Work Order QMS Module — Business Model & Unit Economics
Classification: Internal — Business Strategy Date: 2026-02-13 Artifact: 60 of WO System Series Prompt Section: v8.0 §2 — Business Model & Economics
1. Revenue Model
1.1 Model Structure: Hybrid (Subscription + Usage)
The WO module uses a hybrid revenue model anchored on a platform subscription with usage-based expansion triggers.
| Revenue Stream | Model | Metric | Contribution Target |
|---|---|---|---|
| Platform subscription | Annual contract | Tier-based feature access | 60–70% of revenue |
| Usage overage | Pay-per-unit | WOs processed, agent tokens consumed, storage | 15–25% of revenue |
| Professional services | Time & materials | Validation (IQ/OQ/PQ), migration, integration | 10–15% of revenue |
| Marketplace | Revenue share (20%) | Third-party compliance templates, connectors | <5% initially |
1.2 Pricing Tiers
| Tier | Target ICP | Annual Price | WO Volume | Agent Execution | Key Feature Gates |
|---|---|---|---|---|---|
| Starter | Biotech Series A–B, <50 employees | $36K–$60K | ≤500 WOs/yr | 50K tokens/mo | Manual WOs only, basic compliance reporting, 3 users |
| Professional | Biotech Series C+, mid-market pharma | $96K–$180K | ≤5,000 WOs/yr | 500K tokens/mo | Agent-assisted WOs, full Part 11, Master/Linked hierarchy, 25 users |
| Enterprise | Top-200 pharma, large MedDev | $240K–$600K | Unlimited | Custom token allocation | Full autonomous agents, custom integrations, dedicated support, unlimited users |
| Regulated Cloud | Companies needing dedicated infrastructure | Custom ($400K+) | Unlimited | Dedicated compute | Single-tenant, data residency, private cloud options |
1.3 Value Metric Rationale
Primary value metric: WOs processed with compliance evidence.
Why not seats? Seat-based pricing creates adoption friction in organizations where QA, IT, vendors, and system owners all touch WOs. Per-seat pricing discourages the broad usage that generates compliance value. WO volume scales with operational complexity — organizations with more validated systems process more change control records, and they value the automation proportionally.
Expansion triggers:
- WO volume approaching tier limit (70% threshold → upsell conversation)
- Agent token consumption exceeding allocation (signals high automation adoption)
- New system categories onboarded (each validated system = more WOs)
- Vendor portal usage (external users don't count against seats but generate WO volume)
1.4 Billing Architecture
Metering Pipeline:
WO Created → Classified (auto/manual/vendor) → Counted against tier limit
Agent Invoked → Token consumption recorded → Aggregated daily
Storage Used → Audit trail + documents → Measured monthly
Billing Cycle:
Subscription: Annual prepaid (monthly billing available at 15% premium)
Overage: Monthly in arrears, billed at tier rate + 20%
Services: Milestone-based invoicing
2. Unit Economics
2.1 Revenue Per Customer
| Segment | Year 1 ACV | Year 2 ACV | Year 3 ACV | Net Expansion |
|---|---|---|---|---|
| Starter | $48K | $60K | $96K | 200% (upgrade to Pro) |
| Professional | $144K | $180K | $240K | 167% (usage + features) |
| Enterprise | $420K | $500K | $600K | 143% (expansion + new systems) |
| Blended | $120K | $168K | $228K | 160% |
2.2 Cost Structure (Per Customer, Annualized)
| Cost Category | Starter | Professional | Enterprise | Notes |
|---|---|---|---|---|
| AI model tokens | $2,400 (5%) | $14,400 (8%) | $50,400 (12%) | Haiku/Sonnet/Opus mix; model routing reduces 40–60% |
| Cloud infrastructure | $3,600 (8%) | $10,800 (6%) | $36,000 (9%) | PostgreSQL, NATS, compute, storage |
| Support labor | $4,800 (10%) | $14,400 (8%) | $42,000 (10%) | Pooled (Starter), named CSM (Enterprise) |
| Compliance overhead | $1,200 (3%) | $3,600 (2%) | $12,000 (3%) | Audit report generation, evidence storage |
| Total COGS | $12,000 (25%) | $43,200 (24%) | $140,400 (33%) | |
| Gross Margin | 75% | 76% | 67% | Enterprise lower due to dedicated infrastructure |
Blended gross margin target: 72–76% — consistent with best-in-class vertical SaaS.
