--- name: "sales-engineer" description: Analyzes RFP/RFI responses for coverage gaps, builds competitive feature comparison matrices, and plans proof-of-concept (POC) engagements for pre-sales engineering. Use when responding to RFPs, bids, or proposal requests; comparing product features against competitors; planning or scoring a customer POC or sales demo; preparing a technical proposal; or performing win/loss competitor analysis. Handles tasks described as 'RFP response', 'bid response', 'proposal response', 'competitor comparison', 'feature matrix', 'POC planning', 'sales demo prep', or 'pre-sales engineering'. --- # Sales Engineer Skill ## 5-Phase Workflow ### Phase 1: Discovery & Research **Objective:** Understand customer requirements, technical environment, and business drivers. **Checklist:** - [ ] Conduct technical discovery calls with stakeholders - [ ] Map customer's current architecture and pain points - [ ] Identify integration requirements and constraints - [ ] Document security and compliance requirements - [ ] Assess competitive landscape for this opportunity **Tools:** Run `rfp_response_analyzer.py` to score initial requirement alignment. ```bash python scripts/rfp_response_analyzer.py assets/sample_rfp_data.json --format json > phase1_rfp_results.json ``` **Output:** Technical discovery document, requirement map, initial coverage assessment. **Validation checkpoint:** Coverage score must be >50% and must-have gaps ≤3 before proceeding to Phase 2. Check with: ```bash python scripts/rfp_response_analyzer.py assets/sample_rfp_data.json --format json | python -c "import sys,json; r=json.load(sys.stdin); print('PROCEED' if r['coverage_score']>50 and r['must_have_gaps']<=3 else 'REVIEW')" ``` --- ### Phase 2: Solution Design **Objective:** Design a solution architecture that addresses customer requirements. **Checklist:** - [ ] Map product capabilities to customer requirements - [ ] Design integration architecture - [ ] Identify customization needs and development effort - [ ] Build competitive differentiation strategy - [ ] Create solution architecture diagrams **Tools:** Run `competitive_matrix_builder.py` using Phase 1 data to identify differentiators and vulnerabilities. ```bash python scripts/competitive_matrix_builder.py competitive_data.json --format json > phase2_competitive.json python -c "import json; d=json.load(open('phase2_competitive.json')); print('Differentiators:', d['differentiators']); print('Vulnerabilities:', d['vulnerabilities'])" ``` **Output:** Solution architecture, competitive positioning, technical differentiation strategy. **Validation checkpoint:** Confirm at least one strong differentiator exists per customer priority before proceeding to Phase 3. If no differentiators found, escalate to Product Team (see Integration Points). --- ### Phase 3: Demo Preparation & Delivery **Objective:** Deliver compelling technical demonstrations tailored to stakeholder priorities. **Checklist:** - [ ] Build demo environment matching customer's use case - [ ] Create demo script with talking points per stakeholder role - [ ] Prepare objection handling responses - [ ] Rehearse failure scenarios and recovery paths - [ ] Collect feedback and adjust approach **Templates:** Use `assets/demo_script_template.md` for structured demo preparation. **Output:** Customized demo, stakeholder-specific talking points, feedback capture. **Validation checkpoint:** Demo script must cover every must-have requirement flagged in `phase1_rfp_results.json` before delivery. Cross-reference with: ```bash python -c "import json; rfp=json.load(open('phase1_rfp_results.json')); [print('UNCOVERED:', r) for r in rfp['must_have_requirements'] if r['coverage']=='Gap']" ``` --- ### Phase 4: POC & Evaluation **Objective:** Execute a structured proof-of-concept that validates the solution. **Checklist:** - [ ] Define POC scope, success criteria, and timeline - [ ] Allocate resources and set up environment - [ ] Execute phased testing (core, advanced, edge cases) - [ ] Track progress against success criteria - [ ] Generate evaluation scorecard **Tools:** Run `poc_planner.py` to generate the complete POC plan. ```bash python scripts/poc_planner.py poc_data.json --format json > phase4_poc_plan.json python -c "import json; p=json.load(open('phase4_poc_plan.json')); print('Go/No-Go:', p['recommendation'])" ``` **Templates:** Use `assets/poc_scorecard_template.md` for evaluation tracking. **Output:** POC plan, evaluation scorecard, go/no-go recommendation. **Validation checkpoint:** POC conversion requires scorecard score >60% across all evaluation dimensions (functionality, performance, integration, usability, support). If score <60%, document gaps and loop back to Phase 2 for solution redesign. --- ### Phase 5: Proposal & Closing **Objective:** Deliver a technical proposal that supports the commercial close. **Checklist:** - [ ] Compile POC results and success metrics - [ ] Create technical proposal with implementation plan - [ ] Address outstanding objections with evidence - [ ] Support pricing and packaging discussions - [ ] Conduct win/loss analysis post-decision **Templates:** Use `assets/technical_proposal_template.md` for the proposal document. **Output:** Technical proposal, implementation timeline, risk mitigation plan. --- ## Python Automation Tools ### 1. RFP Response Analyzer **Script:** `scripts/rfp_response_analyzer.py` **Purpose:** Parse RFP/RFI requirements, score coverage, identify gaps, and generate bid/no-bid recommendations. **Coverage Categories:** Full (100%), Partial (50%), Planned (25%), Gap (0%). **Priority Weighting:** Must-Have 3×, Should-Have 2×, Nice-to-Have 1×. **Bid/No-Bid Logic:** - **Bid:** Coverage >70% AND must-have gaps ≤3 - **Conditional Bid:** Coverage 50–70% OR must-have gaps 2–3 - **No-Bid:** Coverage <50% OR must-have gaps >3 **Usage:** ```bash python scripts/rfp_response_analyzer.py assets/sample_rfp_data.json # human-readable python scripts/rfp_response_analyzer.py assets/sample_rfp_data.json --format json # JSON output python scripts/rfp_response_analyzer.py --help ``` **Input Format:** See `assets/sample_rfp_data.json` for the complete schema. --- ### 2. Competitive Matrix Builder **Script:** `scripts/competitive_matrix_builder.py` **Purpose:** Generate feature comparison matrices, calculate competitive scores, identify differentiators and vulnerabilities. **Feature Scoring:** Full (3), Partial (2), Limited (1), None (0). **Usage:** ```bash python scripts/competitive_matrix_builder.py competitive_data.json # human-readable python scripts/competitive_matrix_builder.py competitive_data.json --format json # JSON output ``` **Output Includes:** Feature comparison matrix, weighted competitive scores, differentiators, vulnerabilities, and win themes. --- ### 3. POC Planner **Script:** `scripts/poc_planner.py` **Purpose:** Generate structured POC plans with timeline, resource allocation, success criteria, and evaluation scorecards. **Default Phase Breakdown:** - **Week 1:** Setup — environment provisioning, data migration, configuration - **Weeks 2–3:** Core Testing — primary use cases, integration testing - **Week 4:** Advanced Testing — edge cases, performance, security - **Week 5:** Evaluation — scorecard completion, stakeholder review, go/no-go **Usage:** ```bash python scripts/poc_planner.py poc_data.json # human-readable python scripts/poc_planner.py poc_data.json --format json # JSON output ``` **Output Includes:** Phased POC plan, resource allocation, success criteria, evaluation scorecard, risk register, and go/no-go recommendation framework. --- ## Reference Knowledge Bases | Reference | Description | |-----------|-------------| | `references/rfp-response-guide.md` | RFP/RFI response best practices, compliance matrix, bid/no-bid framework | | `references/competitive-positioning-framework.md` | Competitive analysis methodology, battlecard creation, objection handling | | `references/poc-best-practices.md` | POC planning methodology, success criteria, evaluation frameworks | ## Asset Templates | Template | Purpose | |----------|---------| | `assets/technical_proposal_template.md` | Technical proposal with executive summary, solution architecture, implementation plan | | `assets/demo_script_template.md` | Demo script with agenda, talking points, objection handling | | `assets/poc_scorecard_template.md` | POC evaluation scorecard with weighted scoring | | `assets/sample_rfp_data.json` | Sample RFP data for testing the analyzer | | `assets/expected_output.json` | Expected output from rfp_response_analyzer.py | ## Integration Points - **Marketing Skills** - Leverage competitive intelligence and messaging frameworks from `../../marketing-skill/` - **Product Team** - Coordinate on roadmap items flagged as "Planned" in RFP analysis from `../../product-team/` - **C-Level Advisory** - Escalate strategic deals requiring executive engagement from `../../c-level-advisor/` - **Customer Success** - Hand off POC results and success criteria to CSM from `../customer-success-manager/` --- **Last Updated:** February 2026 **Status:** Production-ready **Tools:** 3 Python automation scripts **References:** 3 knowledge base documents **Templates:** 5 asset files FILE:assets/demo_script_template.md # Demo Script Template ## Demo Information | Field | Value | |-------|-------| | Customer | [Customer Name] | | Date/Time | [Date and Time] | | Duration | [XX minutes] | | Demo Environment | [Environment URL/Details] | | Presenter | [Sales Engineer Name] | | AE/Account Executive | [AE Name] | --- ## Pre-Demo Checklist - [ ] Demo environment tested and confirmed working - [ ] Sample data loaded and validated - [ ] Backup demo environment prepared - [ ] Screen sharing tested with correct resolution - [ ] Browser tabs pre-loaded with key screens - [ ] Recording setup confirmed (if applicable) - [ ] Customer-specific branding applied (if applicable) - [ ] Network and VPN connectivity verified - [ ] All integrations connected and tested - [ ] Backup slides prepared in case of technical issues --- ## Attendees and Roles | Name | Title | Role in Evaluation | Key Interest | |------|-------|-------------------|--------------| | [Name] | [CTO/VP Eng] | Decision Maker | ROI, strategic fit | | [Name] | [Director] | Champion | Solving [specific problem] | | [Name] | [Manager] | Technical Evaluator | Architecture, integrations | | [Name] | [Analyst] | End User | Day-to-day usability | --- ## Agenda | Time | Duration | Topic | Lead | |------|----------|-------|------| | 0:00 | 5 min | Welcome and introductions | AE | | 0:05 | 5 min | Agenda and objectives | SE | | 0:10 | 20 min | Core demo (Use Cases 1-3) | SE | | 0:30 | 10 min | Integration demo | SE | | 0:40 | 5 min | Admin and security overview | SE | | 0:45 | 10 min | Q&A | SE + AE | | 0:55 | 5 min | Next steps and wrap-up | AE | --- ## Demo Flow ### Opening (5 minutes) **Talking Points:** - Thank attendees for their time - Recap what we learned in discovery: "[Summarize 2-3 key challenges]" - Set expectations: "Today I'll show you how we address [Challenge 1], [Challenge 2], and [Challenge 3]" - Frame the demo: "I'll be using [data type] similar to what you described in our earlier conversations" **Transition:** "Let me start with the challenge you mentioned is most pressing: [Challenge 1]." --- ### Use Case 1: [Name] (7 minutes) **Business Context:** [1-2 sentences on why this matters to the customer] **Demo Steps:** 1. **Step 1:** [Navigate to / Click on / Show...] - **What to say:** "[Explain what they're seeing and why it matters]" - **Highlight:** [Specific feature or capability to emphasize] 2. **Step 2:** [Navigate to / Click on / Show...] - **What to say:** "[Connect this to their specific pain point]" - **Highlight:** [Differentiator from competitor] 3. **Step 3:** [Navigate to / Click on / Show...] - **What to say:** "[Quantify the value - time saved, errors reduced, etc.]" - **Highlight:** [Ease of use or power of the feature] **Key Message:** "[One sentence summarizing the value demonstrated]" **Transition:** "Now that you've seen how we handle [Use Case 1], let me show you [Use Case 2]." --- ### Use Case 2: [Name] (7 minutes) **Business Context:** [1-2 sentences on why this matters to the customer] **Demo Steps:** 1. **Step 1:** [Navigate to / Click on / Show...] - **What to say:** "[Explanation]" - **Highlight:** [Key capability] 2. **Step 2:** [Navigate to / Click on / Show...] - **What to say:** "[Explanation]" - **Highlight:** [Key capability] 3. **Step 3:** [Navigate to / Click on / Show...] - **What to say:** "[Explanation]" - **Highlight:** [Key capability] **Key Message:** "[One sentence summarizing the value demonstrated]" **Transition:** "[Transition statement to next section]" --- ### Use Case 3: [Name] (6 minutes) **Business Context:** [1-2 sentences on why this matters to the customer] **Demo Steps:** 1. **Step 1:** [Description] - **What to say:** "[Explanation]" - **Highlight:** [Key capability] 2. **Step 2:** [Description] - **What to say:** "[Explanation]" - **Highlight:** [Key capability] **Key Message:** "[One sentence summarizing the value demonstrated]" --- ### Integration Demo (10 minutes) **Context:** "You mentioned that integration with [System X] and [System Y] is critical. Let me show you how that works." **Demo Steps:** 1. **Show integration configuration:** - **What to say:** "Setting up the connection takes [X minutes/clicks]" - **Highlight:** Native connector, no custom code required 2. **Show data flow:** - **What to say:** "Data syncs in [real-time/X minute intervals]" - **Highlight:** Reliability, error handling, monitoring 3. **Show end-to-end workflow:** - **What to say:** "Here's the complete flow from [source] to [destination]" - **Highlight:** Automation, reduced manual effort --- ### Admin and Security (5 minutes) **Demo Steps:** 1. **Show RBAC configuration:** - **What to say:** "Administrators can define roles and permissions at [granularity level]" 2. **Show audit log:** - **What to say:** "Every action is logged for compliance and security review" 3. **Show SSO setup:** - **What to say:** "Single sign-on integrates with your existing identity provider" --- ## Objection Handling ### Anticipated Objections | Objection | Response | |-----------|----------| | "[Feature X] looks limited compared to [Competitor]" | "Great observation. Our approach to [Feature X] focuses on [benefit]. What specific aspect of [Feature X] is most important to your workflow? [Then demonstrate or explain how we address the specific need]" | | "How does this handle [edge case]?" | "That's an important scenario. [If supported: Let me show you how that works.] [If not directly: Here's how our customers typically handle that use case...]" | | "What about performance at our scale?" | "Excellent question. Our platform handles [benchmark data]. For your specific scale of [X], we'd recommend [architecture approach]. We can validate this in a POC." | | "The implementation timeline seems long" | "The timeline I shared is for the full solution. We can phase the rollout to deliver value sooner. Phase 1 would give you [core capability] within [X weeks]." | | "What happens if we outgrow this?" | "Our architecture is designed for growth. [Describe scaling approach]. We have customers who have scaled from [X] to [Y] without re-architecture." | ### Recovery Strategies **If the demo breaks:** 1. Stay calm: "Let me switch to [backup environment / backup approach]" 2. Explain what they would have seen 3. Offer to follow up with a recorded walkthrough 4. Pivot to the next demo section **If an unexpected question derails the flow:** 1. Acknowledge: "That's an excellent question" 2. Briefly answer or note it for follow-up 3. Return to the demo flow: "Let me continue with [next section] and we can dive deeper into that during Q&A" **If the audience seems disengaged:** 1. Pause and ask: "Before I continue, is this addressing what