Session 3 of 4
Understanding Operational Risk
From business event to operational consequence
Proposed content. This is our suggestion for the slot, not a requirement. The session partner owns the story, the tools and the exercise. What stays fixed is the shared dataset, so the four sessions add up to one day.
What this session covers
How AI can help identify business risks, evaluate possible consequences, and understand how a disruption propagates across an operation.
- Business events and risk signals
- Scenario analysis
- Operational dependencies
- Potential business consequences
- Response paths
- Resilience considerations
The question this session answers
Key questionIf something changes or goes wrong, what could happen across the business?
What participants should leave with
An understanding of how AI can support risk evaluation and scenario exploration before the full operational impact is known.
One handover that matters. Session 4 picks up where this session ends. If this session produces a set of response options for a disruption, Session 4 takes a comparable decision through to an approved, evidenced action. The two work best when the event discussed here is one the room can still recognise an hour later.
What we supply
| Dataset | The same sanitized DataCo supply chain extract used across all four sessions — 180,519 order lines. Source Data |
| Data dictionary | Field definitions, units, and whether each value is source data, derived evidence or a workshop assumption. |
| Room | Screen, connectivity and a facilitator to hand over and hand back. |
| Audience | C-level and senior operations, supply chain and finance leaders. |
What we ask
- Demonstrate on the shared dataset rather than a prepared example, so the day holds together as one story.
- Tell us which parts of this outline you want to keep, change or drop — early enough to brief the room.
- Say what you need from us technically: accounts, connectors, file formats, anything to prepare in advance.