Events Details
  • June 10 & 11, 2021 (8:00-12:00 GMT)
  • Live Online

Who should attend
- Managing Directors, Owners
- Chief Supply Chain Officers/ Chief Logistics Officers/ Chief Operations Officers/ Chief Procurement Officers
- Senior Supply Chain/ Logistics/ Procurement/ Operations Managers
- Chief Information Officer/ Chief Technology Officer

Learning objectives
- Understand the objectives and key principles of Big Data Analytics
- Get an overview of the software applications used in Big Data Analytics
- Get insight into various pragmatic examples of Big Data Analytics that your company can implement now for business improvement. This includes Spend Analytics, TCO and using early warning real-time alerts for better visibility and risk management 

Benefits of attending
- Highly experienced and knowledgeable trainer to share both practical and theoretical insights 
- The Big Data Analytics workshop is designed to provide a clear and operational view of what is analytics in language that is easily understandable, with examples from real world companies in Asia
- The course is very comprehensive and includes all main aspects such as strategy, organization structure, people, process and technology required to be successful in Big Data analytics
- Learn from other companies in Asia through successful implementation case studies

Program agenda

Session 1 – Big Data Analytics overview
This session introduces the core concept of Big Data Analytics:
- Definitions of Big Data and Analytics
- Key Objectives and principles of Analytics for Supply Chain & Procurement
- Analytics framework: Descriptive, Predictive and Prescriptive methods
- Guide to select the right analytics method for the right problem
- Use cases for Analytics in Supply Chain & Procurement    
            · Spend Analytics, Category Analytics, Contract Analytics, Risk Analytics etc.

Session 2 – Challenges to implementing Analytics and how to overcome them
- Obstacles to implementing Analytics
- Data issues and the importance of Master Data Management (MDM)
- Lack of talent and the need for Analytics talent management

Session 3 - Software used for Big Data Analytics
- What are the main vendors offering Analytics software
            · Covers BI tools, Advanced Analytics tools
            · Covers Procure-to-Pay and Strategic Sourcing tools
- Typical features and functionality of Analytics software
- Trends in the market

Session 4 – Practical examples of Big Data Analytics – Spend Analytics
- Spend analytics is the process of providing a holistic visibility of how your company spends money on all your suppliers, in order to better understand, control and optimize all spending (direct, indirect, hidden costs).
- This is the most important type of analytics a sourcing team can do to discover areas for improvement. This session will cover key elements such as long tail consolidation, price variances, contract compliance, category rationalization and reduction of administrative issues such as duplicate invoices/duplicate payments etc.

Session 5 – Practical examples of Big Data Analytics – Total Cost of Ownership (TCO)
- Covers the concept of Total Cost of Ownership (TCO) to better understand the true cost of dealing with your suppliers. While this concept has been around for years and teaches you the importance of value over price, many companies in Asia still have not fully implemented it

Group Exercise and Group Discussion - TCO
This group exercise provides the participants with hands-on practice in applying TCO concept
- Introduce Food Company Case
- Design which parameters to include in TCO and determine the TCO for key suppliers of Food Company
- Group discussion

Session 6 – Practical examples of Big Data Analytics – improve supply chain visibility and risk management
- Using early warning signals to detect potential risks sooner enables a quicker mitigation or response to supply chain risk
- Example of software vendors for real-time early warning systems

Session 7 – Building an inhouse capability for Analytics
Companies should go beyond a “one-off” project approach, but instead adopt Analytics as a core competency and embed it in their organization. This session provides a comprehensive overview of what is required to build Analytics as a capability in your organization.
- How to build an inhouse Center Of Excellence for Big Data analytics
- Covers all main aspects such as strategy, organization structure, people, process and technology, training required to be successful in supply chain analytics

Session 8 – Case studies
Learn from other companies who have applied Big Data Analytics in their procurement organization
- Airbus: spend analysis showed opportunities of 15% cost reduction in spend commonality (don’t pay different price for same item) and purchasing process efficiency improvement
- French retailer Asia sourcing team: implementing a custom-build big data analytics platform  enabled a team of 100+ buyers managing 250K SKUs with 2B Eur annual spend, to move away from Excel based time-consuming process, to standardize supplier contract and price reviews by automating the cost modelling of the exposure to currencies and commodity prices, in order to be better prepared for supplier negotiations
- Chinese plastics parts manufacturer: sourcing process review showed opportunities for category management, supplier rationalization and process efficiency by implementing workflow system