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Managing Supply Chain Data Projects

Vivian Wu
Aug 18, 2020
Managing Supply Chain Data Projects

About the Speech

During this webinar organized by Argyll Scott Hong Kong, we shared our view on how to efficiently conduct data projects in the supply chain industry.

A great starting point is the identification of a specific business pain point that is worth solving and has a measurable ROI (i.e. a direct or indirect increase of revenues or decrease of costs).

Once identified, the project should be a close collaboration between the business (for providing the specifications and regular feedback), the IT (for managing the vendor and ensure the project’s compliance with the company policies), and a software vendor (for deploying and configuring the solution).

The technology used is not important, so long as it covers the specifications in full, has interfacing capabilities (e.g. an API), and a scalable architecture.

What matters is to focus on solving the immediate pain point (scalability comes later) and keep the solution simple. There is no need to build complex AI, blockchain, or RPA solutions if simpler alternatives exist.

Finally, the outcome of the project should be accessed by using one metric only: the usage rate. Are the people who are supposed to benefit from the solution actually using it, or are they doing something else? This metric determines the future of the solution released.

About the Event

Date Time: Aug 18, 2020 06:30 PM HKT
Topic: Impacts of Data Science adoption in the Logistics, Supply Chain and Retail sectors
Event Type: Webinar

Host:

Paris Herard, Senior Executive – Technology, Argyll Scott Hong Kong

Guest panelists:

  • Aravind Nambiar, Data Science & Analytics Lead at Li&Fung
  • Florian Gamper, Managing Director at Lineverge
  • Yuxi Chau, Data Science Manager at A.S. Watson Group
  • Kenneth Shek, Head of Data Science & Analytics, Beta Lab/Lane Crawford (Q&A session guest)
Managing Supply Chain Data Projects
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