
and be monitored in real time. The globalization which has a positive impact on
international trading would urge the immense use of this M2M communication on
cold chain as it shall be taken as the supply chain integrity where daily
products and pharmaceutical companies will need the proof to sell their
products.
Big data and Supply Chain Management
A “supply chain” is a broad term for the resources, activities, information, and people that are involved throughout the entire process of raw material to final product, or supplier to customer. Thus, supply chains are highly linked together and involve anything from transport to storage in warehouses to actual point of sale. Globalization increases the interconnectedness of businesses which leads to a growing complexity of supply chains. Hence, there is one magic word in the logistics industry: efficiency. Big data, with its many applications, has helped boost operational efficiency of supply chains in the logistics industry on a global scale.
A “supply chain” is a broad term for the resources, activities, information, and people that are involved throughout the entire process of raw material to final product, or supplier to customer. Thus, supply chains are highly linked together and involve anything from transport to storage in warehouses to actual point of sale. Globalization increases the interconnectedness of businesses which leads to a growing complexity of supply chains. Hence, there is one magic word in the logistics industry: efficiency. Big data, with its many applications, has helped boost operational efficiency of supply chains in the logistics industry on a global scale.
Some widespread applications of big data include the following:
· Radio Frequency Identification (RFID)
· Enterprise Resource Planning (ERP)
· Automated Storage and Retrieval Systems (ASRS)
Implementing
these types of big data leads to higher efficiency and lower costs, enhancing
the competitiveness of logistics companies today. However, it is often argued
that globalization leads to a lack of fair trading opportunities. In fact, the
World Trade Organization has received much criticism for being heavily influenced
by the interests of wealthy nations and companies. Through globalization it
seems that rich, well-established companies are becoming bigger, stronger and
more dominant. Thus, they are able to afford the opportunities provided by big
data while smaller companies are left struggling to survive in the market.
Big data in the logistics infrastructure
Big
data represents more a wide range of analytical technologies than simply the
ability to handle the large volume of data[1].
There are emerging innovative technologies applied making it happen for
organizations to utilize the big data for a smarter decision-making. Industries
such as logistics fund specializing in providing warehouses to the target
market are the pioneers in employing big data analytics. The decision-making
processes are typically driven by the results generated by analyzing the data
on four key elements: the locations or site selection, economy of scales,
market projections and customers. These four factors are interrelated rather
than independent of each other.
With
the applications of geospatial technology, big data in logistics infrastructure
industry are to be collected in real time model, thus lead to more efficient
and accurate strategic decision-making power.
Conclusion
In summary there is a lot of headroom for Big Data approaches to fill under globalization. The digital revolution in the logistics will continue with no doubt. The transformation into an information-driven business will make logistics smarter, faster and more efficient.
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ReplyDeleteyour work is conving in the sense that big data surely will have a great benefit to the logistics industry. However, I was curious, is there any case that could be used to illustrate how it works? I believe that could have been some successful cases, but failure as well. Maybe you could compare some successful and failure case so as to consolidate your arguments.
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