Predictive Use-Case Framing & ROI Template

{"Title":"Predictive Use-Case Framing & ROI Template","IntroductionHtml":"

Use this short, practical template to frame a predictive analytics use case so it delivers measurable value and remains safe, observable, and maintainable. Complete the fields with concise, decision-focused answers. Saved submissions can be used to prioritize projects, estimate ROI, and hand off to data, product, or operations teams.

","SubmitLabel":"Save Use Case","SuccessMessage":"Use case saved. You can return to edit, export, or use this submission to request resources.","DataType":"PredictiveUseCase","SchemaVersion":"1.0","Fields":[{"Key":"businessObjective","Label":"Business objective","FieldType":"textarea","Required":true,"HelpText":"What specific outcome are you trying to change? Frame as measurable business impact (e.g., reduce late shipments by 20%, cut preventable downtime hours by 30%)."},{"Key":"decisionEnabled","Label":"Decision enabled by the prediction","FieldType":"textarea","Required":true,"HelpText":"What concrete decision will someone make using this prediction? Describe who acts, what they do, and how the action links to the objective (e.g., dispatch maintenance crew, skip inventory replenishment)."},{"Key":"actionOwner","Label":"Action owner / role","FieldType":"text","Required":true,"HelpText":"Who is responsible for taking the action enabled by the prediction? Use a role (e.g., shift supervisor, account manager) rather than a person."},{"Key":"predictionHorizon_value","Label":"Prediction lead time (numeric)","FieldType":"number","Required":true,"HelpText":"How far in advance must the prediction arrive to enable the action? Enter a number; select units in the next field."},{"Key":"predictionHorizon_units","Label":"Prediction lead time units","FieldType":"select","Required":true,"HelpText":"Choose the units for the lead time.","Options":[{"Value":"minutes","Label":"Minutes"},{"Value":"hours","Label":"Hours"},{"Value":"days","Label":"Days"},{"Value":"weeks","Label":"Weeks"}]},{"Key":"performanceTarget","Label":"Performance target for the predictor","FieldType":"text","Required":false,"HelpText":"How will you measure model quality in operational terms? Prefer metrics that relate to decisions (e.g., precision >= 0.8 at 24h lead time, recall >= 0.6)."},{"Key":"baselineMetric","Label":"Baseline (current) metric","FieldType":"number","Required":false,"HelpText":"Enter the current value of the business KPI you aim to improve (e.g., current percent of late shipments = 12). Include units in the field text."},{"Key":"expectedUpliftPercent","Label":"Expected uplift (percent)","FieldType":"number","Required":false,"HelpText":"Estimate the percent improvement in the business KPI attributable to this model (e.g., 20). This is a planning estimate used in ROI calculation."},{"Key":"estimatedAnnualizedROI","Label":"Estimated annualized ROI (USD)","FieldType":"number","Required":false,"HelpText":"If possible, convert the expected uplift into a rough annual dollar value or cost savings. If uncertain, give a conservative estimate or leave blank for later analysis."},{"Key":"deploymentPlanAndGuardrails","Label":"Deployment plan & guardrails","FieldType":"textarea","Required":true,"HelpText":"How will the prediction be consumed? Describe infrastructure (API, dashboard, alert), human-in-the-loop steps, approval gates, rollback criteria, and safety guardrails to prevent harmful automation."},{"Key":"humanInTheLoop","Label":"Requires human-in-the-loop?","FieldType":"yesno","Required":true,"HelpText":"Will a person review model outputs before action? If yes, describe the decision-support UI and expected review workflow in the deployment plan field."},{"Key":"monitoringMetrics","Label":"Monitoring metrics (select all that apply)","FieldType":"checkbox","Required":true,"HelpText":"Choose the monitoring signals you will track continuously after deployment.","Options":[{"Value":"businessKPI","Label":"Primary business KPI (outcome)"},{"Value":"modelAccuracy","Label":"Model accuracy / AUC / other statistical metric"},{"Value":"precision_recall","Label":"Precision / recall or confusion-matrix metrics"},{"Value":"falsePositiveRate","Label":"False positive / false negative rates vs business cost"},{"Value":"latency","Label":"Prediction latency / availability"},{"Value":"dataDrift","Label":"Input data drift / feature distribution change"}]},{"Key":"retrainingCadence","Label":"Retraining cadence","FieldType":"select","Required":true,"HelpText":"Planned schedule or trigger for retraining the model.","Options":[{"Value":"daily","Label":"Daily"},{"Value":"weekly","Label":"Weekly"},{"Value":"monthly","Label":"Monthly"},{"Value":"on_drift","Label":"On detected data or concept drift"},{"Value":"manual","Label":"Manual / as needed"}]},{"Key":"validationPlan","Label":"Validation & acceptance tests","FieldType":"textarea","Required":true,"HelpText":"How will you validate the model before full rollout? Include test datasets, backtesting plan, A/B or shadow-launch approach, and success criteria for acceptance."},{"Key":"keyRisksAndMitigations","Label":"Key risks & mitigation plan","FieldType":"textarea","Required":false,"HelpText":"List major risks (e.g., data leakage, false alarms, regulatory issues) and how you will mitigate them (e.g., stricter thresholds, manual review, conservative rollout)."},{"Key":"notesAndNextSteps","Label":"Notes and next steps","FieldType":"textarea","Required":false,"HelpText":"Any additional context, dependencies, data access needs, stakeholders to engage, or immediate next actions."}]}