you're looking for?" 2. Adjust focus based on their response 3. Skip ahead to the section most relevant to their interests --- ## Post-Demo Actions - [ ] Send thank-you email with recording link (if recorded) - [ ] Share demo environment access credentials (if applicable) - [ ] Send follow-up document addressing unanswered questions - [ ] Schedule next meeting (POC kickoff, technical deep-dive, etc.) - [ ] Update CRM with demo notes and next steps - [ ] Debrief with AE on stakeholder reactions and concerns - [ ] Log key objections and responses for battlecard updates --- ## Notes [Space for real-time notes during the demo] ### Questions Raised 1. [Question] - [Answer / Follow-up needed] 2. [Question] - [Answer / Follow-up needed] ### Feedback Received - [Positive feedback] - [Concerns raised] ### Next Steps Agreed 1. [Action item] - [Owner] - [Date] 2. [Action item] - [Owner] - [Date] FILE:assets/expected_output.json { "rfp_info": { "rfp_name": "Enterprise Data Analytics Platform RFP", "customer": "Acme Financial Services", "due_date": "2026-03-15", "strategic_value": "high", "deal_value": "$450,000 ARR" }, "coverage_summary": { "overall_coverage_percentage": 84.5, "total_requirements": 21, "full": 14, "partial": 3, "planned": 2, "gap": 2, "must_have_gaps": 0 }, "category_scores": { "Data Integration": { "coverage_percentage": 90.0, "requirements_count": 4, "full": 3, "partial": 1, "planned": 0, "gap": 0, "effort_hours": 34 }, "Analytics & Visualization": { "coverage_percentage": 77.8, "requirements_count": 4, "full": 2, "partial": 1, "planned": 1, "gap": 0, "effort_hours": 56 }, "Security & Compliance": { "coverage_percentage": 81.8, "requirements_count": 4, "full": 3, "partial": 0, "planned": 0, "gap": 1, "effort_hours": 50 }, "Performance & Scalability": { "coverage_percentage": 87.5, "requirements_count": 3, "full": 2, "partial": 1, "planned": 0, "gap": 0, "effort_hours": 32 }, "API & Extensibility": { "coverage_percentage": 87.5, "requirements_count": 3, "full": 2, "partial": 0, "planned": 1, "gap": 0, "effort_hours": 38 }, "Support & SLA": { "coverage_percentage": 100.0, "requirements_count": 2, "full": 2, "partial": 0, "planned": 0, "gap": 0, "effort_hours": 4 }, "Deployment": { "coverage_percentage": 0.0, "requirements_count": 1, "full": 0, "partial": 0, "planned": 0, "gap": 1, "effort_hours": 80 } }, "bid_recommendation": { "decision": "BID", "confidence": "high", "overall_coverage_percentage": 84.5, "must_have_gaps": 0, "strategic_value": "high", "reasons": [ "Coverage score 84.5% exceeds 70% threshold" ] }, "gap_analysis": [ { "id": "R-004", "requirement": "Change data capture (CDC) for real-time sync", "category": "Data Integration", "priority": "should-have", "coverage_status": "partial", "severity": "high", "effort_hours": 16, "mitigation": "Document supported CDC sources; provide configuration guide for non-standard sources" }, { "id": "R-007", "requirement": "Natural language query interface for business users", "category": "Analytics & Visualization", "priority": "should-have", "coverage_status": "planned", "severity": "high", "effort_hours": 24, "mitigation": "Share roadmap timeline; offer guided query builder as interim solution" }, { "id": "R-012", "requirement": "HIPAA compliance for healthcare data handling", "category": "Security & Compliance", "priority": "should-have", "coverage_status": "gap", "severity": "high", "effort_hours": 40, "mitigation": "Evaluate HIPAA certification timeline with compliance team; consider data masking as interim" }, { "id": "R-015", "requirement": "Multi-region deployment with data residency controls", "category": "Performance & Scalability", "priority": "should-have", "coverage_status": "partial", "severity": "high", "effort_hours": 20, "mitigation": "Confirm customer region requirements; provide APAC beta access if needed" }, { "id": "R-008", "requirement": "Predictive analytics and ML model integration", "category": "Analytics & Visualization", "priority": "nice-to-have", "coverage_status": "partial", "severity": "low", "effort_hours": 20, "mitigation": "Demonstrate Python integration for custom models; provide example notebooks" }, { "id": "R-018", "requirement": "Custom plugin/extension framework", "category": "API & Extensibility", "priority": "nice-to-have", "coverage_status": "planned", "severity": "low", "effort_hours": 30, "mitigation": "Current API extensibility covers most use cases; plugin framework will expand options" }, { "id": "R-021", "requirement": "On-premise deployment option", "category": "Deployment", "priority": "nice-to-have", "coverage_status": "gap", "severity": "low", "effort_hours": 80, "mitigation": "Position cloud-first architecture benefits; offer VPC deployment as alternative" } ], "risk_assessment": [ { "risk": "High customization effort", "impact": "high", "description": "230 hours estimated for non-full requirements", "mitigation": "Evaluate resource availability and timeline feasibility before committing" } ], "effort_estimate": { "total_hours": 294, "gap_closure_hours": 230, "full_coverage_hours": 64 }, "requirements_detail": [ { "id": "R-001", "requirement": "Real-time data ingestion from multiple sources (APIs, databases, streaming)", "category": "Data Integration", "priority": "must-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 3.0, "weighted_score": 3.0, "max_weighted": 3.0, "effort_hours": 8, "notes": "Native connectors for 200+ data sources", "mitigation": "" }, { "id": "R-002", "requirement": "Support for SQL and NoSQL data sources", "category": "Data Integration", "priority": "must-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 3.0, "weighted_score": 3.0, "max_weighted": 3.0, "effort_hours": 4, "notes": "Supports PostgreSQL, MySQL, MongoDB, Cassandra, and more", "mitigation": "" }, { "id": "R-003", "requirement": "Automated ETL pipeline creation with visual designer", "category": "Data Integration", "priority": "should-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 2.0, "weighted_score": 2.0, "max_weighted": 2.0, "effort_hours": 6, "notes": "Drag-and-drop pipeline builder included", "mitigation": "" }, { "id": "R-004", "requirement": "Change data capture (CDC) for real-time sync", "category": "Data Integration", "priority": "should-have", "coverage_status": "partial", "coverage_score": 0.5, "weight": 2.0, "weighted_score": 1.0, "max_weighted": 2.0, "effort_hours": 16, "notes": "CDC supported for major databases; some require custom configuration", "mitigation": "Document supported CDC sources; provide configuration guide for non-standard sources" }, { "id": "R-005", "requirement": "Interactive dashboard creation with drag-and-drop", "category": "Analytics & Visualization", "priority": "must-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 3.0, "weighted_score": 3.0, "max_weighted": 3.0, "effort_hours": 4, "notes": "Full drag-and-drop dashboard builder with 50+ chart types", "mitigation": "" }, { "id": "R-006", "requirement": "Embedded analytics with white-labeling support", "category": "Analytics & Visualization", "priority": "must-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 3.0, "weighted_score": 3.0, "max_weighted": 3.0, "effort_hours": 8, "notes": "Full embedding SDK with CSS customization", "mitigation": "" }, { "id": "R-007", "requirement": "Natural language query interface for business users", "category": "Analytics & Visualization", "priority": "should-have", "coverage_status": "planned", "coverage_score": 0.25, "weight": 2.0, "weighted_score": 0.5, "max_weighted": 2.0, "effort_hours": 24, "notes": "NLQ feature on roadmap for Q3 2026", "mitigation": "Share roadmap timeline; offer guided query builder as interim solution" }, { "id": "R-008", "requirement": "Predictive analytics and ML model integration", "category": "Analytics & Visualization", "priority": "nice-to-have", "coverage_status": "partial", "coverage_score": 0.5, "weight": 1.0, "weighted_score": 0.5, "max_weighted": 1.0, "effort_hours": 20, "notes": "Python/R integration available; no built-in ML models", "mitigation": "Demonstrate Python integration for custom models; provide example notebooks" }, { "id": "R-009", "requirement": "Role-based access control (RBAC) with row-level security", "category": "Security & Compliance", "priority": "must-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 3.0, "weighted_score": 3.0, "max_weighted": 3.0, "effort_hours": 6, "notes": "Granular RBAC with row-level and column-level security", "mitigation": "" }, { "id": "R-010", "requirement": "SOC 2 Type II certification", "category": "Security & Compliance", "priority": "must-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 3.0, "weighted_score": 3.0, "max_weighted": 3.0, "effort_hours": 2, "notes": "Current SOC 2 Type II report available upon NDA", "mitigation": "" }, { "id": "R-011", "requirement": "Data encryption at rest and in transit (AES-256, TLS 1.3)", "category": "Security & Compliance", "priority": "must-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 3.0, "weighted_score": 3.0, "max_weighted": 3.0, "effort_hours": 2, "notes": "AES-256 at rest, TLS 1.3 in transit, customer-managed keys supported", "mitigation": "" }, { "id": "R-012", "requirement": "HIPAA compliance for healthcare data handling", "category": "Security & Compliance", "priority": "should-have", "coverage_status": "gap", "coverage_score": 0.0, "weight": 2.0, "weighted_score": 0.0, "max_weighted": 2.0, "effort_hours": 40, "notes": "HIPAA BAA not currently offered", "mitigation": "Evaluate HIPAA certification timeline with compliance team; consider data masking as interim" }, { "id": "R-013", "requirement": "Horizontal scaling to handle 10B+ rows", "category": "Performance & Scalability", "priority": "must-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 3.0, "weighted_score": 3.0, "max_weighted": 3.0, "effort_hours": 8, "notes": "Distributed query engine scales to 50B+ rows", "mitigation": "" }, { "id": "R-014", "requirement": "Sub-second query response for cached dashboards", "category": "Performance & Scalability", "priority": "must-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 3.0, "weighted_score": 3.0, "max_weighted": 3.0, "effort_hours": 4, "notes": "Intelligent caching layer with <500ms p95 for cached queries", "mitigation": "" }, { "id": "R-015", "requirement": "Multi-region deployment with data residency controls", "category": "Performance & Scalability", "priority": "should-have", "coverage_status": "partial", "coverage_score": 0.5, "weight": 2.0, "weighted_score": 1.0, "max_weighted": 2.0, "effort_hours": 20, "notes": "US and EU regions available; APAC region in beta", "mitigation": "Confirm customer region requirements; provide APAC beta access if needed" }, { "id": "R-016", "requirement": "RESTful API with comprehensive documentation", "category": "API & Extensibility", "priority": "must-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 3.0, "weighted_score": 3.0, "max_weighted": 3.0, "effort_hours": 4, "notes": "Full REST API with OpenAPI spec and interactive documentation", "mitigation": "" }, { "id": "R-017", "requirement": "Webhook support for event-driven workflows", "category": "API & Extensibility", "priority": "should-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 2.0, "weighted_score": 2.0, "max_weighted": 2.0, "effort_hours": 4, "notes": "Webhook support for 30+ event types", "mitigation": "" }, { "id": "R-018", "requirement": "Custom plugin/extension framework", "category": "API & Extensibility", "priority": "nice-to-have", "coverage_status": "planned", "coverage_score": 0.25, "weight": 1.0, "weighted_score": 0.25, "max_weighted": 1.0, "effort_hours": 30, "notes": "Plugin framework on roadmap for Q4 2026", "mitigation": "Current API extensibility covers most use cases; plugin framework will expand options" }, { "id": "R-019", "requirement": "24/7 enterprise support with 1-hour critical response time", "category": "Support & SLA", "priority": "must-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 3.0, "weighted_score": 3.0, "max_weighted": 3.0, "effort_hours": 2, "notes": "Premium support tier includes 24/7 coverage with 30-min critical response SLA", "mitigation": "" }, { "id": "R-020", "requirement": "Dedicated customer success manager", "category": "Support & SLA", "priority": "should-have", "coverage_status": "full", "coverage_score": 1.0, "weight": 2.0, "weighted_score": 2.0, "max_weighted": 2.0, "effort_hours": 2, "notes": "Included in Enterprise tier", "mitigation": "" }, { "id": "R-021", "requirement": "On-premise deployment option", "category": "Deployment", "priority": "nice-to-have", "coverage_status": "gap", "coverage_score": 0.0, "weight": 1.0, "weighted_score": 0.0, "max_weighted": 1.0, "effort_hours": 80, "notes": "Cloud-only platform; no on-premise offering", "mitigation": "Position cloud-first architecture benefits; offer VPC deployment as alternative" } ] } FILE:assets/poc_scorecard_template.md # POC Evaluation Scorecard ## Scorecard Information | Field | Value | |-------|-------| | POC Name | [POC Name] | | Customer | [Customer Name] | | Vendor/Product | [Product Name] | | Evaluation Period | [Start Date] - [End Date] | | Evaluated By | [Names and Roles] | | Date Completed | [Date] | --- ## Scoring Scale | Score | Label | Definition | |-------|-------|------------| | 5 | Exceeds | Superior capability; exceeds requirements with notable strengths | | 4 | Meets | Full capability; meets all requirements with no significant gaps | | 3 | Partial | Acceptable capability; minor gaps that can be addressed | | 2 | Below | Below expectations; significant gaps that impact value | | 1 | Fails | Does not meet requirements; critical gaps | | N/A | Not Evaluated | Not tested during this POC | --- ## Evaluation Categories ### 1. Functionality (Weight: 30%) | Criterion | Score (1-5) | Evidence / Notes | |-----------|-------------|-----------------| | Core feature completeness | | | | Use case coverage | | | | Customization flexibility | | | | Workflow automation | | | | Data handling and transformation | | | | Reporting and analytics | | | **Category Score:** ___/5.0 **Category Notes:** [Summary of functionality evaluation, key strengths and gaps] --- ### 2. Performance (Weight: 20%) | Criterion | Score (1-5) | Evidence / Notes | |-----------|-------------|-----------------| | Response time under expected load | | | | Response time under peak load | | | | Throughput capacity | | | | Scalability characteristics | | | | Resource utilization | | | | Batch processing performance | | | **Category Score:** ___/5.0 **Category Notes:** [Summary of performance evaluation, benchmark results] --- ### 3. Integration (Weight: 20%) | Criterion | Score (1-5) | Evidence / Notes | |-----------|-------------|-----------------| | API completeness and documentation | | | | Data migration ease | | | | Third-party connector availability | | | | Authentication/SSO integration | | | | Real-time sync reliability | | | | Error handling and recovery | | | **Category Score:** ___/5.0 **Category Notes:** [Summary of integration evaluation, systems tested] --- ### 4. Usability (Weight: 15%) | Criterion | Score (1-5) | Evidence / Notes | |-----------|-------------|-----------------| | User interface intuitiveness | | | | Learning curve assessment | | | | Documentation quality | | | | Admin console functionality | | | | Mobile experience | | | | Accessibility compliance | | | **Category Score:** ___/5.0 **Category Notes:** [Summary of usability evaluation, user feedback] --- ### 5. Support (Weight: 15%) | Criterion | Score (1-5) | Evidence / Notes | |-----------|-------------|-----------------| | Technical support responsiveness | | | | Knowledge base quality | | | | Training resources availability | | | | Community and ecosystem | | | | Issue resolution speed | | | | Proactive engagement quality | | | **Category Score:** ___/5.0 **Category Notes:** [Summary of support evaluation during