Weighted Risk Assessment

Turn your risk register into data-driven insight with simple scoring

■ Why This Use Case
■ Step-by-Step Framework
➤ Step 1: Prepare Your Risk List
➤ Step 2: Add Likelihood and Impact Scales
➤ Step 3: Calculate Exposure and Priority
➤ Step 4: Interpret the Numbers
➤ Step 5: Summarise and Share
■ Example: Website Redesign Project
■ What to Do Next

Why This Use Case

Assigning numbers to risks turns intuition into evidence.

A quantified risk register helps teams prioritise limited time and resources by focusing on what truly matters.

This use case shows how to take your existing risk list and apply simple numeric scoring with AI support. You will calculate exposure values and quickly see which risks carry the greatest threat, building a stronger foundation for proactive decision-making.

Step-by-Step Framework

Step 1: Prepare Your Risk List

Start with your Quick Starter Risk Register or any basic risk table.

Each entry should include: risk description, category, owner, likelihood, and impact.

If you do not have one yet, create a short list manually or reuse the example provided below.

You are a project analyst. Review the following risk list and confirm it is complete for scoring (each risk should include a short description and clear category).

You Get: A clean and structured list ready for numerical scoring.

Step 2: Add Likelihood and Impact Scales

Define simple 1–5 scales for both likelihood and impact.

For example:

Likelihood: 1 (rare) to 5 (very likely)
Impact: 1 (minor) to 5 (critical)

You are a project risk consultant. Assign each risk a likelihood and impact score from 1–5, using the provided scale definitions. Include a short reason for each rating.

You Get: A consistent scoring framework that ensures everyone rates risks the same way.

Step 3: Calculate Exposure and Priority

Now calculate each risk’s exposure score using the formula: Exposure = Likelihood × Impact

You are a data analyst. For each risk, calculate an exposure score using likelihood × impact. Rank risks from highest to lowest exposure and suggest which 3 require the most immediate attention.

You Get: A ranked list that clearly shows which risks pose the greatest threat.

Step 4: Interpret the Numbers

Numbers provide clarity only if you interpret them in context. AI can help explain which risks are critical, moderate, or low, based on thresholds.

You are a risk advisor. Review the exposure scores and group risks into High, Medium, and Low categories. Provide one sentence explaining why each high-risk item should be prioritised.

You Get: Actionable insight, not just data – you now know what to act on first.

Step 5: Summarise and Share

Present your quantified results in a simple table or visual format. Use colour coding (red = high, amber = medium, green = low) for quick scanning.

Create a summary table showing: Risk ID, Description, Likelihood, Impact, Exposure Score, and Risk Level (High/Medium/Low). Sort by highest exposure first.

You Get: A prioritised, easy-to-read risk register ready to share in reports or team meetings.

Example: Website Redesign Project

Risk ID	Description	Likelihood	Impact	Exposure	Level
R1	Content sign-off delays	4	3	12	High
R2	Scope changes mid-project	3	4	12	High
R3	Developer availability issues	2	5	10	Medium
R4	Budget stretch due to new tools	3	3	9	Medium
R5	Missed deadline from design revisions	2	4	8	Low

What to Do Next

Now that you have a weighted risk assessment, use it to guide your project decisions and communicate priorities to stakeholders.