SCM Future Trend – Big Data & IoT application
- 21 Aug 2017 – 21 Aug 2017, Intake: 3
- 1 Nov 2017 – 1 Nov 2017, Intake: 4
Businesses today are facing dynamic challenges posed by disruptive developments, namely IoT (Internet of Things) – connectivity for an integrated business ecosystem. Organizations would need to adopt IoT and Big Data applications to remain competitive in the dynamic marketplace.
Henceforth, there is an increasing need for knowledge and skills, to organize the data and provide the useful analysis required for quick responsive decision making, especially in SCM and logistics dealing with the physical movement of goods.
This workshop would introduce the IoT and Big Data concepts as well as applications in supply chain and logistics management, and identify the impact in business operations – understand the process for discerning relevant data and information sources to facilitate better decision making in business operations.
- Understand the impact of IoT and Big Data applications in supply chain and logistics management.
- Logistics management – WMS and industry 4.0
- Operations management – JIT and lean concepts in supply chain and inventory management
- IoT and Big Data applications
- Process mining – technologies and applications for logistics in the supermarket
- Transportation and fleet management – loading factor, route planning and scheduling
- Managers who manage business operations and need to make business decisions, dependent on data and information from the operations. E.g. manager or supervisors managing retail and manufacturing operations, supply chain and operations management, finance and accounting.
- Professionals or specialists who manage the supply chain operations (e.g. procurement & purchasing, customer fulfilment, inventory management, quality control), business planning (e.g. demand forecast & planning, product portfolio management), finance (e.g. cost analysis, budgeting), customer services.
- Target market and industries – retail, manufacturing, logistics, F&B.
- Introduction of IoT and Big Data concepts
- Information sources and relevance – identify the relevant sources of data and information of value to businesses and customer fulfilment.
- Activity – Amazon logistics looking at WMS and fulfilment operations using IoT system and Big Data application tools
- Industry 4.0 – supply chain and logistics operations with JIT and lean concepts which require real-time online data mining (i.e. Big Data analytics) and IoT technologies (e.g. RFID)
- IoT and Big Data applications
- Process mining – supply chain and logistics operations in the supermarket retail environment
- Operations management – fleet operations system for public transport to improve loading and route planning efficiency
|SLA Member Company
(View member listing)
(payable to TLA)
|PIC Grant||Eligible Companies to claim directly from IRAS.||N.A.|
Payment will only be required after the course is confirmed.
Payment mode (retail payments facilities are not available) :
Overseas – Telegraphic transfer
Local – Cheque or bank transfer
1 day : 9 am to 6 pm
Peter Loh is an experienced professional in strategic management and MBCI (Market, Business & Competitive Intelligence) for over 20 years, spanning across several industries such as electronics, automotive, telecommunication, oil & gas industries. With his immense strategic thinking and analytical skills, he could envision the future trends in IoT and Big Data applications across various industries and markets, which he foresees could potentially exceed $50 trillion in 2020.
Peter is now an Adjunct faculty member at Singapore Institute of Technology, introducing the McKinsey 7-S concept as an analytical tool for organizational management. He is also a mentor for Lithan Academy’s Technopreneruship program and the Edupreneur startup boot-camp.
Peter holds a Master’s in Business Administration from Indiana University, and also an Advanced Certificate in Training and Assessment from the Singapore Workforce Development Agency.
A Certificate of Attendance will be awarded upon successful completion of the course with 75% attendance.