POC] --- ## Score Summary | Category | Weight | Score | Weighted Score | |----------|--------|-------|----------------| | Functionality | 30% | ___/5.0 | ___ | | Performance | 20% | ___/5.0 | ___ | | Integration | 20% | ___/5.0 | ___ | | Usability | 15% | ___/5.0 | ___ | | Support | 15% | ___/5.0 | ___ | | **Overall** | **100%** | | **___/5.0** | ### Decision Thresholds | Weighted Average | Decision | |-----------------|----------| | >= 4.0 | **Strong Pass** - Proceed to procurement | | 3.5 - 3.9 | **Pass** - Proceed with noted conditions | | 3.0 - 3.4 | **Conditional** - Requires further evaluation | | < 3.0 | **Fail** - Does not meet requirements | --- ## Success Criteria Results | # | Criterion | Priority | Target | Actual | Pass/Fail | |---|-----------|----------|--------|--------|-----------| | 1 | [Criterion 1] | Must-Have | [Target] | [Result] | [ ] | | 2 | [Criterion 2] | Must-Have | [Target] | [Result] | [ ] | | 3 | [Criterion 3] | Must-Have | [Target] | [Result] | [ ] | | 4 | [Criterion 4] | Should-Have | [Target] | [Result] | [ ] | | 5 | [Criterion 5] | Should-Have | [Target] | [Result] | [ ] | | 6 | [Criterion 6] | Nice-to-Have | [Target] | [Result] | [ ] | **Must-Have Pass Rate:** ___/% **Overall Pass Rate:** ___/% --- ## Issues Log | # | Issue | Severity | Status | Resolution | Impact on Score | |---|-------|----------|--------|------------|----------------| | 1 | [Issue] | [Critical/High/Medium/Low] | [Open/Resolved] | [Resolution] | [Category affected] | | 2 | [Issue] | [Critical/High/Medium/Low] | [Open/Resolved] | [Resolution] | [Category affected] | --- ## Stakeholder Feedback ### [Stakeholder Name 1] - [Role] **Rating:** ___/5 **Comments:** [Feedback] ### [Stakeholder Name 2] - [Role] **Rating:** ___/5 **Comments:** [Feedback] ### [Stakeholder Name 3] - [Role] **Rating:** ___/5 **Comments:** [Feedback] --- ## Recommendation ### Decision: [ ] GO / [ ] CONDITIONAL GO / [ ] NO-GO **Rationale:** [2-3 paragraphs explaining the recommendation based on scorecard results, success criteria outcomes, stakeholder feedback, and overall evaluation] **Conditions (if Conditional GO):** 1. [Condition 1 that must be met before proceeding] 2. [Condition 2 that must be met before proceeding] **Key Strengths:** 1. [Strength 1] 2. [Strength 2] 3. [Strength 3] **Key Concerns:** 1. [Concern 1 with proposed mitigation] 2. [Concern 2 with proposed mitigation] **Next Steps:** 1. [Action item] - [Owner] - [Date] 2. [Action item] - [Owner] - [Date] 3. [Action item] - [Owner] - [Date] --- ## Sign-Off | Role | Name | Signature | Date | |------|------|-----------|------| | Technical Evaluator | | | | | Business Sponsor | | | | | Decision Maker | | | | | Sales Engineer | | | | FILE:assets/sample_rfp_data.json { "rfp_name": "Enterprise Data Analytics Platform RFP", "customer": "Acme Financial Services", "due_date": "2026-03-15", "deal_value": "$450,000 ARR", "strategic_value": "high", "requirements": [ { "id": "R-001", "requirement": "Real-time data ingestion from multiple sources (APIs, databases, streaming)", "category": "Data Integration", "priority": "must-have", "coverage_status": "full", "effort_hours": 8, "notes": "Native connectors for 200+ data sources", "mitigation": "" }, { "id": "R-002", "requirement": "Support for SQL and NoSQL data sources", "category": "Data Integration", "priority": "must-have", "coverage_status": "full", "effort_hours": 4, "notes": "Supports PostgreSQL, MySQL, MongoDB, Cassandra, and more", "mitigation": "" }, { "id": "R-003", "requirement": "Automated ETL pipeline creation with visual designer", "category": "Data Integration", "priority": "should-have", "coverage_status": "full", "effort_hours": 6, "notes": "Drag-and-drop pipeline builder included", "mitigation": "" }, { "id": "R-004", "requirement": "Change data capture (CDC) for real-time sync", "category": "Data Integration", "priority": "should-have", "coverage_status": "partial", "effort_hours": 16, "notes": "CDC supported for major databases; some require custom configuration", "mitigation": "Document supported CDC sources; provide configuration guide for non-standard sources" }, { "id": "R-005", "requirement": "Interactive dashboard creation with drag-and-drop", "category": "Analytics & Visualization", "priority": "must-have", "coverage_status": "full", "effort_hours": 4, "notes": "Full drag-and-drop dashboard builder with 50+ chart types", "mitigation": "" }, { "id": "R-006", "requirement": "Embedded analytics with white-labeling support", "category": "Analytics & Visualization", "priority": "must-have", "coverage_status": "full", "effort_hours": 8, "notes": "Full embedding SDK with CSS customization", "mitigation": "" }, { "id": "R-007", "requirement": "Natural language query interface for business users", "category": "Analytics & Visualization", "priority": "should-have", "coverage_status": "planned", "effort_hours": 24, "notes": "NLQ feature on roadmap for Q3 2026", "mitigation": "Share roadmap timeline; offer guided query builder as interim solution" }, { "id": "R-008", "requirement": "Predictive analytics and ML model integration", "category": "Analytics & Visualization", "priority": "nice-to-have", "coverage_status": "partial", "effort_hours": 20, "notes": "Python/R integration available; no built-in ML models", "mitigation": "Demonstrate Python integration for custom models; provide example notebooks" }, { "id": "R-009", "requirement": "Role-based access control (RBAC) with row-level security", "category": "Security & Compliance", "priority": "must-have", "coverage_status": "full", "effort_hours": 6, "notes": "Granular RBAC with row-level and column-level security", "mitigation": "" }, { "id": "R-010", "requirement": "SOC 2 Type II certification", "category": "Security & Compliance", "priority": "must-have", "coverage_status": "full", "effort_hours": 2, "notes": "Current SOC 2 Type II report available upon NDA", "mitigation": "" }, { "id": "R-011", "requirement": "Data encryption at rest and in transit (AES-256, TLS 1.3)", "category": "Security & Compliance", "priority": "must-have", "coverage_status": "full", "effort_hours": 2, "notes": "AES-256 at rest, TLS 1.3 in transit, customer-managed keys supported", "mitigation": "" }, { "id": "R-012", "requirement": "HIPAA compliance for healthcare data handling", "category": "Security & Compliance", "priority": "should-have", "coverage_status": "gap", "effort_hours": 40, "notes": "HIPAA BAA not currently offered", "mitigation": "Evaluate HIPAA certification timeline with compliance team; consider data masking as interim" }, { "id": "R-013", "requirement": "Horizontal scaling to handle 10B+ rows", "category": "Performance & Scalability", "priority": "must-have", "coverage_status": "full", "effort_hours": 8, "notes": "Distributed query engine scales to 50B+ rows", "mitigation": "" }, { "id": "R-014", "requirement": "Sub-second query response for cached dashboards", "category": "Performance & Scalability", "priority": "must-have", "coverage_status": "full", "effort_hours": 4, "notes": "Intelligent caching layer with <500ms p95 for cached queries", "mitigation": "" }, { "id": "R-015", "requirement": "Multi-region deployment with data residency controls", "category": "Performance & Scalability", "priority": "should-have", "coverage_status": "partial", "effort_hours": 20, "notes": "US and EU regions available; APAC region in beta", "mitigation": "Confirm customer region requirements; provide APAC beta access if needed" }, { "id": "R-016", "requirement": "RESTful API with comprehensive documentation", "category": "API & Extensibility", "priority": "must-have", "coverage_status": "full", "effort_hours": 4, "notes": "Full REST API with OpenAPI spec and interactive documentation", "mitigation": "" }, { "id": "R-017", "requirement": "Webhook support for event-driven workflows", "category": "API & Extensibility", "priority": "should-have", "coverage_status": "full", "effort_hours": 4, "notes": "Webhook support for 30+ event types", "mitigation": "" }, { "id": "R-018", "requirement": "Custom plugin/extension framework", "category": "API & Extensibility", "priority": "nice-to-have", "coverage_status": "planned", "effort_hours": 30, "notes": "Plugin framework on roadmap for Q4 2026", "mitigation": "Current API extensibility covers most use cases; plugin framework will expand options" }, { "id": "R-019", "requirement": "24/7 enterprise support with 1-hour critical response time", "category": "Support & SLA", "priority": "must-have", "coverage_status": "full", "effort_hours": 2, "notes": "Premium support tier includes 24/7 coverage with 30-min critical response SLA", "mitigation": "" }, { "id": "R-020", "requirement": "Dedicated customer success manager", "category": "Support & SLA", "priority": "should-have", "coverage_status": "full", "effort_hours": 2, "notes": "Included in Enterprise tier", "mitigation": "" }, { "id": "R-021", "requirement": "On-premise deployment option", "category": "Deployment", "priority": "nice-to-have", "coverage_status": "gap", "effort_hours": 80, "notes": "Cloud-only platform; no on-premise offering", "mitigation": "Position cloud-first architecture benefits; offer VPC deployment as alternative" } ] } FILE:assets/technical_proposal_template.md # Technical Proposal Template ## Document Information | Field | Value | |-------|-------| | Customer | [Customer Name] | | Opportunity | [Opportunity Name / RFP Reference] | | Prepared By | [Sales Engineer Name] | | Date | [Date] | | Version | [Version Number] | | Classification | [Confidential / Internal] | --- ## 1. Executive Summary ### Business Context [2-3 paragraphs summarizing the customer's business challenges and strategic objectives that this solution addresses. Focus on business outcomes, not technical features.] ### Proposed Solution [1-2 paragraphs describing the solution at a high level, emphasizing how it addresses the specific challenges identified above.] ### Key Value Propositions 1. **[Value 1]:** [Quantified benefit, e.g., "Reduce reporting time by 60%"] 2. **[Value 2]:** [Quantified benefit] 3. **[Value 3]:** [Quantified benefit] ### Recommended Approach [Brief overview of the implementation approach, timeline, and key milestones.] --- ## 2. Requirements Summary ### Coverage Overview | Category | Requirements | Full | Partial | Planned | Gap | Coverage | |----------|-------------|------|---------|---------|-----|----------| | [Category 1] | [N] | [N] | [N] | [N] | [N] | [X%] | | [Category 2] | [N] | [N] | [N] | [N] | [N] | [X%] | | **Total** | **[N]** | **[N]** | **[N]** | **[N]** | **[N]** | **[X%]** | ### Key Differentiators 1. [Differentiator 1 with brief explanation] 2. [Differentiator 2 with brief explanation] 3. [Differentiator 3 with brief explanation] ### Gap Mitigation Plan | Gap | Priority | Mitigation Strategy | Timeline | |-----|----------|-------------------|----------| | [Gap 1] | [Must/Should/Nice] | [Strategy] | [Date] | | [Gap 2] | [Must/Should/Nice] | [Strategy] | [Date] | --- ## 3. Solution Architecture ### Architecture Overview [High-level architecture description. Include or reference an architecture diagram.] ``` [ASCII architecture diagram or reference to attached diagram] Example: +------------------+ +------------------+ +------------------+ | Data Sources | --> | Our Platform | --> | Delivery | | - System A | | - Ingestion | | - Dashboards | | - System B | | - Processing | | - API | | - System C | | - Analytics | | - Exports | +------------------+ +------------------+ +------------------+ | +------------------+ | Management | | - Security | | - Monitoring | | - Admin | +------------------+ ``` ### Component Details #### [Component 1] - **Purpose:** [What this component does] - **Technology:** [Underlying technology] - **Scaling:** [How it scales] - **Availability:** [HA/DR approach] #### [Component 2] - **Purpose:** [What this component does] - **Technology:** [Underlying technology] - **Scaling:** [How it scales] - **Availability:** [HA/DR approach] ### Integration Architecture | Integration Point | Protocol | Direction | Frequency | Authentication | |-------------------|----------|-----------|-----------|---------------| | [System A] | REST API | Inbound | Real-time | OAuth 2.0 | | [System B] | JDBC | Inbound | Batch (hourly) | Service Account | | [System C] | Webhook | Outbound | Event-driven | API Key | ### Security Architecture - **Authentication:** [SSO, SAML, OAuth, etc.] - **Authorization:** [RBAC, row-level security, etc.] - **Encryption:** [At rest, in transit, key management] - **Compliance:** [SOC 2, GDPR, HIPAA, etc.] - **Network:** [VPC, firewall, IP restrictions] --- ## 4. Implementation Plan ### Phase Overview | Phase | Duration | Focus | Deliverables | |-------|----------|-------|-------------| | Phase 1: Foundation | [X weeks] | Environment setup, core configuration | Working environment, admin access | | Phase 2: Core Implementation | [X weeks] | Primary use cases, integrations | [Deliverables] | | Phase 3: Advanced Features | [X weeks] | Advanced scenarios, optimization | [Deliverables] | | Phase 4: Go-Live | [X weeks] | Testing, training, cutover | Production deployment | ### Detailed Timeline ``` Week 1-2: [Phase 1 - Foundation] - Environment provisioning - Security configuration - Data source connectivity Week 3-6: [Phase 2 - Core Implementation] - Use case 1 implementation - Use case 2 implementation - Integration testing Week 7-8: [Phase 3 - Advanced Features] - Advanced analytics - Custom workflows - Performance optimization Week 9-10: [Phase 4 - Go-Live] - User acceptance testing - Training sessions - Production cutover - Post-launch support ``` ### Resource Requirements | Role | Hours | Phase(s) | Provider | |------|-------|----------|----------| | Solutions Architect | [X] | All | [Vendor] | | Implementation Engineer | [X] | 1-3 | [Vendor] | | Project Manager | [X] | All | [Vendor] | | Customer IT Admin | [X] | 1, 4 | [Customer] | | Customer Business Lead | [X] | 2-4 | [Customer] | ### Training Plan | Audience | Format | Duration | Content | |----------|--------|----------|---------| | Administrators | Workshop | [X hours] | Configuration, security, monitoring | | Power Users | Workshop | [X hours] | Advanced features, reporting, automation | | End Users | Webinar | [X hours] | Core workflows, self-service analytics | --- ## 5. Risk Mitigation | Risk | Probability | Impact | Mitigation | |------|------------|--------|------------| | [Risk 1] | [H/M/L] | [H/M/L] | [Strategy] | | [Risk 2] | [H/M/L] | [H/M/L] | [Strategy] | | [Risk 3] | [H/M/L] | [H/M/L] | [Strategy] | --- ## 6. Commercial Summary ### Pricing Overview | Component | Annual Cost | |-----------|------------| | Platform License | $[X] | | Implementation Services | $[X] | | Training | $[X] | | Premium Support | $[X] | | **Total Year 1** | **$[X]** | | **Annual Renewal** | **$[X]** | ### ROI Projection | Metric | Current State | With Solution | Improvement | |--------|--------------|---------------|-------------| | [Metric 1] | [Value] | [Value] | [%] | | [Metric 2] | [Value] | [Value] | [%] | | [Metric 3] | [Value] | [Value] | [%] | **Estimated payback period:** [X months] --- ## 7. Next Steps 1. [Next step 1 with owner and date] 2. [Next step 2 with owner and date] 3. [Next step 3 with owner and date] --- ## Appendices ### A. Detailed Compliance Matrix [Reference to full requirement-by-requirement response] ### B. Reference Customers [2-3 relevant customer references with industry, use case, and outcomes] ### C. Architecture Diagrams [Detailed architecture diagrams] ### D. Product Roadmap (Relevant Items) [Roadmap items relevant to this proposal with estimated delivery dates] FILE:references/competitive-positioning-framework.md # Competitive Positioning Framework A comprehensive guide for Sales Engineers to analyze competitors, build battlecards, handle objections, and position for wins. ## Competitive Analysis Methodology ### 1. Intelligence Gathering **Primary