Takeaways from Kopi Chat: Riding the Waves of Change with Technology

As part of Kopi Chat: Riding the Waves of Change of Technology on 26 Feb, Eugene Qian, Senior Manager (Network Planning), Ocean Network Express and Li Yan, Consultant, Accenture Strategy gave their two cent’s worth on the challenges in the container liner business, the disruptive technologies (e.g. Robotic Process Automation (RPA), Autonomous Vessels, Big Data Analytics) revolutionising them and how to promote a culture of innovation in a company! If you would like to find out more, read the takeaways we have compiled below!

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Eugene Qian, Senior Manager (Network Planning), Ocean Network Express presents on container liner shipping in the era of exponential growth.

How the liner business operates

  • Growing capacity of single ships (1200% growth since 1968)

Opportunities: hardware tech that reshapes, and software tech that revolutionizes the industry

- Abundant Opportunities — Hardware

o Exponential growth -> need for hardware advancements (eg Hyperloop)

o 2017: first full scale test on Hyperloop

o Major players from China and Canada and others

o Delivery time reduced tremendously

o Revolutionize containerization

o Another example: Eco-ships, automated ships

- Abundant Opportunities — Software

o Consolidation of the industry (mergers, acquisitions to achieve greater economies of scale)

o Robotic Process Automation (RPA) in the Liner business

o Linking up the various platforms involved (eg vessel cascading, equipment control, etc.)

o Using big data to get better forecast

- Innovation-Friendly Culture

o Before we go More Machine, we have to be More Human

o We may fear a Machine Future, but human involvement will remain necessary, albeit in a different manner

Robotics Process Automation (RPA)

  • Digitizing the workforce (for the liner industry)

Working together with machines is a certainty in the future.

Benefits of RPA:

40% reduction in handling time, up to 80% reduction of processing costs (so humans can focus on more productive tasks), 24/7 potential to operate (not limited to human working hours), <12 months full return on investment

Areas to use RPA in a business:

  • Pre-defined decision, rule-based processes

Areas in the shipping business where RPA can add value: documentation, invoice processing etc.

RPA can have major benefits, but a more holistic approach will allow it to reach potential:

1. People, robots and systems need to work effectively together

2. Build RPA as a capability and not just a piece of technology

3. Upfront mindset change is absolutely critical

Range of AI technologies: Natural Language Processing that can be trained, Expert Systems and Analytics

Competition in the shipping industry was about getting greater economies of scale, but now that most companies are so huge, it is no longer worth chasing. Instead, turning to automation is needed to further reduce per unit cost to maximise returns.

Q & A

Q1: As a result of an industrial consolidation, 70–75% of capacity is estimated to be held by top companies. What type of efficiencies should companies be looking at? Just time-based?

There are a lot of areas where a liner business can generate efficiency. I can already name four major areas at this moment: first is assets, in terms of hardware. For instance, millions of containers and ships coming and going, how do we manage them and ensure them in good working conditions, on schedule, ready to meet the commercial commitments and so on? The second would be communication. For example, how to have effective communications between masters and crews onboard and those onshore, e.g. operations people at terminals? Communication is very important considering so many parts constantly moving in a given shipping network. As you have seen in my slides, having good communications is also a key factor for the success in a liner company given its complex structure and vast network. Thirdly, the bigger the network, the more manpower, the more human errors. That is a natural result. RPA can play a big role in reducing human errors and mistakes made in work. Last, would be decision making. For a big company, when so many departments working towards a common goal, and it is going to be a large aggregation of those goals at the end of the day, how can we streamline this? How do we make strategic decisions quickly and correctly with a highly data-driven approach? Elon Musk has a vision of having a future of half human half machine. That is for individuals. But if you see a company as a human, that would be a tempting future.’ — Eugene

Q2: Will companies be better off going to NYK directly or to Accenture who can package the solutions better?

‘There are corporate companies who have events like innovation days and bring start-ups in to talk to clients directly. Also have Accenture who scouts start-ups to bring their solutions to life. One takeaway for start-ups will be to have something tangible, some prototypes that work and also partner places like Block 71. Jobs that are repetitive, prone to human errors, unmotivating: replace with RPA. Let workers do more effective jobs that tap on their experience.’ — Li Yan

Q3: If hyperloop ships by land more effectively, wouldn’t it disrupt the container shipping industry?

When I first saw such a futuristic concept 5–6 years ago, that was in my mind too, but after I have paid attention to its development along the years, it seemed to me more like a complement to the shipping industry. They win in terms of speed and efficiency. But it has a very limited capacity according to the current design. The world trade volume will continue to grow. Hyperloop is not capable to accommodate such volume and fully replace shipping. Financial justification is another concern. In the world and in many countries, we have misaligned infrastructure developments in developed and developing areas, coastal areas and hinterland. In coastal areas, we have huge ports able to berth large ships like those with 22000–23000TEU nominal capacity. But the hinterland is much less developed. Hyperloop could be an effective solution to eliminating or at least, mitigating such disparity. Hyperloop may be a popular idea for local governments in terms of infrastructure improvement, as they may not need to build enormous inland depots and so on. They can use those pods for both shipping and passenger transport.’ — Eugene

Q4: With increasing automation and larger data volumes, will the maritime industry require more supercomputing?

‘Having the right infrastructure to support large volume is absolutely critical. Apart from computing powers, people will need to be able to adapt to it.’ — Li Yan

Q5: The maritime industry is one of the largest contributors to greenhouse. Will RPA have an impact on greenhouse gas emission? Could it improve efficiency at the cost of further climate change?

‘We have seen higher and higher awareness of environmental protection in the industry. We do assume responsibility when it comes to our impact and will certainly assume more responsibilities in the future. By 2020, there will be a new global cap for all shipping companies that would further control the bunker we could use and reduce the harmful emission. Efficiencies generated by automation will help protect the environment too. Today, we have already seen more ports having many AGVs, and even automated quay cranes as well as more automated process. I imagine if we further automation by using autonomous ships, efficiencies would be very much improved. Improved efficiencies will then help reduce the speed between ports, and then reduce the emission of greenhouse gases. So technology does help. — Eugene

‘Digitalization and automation would help. Eg pooling of assets together and using them with an uber-like app will drastically increase the utilization of the asset, hence reducing the environmental impact.’ — Li Yan

Q6: With regards to Accenture RPA, AI-centric, machine learning and thinking capability, proprietary or open source?

‘My personal view is that Open source is definitely a way to consider. Take blockchain and its potential application in supply chain and shipping as an example. The more players we have in this field, the higher chance of its success and us getting more benefits and more intelligent robots.’ — Eugene

‘The fundamental value creation of AI is to continuously improve and self-learn through large amount of data. Open source software will help improve AI in short period of time. — Li Yan

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From left to right: Ms Teo Cheng Yoke, Assistant Manager, Corporate Partnerships, NUS Enterprise, Ms Li Yan, Consultant, Accenture Strategy, Mr Eugene Qian, Senior Manager (Network Planning), Ocean Network Express, Mr Ong Seng Yeow, Executive Director, Maybank Kim Eng Research and Regional Head of Research, Maybank Kim Eng and Mr Tetsuya Haraoka, Project Manager, Symphony Creative Solutions.

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NUS Enterprise nurtures entrepreneurial talents with global mindsets, while advancing innovation and entrepreneurship at Asia’s leading university.

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