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04 · Risk Management Deep Dive

Level 1 introduced the risk register and the probability/impact grid. That is qualitative risk analysis, and it answers "which risks should we worry about first?" This module goes further: it covers how to write a risk statement that is actually actionable, how to calibrate a scoring scale so two people score the same risk the same way, and — the part most PMs never learn — how to convert a risk register into a defensible contingency reserve number using expected monetary value and decision trees.

Writing a risk that can be managed

Most risk registers fail at the first column. "Resourcing" is not a risk; it is a topic. A usable risk statement has three parts:

CauseUncertain eventEffect on an objective

Because the hardware vendor is a single source with no contractual delivery date, the servers may arrive after the integration window opens, which would delay go-live and incur data-centre holding costs.

The test is simple: if you cannot name the objective it threatens (cost, schedule, scope, quality, benefit), you have not written a risk. Note also that risks include opportunities — uncertain events with positive effect. A register containing only threats is half a register.

Category Prompts to generate risks
Technical Unproven technology, integration complexity, performance limits
External Vendors, regulation, market, weather, geopolitics
Organisational Funding stability, competing priorities, key person dependency
Project management Estimating accuracy, poor requirements, unrealistic baseline

The risk register template

This is the working artefact. Columns to the left of the double line are identification; to the right are analysis and response.

ID Risk statement (cause → event → effect) Category Owner P I Score Response Action Trigger Residual
R1 Single-source vendor has no contractual date → servers arrive late → go-live slips External Ops Lead 0.30 4 1.2 Mitigate Add contractual delivery date + penalty; qualify second supplier Vendor misses design freeze 0.10 × 4
R2 Only one architect knows the payments module → they leave → rework and delay Organisational PM 0.20 3 0.6 Mitigate Pair a second engineer; document interfaces by month 3 Resignation, or 2 weeks leave 0.10 × 3
R3 Regulator consulting on new data rules → spec changes mid-build → major rework External Sponsor 0.15 5 0.75 Accept (active) Contingency reserve; monitor consultation Draft rules published 0.15 × 5
R4 Interfaces defined late → integration defects → retest cycles Technical Tech Lead 0.40 2 0.8 Mitigate Contract-first interface design; CI from week 2 Interface spec late by 1 week 0.20 × 2
R5 Vendor offers discount for signing before Q3 → lower licence cost External PM 0.50 +2 Exploit (opportunity) Bring the approval gate forward two weeks Vendor confirms offer

Five columns are the ones people omit and then regret. Owner must be a named person, never a team. Trigger is the observable event that says the risk is materialising — without it, nobody knows when to execute the response. Residual is the risk that remains after the response, which is what you actually carry. And responses must be distinct actions, not restatements of the risk.

Response (threats) Meaning Response (opportunities) Meaning
Avoid Change the plan so the risk cannot occur Exploit Change the plan so it certainly occurs
Transfer Move impact to a third party (insurance, fixed-price contract) Share Partner with someone better placed to capture it
Mitigate Reduce probability or impact Enhance Increase probability or impact
Accept Take it knowingly — with a reserve (active) or not (passive) Accept Take the upside if it arrives

Calibrating the scales

Qualitative scoring is worthless if "high impact" means different things to different people. Define the scale in project-specific units before the first workshop.

Score Probability Cost impact Schedule impact
1 — Very low < 10% < $10k < 3 days
2 — Low 10–30% $10k–50k 3–10 days
3 — Moderate 30–50% $50k–150k 10–20 days
4 — High 50–70% $150k–400k 20–40 days
5 — Very high > 70% > $400k > 40 days

Score against the highest applicable dimension: a risk that costs $20k but delays 30 days is a 4, not a 2. And score impact if it occurs, never impact discounted by likelihood — probability is already the other axis, and discounting twice buries genuinely severe risks.

Quantitative analysis: expected monetary value

Qualitative scoring ranks risks. It cannot tell you how much contingency to hold. Expected monetary value (EMV) = probability × impact in currency, which converts the register into money.

Risk Probability Impact ($) EMV ($)
R1 Vendor hardware delay 0.30 −120,000 −36,000
R2 Lead architect leaves 0.20 −60,000 −12,000
R3 Regulatory spec change 0.15 −200,000 −30,000
R4 Integration rework 0.40 −45,000 −18,000
R5 Early-signing licence discount 0.50 +40,000 +20,000
Net EMV −76,000

Check R1: 0.30 × (−$120,000) = −$36,000. Threats alone total −$96,000; the single opportunity offsets $20,000 of that, giving a net exposure of $76,000.