Sources:** - Competitor product documentation and release notes - Analyst reports (Gartner, Forrester, IDC) - Customer feedback from win/loss reviews - Industry conferences and webinars - Public case studies and testimonials - Open-source repositories and API documentation **Secondary Sources:** - Glassdoor reviews (engineering culture, product direction) - Job postings (technology stack, expansion areas) - Patent filings (future direction signals) - Social media and community forums - Partner ecosystem announcements ### 2. Feature Comparison Best Practices **Feature Scoring Scale:** | Score | Label | Definition | |-------|-------|------------| | 3 | Full | Complete, production-ready feature support | | 2 | Partial | Feature exists but with limitations or caveats | | 1 | Limited | Minimal implementation, significant gaps | | 0 | None | Feature not available | **Comparison Categories:** Organize features into weighted categories that reflect customer priorities: | Category | Typical Weight | What to Evaluate | |----------|---------------|------------------| | Core Functionality | 25-35% | Primary use case coverage | | Integration & API | 15-25% | Ecosystem connectivity | | Security & Compliance | 15-20% | Enterprise readiness | | Scalability & Performance | 10-20% | Growth capacity | | Usability & UX | 10-15% | Time to value | | Support & Services | 5-10% | Vendor partnership quality | **Weighting Guidelines:** - Adjust weights based on the specific customer's priorities - Security-sensitive industries (healthcare, finance) should weight compliance higher - High-growth companies should weight scalability higher - Enterprise deals should weight integration and support higher ### 3. Differentiator Identification A differentiator is a feature or capability where your product scores highest among all compared products. Strong differentiators have these properties: - **Unique:** Only your product offers this capability - **Valuable:** Customers care about this capability - **Defensible:** Not easily replicated by competitors - **Demonstrable:** Can be shown in a demo or POC **Differentiator Categories:** | Type | Description | Example | |------|-------------|---------| | Feature Differentiator | Unique product capability | Native ML-powered anomaly detection | | Architecture Differentiator | Fundamental design advantage | Multi-tenant with data isolation | | Ecosystem Differentiator | Partner or integration advantage | 200+ native integrations | | Service Differentiator | Support or engagement model | Dedicated SE throughout contract | | Economic Differentiator | Pricing or TCO advantage | Usage-based pricing with no minimums | ### 4. Vulnerability Assessment Vulnerabilities are features where competitors score higher than your product. Address vulnerabilities proactively: **Vulnerability Response Strategies:** 1. **Acknowledge and redirect:** Confirm the gap, then pivot to your strength areas 2. **Reframe the requirement:** Show why the customer's real need is better met differently 3. **Demonstrate workaround:** Show how existing capabilities address the underlying need 4. **Commit to roadmap:** Provide a credible timeline for native support 5. **Partner solution:** Identify an integration partner that fills the gap ## Objection Handling ### Common Technical Objections #### "Your product lacks [Feature X]" **Response Framework:** 1. Acknowledge: "You're right that [Feature X] is not a standalone feature today." 2. Explore: "Help me understand the specific use case you need [Feature X] for." 3. Redirect: "Our approach to solving that is [alternative], which actually provides [benefit]." 4. Evidence: "Customer [reference] had the same concern and found [outcome]." #### "Competitor [Y] has better [Capability]" **Response Framework:** 1. Acknowledge: "I understand [Competitor Y] has invested in [Capability]." 2. Qualify: "Can you share what specific aspects of [Capability] are most important?" 3. Differentiate: "While they focus on [approach], we take a different approach with [our method] because [reason]." 4. Quantify: "The practical difference in real-world usage is [metric/evidence]." #### "Your product is too expensive" **Response Framework:** 1. Acknowledge: "I appreciate you sharing that concern." 2. Reframe: "Let's look at total cost of ownership rather than license cost alone." 3. Quantify: "When you factor in [implementation, training, maintenance, time-to-value], the TCO comparison shows..." 4. Value: "Based on our analysis, the ROI timeline is [X months], delivering [Y value]." #### "We're concerned about vendor lock-in" **Response Framework:** 1. Acknowledge: "That's a smart concern for any technology investment." 2. Evidence: "Our architecture uses [open standards, APIs, data portability features]." 3. Demonstrate: "Here's how data export and migration work [show the feature]." 4. Reference: "We can connect you with customers who evaluated this exact concern." ### Objection Handling Principles 1. **Never disparage competitors.** Focus on your strengths, not their weaknesses. 2. **Ask questions first.** Understand the real concern behind the objection. 3. **Use evidence.** Reference customers, benchmarks, and demonstrations. 4. **Be honest about gaps.** Credibility is your most valuable asset. 5. **Redirect to value.** Connect every response back to business outcomes. ## Win/Loss Analysis ### Post-Decision Review Process **Timing:** Conduct within 2 weeks of the decision for accurate recall. **Interview Questions (for wins):** 1. What was the deciding factor in choosing us? 2. Which features or capabilities were most compelling? 3. How did our demo/POC compare to alternatives? 4. What concerns did you have that were resolved during the process? 5. What could we have done better in the evaluation process? **Interview Questions (for losses):** 1. What was the primary reason for choosing the competitor? 2. Were there specific requirements we did not meet? 3. How did our demo/POC compare to the winning vendor? 4. What would have changed your decision? 5. Would you consider us for future evaluations? ### Win/Loss Data Tracking | Data Point | Purpose | |-----------|---------| | Deal size | Pattern analysis by segment | | Industry | Vertical-specific insights | | Competitor | Head-to-head record | | Decision factors | Feature priority validation | | Sales cycle length | Process efficiency | | Stakeholder roles | Engagement strategy | | Technical requirements | Capability gap tracking | | POC outcome | POC process improvement | ### Analysis Dimensions 1. **By Competitor:** Win rate per competitor, common objections, feature gaps 2. **By Segment:** Enterprise vs mid-market vs SMB patterns 3. **By Industry:** Vertical-specific win factors 4. **By Deal Size:** Large vs small deal dynamics 5. **By Feature Category:** Which capabilities drive wins vs losses ## Battlecard Creation ### Battlecard Structure **Page 1: Quick Reference** - Competitor overview (company size, funding, market position) - Key strengths (top 3) - Key weaknesses (top 3) - Ideal customer profile for the competitor - Our win rate against this competitor **Page 2: Feature Comparison** - Category-by-category comparison (summary view) - Top differentiators (features where we lead) - Top vulnerabilities (features where they lead) - Parity features (features at same level) **Page 3: Talk Track** - Opening positioning statement - Discovery questions that expose competitor weaknesses - Objection responses for their key strengths - Proof points (customer references, benchmarks, case studies) - Trap-setting questions for demos and POCs **Page 4: Win Strategies** - Recommended evaluation criteria that favor our strengths - Demo scenarios that highlight our differentiators - POC success criteria that align with our capabilities - Pricing and packaging positioning - Stakeholder engagement strategy ### Battlecard Maintenance - **Monthly review:** Update feature scores based on new releases - **Quarterly refresh:** Incorporate win/loss analysis findings - **Trigger-based update:** Major competitor release, pricing change, or acquisition ## Competitive Positioning During Evaluations ### Evaluation Stage Tactics | Stage | Tactic | |-------|--------| | Discovery | Ask questions that expose competitor weaknesses | | Demo | Lead with differentiators, show end-to-end workflows | | POC | Define success criteria aligned with your strengths | | Proposal | Quantify TCO advantage, emphasize implementation risk | | Negotiation | Leverage competitive urgency, offer migration assistance | ### Influencing Evaluation Criteria The sales engineer's most impactful opportunity is shaping the evaluation criteria before the formal process begins: 1. **Map criteria to strengths:** Propose evaluation categories where you excel 2. **Weight appropriately:** Ensure critical categories (where you lead) carry higher weight 3. **Define metrics:** Specific, measurable criteria favor the more capable product 4. **Include non-obvious criteria:** Total cost of ownership, time-to-value, ecosystem breadth --- **Last Updated:** February 2026 FILE:references/poc-best-practices.md # Proof of Concept (POC) Best Practices A comprehensive guide for Sales Engineers planning, executing, and evaluating proof-of-concept engagements. ## POC Planning Methodology ### 1. Pre-POC Qualification Not every deal warrants a POC. Qualify before committing resources: **POC-Worthy Indicators:** - Deal value justifies 80-200+ hours of SE and engineering time - Customer has an identified champion who will actively participate - Clear decision timeline with POC as a defined evaluation step - Budget is allocated or allocation process is underway - Technical stakeholders are available for the evaluation period **POC Red Flags:** - "Free trial" request with no commitment to evaluate - No identified decision-maker or budget owner - Competitor has already been selected; POC is for validation only - Customer expects production-grade environment for extended period - No defined success criteria or evaluation framework ### 2. Scope Definition The most critical success factor is a well-defined scope. An uncontrolled scope leads to extended timelines, unmet expectations, and lost deals. **Scope Elements:** - **Use cases:** 3-5 specific scenarios to validate (not "everything") - **Integrations:** Which systems must connect during the POC - **Data:** What data will be used (sample, synthetic, production subset) - **Users:** Who will access the POC environment and in what roles - **Duration:** Fixed timeline with clear milestones - **Success criteria:** Measurable, objective criteria for each use case **Scope Control Tactics:** - Document scope in writing with customer sign-off - Define what is explicitly out of scope - Create a change request process for scope additions - Set a maximum number of use cases per complexity tier ### 3. Timeline Planning **Standard 5-Week Framework:** | Week | Phase | Focus | Key Activities | |------|-------|-------|---------------| | 1 | Setup | Foundation | Environment, data, access, kickoff | | 2-3 | Core Testing | Validation | Primary use cases, integrations, workflows | | 4 | Advanced Testing | Edge cases | Performance, security, scale, administration | | 5 | Evaluation | Decision | Scorecard, review, recommendation | **Timeline Adjustments by Complexity:** | Complexity | Duration | Use Cases | Integrations | |-----------|----------|-----------|-------------| | Low | 3 weeks | 2-3 | 0-1 | | Medium | 5 weeks | 3-5 | 2-3 | | High | 6-8 weeks | 5-8 | 4+ | **Timeline Rules:** - Never exceed 8 weeks. Longer POCs lose momentum and stakeholder attention. - Front-load the most impressive capabilities to build early momentum. - Schedule stakeholder checkpoints at the end of each phase. - Build 20% buffer into each phase for unexpected issues. ### 4. Resource Planning **SE Allocation:** | Activity | Hours/Week (Medium Complexity) | |----------|-------------------------------| | Environment setup and configuration | 15-20 (Week 1 only) | | Use case execution and testing | 20-25 | | Stakeholder communication | 3-5 | | Documentation and reporting | 3-5 | | Issue resolution | 5-8 | **Engineering Support:** - Allocate dedicated engineering support for complex integrations - Establish an escalation path for blocking issues - Pre-schedule engineering availability during Core Testing phase - Request customer IT support for integration access and credentials **Customer Resources:** - Technical sponsor for daily communication - Business stakeholders for use case validation - IT/Security for environment access and compliance review - End users for usability feedback (if applicable) ## Success Criteria Definition ### Writing Effective Success Criteria Each criterion must be: - **Specific:** Clearly defined with no ambiguity - **Measurable:** Quantifiable metric or clear pass/fail - **Agreed:** Documented and signed off by both parties - **Relevant:** Tied to a business outcome or technical requirement - **Time-bound:** Evaluated within the POC timeline ### Success Criteria Categories **Functionality Criteria:** - "System processes [X] transactions per hour without errors" - "Workflow automation reduces manual steps from [Y] to [Z]" - "Report generation completes within [N] seconds for [M] records" - "All [X] defined use cases completed successfully" **Performance Criteria:** - "API response time <200ms at p95 under [N] concurrent users" - "Batch processing completes [X] records in under [Y] minutes" - "System maintains performance with [N]x expected data volume" **Integration Criteria:** - "Bidirectional sync with [System X] operates within [Y] minute latency" - "SSO integration with [IdP] supports all required authentication flows" - "Data import from [Source] completes with <1% error rate" **Usability Criteria:** - "New users complete [task] within [N] minutes without assistance" - "Admin configuration for [scenario] requires fewer than [N] steps" - "Stakeholder satisfaction rating >= 4.0/5.0" ### Anti-Patterns in Success Criteria - **Too vague:** "System performs well" (what is "well"?) - **Too many:** More than 15 criteria dilutes focus and extends timeline - **Unmeasurable:** "Users like the interface" (how do you measure "like"?) - **Biased toward feature count:** "Must have Feature X" instead of "Must solve Problem Y" - **Moving target:** Criteria that change mid-POC without formal agreement ## Stakeholder Management ### Stakeholder Map | Role | Priority | Engagement Strategy | |------|----------|-------------------| | Decision Maker | High | Executive briefings, ROI summaries | | Champion | Critical | Daily communication, progress updates | | Technical Evaluator | High | Hands-on access, deep-dive sessions | | End User | Medium | Usability testing, feedback sessions | | IT/Security | High | Compliance reviews, architecture sessions | | Procurement | Low-Medium | TCO documentation, reference connections | ### Engagement Cadence - **Daily:** Champion check-in (10 min, Slack/email) - **Weekly:** Progress report to all stakeholders (written summary) - **Phase transitions:** Formal review meeting with demo of progress - **Final:** Executive presentation with scorecard results and recommendation ### Managing Stakeholder Expectations 1. **Set clear boundaries:** Define what will and will not be demonstrated 2. **Communicate early and often:** No surprises; surface issues immediately 3. **Document everything:** Meeting notes, decisions, change requests 4. **Celebrate wins:** Highlight successful milestones to maintain momentum 5. **Address concerns immediately:** Delays in resolution erode confidence ## Evaluation Frameworks ### Weighted Scorecard Model The evaluation scorecard provides an objective, comparable assessment: | Category | Weight | Score (1-5) | Weighted Score | |----------|--------|-------------|----------------| | Functionality | 30% | | | | Performance | 20% | | | | Integration | 20% | | | | Usability | 15% | | | | Support | 15% | | | | **Total** | **100%** | | | **Scoring Scale:** - 5: Exceeds requirements - superior capability demonstrated - 4: Meets requirements - full capability with minor enhancements possible - 3: Partially meets - acceptable but notable gaps remain - 2: Below expectations - significant gaps that impact value - 1: Does not meet - critical failure for this category **Decision Thresholds:** - Weighted average >= 4.0: **Strong Pass** - proceed to procurement - Weighted average 3.5-3.9: **Pass** - proceed with noted conditions - Weighted average 3.0-3.4: **Conditional** - requires further evaluation or negotiation - Weighted average < 3.0: **Fail** - does not meet requirements ### Go/No-Go Decision Framework The go/no-go decision should be based on multiple factors, not just the scorecard: **Go Indicators:** - Scorecard score >= 3.5 - All must-have success criteria met - Champion and decision-maker both express positive sentiment - No unresolved critical technical blockers - Clear implementation path identified **No-Go Indicators:** - Scorecard score < 3.0 - Critical success criteria failed without clear resolution - Decision-maker expresses significant concerns - Multiple unresolved technical blockers - Competitive alternative clearly preferred by evaluators **Conditional Go Indicators:** - Scorecard score 3.0-3.5 with clear path to improvement - 1-2 minor success criteria not met but with workarounds - Mixed stakeholder sentiment that can be addressed - Blockers identified but resolution path confirmed with engineering ## Common POC Failure Modes ### 1. Scope Creep **Symptom:** Customer continuously adds requirements during the POC. **Prevention:** Written scope agreement with change request process. **Recovery:** Renegotiate timeline or defer additions to Phase 2. ### 2. Champion Absence **Symptom:** Champion becomes unavailable or disengaged mid-POC. **Prevention:** Identify a backup champion. Schedule regular touchpoints. **Recovery:** Escalate to decision-maker. Demonstrate value already achieved. ### 3. Data Issues **Symptom:** Customer data is unavailable, poor quality, or incompatible. **Prevention:** Request sample data before kickoff. Prepare synthetic data. **Recovery:** Use synthetic data for core testing. Document data requirements for implementation. ### 4. Environment Problems **Symptom:** POC environment is unstable, slow, or inaccessible. **Prevention:** Use a dedicated, pre-configured environment. Test before kickoff. **Recovery:** Have a backup environment. Communicate honestly about delays. ### 5. Moving Goalposts **Symptom:** Evaluation criteria change mid-POC, often influenced by competitor demos. **Prevention:** Get written sign-off on criteria before starting. Reference agreement when changes arise. **Recovery:** Agree to evaluate new criteria as addendum, not replacement. Highlight what has already been validated. ### 6. Extended Timeline **Symptom:** POC drags beyond planned duration without clear progress. **Prevention:** Set hard deadlines in the agreement. Schedule decision meetings in advance. **Recovery:** Force a checkpoint. Present results to date and ask for a go/no-go with current evidence. ### 7. Technical Blockers **Symptom:** Unexpected technical issues prevent completion of key use cases. **Prevention:** Conduct technical discovery before committing to POC. Have engineering on standby. **Recovery:** Escalate immediately. Provide transparent status updates. Offer alternative approaches. ## POC Documentation ### Required Artifacts | Document | When | Owner | |----------|------|-------| | Scope agreement | Pre-POC | SE + Customer | | Environment setup guide | Week 1 | SE | | Progress reports | Weekly | SE | | Phase review presentations | Phase transitions | SE | | Issue log | Ongoing | SE | | Final evaluation report | Week 5 | SE + Customer | | Lessons learned | Post-POC | SE | ### Final Report Template 1. **Executive Summary** - POC objectives, approach, and outcome 2. **Scope and Success Criteria** - What was tested and how 3. **Results Summary** - Success criteria outcomes with evidence 4. **Evaluation Scorecard** - Weighted scores across all categories 5. **Issues and Resolutions** - Problems encountered and how they were addressed 6. **Recommendation** - Go/No-Go with rationale 7. **Implementation Considerations** - Next steps, timeline, and resource needs --- **Last Updated:** February 2026 FILE:references/rfp-response-guide.md # RFP/RFI Response Guide A comprehensive reference for Sales Engineers responding to Requests for Proposal (RFP) and Requests for Information (RFI). ## RFP Response Best Practices ### 1. Pre-Response Assessment Before investing time in a response, conduct a thorough bid/no-bid assessment: **Bid Criteria Checklist:** - Do we have a pre-existing relationship with the customer? - Is there an identified champion or sponsor? - Do our capabilities align with >70% of requirements? - Is the deal size justified against the response effort? - Do we understand the competitive landscape? - Is the timeline realistic for our solution? **Red Flags for No-Bid:** - No prior customer engagement (blind RFP) - Requirement language mirrors a competitor's product - Timeline is unrealistically short - Must-have requirements fall outside our platform - Budget is undefined or misaligned with our pricing ### 2. Response Organization **Executive Summary (1-2 pages):** - Lead with business outcomes, not features - Reference the customer's specific challenges - Quantify value proposition with relevant metrics - State confidence level and key differentiators **Solution Overview:** - Map directly to the customer's stated requirements - Use the customer's language and terminology - Include architecture diagrams for technical sections - Address integration with existing systems **Compliance Matrix:** - Mirror the RFP's requirement numbering exactly - Use consistent coverage categories: Full, Partial, Planned, Gap - Provide clear explanations for each response - Include roadmap dates for "Planned" items ### 3. Coverage Classification | Status | Score | Definition | Response Approach | |--------|-------|------------|-------------------| | Full | 100% | Current product fully meets requirement | Describe capability with evidence | | Partial | 50% | Met with configuration or workaround | Explain approach and any limitations | | Planned | 25% | On product roadmap | Provide timeline and interim solution | | Gap | 0% | Not currently supported | Acknowledge gap and propose alternatives | ### 4. Priority-Weighted Scoring Not all requirements are equal. Weight them by business impact: - **Must-Have (3x weight):** Core requirements that are deal-breakers. Gaps here typically result in disqualification. - **Should-Have (2x weight):** Important requirements that influence the decision significantly. - **Nice-to-Have (1x weight):** Desirable but not critical. Often used as tie-breakers. ### 5. Response Writing Tips **Do:** - Answer the question directly before elaborating - Use the customer's terminology, not internal jargon - Provide specific examples, case studies, and metrics - Include screenshots or architecture diagrams where relevant - Cross-reference related answers to avoid redundancy - Proofread for consistency across sections (multiple authors) **Avoid:** - Marketing fluff or vague language ("best-in-class", "world-class") - Answering a question you were not asked - Contradictions between sections - Overselling capabilities you do not have - Ignoring the question format (tables vs. narrative) ## Bid/No-Bid Decision Framework ### Decision Matrix | Factor | Weight | Score (1-5) | Weighted | |--------|--------|-------------|----------| | Technical fit | 25% | | | | Relationship strength | 20% | | | | Competitive position | 20% | | | | Deal value vs effort | 15% | | | | Strategic importance | 10% | | | | Win probability | 10% | | | | **Total** | **100%** | | | **Scoring Guide:** - 5: Strong advantage - 4: Slight advantage - 3: Neutral / competitive parity - 2: Slight disadvantage - 1: Significant disadvantage **Decision Thresholds:** - Score >= 3.5: **Bid** - proceed with full response - Score 2.5 - 3.4: **Conditional Bid** - proceed with executive approval - Score < 2.5: **No-Bid** - decline or submit information-only response ### Effort Estimation Estimate the total effort required and compare against deal value: | Response Component | Typical Effort (hours) | |-------------------|----------------------| | Requirements analysis | 4-8 | | Technical writing | 16-40 | | Architecture diagrams | 4-8 | | Demo preparation | 8-16 | | Internal review | 4-8 | | Final formatting | 2-4 | | **Total** | **38-84 hours** | **Rule of thumb:** The response effort should not exceed 2% of the deal value. ## Compliance Matrix Structure ### Standard Format ``` | Req ID | Requirement Description | Priority | Compliance | Response | Evidence | |--------|------------------------|----------|------------|----------|----------| | R-001 | SSO via SAML 2.0 | Must | Full | Native SAML 2.0 support... | Config guide | | R-002 | Custom reporting | Should | Partial | Standard reports + API... | API docs | ``` ### Section Organization Organize requirements by category for clarity: 1. **Functional Requirements** - Core features and capabilities 2. **Technical Requirements** - Architecture, APIs, performance 3. **Security & Compliance** - Authentication, encryption, certifications 4. **Integration Requirements** - Third-party systems, data flows 5. **Support & SLA** - Support tiers, response times, uptime 6. **Vendor Qualifications** - Company size, financials, references ## Common Pitfalls ### 1. The Wired RFP **Symptom:** Requirements language matches a competitor's product feature list. **Response:** Focus on outcomes over features. Highlight areas of differentiation. Ask clarifying questions that expose broader needs. ### 2. Feature Checklist Syndrome **Symptom:** RFP is a massive feature checklist with no context about business problems. **Response:** Group features by business outcome. Add context in your response that demonstrates understanding of the underlying need. ### 3. Scope Creep in Response **Symptom:** Team keeps adding content that was not requested. **Response:** Assign a response manager to enforce scope. Answer what was asked, provide references for additional information. ### 4. Inconsistent Messaging **Symptom:** Multiple authors provide contradictory information. **Response:** Assign a single editor for final review. Create a response style guide. Use consistent terminology throughout. ### 5. Overcommitting on Gaps **Symptom:** Marking "Planned" items as "Full" to improve scores. **Response:** Never misrepresent coverage. Planned items with firm timelines and interim workarounds are better than lies discovered during POC. ## RFP Response Timeline Management ### Typical Response Timeline | Day | Activity | |-----|----------| | Day 1 | Receive RFP, conduct initial review, assign team | | Day 2-3 | Bid/no-bid decision, questions submission | | Day 4-7 | Requirements analysis, coverage assessment | | Day 8-14 | Draft responses, architecture diagrams | | Day 15-17 | Internal review, quality check | | Day 18-19 | Final edits, formatting, executive review | | Day 20 | Submission | ### Time-Saving Strategies 1. **Maintain a response library** - Reusable answers for common requirements 2. **Pre-built architecture diagrams** - Template diagrams for common integration patterns 3. **Standardized compliance language** - Pre-approved language for security and compliance sections 4. **Question templates** - Standard clarifying questions for common ambiguities --- **Last Updated:** February 2026 FILE:scripts/competitive_matrix_builder.py #!/usr/bin/env python3 """Competitive Matrix Builder - Generate feature comparison matrices and positioning analysis. Builds feature-by-feature comparison matrices, calculates weighted competitive scores, identifies differentiators and vulnerabilities, and generates win themes. Usage: python competitive_matrix_builder.py competitive_data.json python competitive_matrix_builder.py competitive_data.json --format json python competitive_matrix_builder.py competitive_data.json --format text """ import argparse import json import sys from typing import Any # Feature scoring levels FEATURE_SCORES: dict[str, int] = { "full": 3, "partial": 2, "limited": 1, "none": 0, } FEATURE_LABELS: dict[int, str] = { 3: "Full", 2: "Partial", 1: "Limited", 0: "None", } def safe_divide(numerator: float, denominator: float, default: float = 0.0) -> float: """Safely divide two numbers, returning default if denominator is zero.""" if denominator == 0: return default return numerator / denominator def load_competitive_data(filepath: str) -> dict[str, Any]: """Load and validate competitive data from a JSON file. Args: filepath: Path to the JSON file containing competitive data. Returns: Parsed competitive data dictionary. Raises: SystemExit: If the file cannot be read or parsed. """ try: with open(filepath, "r", encoding="utf-8") as f: data = json.load(f) except FileNotFoundError: print(f"Error: File not found: {filepath}", file=sys.stderr) sys.exit(1) except json.JSONDecodeError as e: print(f"Error: Invalid JSON in {filepath}: {e}", file=sys.stderr) sys.exit(1) if "categories" not in data: print("Error: JSON must contain a 'categories' array.", file=sys.stderr) sys.exit(1) if "our_product" not in data: print("Error: JSON must contain 'our_product' name.", file=sys.stderr) sys.exit(1) if "competitors" not in data or not data["competitors"]: print("Error: JSON must contain a non-empty 'competitors' array.", file=sys.stderr) sys.exit(1) return data def normalize_score(score_value: Any) -> int: """Normalize a score value to an integer. Args: score_value: Score as string label or integer. Returns: Normalized integer score (0-3). """ if isinstance(score_value, str): return FEATURE_SCORES.get(score_value.lower(), 0) if isinstance(score_value, (int, float)): return max(0, min(3, int(score_value))) return 0 def build_comparison_matrix(data: dict[str, Any]) -> dict[str, Any]: """Build the feature comparison matrix from input data. Args: data: Competitive data with categories, features, and scores. Returns: Comparison matrix with per-feature and per-category scores. """ our_product = data["our_product"] competitors = data["competitors"] all_products = [our_product] + competitors matrix: list[dict[str, Any]] = [] category_summaries: dict[str, dict[str, Any]] = {} for category in data["categories"]: cat_name = category["name"] cat_weight = category.get("weight", 1.0) cat_features = category.get("features", []) cat_scores: dict[str, list[int]] = {p: [] for p in all_products} for feature in cat_features: feature_name = feature["name"] scores: dict[str, int] = {} for product in all_products: raw_score = feature.get("scores", {}).get(product, 0) scores[product] = normalize_score(raw_score) cat_scores[product].append(scores[product]) # Determine leader for this feature max_score = max(scores.values()) leaders = [p for p, s in scores.items() if s == max_score] matrix.append({ "category": cat_name, "feature": feature_name, "scores": scores, "leaders": leaders, "our_score": scores[our_product], "max_score": max_score, "we_lead": our_product in leaders and len(leaders) == 1, "we_trail": scores[our_product] < max_score, }) # Category summary cat_product_scores = {} for product in all_products: product_scores = cat_scores[product] total = sum(product_scores) max_possible = len(product_scores) * 3 pct = safe_divide(total, max_possible) * 100 cat_product_scores[product] = { "total_score": total, "max_possible": max_possible, "percentage": round(pct, 1), } category_summaries[cat_name] = { "weight": cat_weight, "feature_count": len(cat_features), "product_scores": cat_product_scores, } return { "our_product": our_product, "competitors": competitors, "all_products": all_products, "matrix": matrix, "category_summaries": category_summaries, } def compute_competitive_scores( comparison: dict[str, Any], ) -> dict[str, dict[str, Any]]: """Compute weighted competitive scores for each product. Args: comparison: Comparison matrix data. Returns: Product scores with weighted and unweighted totals. """ all_products = comparison["all_products"] category_summaries = comparison["category_summaries"] product_scores: dict[str, dict[str, float]] = { p: {"weighted_total": 0.0, "max_weighted": 0.0, "unweighted_total": 0, "max_unweighted": 0} for p in all_products } for cat_name, cat_data in category_summaries.items(): weight = cat_data["weight"] for product in all_products: p_data = cat_data["product_scores"][product] product_scores[product]["weighted_total"] += p_data["total_score"] * weight product_scores[product]["max_weighted"] += p_data["max_possible"] * weight product_scores[product]["unweighted_total"] += p_data["total_score"] product_scores[product]["max_unweighted"] += p_data["max_possible"] result = {} for product in all_products: ps = product_scores[product] weighted_pct = safe_divide(ps["weighted_total"], ps["max_weighted"]) * 100 unweighted_pct = safe_divide(ps["unweighted_total"], ps["max_unweighted"]) * 100 result[product] = { "weighted_score": round(weighted_pct, 1), "unweighted_score": round(unweighted_pct, 1), "weighted_total": round(ps["weighted_total"], 2), "max_weighted": round(ps["max_weighted"], 2), } return result def identify_differentiators(comparison: dict[str, Any]) -> list[dict[str, Any]]: """Identify features where our product leads all competitors. Args: comparison: Comparison matrix data. Returns: List of differentiator features with details. """ differentiators = [] for entry in comparison["matrix"]: if entry["we_lead"] and entry["our_score"] >= 2: # Calculate gap from nearest competitor competitor_scores = [ entry["scores"][c] for c in comparison["competitors"] ] max_competitor = max(competitor_scores) if competitor_scores else 0 gap = entry["our_score"] - max_competitor differentiators.append({ "feature": entry["feature"], "category": entry["category"], "our_score": entry["our_score"], "our_label": FEATURE_LABELS.get(entry["our_score"], "Unknown"), "best_competitor_score": max_competitor, "gap": gap, }) # Sort by gap size descending differentiators.sort(key=lambda d: d["gap"], reverse=True) return differentiators def identify_vulnerabilities(comparison: dict[str, Any]) -> list[dict[str, Any]]: """Identify features where competitors lead our product. Args: comparison: Comparison matrix data. Returns: List of vulnerability features with details. """ vulnerabilities = [] for entry in comparison["matrix"]: if entry["we_trail"]: # Find which competitor leads leader_scores = { p: entry["scores"][p] for p in comparison["competitors"] if entry["scores"][p] == entry["max_score"] } gap = entry["max_score"] - entry["our_score"] vulnerabilities.append({ "feature": entry["feature"], "category": entry["category"], "our_score": entry["our_score"], "our_label": FEATURE_LABELS.get(entry["our_score"], "Unknown"), "leading_competitors": leader_scores, "gap": gap, }) # Sort by gap size descending vulnerabilities.sort(key=lambda v: v["gap"], reverse=True) return vulnerabilities def generate_win_themes( differentiators: list[dict[str, Any]], competitive_scores: dict[str, dict[str, Any]], our_product: str, ) -> list[str]: """Generate win themes based on differentiators and competitive position. Args: differentiators: List of differentiator features. competitive_scores: Product competitive scores. our_product: Our product name. Returns: List of win theme strings. """ themes = [] # Theme from top differentiators if differentiators: top_diff_categories = list({d["category"] for d in differentiators[:5]}) for cat in top_diff_categories[:3]: cat_diffs = [d for d in differentiators if d["category"] == cat] feature_names = [d["feature"] for d in cat_diffs[:3]] themes.append( f"Superior {cat} capabilities: {', '.join(feature_names)}" ) # Theme from overall competitive position our_score = competitive_scores.get(our_product, {}).get("weighted_score", 0) competitor_scores = [ (p, s["weighted_score"]) for p, s in competitive_scores.items() if p != our_product ] if competitor_scores: best_competitor_name, best_competitor_score = max( competitor_scores, key=lambda x: x[1] ) if our_score > best_competitor_score: themes.append( f"Overall strongest solution ({our_score:.1f}% vs {best_competitor_name} at {best_competitor_score:.1f}%)" ) # Theme from breadth of coverage strong_diffs = [d for d in differentiators if d["gap"] >= 2] if len(strong_diffs) >= 3: themes.append( f"Clear technical leadership across {len(strong_diffs)} key features with significant competitive gaps" ) if not themes: themes.append("Competitive parity - emphasize implementation quality, support, and total cost of ownership") return themes def analyze_competitive(data: dict[str, Any]) -> dict[str, Any]: """Run the complete competitive analysis pipeline. Args: data: Parsed competitive data dictionary. Returns: Complete analysis results dictionary. """ comparison = build_comparison_matrix(data) competitive_scores = compute_competitive_scores(comparison) differentiators = identify_differentiators(comparison) vulnerabilities = identify_vulnerabilities(comparison) win_themes = generate_win_themes( differentiators, competitive_scores, comparison["our_product"] ) return { "analysis_info": { "our_product": comparison["our_product"], "competitors": comparison["competitors"], "total_features": len(comparison["matrix"]), "total_categories": len(comparison["category_summaries"]), }, "competitive_scores": competitive_scores, "category_breakdown": comparison["category_summaries"], "comparison_matrix": comparison["matrix"], "differentiators": differentiators, "vulnerabilities": vulnerabilities, "win_themes": win_themes, } def format_text(result: dict[str, Any]) -> str: """Format analysis results as human-readable text. Args: result: Complete analysis results dictionary. Returns: Formatted text string. """ lines = [] info = result["analysis_info"] all_products = [info["our_product"]] + info["competitors"] lines.append("=" * 80) lines.append("COMPETITIVE MATRIX ANALYSIS") lines.append("=" * 80) lines.append(f"Our Product: {info['our_product']}") lines.append(f"Competitors: {', '.join(info['competitors'])}") lines.append(f"Features: {info['total_features']}") lines.append(f"Categories: {info['total_categories']}") lines.append("") # Competitive scores lines.append("-" * 80) lines.append("COMPETITIVE SCORES") lines.append("-" * 80) lines.append(f"{'Product':<25} {'Weighted':>10} {'Unweighted':>12}") lines.append("-" * 80) # Sort by weighted score descending sorted_scores = sorted( result["competitive_scores"].items(), key=lambda x: x[1]["weighted_score"], reverse=True, ) for product, scores in sorted_scores: marker = " <-- US" if product == info["our_product"] else "" lines.append( f"{product:<25} {scores['weighted_score']:>9.1f}% {scores['unweighted_score']:>11.1f}%{marker}" ) lines.append("") # Feature matrix lines.append("-" * 80) lines.append("FEATURE COMPARISON MATRIX") lines.append("-" * 80) # Build header product_cols = " ".join(f"{p[:10]:>10}" for p in all_products) lines.append(f"{'Feature':<30} {product_cols}") lines.append("-" * 80) current_category = "" for entry in result["comparison_matrix"]: if entry["category"] != current_category: current_category = entry["category"] cat_data = result["category_breakdown"].get(current_category, {}) weight = cat_data.get("weight", 1.0) lines.append(f"\n [{current_category}] (weight: {weight}x)") score_cols = " ".join( f"{FEATURE_LABELS.get(entry['scores'].get(p, 0), 'N/A'):>10}" for p in all_products ) lead_marker = " *" if entry["we_lead"] else (" !" if entry["we_trail"] else "") feature_display = entry["feature"][:28] lines.append(f" {feature_display:<28} {score_cols}{lead_marker}") lines.append("") lines.append(" * = We lead | ! = We trail") lines.append("") # Differentiators diffs = result["differentiators"] if diffs: lines.append("-" * 80) lines.append(f"DIFFERENTIATORS ({len(diffs)} features where we lead)") lines.append("-" * 80) for d in diffs: lines.append( f" + {d['feature']} [{d['category']}] " f"- Us: {d['our_label']} vs Best Competitor: {FEATURE_LABELS.get(d['best_competitor_score'], 'N/A')} " f"(gap: +{d['gap']})" ) lines.append("") # Vulnerabilities vulns = result["vulnerabilities"] if vulns: lines.append("-" * 80) lines.append(f"VULNERABILITIES ({len(vulns)} features where competitors lead)") lines.append("-" * 80) for v in vulns: leaders = ", ".join( f"{p}: {FEATURE_LABELS.get(s, 'N/A')}" for p, s in v["leading_competitors"].items() ) lines.append( f" - {v['feature']} [{v['category']}] " f"- Us: {v['our_label']} vs {leaders} " f"(gap: -{v['gap']})" ) lines.append("") # Win themes themes = result["win_themes"] lines.append("-" * 80) lines.append("WIN THEMES") lines.append("-" * 80) for i, theme in enumerate(themes, 1): lines.append(f" {i}. {theme}") lines.append("") lines.append("=" * 80) return "\n".join(lines) def main() -> None: """Main entry point for the Competitive Matrix Builder.""" parser = argparse.ArgumentParser( description="Build competitive feature comparison matrices and positioning analysis.", formatter_class=argparse.RawDescriptionHelpFormatter, epilog=( "Feature Scoring:\n" " Full (3) - Complete feature support\n" " Partial (2) - Partial or limited support\n" " Limited (1) - Minimal or basic support\n" " None (0) - Feature not available\n" "\n" "Example:\n" " python competitive_matrix_builder.py competitive_data.json --format json\n" ), ) parser.add_argument( "input_file", help="Path to JSON file containing competitive data", ) parser.add_argument( "--format", choices=["json", "text"], default="text", dest="output_format", help="Output format: json or text (default: text)", ) args = parser.parse_args() data = load_competitive_data(args.input_file) result = analyze_competitive(data) if args.output_format == "json": print(json.dumps(result, indent=2)) else: print(format_text(result)) if __name__ == "__main__": main() FILE:scripts/poc_planner.py #!/usr/bin/env python3 """POC Planner - Plan proof-of-concept engagements with timeline, resources, and scorecards. Generates structured POC plans including phased timelines, resource allocation, success criteria with measurable metrics, evaluation scorecards, risk identification, and go/no-go recommendation frameworks. Usage: python poc_planner.py poc_data.json python poc_planner.py poc_data.json --format json python poc_planner.py poc_data.json --format text """ import argparse import json import sys from typing import Any # Default phase definitions DEFAULT_PHASES = [ { "name": "Setup", "duration_weeks": 1, "description": "Environment provisioning, data migration, initial configuration", "activities": [ "Provision POC environment", "Configure authentication and access", "Migrate sample data sets", "Set up monitoring and logging", "Conduct kickoff meeting with stakeholders", ], }, { "name": "Core Testing", "duration_weeks": 2, "description": "Primary use case validation and integration testing", "activities": [ "Execute primary use case scenarios", "Test core integrations", "Validate data flow and transformations", "Conduct mid-point review with stakeholders", "Document findings and adjust test plan", ], }, { "name": "Advanced Testing", "duration_weeks": 1, "description": "Edge cases, performance testing, and security validation", "activities": [ "Execute edge case scenarios", "Run performance and load tests", "Validate security controls and compliance", "Test disaster recovery and failover", "Test administrative workflows", ], }, { "name": "Evaluation", "duration_weeks": 1, "description": "Scorecard completion, stakeholder review, and go/no-go decision", "activities": [ "Complete evaluation scorecard", "Compile POC results documentation", "Conduct final stakeholder review", "Present go/no-go recommendation", "Gather lessons learned", ], }, ] # Evaluation categories with default weights DEFAULT_EVAL_CATEGORIES = { "Functionality": { "weight": 0.30, "criteria": [ "Core feature completeness", "Use case coverage", "Customization flexibility", "Workflow automation", ], }, "Performance": { "weight": 0.20, "criteria": [ "Response time under load", "Throughput capacity", "Scalability characteristics", "Resource utilization", ], }, "Integration": { "weight": 0.20, "criteria": [ "API completeness and documentation", "Data migration ease", "Third-party connector availability", "Authentication/SSO integration", ], }, "Usability": { "weight": 0.15, "criteria": [ "User interface intuitiveness", "Learning curve assessment", "Documentation quality", "Admin console functionality", ], }, "Support": { "weight": 0.15, "criteria": [ "Technical support responsiveness", "Knowledge base quality", "Training resources availability", "Community and ecosystem", ], }, } def safe_divide(numerator: float, denominator: float, default: float = 0.0) -> float: """Safely divide two numbers, returning default if denominator is zero.""" if denominator == 0: return default return numerator / denominator def load_poc_data(filepath: str) -> dict[str, Any]: """Load and validate POC data from a JSON file. Args: filepath: Path to the JSON file containing POC data. Returns: Parsed POC data dictionary. Raises: SystemExit: If the file cannot be read or parsed. """ try: with open(filepath, "r", encoding="utf-8") as f: data = json.load(f) except FileNotFoundError: print(f"Error: File not found: {filepath}", file=sys.stderr) sys.exit(1) except json.JSONDecodeError as e: print(f"Error: Invalid JSON in {filepath}: {e}", file=sys.stderr) sys.exit(1) if "poc_name" not in data: print("Error: JSON must contain 'poc_name' field.", file=sys.stderr) sys.exit(1) return data def estimate_resources(data: dict[str, Any], phases: list[dict[str, Any]]) -> dict[str, Any]: """Estimate resource requirements for the POC. Args: data: POC data with scope and requirements. phases: List of phase definitions. Returns: Resource allocation dictionary. """ total_weeks = sum(p["duration_weeks"] for p in phases) complexity = data.get("complexity", "medium").lower() scope_items = data.get("scope_items", []) num_integrations = data.get("num_integrations", 0) # Base SE hours per week by complexity se_hours_per_week = {"low": 15, "medium": 25, "high": 35}.get(complexity, 25) # Engineering support hours eng_base = {"low": 5, "medium": 10, "high": 20}.get(complexity, 10) eng_integration_hours = num_integrations * 8 # Customer resource hours customer_hours_per_week = {"low": 5, "medium": 8, "high": 12}.get(complexity, 8) se_total = se_hours_per_week * total_weeks eng_total = (eng_base * total_weeks) + eng_integration_hours customer_total = customer_hours_per_week * total_weeks # Phase-level breakdown phase_resources = [] for phase in phases: weeks = phase["duration_weeks"] # Setup phase has higher SE and eng effort se_multiplier = 1.3 if phase["name"] == "Setup" else ( 1.0 if phase["name"] in ("Core Testing", "Advanced Testing") else 0.7 ) eng_multiplier = 1.5 if phase["name"] == "Setup" else ( 1.0 if phase["name"] == "Core Testing" else ( 1.2 if phase["name"] == "Advanced Testing" else 0.5 ) ) phase_resources.append({ "phase": phase["name"], "duration_weeks": weeks, "se_hours": round(se_hours_per_week * weeks * se_multiplier), "engineering_hours": round(eng_base * weeks * eng_multiplier), "customer_hours": round(customer_hours_per_week * weeks), }) return { "total_duration_weeks": total_weeks, "complexity": complexity, "totals": { "se_hours": se_total, "engineering_hours": eng_total, "customer_hours": customer_total, "total_hours": se_total + eng_total + customer_total, }, "phase_breakdown": phase_resources, "additional_resources": { "integration_hours": eng_integration_hours, "num_integrations": num_integrations, }, } def generate_success_criteria(data: