Avoided loss
Prevented spend, refund abuse, fraud, bad disbursements, or unauthorized system changes.
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Close-stage economics
If one execution-certainty workflow does not pay back in 60 days, it should not deploy
This is a public ROI proof surface for Decionis decisioning infrastructure. Model one workflow, expose the current approval drag, inspect the certified state, and decide whether the pilot pays back fast enough to deserve expansion.
Modeled economics
Expose the drag before you argue about the platform
The page is designed to answer three questions fast: what approval drag costs now, what changes under certified execution, and whether the pilot repays inside 60 days.
Scenario model
One workflow. One payback case. No vague platform math.
This model exposes the economic bottleneck in one governed workflow. Replace the public defaults with your own signal volume, cycle time, and pilot assumptions.
Current drag
$92,235
Modeled monthly cost of review labor, approval delay, avoidable loss, and low-signal work.
Cycle compression
58%
4.5d down to 1.9d in the governed state.
No-action wins
$6,199
65 operator hours recovered by not creating work on weak signals.
Estimated payback
41 days
$50,924 realized in 60 days against $35,140 of deployment cost.
Workflow profile
Decision drag inputs
AI-agent report triage
Approval drag
Labor and delay model
Restraint value
No-action wins and avoidable loss
Pilot economics
60-day deployment assumptions
Status quo comparison
Approvals and logs are not execution certainty
Most buyers already have approvals, permissions, and audit logs. The close question is whether those controls certify the action before it lands.
Approvals
Show someone clicked yes, but not whether the action had enough evidence to proceed.
Returns one allow/block/escalate verdict before execution.
ERP permissions
Show who had access, but not whether this specific action matched policy.
Evaluates the action, context, thresholds, and policy snapshot together.
Audit logs
Reconstruct what happened after the fact.
Creates a signed Decision Dossier at the execution boundary.
Human review
Can degrade into rubber-stamping when thresholds are unclear.
Routes gray-zone actions to named owners with reason codes attached.
What buyers can defend
The proof model is intentionally narrow
It stays on one workflow because broad platform ROI is a weak close story. The model should prove specific operating value before the rollout expands.
Approval compression
Days to minutes or seconds when policy is clear and the safe path should not wait.
Audit prep reduction
Signed dossiers replace screenshot hunts, ticket archaeology, and manual evidence assembly.
Policy coverage
The percentage of high-risk actions evaluated before money moves or state changes.
Do not overclaim universal ROI before workflow-specific data exists. The stronger close-stage claim is that Decionis creates the measurement layer: replay actions in Shadow Mode, convert results into signed evidence, then promote only the workflows that clear the payback and false-positive bar.
The strongest Decionis close is one workflow with visible drag and visible restraint.
If the model clears the 60-day bar, move into the assessment or guided pilot. If it does not, the right answer is to narrow the workflow until the economics are defensible.
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