Use cases
Decision questionHow do you use “Use cases” to apply methods, calculations and tools to a real context?
How can a complete decision be taken from situation to deliverable?Apply methods, calculations and tools to a real context.
Guiding question
How can a complete decision be taken from situation to deliverable?
Apply methods, calculations and tools to a real context. The expected outcome is a quantified decision, with its assumptions, its limits and a review condition.
In depth
Use cases : mechanisms, measurements and decision thresholds.
A useful case sets out a complete decision: starting situation, available data, assumptions, calculations, trade-off, measurement plan and review conditions.The result is not a transferable recipe. It is an audited demonstration that lets the reader see what depends on the context and what can be reused.
Operational decision applied to a defined population, area or cohort, with an owner and responsibility for execution.
Cover the pilot, the scale-up and the side effects; state the conditions that still make a rollback possible.
Plan for the status quo, a limited pilot and a rollout, with control units or explicit assumptions about what would have happened without action.
Test the representativeness of the pilot, the transfer, the hidden costs, the heterogeneity and the ability to generalise.
Move to the next stage only when the result, the quality and the exit conditions meet the thresholds written before the test.
Points of vigilance
The distinctions that prevent a misreading.
An observed value with its source, period, unit and grain.
An unobserved value used to project; it must be tested for sensitivity.
A choice with an owner, a success threshold and a review date.
Protocol
From framing to validation.
Reconstruct the status quo and the unit economics before any recommendation.
Include the status quo, a prudent option and an ambitious one on consistent assumptions.
Identify the parameters that reverse the order of the options.
Define the measurement, the thresholds and the post-launch decision calendar.
A recommendation becomes steerable when it carries its thresholds
Situation. A new offer needs €180k to launch. Expected contribution: €80 per customer.
Calculation. Payback threshold: 180,000 ÷ 80 = 2,250 incremental customers, before recurring fixed costs and cannibalisation.
Decision. The case must show the increment assumptions, the lead time, the sales capacity and the plan for measuring the threshold.
Adversarial review
Five questions to settle before presenting a recommendation.
- Is the unit actionable?
Check that it matches the level at which a decision can be executed and tracked. A broader average can reverse the reading by hiding loss-making segments, channels or periods.
- Does the horizon cover the mechanism?
Recompute the conclusion over a short window and a long one. Immediate costs, retention, saturation and delayed effects do not materialise at the same time.
- Does the comparator really represent the absence of action?
Explain what would have happened without the decision. A historical trend or an attribution of contacts is not enough if selection, seasonality or simultaneous changes remain active.
- Which assumption tips the choice?
Identify the parameter that changes the ranking, publish its plausible range and show the prudent scenario. A recommendation without sensitivity hides its main risk.
- Who stops or revises the decision?
Name the owner, the observed signal, the threshold and the review date. Without a stopping rule, a favourable pilot easily becomes a permanent, unexamined commitment.
Acceptance conditions
What must be true before acting.
- Keep the status quo as an explicit option.
- Identify the three assumptions that change the result the most.
- Turn the recommendation into a conditional, reviewable decision.
Limits
What the analysis does not prove.
- A case does not provide a universal benchmark.
- Results change with margin, maturity, competition and channel.
- An educational demonstration does not replace the organisation's own data.
References
Works used to frame the method.
- Kahneman, D., Lovallo, D. & Sibony, O. (2011), “Before You Make That Big Decision”, Harvard Business Review.
- Kohavi, R., Tang, D. & Xu, Y. (2020), Trustworthy Online Controlled Experiments.
Questions to settle
Choose your
next decision.
Start with the uncertainty most likely to change the choice: demand, margin, channel, measurement, capacity or risk.
Build a budget cut by marginal losses, contractual floors and uncertainty with a downloadable quantified scenario.
Compare an opportunistic cut, a robust reduction and a pro-rata cut by expected loss, stress scenarios and capabilities to rebuild.
Allocate an additional budget with marginal returns, capacity ceilings, creative dependencies and comparison with a uniform increase.
A reproducible omnichannel marketing-budget reallocation case: 156 weeks, five channels, explicit uncertainty and a two-stage decision.
Complete offer-launch case: contribution threshold, pilot, cannibalisation, capacity, passage rules and downloadable dossier.
Test a new price with plausible elasticities, contribution, financial exposure and a rollout rule in a downloadable model.
Apply the channel-evaluation method to a simulated file: orders, net margin, transfers, fixed costs, repeat purchase and volume threshold.
Compare immediate repositioning, waiting and a pilot, with demand drift, fixed cost, outcome probabilities and a downloadable tree.
Prioritise experiments, studies and measurements by value of information, with costs, probability of changing the decision and a downloadable template.
Compare countries after margin, currency, tax, capacity and risk scenarios with a downloadable tranche matrix.
Continue the analysis