Supply Chain LabUncertainty Lens · Match evidence to modelLab Home
Decision-modelling tool

Uncertainty Lens Lab

Uncertain data are not all the same. Diagnose the evidence, choose a representation and watch how stochastic probability, fuzzy possibility, robust intervals and discrete scenarios produce different supply-chain decisions.

1 · Inspect the evidenceIs it measured history, expert language, a hard bound or a branching event?
2 · Choose a lensEach method preserves a different kind of information.
3 · Simulate fairlyAll four decisions face the same 200 hidden outcomes.
4 · Defend the choiceBalance service, cost and how honestly the model represents what is known.

Australian evidence stream

Select the lens that fits what the planner actually knows.

Diagnosis due
Dynamic uncertainty representationEvidence passes through the selected uncertainty lens to produce a supply-chain buffer decision and simulated performance.
1 / 8Evidence case
- Recommended buffer
- Simulated service
0Diagnosis score

What the planner knows

Diagnosis briefing

Choose a representation, then check it against the evidence.

Average cost · same 200 outcomes

Service achieved

The cheapest model is not automatically the best. Compare performance with how faithfully each method encodes the available evidence.

Stochastic

Use when repeated observations support probabilities or a fitted distribution.

Data says how often

Fuzzy

Use when knowledge is linguistic, subjective or expressed in degrees of plausibility.

Experts say how plausible

Robust / interval

Use when only defensible bounds are known and protection against adverse values matters.

Contracts say the limits

Scenarios

Use for a small set of structurally different futures that cannot be blended into one number.

Events create branches

Eight-case diagnosis trail

About this tool

Uncertainty versus variability

Variability can be measured from repeated data. Uncertainty may instead come from incomplete knowledge, vague language, bounded guarantees or rare structural events.

No universal winner

Stochastic, fuzzy, robust and scenario methods answer different questions. The right method follows the evidence and decision stakes.

Supply-chain insight

Demand, lead time, disruption and quality risk often need different representations inside the same planning system.