Guide
Read the Answer
Results separates the solved answer, its supporting analysis, a counterfactual comparison, and the material you share. The answer keeps the same Form as the model you built.
How the Results screen is organized
Four destinations keep the answer separate from deeper diagnostics:
Solved decision, achieved outcome, governing limits, repair, and the relevant time plan.
Drivers, sensitivity, pressure tests, uncertainty, tradeoffs, decision maps, and scenario-aware analysis when enabled.
Scenario B, changed assumptions, a Form-native solution diff, interventions, and reviewed hypotheses.
Decision brief, PDF and CSV exports, constraint audit, input documentation, and scenario results.
Answer: baseline and next move
The baseline answer is the optimal feasible value for the selected objective under the current assumptions. For a maximization objective it is the highest achievable outcome; for a minimization objective it is the lowest achievable cost or resource use.
Below the headline value, the Answer tab calls out the binding constraint, the strongest sensitivity signal when it differs, and the Next move: a concrete relaxation or test to stage before tuning lower-impact assumptions.
The solved visual follows the model's Form. Network shows stages and routes, Composition shows inputs and the blend, Portfolio shows candidates against windows, and Assignment groups items by destination. The detailed flow diagram is reserved for Network models.
If you are running a multi-period plan, the answer also shows horizon totals, average value per period, demand growth, carry-over settings, inventory, backlog, and period-by-period trajectory details when available.
When the model has decision alternatives, the answer also lists which options were selected and how much of each, and whether every group's selection rule was satisfied, using your option names rather than solver variables. If any constraint was set to allow a penalized violation, the violations are listed separately from binding constraints, each with the penalty it added.
The headline number is the real physical or economic outcome. Soft-constraint penalties are reported alongside it and are part of what the solver optimized, but they are never folded into the KPI you report, so a figure such as "18,400 units" always means units.
If you asked for a target instead
A target-seeking solve answers a different question, so it reports differently: whether the target was verified as achieved, the achieved value and any remaining gap, which interventions were selected and in what quantity, what they cost in the resource you nominated, and which limits stay binding or become limiting next.
Achieved means the final operating plan solved to optimality with the gap inside tolerance, not merely that the intervention model produced a number. See Decisions & Targets.
Analysis: what governs the answer
Active limits, also called binding constraints, are constraints fully used up by the baseline answer. They have zero slack, so the solver cannot improve the objective without changing one of those limits or the model structure.
The Most sensitive drivers panel ranks the limits with the largest local impact. When pressure-test results are ready, the ranking reflects objective loss in the pressure test. Otherwise it falls back to marginal value near the current solution.
How much the optimized outcome improves when a constraint is relaxed by one unit. For yes/no or whole-number decisions, treat this as approximate.
Sweep one constraint from tighter to looser and see how the objective changes. The current setup is marked so you can compare nearby alternatives.
Re-solves the top binding constraints after a 10% relaxation and shows whether the same limit still governs the result or a new active limit takes over.
The All constraints table is the audit view: each limit is labeled Binding, Near limit, or Available, with its current limit and remaining room.
Analysis: test the assumptions
Analysis asks whether the baseline answer still holds when assumptions move against it. The pressure test tightens one limit at a time by the selected level and re-solves. A result can stay stable, lose objective value, or become infeasible.
Uncertainty simulation uses the uncertainty ranges you set in Step 3. It samples many deterministic scenarios, reports the feasibility rate, shows the feasible objective spread, and attributes failed samples to the constraints most associated with failure.
Use the pressure test for a quick local fragility check. Use uncertainty simulation when you have uncertainty percentages configured and need to estimate how often sampled scenarios survive variation.
If the model carries saved scenarios, this tab also holds the Scenario plan comparison. Evaluate plans reports adaptive re-optimization and the committed-plan check side by side: how many scenarios stayed feasible, the worst-case and expected outcome, the target success rate, and how much value each scenario loses to your commitments. Below that, Run scenario-aware optimization builds a single plan across the whole set on an expected-value or worst-case rule and shows the committed plan it recommends.
In scenario-aware optimization the headline KPI is the expected-value or worst-case objective, while the detailed flow, capacity, decision, and bottleneck views show the limiting scenario. Full detail in Scenario Planning.
Compare: Scenario B against baseline
The Compare tab stages a second scenario beside the baseline. Scenario B can come from a preset, an intervention, manual changes, a selected decision-map region, or a plain-language hypothesis.
The comparison shows objective delta, changed assumptions, active-limit changes, and what changed in the plan. Portfolio compares candidates, Assignment compares item placements, Composition compares inputs and quantities, and Network can additionally show its route-level diagram.
- -Presets cover broad moves such as aggressive growth, budget cuts, and supplier slip.
- -The intervention library stages model-specific moves, such as raising capacity or expanding a route.
- -The hypothesis interpreter turns a plain-language what-if into proposed limit and flow changes that you can review before solving Scenario B.
Analysis: explore a range
These tools answer questions bigger than one baseline and one alternative.
Sweeps two constraints on a grid. Colors show which limit is active, amber rings mark transitions, and dark points are infeasible. You can compare a selected region in Scenario B.
Shows efficient tradeoffs between two objectives. Selecting a frontier point reveals active limits, limit-status changes, and marginal shifts from the previous point.
Draws the boundary between feasible and infeasible combinations for two high-impact constraints while preserving the current objective level.
Report: share and audit the solve
The Report tab collects the decision brief, exports, constraint audit, input documentation, risk and uncertainty checks, and scenario results. Copy brief is a compact narrative for sharing; Download PDF creates a decision report; CSV exports include the scenario comparison and constraint audit tables.
Input documentation is a data-quality view, not a mathematical guarantee. It shows which inputs have sources, owners, input confidence, value types, notes, and optional review bounds so you know what to validate before acting on the answer. See Assumptions & Validation for the full workflow.
No workable plan
When no plan can satisfy all constraints simultaneously, SSPLAX shows a No workable plan state instead of the normal Results tabs. This means the assumptions contradict each other or require more capacity than the model allows.
If pre-solve checks find direct contradictions, review those first. They name the specific conflict, such as a minimum requirement that exceeds available flow, a limit below unavoidable activity, or a commitment that a scenario makes unreachable.
You then get two kinds of fix. The combined repair package is a single set of changes across several limits that works as a package. SSPLAX applies the proposed values to a hard model and re-solves it before offering the package, so it is a verified fix rather than an estimate. Apply package stages every change at once.
Below that, ways to make it workable lists ranked single-limit changes: which constraint to increase or decrease, by how much, and the required value. Use these when you'd rather make one change than apply a bundle.
Constraints you marked as protected requirements never appear in either list, and a change to a policy-relief constraint is labeled as policy relief, so a repair depending on a relaxed commitment is not presented as routine.
Use Apply when you want to stage one of those changes, or Review constraints when the right fix should be edited manually. For scenario workflows, see Decision Workflow.