2.3 Customer Acquisition Cost
| Channel | CAC | Payback (months) | LTV:CAC | Best For |
|---|---|---|---|---|
| Direct sales (enterprise) | $45,000 | 14 | 8:1 | Enterprise pharma |
| Partner/consultant referral | $18,000 | 7 | 12:1 | Mid-market biotech |
| Google AI Accelerator network | $8,000 | 4 | 18:1 | Early-stage biotech |
| Content marketing + inbound | $12,000 | 6 | 14:1 | Professional tier |
| PLG (self-serve Starter) | $3,500 | 2 | 20:1 | Starter → Professional upgrade |
| Blended | $15,000 | 8 | 12:1 |
2.4 Lifetime Value Model
LTV = (ACV × Gross Margin × Avg Lifespan) / (1 + Discount Rate)^years
Assumptions:
Average ACV: $168K (weighted blend)
Gross Margin: 74%
Avg Customer Lifespan: 6.5 years (regulated = sticky; validated systems = high switching cost)
Annual Expansion: 15% NRR above 100%
Discount Rate: 10%
LTV Calculation:
Year 1: $168K × 74% = $124K
Year 2: $193K × 74% = $143K (15% expansion)
Year 3: $222K × 74% = $164K
Year 4: $255K × 74% = $189K
Year 5: $294K × 74% = $217K
Year 6: $338K × 74% = $250K
Year 6.5 (half): $175K × 74% = $130K
Discounted LTV ≈ $810K
LTV:CAC = $810K / $15K = 54:1 (blended)
This LTV:CAC ratio is exceptionally high because regulated industries have extreme switching costs — validated system changes require formal change control (the exact problem CODITECT solves), creating a virtuous lock-in cycle.
2.5 Token Economics as Margin Lever
The model routing system (§3.4 of system prompt) is the primary margin lever:
| Routing Strategy | Avg Token Cost/WO | Monthly Cost (5K WOs) | Gross Margin Impact |
|---|---|---|---|
| All Opus (no routing) | $0.42 | $2,100 | Baseline |
| Intelligent routing | $0.18 | $900 | +$1,200/mo (+57% reduction) |
| Aggressive Haiku | $0.08 | $400 | +$1,700/mo (compliance risk) |
Optimal strategy: Intelligent routing (Haiku for simple tasks, Sonnet for complex, Opus for compliance/security only). This is the default configuration.
3. Customer Segmentation
3.1 Ideal Customer Profiles
ICP 1: Mid-Market Pharma QA Director (Primary Target)
firmographic:
industry: Pharmaceutical, biotech
revenue: $200M–$2B
employees: 500–5,000
regulation: FDA 21 CFR Part 11, EU Annex 11
validated_systems: 15–50
behavioral:
current_qms: MasterControl, paper-based, or homegrown
pain: 40+ hours/week on manual change control documentation
trigger: Failed audit finding, digital transformation initiative, IPO preparation
buying_committee: QA Director (champion), VP IT (budget), Head of Regulatory (approver)
deal_characteristics:
target_acv: $144K–$240K
sales_cycle: 4–6 months
decision_criteria: Part 11 compliance proof, implementation speed, audit readiness
competitive_displacement: MasterControl, paper-based systems
ICP 2: Biotech IT Director (Growth Target)
firmographic:
industry: Biotech, cell therapy, gene therapy
revenue: $20M–$200M (often pre-revenue)
employees: 50–500
regulation: FDA Part 11, HIPAA (if clinical)
validated_systems: 3–15
behavioral:
current_qms: None or Excel/SharePoint
pain: Building QMS from scratch for FDA submission
trigger: IND filing preparation, Series C/D fundraise, first GMP facility
buying_committee: IT Director (champion/budget), VP Quality (approver)
deal_characteristics:
target_acv: $48K–$96K
sales_cycle: 2–3 months
decision_criteria: Speed to compliance, cost vs. hiring QA FTEs, scalability
competitive_displacement: Greenfield (no existing system)
ICP 3: Enterprise Pharma VP Quality (Strategic Target)
firmographic:
industry: Top-200 pharma, multinational
revenue: $2B+
employees: 5,000+
regulation: FDA, EMA, PMDA, TGA (multi-jurisdictional)
validated_systems: 50–500+
behavioral:
current_qms: TrackWise, Veeva Vault, SAP QM
pain: Legacy QMS modernization, multi-site coordination, audit volume