That number is the contingency reserve request, and this is the whole reason to do the arithmetic. "We'd like a 10% contingency" invites a negotiation down to 5%. "We need $76,000, and here is the line-by-line derivation" is a different conversation — and when a risk closes without occurring, you can release its EMV back to the sponsor, which builds the credibility to ask again next time.

Two cautions. EMV is an average across many projects, and your project runs once: the $76,000 reserve does not cover the $200,000 regulatory hit if it lands. Reserve against the portfolio of risks, and escalate any single risk whose impact exceeds the whole reserve. Second, contingency reserve covers identified risks and sits inside the cost baseline, under the PM's control. Management reserve covers unknown-unknowns, sits outside the baseline, and needs sponsor approval to access. Never conflate them.

Decision trees

When a choice must be made under uncertainty, EMV extends to comparing whole options. The team must decide whether to build a payments module in-house or buy a vendor product.

Option Outcome Probability Total cost Weighted
Build Goes well 0.60 −$900,000 −$540,000
Overruns 0.40 −$1,400,000 −$560,000
EMV −$1,100,000
Buy Integrates cleanly 0.80 −$1,050,000 −$840,000
Needs customisation 0.20 −$1,250,000 −$250,000
EMV −$1,090,000

Buy wins — by $10,000, which is 0.9% of the decision. The honest conclusion is not "buy is better"; it is "on cost, these options are indistinguishable, so decide on the factors the tree doesn't model." Buy has a much narrower spread ($1.05m–$1.25m versus $0.9m–$1.4m), so it is the lower-variance choice — which matters if a $1.4m outcome would breach the funding envelope. Build retains in-house capability. Present the tree, then argue those points explicitly; a decision tree is an input to judgement, not a replacement for it.

If the tree had come out $300,000 apart, the arithmetic would be decisive. Knowing the difference between a decisive and an indistinguishable result is the skill.

A register nobody reviews is documentation, not management

The most common failure in risk management is not bad analysis — it is a register built during initiation and never opened again. Put a risk review on a fixed cadence (weekly for the top 5, monthly for the full register), and at every review do three things: re-score existing risks, check whether any triggers have fired, and add newly identified ones. Risk scores are perishable, and a stale register gives false comfort.

How It Actually Works

A decision tree's expected value at each node is computed by backward induction — the same right-to-left mechanic as CPM's backward pass in Module 2: you solve the rightmost (latest) branches first, collapse each decision node to the value of its best child, and roll that collapsed value leftward, node by node, until the root shows the EV-optimal path. This is why decision trees handle sequential, conditional risk decisions (e.g. "test the prototype first, and only pay for full tooling if the test passes") correctly while a flat EMV table cannot — the flat table assumes independent one-shot bets, while the tree correctly discounts a later cost by the probability of even reaching that branch. The calibration step (turning "high/medium/low" into numeric probability bands) matters because miscalibrated qualitative scales silently break EMV math downstream: if your organization's "high probability" secretly means anywhere from 40% to 90% depending on who's estimating, two risks rated identically on the heat map can carry EMVs that differ by more than 2×, and the reserve pooled from a register of miscalibrated risks will be systematically wrong in a direction nobody can detect from the register itself — only a calibration exercise (asking "if we ran this exact risk 10 times, how many times would it occur?") catches it.

Exercise

Build a full risk analysis for a project of your own.

  1. Identify at least 10 risks — including at least two opportunities — written in strict cause → event → effect form. If you cannot name the objective threatened, rewrite the risk.
  2. Define your own calibrated probability and impact scales in project-specific units, as in the table above.
  3. Complete the full register template, including owner, trigger, response type, action and residual score for every risk. Ensure each response is an action, not a restatement.
  4. Convert your top 6 risks to currency and compute the EMV of each and the net EMV. State the contingency reserve you would request and how you would justify it to a sponsor who asks you to halve it.
  5. Identify one genuine either/or decision on your project, build a decision tree with at least two outcomes per branch, and compute the EMV of each option. State whether the result is decisive or indistinguishable, and if indistinguishable, name the non-cost factors you would decide on.
  6. State your risk review cadence and who attends.