Prioritise supplier vulnerabilities
How can you use AI to prioritise supplier risks without confusing evidence, assumptions and missing information?
1960 € per session, excl. VAT
In short
One seven-hour day, excluding breaks, to turn disparate supplier files into an evidence-based risk map and a risk control plan. Generative AI supports the extraction of signals and the drafting of analyses; participants check sources, recalculate scores and prepare procurement decision trade-offs using a fictional case.
Why this training?
Supplier assessments often mix purchasing criticality, recent incidents and commercial judgements. Without common scales or dated sources, two buyers can arrive at opposing priorities and overlook a major industrial dependency. AI makes it easier to cross-reference files and formulate scenarios, but may invent a justification or overinterpret an old document. The approach requires traceable evidence, human validation and explicit checks of risk ratings. Case used throughout: The fictional company Ondrave Assemblages is preparing to ramp up production. Among its eight suppliers of critical parts, some face delays, dependence on a single site or incomplete financial documents. The procurement committee expects three justified priorities, without equating missing information with low risk. Transfer to the workplace: Reuse the assessment grid for an authorised set of suppliers, have procurement and operations validate the ratings, then follow up on actions that have fallen due and missing evidence at the next supplier review.
Objectives of this training
- Define a scope based on purchasing criticality and substitutability
- Extract source-referenced signals with a generative AI assistant
- Distinguish established facts, assumptions and missing information
- Rate risks using explicit, reproducible scales
- Prioritise actions with assigned owners, deadlines and indicators
Who is it for and what are the prerequisites?
Roles and tasks concerned
- Category buyers and procurement managers managing a supplier portfolio
- Supply, supplier quality and operations managers taking part in risk reviews
Prior skills
- Understand supplier qualification and monitoring processes.
- Be able to formulate a structured request to a generative AI assistant.
- Use a spreadsheet to sort data and check calculations.
What you will work on
Define critical dependencies
Objective: Separate purchasing criticality from risk exposure. Substitutability, requalification lead times, concentration and the consequences of a supply disruption.
Compile the evidence file
Objective: Make information usable and traceable. Confidentiality, age of documents, contradictions and missing data.
Characterise risk scenarios
Objective: Link each signal to a business consequence. Financial, industrial, logistical, cyber and compliance risks; distinction between cause, event and impact.
Assign ratings and test the ranking
Objective: Produce a reproducible ranking. Likelihood and impact scales, confidence level, limitations of scores and risk of double counting.
Select risk control measures
Objective: Tailor actions to priority vulnerabilities. Second source, safety stock, targeted audit, monitoring and residual risk.
Defend procurement decision trade-offs
Objective: Present a verifiable recommendation. Decision-making summary, alert thresholds, review frequency and human validation.
What you take away
- Register of evidence, gaps and assumptions for each supplier
- Documented rating grid with verified scores
- Prioritised risk map and supply disruption scenarios
- Risk control plan and decision briefing for the procurement committee
Method and assessment
- Short instructional sessions followed by immediate practice using the case studied throughout.
- Individual work followed by work in pairs, with peer review of outputs.
- Guided group discussion: what works, what needs correcting and what remains a human decision.
- Preparation: Identify critical purchasing categories and the internal confidentiality rules applicable to supplier files. Check access to the tools authorised by the organisation; exercises use only fictional or anonymised data.
Observable criteria: Each retained signal refers to a document, a date and a verifiable extract. ; Missing information is flagged without automatically receiving a favourable rating. ; All scores are recalculated and comply with the defined scales. ; The three priorities are justified by operational consequences and the available evidence. ; Each priority action has an owner, a deadline and a monitoring indicator..
Frequently asked questions
Can AI decide to exclude a supplier?
No. It helps structure the analysis; the decision rests with authorised managers.
How should an incomplete financial file be handled?
Flag the uncertainty, request the necessary documents and avoid any unsupported conclusion about solvency.
Does AI need to be connected to the procurement system?
No. Training files and a spreadsheet are sufficient to practise the approach.
Can real contracts be used?
Only after anonymisation and internal authorisation, in an approved environment; otherwise, use the fictional case.
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