trigger: Major regulatory action, M&A integration, digital transformation mandate
buying_committee: VP Quality (sponsor), CIO (budget), Global QA Heads (evaluation)
deal_characteristics:
target_acv: $420K–$600K+
sales_cycle: 9–18 months
decision_criteria: Enterprise integration, multi-region, migration path, vendor stability
competitive_displacement: TrackWise, Veeva Vault
4. Channel Economics
4.1 Channel Strategy
| Channel | Year 1 Revenue Mix | Year 3 Revenue Mix | Unit Economics |
|---|---|---|---|
| Direct sales | 60% | 40% | High CAC ($45K), high ACV ($300K+) |
| Partner/VAR | 20% | 30% | Medium CAC ($18K), medium ACV ($144K) |
| PLG/self-serve | 5% | 15% | Low CAC ($3.5K), low ACV ($48K), upgrade path |
| Google AI Accelerator | 15% | 5% | Low CAC ($8K), mixed ACV (relationship-based) |
| Marketplace | 0% | 10% | Variable (partner-sourced deals) |
4.2 Partner Economics
| Partner Type | Revenue Share | Services Revenue | Strategic Value |
|---|---|---|---|
| QMS consultants (Lachman, IQVIA) | 15–20% referral fee | Customer-billed | FDA validation expertise, credibility |
| System integrators (Deloitte, Accenture) | 10–15% referral fee | Customer-billed | Enterprise access, multi-year programs |
| Technology partners (EHR, LIMS vendors) | Joint marketing budget | Mutual referrals | Integration-driven demand |
5. Build vs. Buy Economics
5.1 Total Cost of Ownership: WO Module
| Cost Category | Build In-House | CODITECT WO Module |
|---|---|---|
| Development (Year 1) | $1.8M (6 engineers × 12 months × $25K fully loaded) | $0 (included in subscription) |
| Compliance validation | $400K (IQ/OQ/PQ documentation + QA review) | $75K (pre-validated, customer OQ/PQ only) |
| Infrastructure | $120K/yr (PostgreSQL, compute, monitoring) | Included in subscription |
| Ongoing maintenance | $600K/yr (3 engineers dedicated) | Included in subscription |
| Regulatory updates | $200K/yr (Part 11 changes, new regulations) | Included in subscription |
| 3-Year TCO | $4.6M | $432K–$720K |
| 5-Year TCO | $6.2M | $720K–$1.2M |
ROI of CODITECT vs. build: 5–8× cost reduction over 3 years, with the additional benefit that CODITECT's multi-tenant model amortizes compliance investment across all customers.
5.2 Opportunity Cost
Building an in-house WO system for a pharma company means 6 engineers not working on drug development infrastructure, clinical data pipelines, or revenue-generating capabilities. CODITECT converts this fixed engineering cost into a variable OpEx line item.
6. Revenue Projection
6.1 Three-Year Model
| Metric | Year 1 | Year 2 | Year 3 |
|---|---|---|---|
| New customers | 8 | 20 | 47 |
| Total customers | 8 | 28 | 75 |
| Blended ACV | $120K | $168K | $228K |
| New ARR | $960K | $3.4M | $10.7M |
| Expansion ARR | — | $250K | $1.2M |
| Churned ARR | — | ($48K) | ($180K) |
| Total ARR | $960K | $4.6M | $16.3M |
| Gross margin | 74% | 75% | 76% |
| Gross profit | $710K | $3.5M | $12.4M |
6.2 Key Assumptions & Risks
| Assumption | Value | Risk if Wrong | Mitigation |
|---|---|---|---|
| Logo churn | 5%/yr | Higher → ARR gap | Validated system lock-in reduces churn |
| Net revenue retention | 115% | Lower → growth stall | Usage-based expansion + tier upgrades |
| Sales cycle (enterprise) | 9 months | Longer → CAC increase | POC-to-paid program reduces cycle |
| Gross margin | 74%+ | Lower → unit economics fail | Model routing + multi-tenancy leverage |
| Token cost trend | Declining 20%/yr | Flat → margin pressure | Multi-model routing hedges provider risk |
Every technical decision in the WO system should be evaluated against its impact on these economics. If a feature doesn't improve ACV, reduce churn, lower COGS, or enable tier expansion — question whether it belongs in the roadmap.