Use scenarios and probabilities carefully
Course overview · 4 min reading + 12 min practice, estimated
Principles and method
Probability-weighted forecasts can be useful if stage probabilities are based on relevant history and reviewed. They are not guarantees for individual opportunities. Small samples, changing markets and different service types can make historical rates unreliable. Present downside, base and upside scenarios with explicit assumptions. Consider correlated risks, such as several clients pausing hiring at once, rather than treating every opportunity as independent. Show concentration and timing sensitivity. A forecast should help choose actions and manage exposure, not provide false comfort through a precise decimal.
Worked example
Five opportunities all depend on the same sector expansion. A downturn could affect them together, so adding independent weighted values understates the shared risk. The downside scenario models a sector-wide delay.
Put it into practice
Build three scenarios for five fictional opportunities and identify one correlated risk.
Use fictional information and keep your work in your own notes.
Compare your approach: self-review guidance
State probability assumptions and timing ranges. Explain why the weighted total is an expectation under assumptions, not a promised minimum. Include the effect of losing the largest client.
Sources and further reading
Original Academy teaching and fictional examples. These references provide context, not endorsement. Edition 2026.09; updated 2026-09-24.
- CIPD: Recruitment
Professional context for the recruitment lifecycle.
- GOV.UK: Set up a business
UK starting point. Business structure and obligations depend on the circumstances.