dict[str, Any]) -> list[dict[str, Any]]: """Generate success criteria based on POC scope and requirements. Args: data: POC data with scope and requirements. Returns: List of success criteria with metrics. """ criteria = [] # Custom criteria from input custom_criteria = data.get("success_criteria", []) for cc in custom_criteria: criteria.append({ "criterion": cc.get("criterion", "Unnamed criterion"), "metric": cc.get("metric", "Pass/Fail"), "target": cc.get("target", "Met"), "category": cc.get("category", "Functionality"), "priority": cc.get("priority", "must-have"), }) # Auto-generated criteria based on scope scope_items = data.get("scope_items", []) for item in scope_items: if isinstance(item, str): criteria.append({ "criterion": f"Validate: {item}", "metric": "Pass/Fail", "target": "Pass", "category": "Functionality", "priority": "must-have", }) elif isinstance(item, dict): criteria.append({ "criterion": item.get("name", "Unnamed scope item"), "metric": item.get("metric", "Pass/Fail"), "target": item.get("target", "Pass"), "category": item.get("category", "Functionality"), "priority": item.get("priority", "must-have"), }) # Default criteria if none provided if not criteria: criteria = [ { "criterion": "Core use case validation", "metric": "Percentage of use cases successfully demonstrated", "target": ">90%", "category": "Functionality", "priority": "must-have", }, { "criterion": "Performance under expected load", "metric": "Response time at target concurrency", "target": "<2 seconds p95", "category": "Performance", "priority": "must-have", }, { "criterion": "Integration with existing systems", "metric": "Number of integrations successfully tested", "target": "All planned integrations", "category": "Integration", "priority": "must-have", }, { "criterion": "User acceptance", "metric": "Stakeholder satisfaction score", "target": ">4.0/5.0", "category": "Usability", "priority": "should-have", }, ] return criteria def generate_evaluation_scorecard(data: dict[str, Any]) -> dict[str, Any]: """Generate the POC evaluation scorecard template. Args: data: POC data. Returns: Evaluation scorecard structure. """ custom_categories = data.get("evaluation_categories", {}) # Merge custom categories with defaults categories = {} for cat_name, cat_data in DEFAULT_EVAL_CATEGORIES.items(): if cat_name in custom_categories: custom = custom_categories[cat_name] categories[cat_name] = { "weight": custom.get("weight", cat_data["weight"]), "criteria": custom.get("criteria", cat_data["criteria"]), "score": None, "notes": "", } else: categories[cat_name] = { "weight": cat_data["weight"], "criteria": cat_data["criteria"], "score": None, "notes": "", } # Normalize weights to sum to 1.0 total_weight = sum(c["weight"] for c in categories.values()) if total_weight > 0 and abs(total_weight - 1.0) > 0.01: for cat in categories.values(): cat["weight"] = round(safe_divide(cat["weight"], total_weight), 2) return { "scoring_scale": { "5": "Exceeds requirements - superior capability", "4": "Meets requirements - full capability", "3": "Partially meets - acceptable with minor gaps", "2": "Below expectations - significant gaps", "1": "Does not meet - critical gaps", }, "categories": categories, "pass_threshold": 3.5, "strong_pass_threshold": 4.0, } def identify_risks(data: dict[str, Any], resources: dict[str, Any]) -> list[dict[str, Any]]: """Identify POC risks and generate mitigation strategies. Args: data: POC data. resources: Resource allocation data. Returns: List of risk entries with probability, impact, and mitigation. """ risks = [] complexity = data.get("complexity", "medium").lower() num_integrations = data.get("num_integrations", 0) total_weeks = resources["total_duration_weeks"] stakeholders = data.get("stakeholders", []) # Timeline risk if total_weeks > 6: risks.append({ "risk": "Extended timeline may lose stakeholder attention", "probability": "high", "impact": "high", "mitigation": "Schedule weekly progress checkpoints; deliver early wins in week 2", "category": "Timeline", }) elif total_weeks >= 4: risks.append({ "risk": "Timeline may slip due to unforeseen technical issues", "probability": "medium", "impact": "medium", "mitigation": "Build 20% buffer into each phase; identify critical path early", "category": "Timeline", }) # Integration risks if num_integrations > 3: risks.append({ "risk": "Multiple integrations increase complexity and failure points", "probability": "high", "impact": "high", "mitigation": "Prioritize integrations by business value; test incrementally; have fallback demo data", "category": "Technical", }) elif num_integrations > 0: risks.append({ "risk": "Integration dependencies may cause delays", "probability": "medium", "impact": "medium", "mitigation": "Engage customer IT early; confirm API access and credentials in setup phase", "category": "Technical", }) # Data risks risks.append({ "risk": "Customer data quality or availability issues", "probability": "medium", "impact": "high", "mitigation": "Request sample data early; prepare synthetic data as fallback; validate data format in setup", "category": "Data", }) # Stakeholder risks if len(stakeholders) > 5: risks.append({ "risk": "Too many stakeholders may slow decision-making", "probability": "medium", "impact": "medium", "mitigation": "Identify decision-maker and champion; schedule focused reviews per stakeholder group", "category": "Stakeholder", }) if not stakeholders: risks.append({ "risk": "Undefined stakeholder map may lead to misaligned evaluation", "probability": "high", "impact": "high", "mitigation": "Confirm stakeholder list, roles, and evaluation criteria before setup phase", "category": "Stakeholder", }) # Resource risks if complexity == "high": risks.append({ "risk": "High complexity may require additional engineering resources", "probability": "medium", "impact": "high", "mitigation": "Secure engineering commitment upfront; identify escalation path for blockers", "category": "Resource", }) # Competitive risk risks.append({ "risk": "Competitor POC running in parallel may shift evaluation criteria", "probability": "medium", "impact": "medium", "mitigation": "Stay close to champion; align success criteria early; differentiate on unique strengths", "category": "Competitive", }) return risks def generate_go_no_go_framework(data: dict[str, Any]) -> dict[str, Any]: """Generate the go/no-go decision framework. Args: data: POC data. Returns: Go/no-go framework with criteria and thresholds. """ return { "decision_criteria": [ { "criterion": "Overall scorecard score", "go_threshold": ">=3.5 weighted average", "no_go_threshold": "<3.0 weighted average", "conditional_range": "3.0 - 3.5", }, { "criterion": "Must-have success criteria met", "go_threshold": "100% of must-have criteria pass", "no_go_threshold": "<80% of must-have criteria pass", "conditional_range": "80-99% with mitigation plan", }, { "criterion": "Stakeholder satisfaction", "go_threshold": "Champion and decision-maker both positive", "no_go_threshold": "Decision-maker negative", "conditional_range": "Mixed signals - needs follow-up", }, { "criterion": "Technical blockers", "go_threshold": "No unresolved critical blockers", "no_go_threshold": ">2 unresolved critical blockers", "conditional_range": "1-2 blockers with clear resolution path", }, ], "recommendation_logic": { "GO": "All criteria meet go thresholds, or majority go with no no-go triggers", "CONDITIONAL_GO": "Some criteria in conditional range, but no no-go triggers and clear resolution plan", "NO_GO": "Any criterion triggers no-go threshold without clear mitigation", }, } def plan_poc(data: dict[str, Any]) -> dict[str, Any]: """Run the complete POC planning pipeline. Args: data: Parsed POC data dictionary. Returns: Complete POC plan dictionary. """ poc_info = { "poc_name": data.get("poc_name", "Unnamed POC"), "customer": data.get("customer", "Unknown Customer"), "opportunity_value": data.get("opportunity_value", "Not specified"), "complexity": data.get("complexity", "medium"), "start_date": data.get("start_date", "TBD"), "champion": data.get("champion", "Not identified"), "decision_maker": data.get("decision_maker", "Not identified"), } # Use custom phases if provided, otherwise defaults phases = data.get("phases", DEFAULT_PHASES) # Resource estimation resources = estimate_resources(data, phases) # Success criteria success_criteria = generate_success_criteria(data) # Evaluation scorecard scorecard = generate_evaluation_scorecard(data) # Risk identification risks = identify_risks(data, resources) # Go/No-Go framework go_no_go = generate_go_no_go_framework(data) # Timeline with phase details timeline = [] current_week = 1 for phase in phases: end_week = current_week + phase["duration_weeks"] - 1 timeline.append({ "phase": phase["name"], "start_week": current_week, "end_week": end_week, "duration_weeks": phase["duration_weeks"], "description": phase["description"], "activities": phase["activities"], }) current_week = end_week + 1 # Stakeholder plan stakeholders = data.get("stakeholders", []) stakeholder_plan = [] for s in stakeholders: if isinstance(s, str): stakeholder_plan.append({ "name": s, "role": "Evaluator", "engagement": "Weekly updates, phase reviews", }) elif isinstance(s, dict): stakeholder_plan.append({ "name": s.get("name", "Unknown"), "role": s.get("role", "Evaluator"), "engagement": s.get("engagement", "Weekly updates, phase reviews"), }) return { "poc_info": poc_info, "timeline": timeline, "resource_allocation": resources, "success_criteria": success_criteria, "evaluation_scorecard": scorecard, "risk_register": risks, "go_no_go_framework": go_no_go, "stakeholder_plan": stakeholder_plan, } def format_text(result: dict[str, Any]) -> str: """Format POC plan as human-readable text. Args: result: Complete POC plan dictionary. Returns: Formatted text string. """ lines = [] info = result["poc_info"] lines.append("=" * 70) lines.append("PROOF OF CONCEPT PLAN") lines.append("=" * 70) lines.append(f"POC Name: {info['poc_name']}") lines.append(f"Customer: {info['customer']}") lines.append(f"Opportunity Value: {info['opportunity_value']}") lines.append(f"Complexity: {info['complexity'].upper()}") lines.append(f"Start Date: {info['start_date']}") lines.append(f"Champion: {info['champion']}") lines.append(f"Decision Maker: {info['decision_maker']}") lines.append("") # Timeline lines.append("-" * 70) lines.append("TIMELINE") lines.append("-" * 70) for phase in result["timeline"]: week_range = ( f"Week {phase['start_week']}" if phase["start_week"] == phase["end_week"] else f"Weeks {phase['start_week']}-{phase['end_week']}" ) lines.append(f"\n Phase: {phase['phase']} ({week_range})") lines.append(f" {phase['description']}") lines.append(" Activities:") for activity in phase["activities"]: lines.append(f" - {activity}") lines.append("") # Resource allocation res = result["resource_allocation"] lines.append("-" * 70) lines.append("RESOURCE ALLOCATION") lines.append("-" * 70) lines.append(f"Total Duration: {res['total_duration_weeks']} weeks") lines.append(f"Complexity: {res['complexity'].upper()}") lines.append("") lines.append(" Totals:") lines.append(f" SE Hours: {res['totals']['se_hours']}") lines.append(f" Engineering Hours: {res['totals']['engineering_hours']}") lines.append(f" Customer Hours: {res['totals']['customer_hours']}") lines.append(f" Total Hours: {res['totals']['total_hours']}") lines.append("") lines.append(" Phase Breakdown:") lines.append(f" {'Phase':<20} {'Weeks':>5} {'SE':>6} {'Eng':>6} {'Cust':>6}") lines.append(" " + "-" * 45) for pr in res["phase_breakdown"]: lines.append( f" {pr['phase']:<20} {pr['duration_weeks']:>5} " f"{pr['se_hours']:>5}h {pr['engineering_hours']:>5}h {pr['customer_hours']:>5}h" ) lines.append("") # Success criteria criteria = result["success_criteria"] lines.append("-" * 70) lines.append("SUCCESS CRITERIA") lines.append("-" * 70) for i, sc in enumerate(criteria, 1): priority_marker = "[MUST]" if sc["priority"] == "must-have" else ( "[SHOULD]" if sc["priority"] == "should-have" else "[NICE]" ) lines.append(f" {i}. {priority_marker} {sc['criterion']}") lines.append(f" Metric: {sc['metric']}") lines.append(f" Target: {sc['target']}") lines.append(f" Category: {sc['category']}") lines.append("") # Evaluation scorecard scorecard = result["evaluation_scorecard"] lines.append("-" * 70) lines.append("EVALUATION SCORECARD") lines.append("-" * 70) lines.append(f" Pass Threshold: {scorecard['pass_threshold']}/5.0") lines.append(f" Strong Pass Threshold: {scorecard['strong_pass_threshold']}/5.0") lines.append("") lines.append(" Scoring Scale:") for score, desc in scorecard["scoring_scale"].items(): lines.append(f" {score} = {desc}") lines.append("") lines.append(" Categories:") for cat_name, cat_data in scorecard["categories"].items(): lines.append(f"\n {cat_name} (weight: {cat_data['weight']:.0%})") for criterion in cat_data["criteria"]: lines.append(f" [ ] {criterion}") lines.append("") # Risk register risks = result["risk_register"] lines.append("-" * 70) lines.append("RISK REGISTER") lines.append("-" * 70) for risk in risks: lines.append(f" [{risk['impact'].upper()}] {risk['risk']}") lines.append(f" Probability: {risk['probability']} | Impact: {risk['impact']}") lines.append(f" Category: {risk['category']}") lines.append(f" Mitigation: {risk['mitigation']}") lines.append("") # Go/No-Go framework framework = result["go_no_go_framework"] lines.append("-" * 70) lines.append("GO / NO-GO DECISION FRAMEWORK") lines.append("-" * 70) for dc in framework["decision_criteria"]: lines.append(f" {dc['criterion']}:") lines.append(f" GO: {dc['go_threshold']}") lines.append(f" CONDITIONAL: {dc['conditional_range']}") lines.append(f" NO-GO: {dc['no_go_threshold']}") lines.append("") lines.append(" Recommendation Logic:") for decision, logic in framework["recommendation_logic"].items(): lines.append(f" {decision}: {logic}") lines.append("") # Stakeholder plan stakeholders = result["stakeholder_plan"] if stakeholders: lines.append("-" * 70) lines.append("STAKEHOLDER PLAN") lines.append("-" * 70) for s in stakeholders: lines.append(f" {s['name']} ({s['role']})") lines.append(f" Engagement: {s['engagement']}") lines.append("") lines.append("=" * 70) return "\n".join(lines) def main() -> None: """Main entry point for the POC Planner.""" parser = argparse.ArgumentParser( description="Plan proof-of-concept engagements with timeline, resources, and evaluation scorecards.", formatter_class=argparse.RawDescriptionHelpFormatter, epilog=( "Default Phases:\n" " Week 1: Setup - Environment provisioning, configuration\n" " Weeks 2-3: Core Testing - Primary use cases, integrations\n" " Week 4: Advanced Testing - Edge cases, performance, security\n" " Week 5: Evaluation - Scorecard, stakeholder review, go/no-go\n" "\n" "Example:\n" " python poc_planner.py poc_data.json --format json\n" ), ) parser.add_argument( "input_file", help="Path to JSON file containing POC scope and requirements", ) parser.add_argument( "--format", choices=["json", "text"], default="text", dest="output_format", help="Output format: json or text (default: text)", ) args = parser.parse_args() data = load_poc_data(args.input_file) result = plan_poc(data) if args.output_format == "json": print(json.dumps(result, indent=2)) else: print(format_text(result)) if __name__ == "__main__": main() FILE:scripts/rfp_response_analyzer.py #!