Deltor AI clients onboarding new enterprise engagements spend 16-24 manual hours per engagement conducting discovery interviews, mapping workflows, and building Ops Canvas frameworks to identify automation opportunities. This friction extends sales cycles and delays ROI realization — a critical pain point when 78% of prospects cite "time-to-value" as their top vendor selection factor (source: 2024 Gartner AI Ops Survey). Our operations team currently executes 14 client onboardings monthly at $210/hour blended consultant cost, consuming $47,040/month in high-value resources that could be redeployed to solution delivery.

The business case: 14 onboardings/month × 20 saved hours/onboarding × $210/hour × 12 months = $705,600/year recoverable (source: ClientOps team utilization data Aug 2023-Jul 2024). If adoption is 40% of estimate: $282,240/year. This excludes the hidden cost of delayed automation pipelines — clients who wait 3 extra days for assessments miss $28K/day in operational savings per engagement (source: avg client ROI case study library). This feature is an AI-powered generator producing baseline Ops Canvases from structured diagnostics. It is not a replacement for expert-led deep dives or a production workflow automation tool.

By automating the discovery baseline, clients instantly visualize friction points with ROI estimates before the first consultant call. Early adopters in our beta program shortened sales cycles by 11 days (source: Pilot A/B test July 2024) — translating to $308K/year pipeline acceleration. The tool creates capacity for consultants to focus on high-value solution design rather than manual data aggregation.

Competitors force clients through manual discovery: McKinsey relies on consultant-led workshops (high cost), UiPath requires full platform deployment before diagnosis, and Hyperscience's questionnaire lacks Deltor's industry-specific ROI modeling.

Our wedge is quantified urgency creation because clients see exact dollar figures attached to latency 48 hours faster than competitors.

WHO/JTBD: When an enterprise operations director initiates an AI opportunity assessment with Deltor, they need to rapidly surface and prioritize operational bottlenecks — so they can align stakeholders on automation targets before committing consultant resources.

WHERE IT BREAKS: Today, the client schedules multiple discovery sessions across departments, manually aggregates system metrics, and struggles to standardize friction documentation. Deltor consultants then spend days reconciling disjointed inputs into the Ops Canvas framework, delaying the ROI conversation by 5-8 business days.

WHAT IT COSTS:

JTBD statement: "When we start an automation assessment, we need a data-driven, self-serve Ops Canvas draft highlighting high-ROI friction points within 2 hours — so we can focus consultant time on solution design instead of baseline mapping."

Integration Map:

• Reads: Client CRM (deal stage), Deltor ROI database (industry benchmarks), Diagnostic API responses
• Writes: Ops Canvas database (new schema), Recommendation engine (module mapping)

Core Mechanics:

1. Client completes 20-question diagnostic (system integrations, process error rates, manual touchpoints)
2. AI maps responses to Deltor’s friction taxonomy
3. Engine prioritizes bottlenecks by combining client data + industry benchmarks
4. Canvas renders with: ROI estimates, module recommendations, data gaps

Primary User Flow:

┌───────────────────────────────────────────────────────────┐
│ DIAGNOSTIC PROGRESS: 8/20               [Pause] [Save]    │
├───────────────────────────────────────────────────────────┤
│ PROCESS: Order Fulfillment                               │ 
│ Volume: ███ 12,000/month                                 │
│ Manual Interventions: ██████████ 28% of transactions      │
│ Error Rate: ████ 6.2% (Industry avg: 3.1%) → $42K/mo loss│
│                                                    [Edit] │
└───────────────────────────────────────────────────────────┘

┌───────────────────────────────────────────────────────────┐
│ OPS CANVAS PREVIEW: Priority Bottlenecks        [Export]  │
├───────────────────┬─────────────────┬─────────────────────┤
│ Bottleneck        │ Impact Score    │ Rec. Modules        │
├───────────────────┼─────────────────┼─────────────────────┤
│ Manual PO matching│ 92              │ InvoiceAI           │
│ $▲ $38K/mo savings│                 │ OCR+GL Integration  │
├───────────────────┼─────────────────┼─────────────────────┤
│ Credit check delays│ 87              │ RiskOracle          │
│ $▲ $12K/mo savings│                 │ (needs KYC details) │
└───────────────────┴─────────────────┴─────────────────────┘

Phase 1 — MVP (6 weeks)
US#1 — Diagnostic Builder

• Given sales marks deal as "Discovery Pending"
• When client accesses diagnostic portal
• Then system renders first 5 dynamic questions based on industry vertical
• If questionnaire fails, fallback to email PDF (validated by Ops Lead)

US#2 — ROI Calculator

• Given diagnostic submission with process volume data
• Then system surfaces cost/error benchmarks with ±15% accuracy P0
• If benchmark missing, flag "manual review needed" (validated against 20 client datasets)

Out of Scope (Phase 1):

Phase 1.1 — 2 weeks post-MVP:

• SAP/Oracle ERP direct ingestion
• Export to PowerPoint format

Primary Metrics:

Guardrail Metrics:

What We Are NOT Measuring:

• Number of generated Canvases (vanity metric — doesn't measure quality)
• Canvas generation speed (latency under 5s not business-critical)

Risk 1 — Inaccurate ROI Models

• Probability: Medium │ Impact: High
• Trigger: Client disputes ROI figures → erodes trust
• Mitigation: Embed "confidence scores" + source footnotes (Owner: Data Sci Lead by 10/15)
• Kill Criteria: >2 clients dispute ROI accuracy in D30

Risk 2 — Integration Blind Spots

• Probability: High │ Impact: Medium
• Trigger: Questionnaire misses critical system → incomplete Canvas
• Mitigation: Auto-flag gaps against industry templates (Owner: Product by launch)

Compliance Risk — RBI PA License Gap

• Probability: Low │ Impact: Critical
• Trigger: Data export includes PII without certification
• Mitigation: Legal review before diagnostic live (Owner: Legal by 11/30; if blocked: disable exports)

Kill Criteria — review triggered if:

1. Deal conversion drops >15% in first 30 days
2. More than 40% of Canvases require manual rework

1. Should we gate diagnostics behind sales-assisted config? → Decision: Open access but require deal ID
2. How to handle unvalidated industry profiles? → Decision: Flag "beta" models with manual review option

Before/After Narrative:
Before: Acme Corp’s COO spent 3 days gathering input from warehouse, AR, and IT teams for their Deltor assessment. Critical invoice matching bottlenecks were buried in PDF attachments until day 5.

After: Acme’s ops lead completed the diagnostic in 73 minutes. The Canvas prioritized manual PO matching as a $38K/mo opportunity before the consultant joined. Implementation started 8 days sooner.

Pre-Mortem:
It is 6 months from now and this feature has failed. The 3 most likely reasons are:

1. Clients couldn’t access required system metrics without IT help — causing 60% drop-off at question 12.
2. ROI models for healthcare verticals used retail benchmarks — triggering 3 contract cancellations.
3. UiPath launched Process HQ 3 weeks before us — neutralizing our speed advantage.

Success looks like: Clients reference the Canvas in board meetings. Sales reports 20% shorter discovery cycles. Consultants request MORE engagements because they start at solution design. The CPO cites this in Q3 earnings as "fundamentally changing our delivery economics."