Artificial intelligence is a buzzword whose meaning can sometimes be confusing. It is therefore essential for a Purchasing manager or director to be able to understand its specificities in order to integrate and measure the impact of this new discipline on Procurement performance.
GOALS
- Understand how AI is going to change the positioning of the Procurement function
and its organization. - Know the main AI technologies and their scope of use by the Procurement Departments.
- Identify the impacts of AI, both in terms of gains (increased productivity, increased analysis capacities) and risks for the organization (HR challenges).
ADVANTAGES
- Concrete use cases related to Procurement
- Feedback on what works and what doesn't work
AUDIENCE
- Chief Procurement Officers (CPOs)
- Category Managers
- Chief Innovation/Information Officers (CIOs)
CONTENT
- Context
- What is AI? How to differentiate AI from descriptive decision-making or solutions
based on statistics? - The main AI technologies, the lexicon that can't be ignored
- What are the stakes for the Procurement function, attached to the valorization of data and the automation of tasks?
- Machine Learning
- Machine Learning and the different components of supervised, unsupervised and reinforced learning. The notions of classification, regression, and predictive models.
- The onboarding Strategy
- The main application fields of AI, in 2020, on Procurement processes (S2C/P2P)
- What are the first projects to consider ? Why?
- How to internally "sell" an AI project (Examples of ROI models)?
- How to manage an AI-type project (Which skills and technologies, which approaches?)?
- What collaboration models (including business models) with providers?
- Essential Precautions
- What data culture to develop and how to develop it?
- How to retrieve, secure and manage data, whether it comes from internal or external sources? Which data management technologies to use (What are data lakes, data plants, IaaS platforms, PaaS, API, ELT...?)?
- Use Cases
- Use case #1: Contract management and risk control through the NLP approach
- Use case # 2: Process mining applied to S2C and P2P processes
- Use case #3: Work organization thanks to loading anticipation algorithms
Duration: 1 Day
Date: Contact us