/usr/bin/env python3 """RFP/RFI Response Analyzer - Score coverage, identify gaps, and recommend bid/no-bid. Parses RFP/RFI requirements and scores coverage using Full/Partial/Planned/Gap categories. Generates weighted coverage scores, gap analysis with mitigation strategies, effort estimation, and bid/no-bid recommendations. Usage: python rfp_response_analyzer.py rfp_data.json python rfp_response_analyzer.py rfp_data.json --format json python rfp_response_analyzer.py rfp_data.json --format text """ import argparse import json import sys from typing import Any # Coverage status to score mapping COVERAGE_SCORES: dict[str, float] = { "full": 1.0, "partial": 0.5, "planned": 0.25, "gap": 0.0, } # Priority to weight mapping PRIORITY_WEIGHTS: dict[str, float] = { "must-have": 3.0, "should-have": 2.0, "nice-to-have": 1.0, } # Bid thresholds BID_THRESHOLD = 0.70 CONDITIONAL_THRESHOLD = 0.50 MAX_MUST_HAVE_GAPS_FOR_BID = 3 def safe_divide(numerator: float, denominator: float, default: float = 0.0) -> float: """Safely divide two numbers, returning default if denominator is zero.""" if denominator == 0: return default return numerator / denominator def load_rfp_data(filepath: str) -> dict[str, Any]: """Load and validate RFP data from a JSON file. Args: filepath: Path to the JSON file containing RFP data. Returns: Parsed RFP data dictionary. Raises: SystemExit: If the file cannot be read or parsed. """ try: with open(filepath, "r", encoding="utf-8") as f: data = json.load(f) except FileNotFoundError: print(f"Error: File not found: {filepath}", file=sys.stderr) sys.exit(1) except json.JSONDecodeError as e: print(f"Error: Invalid JSON in {filepath}: {e}", file=sys.stderr) sys.exit(1) if "requirements" not in data: print("Error: JSON must contain a 'requirements' array.", file=sys.stderr) sys.exit(1) return data def analyze_requirement(req: dict[str, Any]) -> dict[str, Any]: """Analyze a single requirement and compute its score. Args: req: Requirement dictionary with category, priority, coverage_status, etc. Returns: Enriched requirement with computed score and weight. """ coverage_status = req.get("coverage_status", "gap").lower() priority = req.get("priority", "nice-to-have").lower() coverage_score = COVERAGE_SCORES.get(coverage_status, 0.0) weight = PRIORITY_WEIGHTS.get(priority, 1.0) weighted_score = coverage_score * weight max_weighted = weight effort_hours = req.get("effort_hours", 0) result = { "id": req.get("id", "unknown"), "requirement": req.get("requirement", "Unnamed requirement"), "category": req.get("category", "Uncategorized"), "priority": priority, "coverage_status": coverage_status, "coverage_score": coverage_score, "weight": weight, "weighted_score": weighted_score, "max_weighted": max_weighted, "effort_hours": effort_hours, "notes": req.get("notes", ""), "mitigation": req.get("mitigation", ""), } return result def generate_gap_analysis(analyzed_reqs: list[dict[str, Any]]) -> list[dict[str, Any]]: """Generate gap analysis for requirements not fully covered. Args: analyzed_reqs: List of analyzed requirement dictionaries. Returns: List of gap entries with mitigation strategies. """ gaps = [] for req in analyzed_reqs: if req["coverage_status"] in ("gap", "partial", "planned"): severity = "critical" if req["priority"] == "must-have" else ( "high" if req["priority"] == "should-have" else "low" ) mitigation = req["mitigation"] if not mitigation: if req["coverage_status"] == "partial": mitigation = "Enhance existing capability to achieve full coverage" elif req["coverage_status"] == "planned": mitigation = "Communicate roadmap timeline and interim workaround" else: mitigation = "Evaluate build vs. partner vs. no-bid for this requirement" gaps.append({ "id": req["id"], "requirement": req["requirement"], "category": req["category"], "priority": req["priority"], "coverage_status": req["coverage_status"], "severity": severity, "effort_hours": req["effort_hours"], "mitigation": mitigation, }) # Sort by severity: critical > high > low severity_order = {"critical": 0, "high": 1, "low": 2} gaps.sort(key=lambda g: severity_order.get(g["severity"], 3)) return gaps def compute_category_scores(analyzed_reqs: list[dict[str, Any]]) -> dict[str, dict[str, Any]]: """Compute coverage scores grouped by requirement category. Args: analyzed_reqs: List of analyzed requirement dictionaries. Returns: Dictionary of category names to score summaries. """ categories: dict[str, dict[str, float]] = {} for req in analyzed_reqs: cat = req["category"] if cat not in categories: categories[cat] = { "weighted_score": 0.0, "max_weighted": 0.0, "count": 0, "full_count": 0, "partial_count": 0, "planned_count": 0, "gap_count": 0, "effort_hours": 0, } categories[cat]["weighted_score"] += req["weighted_score"] categories[cat]["max_weighted"] += req["max_weighted"] categories[cat]["count"] += 1 categories[cat]["effort_hours"] += req["effort_hours"] status_key = f"{req['coverage_status']}_count" if status_key in categories[cat]: categories[cat][status_key] += 1 result = {} for cat, scores in categories.items(): coverage_pct = safe_divide(scores["weighted_score"], scores["max_weighted"]) * 100 result[cat] = { "coverage_percentage": round(coverage_pct, 1), "requirements_count": int(scores["count"]), "full": int(scores["full_count"]), "partial": int(scores["partial_count"]), "planned": int(scores["planned_count"]), "gap": int(scores["gap_count"]), "effort_hours": int(scores["effort_hours"]), } return result def determine_bid_recommendation( overall_coverage: float, must_have_gaps: int, strategic_value: str, ) -> dict[str, Any]: """Determine bid/no-bid recommendation based on coverage and gaps. Args: overall_coverage: Overall weighted coverage percentage (0-100). must_have_gaps: Number of must-have requirements with gap status. strategic_value: Strategic value assessment (high, medium, low). Returns: Recommendation dictionary with decision and rationale. """ coverage_ratio = overall_coverage / 100.0 reasons = [] # Primary decision logic if coverage_ratio >= BID_THRESHOLD and must_have_gaps <= MAX_MUST_HAVE_GAPS_FOR_BID: decision = "BID" reasons.append(f"Coverage score {overall_coverage:.1f}% exceeds {BID_THRESHOLD*100:.0f}% threshold") if must_have_gaps > 0: reasons.append(f"{must_have_gaps} must-have gap(s) within acceptable range (max {MAX_MUST_HAVE_GAPS_FOR_BID})") elif coverage_ratio >= CONDITIONAL_THRESHOLD or ( must_have_gaps <= MAX_MUST_HAVE_GAPS_FOR_BID and coverage_ratio >= 0.4 ): decision = "CONDITIONAL BID" reasons.append(f"Coverage score {overall_coverage:.1f}% in conditional range ({CONDITIONAL_THRESHOLD*100:.0f}%-{BID_THRESHOLD*100:.0f}%)") if must_have_gaps > 0: reasons.append(f"{must_have_gaps} must-have gap(s) require mitigation plan") else: decision = "NO-BID" if coverage_ratio < CONDITIONAL_THRESHOLD: reasons.append(f"Coverage score {overall_coverage:.1f}% below {CONDITIONAL_THRESHOLD*100:.0f}% minimum") if must_have_gaps > MAX_MUST_HAVE_GAPS_FOR_BID: reasons.append(f"{must_have_gaps} must-have gaps exceed maximum of {MAX_MUST_HAVE_GAPS_FOR_BID}") # Strategic value adjustment if strategic_value.lower() == "high" and decision == "CONDITIONAL BID": reasons.append("High strategic value supports pursuing despite coverage gaps") elif strategic_value.lower() == "low" and decision == "CONDITIONAL BID": decision = "NO-BID" reasons.append("Low strategic value does not justify investment for conditional coverage") confidence = "high" if coverage_ratio >= 0.80 else ( "medium" if coverage_ratio >= 0.60 else "low" ) return { "decision": decision, "confidence": confidence, "overall_coverage_percentage": round(overall_coverage, 1), "must_have_gaps": must_have_gaps, "strategic_value": strategic_value, "reasons": reasons, } def generate_risk_assessment( analyzed_reqs: list[dict[str, Any]], gaps: list[dict[str, Any]], ) -> list[dict[str, str]]: """Generate risk assessment based on gaps and coverage patterns. Args: analyzed_reqs: List of analyzed requirement dictionaries. gaps: List of gap analysis entries. Returns: List of risk entries with impact and mitigation. """ risks = [] critical_gaps = [g for g in gaps if g["severity"] == "critical"] if critical_gaps: risks.append({ "risk": "Critical requirement gaps", "impact": "high", "description": f"{len(critical_gaps)} must-have requirements not fully met", "mitigation": "Prioritize engineering effort or partner integration for gap closure", }) total_effort = sum(r["effort_hours"] for r in analyzed_reqs if r["coverage_status"] != "full") if total_effort > 200: risks.append({ "risk": "High customization effort", "impact": "high", "description": f"{total_effort} hours estimated for non-full requirements", "mitigation": "Evaluate resource availability and timeline feasibility before committing", }) elif total_effort > 80: risks.append({ "risk": "Moderate customization effort", "impact": "medium", "description": f"{total_effort} hours estimated for non-full requirements", "mitigation": "Phase implementation and set clear expectations on delivery timeline", }) planned_count = sum(1 for r in analyzed_reqs if r["coverage_status"] == "planned") if planned_count > 3: risks.append({ "risk": "Roadmap dependency", "impact": "medium", "description": f"{planned_count} requirements depend on planned product features", "mitigation": "Confirm roadmap timelines with product team; include contractual commitments if needed", }) partial_count = sum(1 for r in analyzed_reqs if r["coverage_status"] == "partial") if partial_count > 5: risks.append({ "risk": "Workaround complexity", "impact": "medium", "description": f"{partial_count} requirements need workarounds or configuration", "mitigation": "Document workarounds clearly; plan for native support in future releases", }) if not risks: risks.append({ "risk": "No significant risks identified", "impact": "low", "description": "Strong coverage across all requirement categories", "mitigation": "Maintain standard engagement process", }) return risks def analyze_rfp(data: dict[str, Any]) -> dict[str, Any]: """Run the complete RFP analysis pipeline. Args: data: Parsed RFP data with requirements array. Returns: Complete analysis results dictionary. """ rfp_info = { "rfp_name": data.get("rfp_name", "Unnamed RFP"), "customer": data.get("customer", "Unknown Customer"), "due_date": data.get("due_date", "Not specified"), "strategic_value": data.get("strategic_value", "medium"), "deal_value": data.get("deal_value", "Not specified"), } # Analyze each requirement analyzed_reqs = [analyze_requirement(req) for req in data["requirements"]] # Compute overall scores total_weighted = sum(r["weighted_score"] for r in analyzed_reqs) total_max = sum(r["max_weighted"] for r in analyzed_reqs) overall_coverage = safe_divide(total_weighted, total_max) * 100 # Coverage summary total_count = len(analyzed_reqs) full_count = sum(1 for r in analyzed_reqs if r["coverage_status"] == "full") partial_count = sum(1 for r in analyzed_reqs if r["coverage_status"] == "partial") planned_count = sum(1 for r in analyzed_reqs if r["coverage_status"] == "planned") gap_count = sum(1 for r in analyzed_reqs if r["coverage_status"] == "gap") # Must-have gap count must_have_gaps = sum( 1 for r in analyzed_reqs if r["priority"] == "must-have" and r["coverage_status"] == "gap" ) # Category breakdown category_scores = compute_category_scores(analyzed_reqs) # Gap analysis gaps = generate_gap_analysis(analyzed_reqs) # Bid recommendation bid_recommendation = determine_bid_recommendation( overall_coverage, must_have_gaps, rfp_info["strategic_value"], ) # Risk assessment risks = generate_risk_assessment(analyzed_reqs, gaps) # Effort summary total_effort = sum(r["effort_hours"] for r in analyzed_reqs) gap_effort = sum(r["effort_hours"] for r in analyzed_reqs if r["coverage_status"] != "full") return { "rfp_info": rfp_info, "coverage_summary": { "overall_coverage_percentage": round(overall_coverage, 1), "total_requirements": total_count, "full": full_count, "partial": partial_count, "planned": planned_count, "gap": gap_count, "must_have_gaps": must_have_gaps, }, "category_scores": category_scores, "bid_recommendation": bid_recommendation, "gap_analysis": gaps, "risk_assessment": risks, "effort_estimate": { "total_hours": total_effort, "gap_closure_hours": gap_effort, "full_coverage_hours": total_effort - gap_effort, }, "requirements_detail": analyzed_reqs, } def format_text(result: dict[str, Any]) -> str: """Format analysis results as human-readable text. Args: result: Complete analysis results dictionary. Returns: Formatted text string. """ lines = [] info = result["rfp_info"] lines.append("=" * 70) lines.append("RFP RESPONSE ANALYSIS") lines.append("=" * 70) lines.append(f"RFP: {info['rfp_name']}") lines.append(f"Customer: {info['customer']}") lines.append(f"Due Date: {info['due_date']}") lines.append(f"Deal Value: {info['deal_value']}") lines.append(f"Strategic Value: {info['strategic_value'].upper()}") lines.append("") # Coverage summary cs = result["coverage_summary"] lines.append("-" * 70) lines.append("COVERAGE SUMMARY") lines.append("-" * 70) lines.append(f"Overall Coverage: {cs['overall_coverage_percentage']}%") lines.append(f"Total Requirements: {cs['total_requirements']}") lines.append(f" Full: {cs['full']} | Partial: {cs['partial']} | Planned: {cs['planned']} | Gap: {cs['gap']}") lines.append(f"Must-Have Gaps: {cs['must_have_gaps']}") lines.append("") # Bid recommendation bid = result["bid_recommendation"] lines.append("-" * 70) lines.append(f"BID RECOMMENDATION: {bid['decision']}") lines.append(f"Confidence: {bid['confidence'].upper()}") lines.append("-" * 70) for reason in bid["reasons"]: lines.append(f" - {reason}") lines.append("") # Category scores lines.append("-" * 70) lines.append("CATEGORY BREAKDOWN") lines.append("-" * 70) lines.append(f"{'Category':<25} {'Coverage':>8} {'Full':>5} {'Part':>5} {'Plan':>5} {'Gap':>5} {'Effort':>7}") lines.append("-" * 70) for cat, scores in result["category_scores"].items(): lines.append( f"{cat:<25} {scores['coverage_percentage']:>7.1f}% " f"{scores['full']:>5} {scores['partial']:>5} " f"{scores['planned']:>5} {scores['gap']:>5} " f"{scores['effort_hours']:>6}h" ) lines.append("") # Gap analysis gaps = result["gap_analysis"] if gaps: lines.append("-" * 70) lines.append("GAP ANALYSIS") lines.append("-" * 70) for gap in gaps: severity_marker = "!!!" if gap["severity"] == "critical" else ( "!!" if gap["severity"] == "high" else "!" ) lines.append(f" [{severity_marker}] {gap['id']}: {gap['requirement']}") lines.append(f" Category: {gap['category']} | Priority: {gap['priority']} | Status: {gap['coverage_status']}") lines.append(f" Effort: {gap['effort_hours']}h | Mitigation: {gap['mitigation']}") lines.append("") # Risk assessment risks = result["risk_assessment"] lines.append("-" * 70) lines.append("RISK ASSESSMENT") lines.append("-" * 70) for risk in risks: lines.append(f" [{risk['impact'].upper()}] {risk['risk']}") lines.append(f" {risk['description']}") lines.append(f" Mitigation: {risk['mitigation']}") lines.append("") # Effort estimate effort = result["effort_estimate"] lines.append("-" * 70) lines.append("EFFORT ESTIMATE") lines.append("-" * 70) lines.append(f" Total Effort: {effort['total_hours']} hours") lines.append(f" Gap Closure Effort: {effort['gap_closure_hours']} hours") lines.append(f" Supported Effort: {effort['full_coverage_hours']} hours") lines.append("") lines.append("=" * 70) return "\n".join(lines) def main() -> None: """Main entry point for the RFP Response Analyzer.""" parser = argparse.ArgumentParser( description="Analyze RFP/RFI requirements for coverage, gaps, and bid recommendation.", formatter_class=argparse.RawDescriptionHelpFormatter, epilog=( "Coverage Categories:\n" " Full (100%) - Requirement fully met\n" " Partial (50%) - Partially met, workaround needed\n" " Planned (25%) - On roadmap, not yet available\n" " Gap (0%) - Not supported\n" "\n" "Priority Weights:\n" " Must-Have (3x) | Should-Have (2x) | Nice-to-Have (1x)\n" "\n" "Example:\n" " python rfp_response_analyzer.py rfp_data.json --format json\n" ), ) parser.add_argument( "input_file", help="Path to JSON file containing RFP requirements data", ) parser.add_argument( "--format", choices=["json", "text"], default="text", dest="output_format", help="Output format: json or text (default: text)", ) args = parser.parse_args() data = load_rfp_data(args.input_file) result = analyze_rfp(data) if args.output_format == "json": print(json.dumps(result, indent=2)) else: print(format_text(result)) if __name__ == "__main__": main()

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