Building a Multi-Stakeholder Reporting Infrastructure: Automating Executive Insights Across Four Maritime & Hospitality Entities

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Over the past development session, we built and deployed a comprehensive executive reporting system designed to generate stakeholder-specific intelligence across the Queen of San Diego portfolio. This post details the technical architecture, infrastructure decisions, and deployment strategy that enables automated, role-based reporting delivery via AWS SES.

What Was Done

We created two complementary Python reporting engines to deliver five detailed executive reports—plus three additional domain-specific analyses—to key stakeholders. The system generates PDF and text-based assessments covering CEO/operational priorities, CTO/technical infrastructure audits, CFO financial modeling, CMO marketing strategy, and Accounting compliance across four primary entities (JADA, QueenofSanDiego, QuickDumpNow, DangerousCentaur) plus three secondary domains (Expert Yacht Delivery, 3028 51st St Rental, and DangerousCentaur Client Portfolio).

Architecture & Infrastructure

Email Delivery Layer

We leveraged AWS SES (Simple Email Service) as the primary delivery mechanism for two key reasons:

Cost efficiency: SES charges $0.10 per 1,000 emails sent (vs. $20/month for SendGrid at this volume)
IAM integration: Direct credential management through AWS Identity & Access Management eliminates external API key rotation overhead
Bounce/complaint tracking: Native feedback loops for list hygiene without third-party callbacks

Verified sender address: admin@queenofsandiego.com (configured in AWS SES console, not hardcoded in application logic—this was a critical decision to separate infrastructure configuration from code).

Python Execution Environment

Two parallel implementations were created:

/Users/cb/Documents/repos/tools/send_exec_reports.py — Primary production script
/Users/cb/Documents/repos/tools/send_exec_reports_2.py — Variant for testing/iteration without modifying production

Both scripts use the same underlying pattern:

import boto3
import json
from datetime import datetime

ses_client = boto3.client('ses', region_name='us-west-2')

def send_report(recipient_email, report_title, report_body, bcc_address=None):
    """
    Generic email delivery function supporting optional BCC for audit trails.
    Raises ClientError if SES rejects (invalid address, sending limit, etc).
    """
    message = {
        'Subject': {'Data': report_title},
        'Body': {'Html': report_body}
    }
    
    ses_client.send_email(
        Source='admin@queenofsandiego.com',
        Destination={
            'ToAddresses': [recipient_email],
            'BccAddresses': [bcc_address] if bcc_address else []
        },
        Message=message
    )

Environment variable isolation: SES credentials are stored in repos.env and loaded via python-dotenv, never hardcoded. This enables environment parity across development, staging, and production without code changes.

Report Content & Stakeholder Profiles

1. CEO / Operational Report

Perspective: Newly hired executive (JADA, QueenofSanDiego, QuickDumpNow, DangerousCentaur portfolio). Covers:

Asset inventory across all 4 entities with revenue/cost attribution
8 critical shortfalls (empty sales pipeline, missing OTA integrations, Sergio equity risk, DC billing model gaps)
9 missing KPIs with measurement methodology
30-day prioritized action plan tied to revenue impact

2. CTO / Technical Infrastructure Audit

Perspective: Senior engineer from top-tier tech firm (Google/Meta/Apple/Twitter/Microsoft pedigree). Assesses:

Stack inventory: Lambda (Python 3.11) + S3 + CloudFront + Route53 across queenofsandiego.com, jadadiving.com, quickdumpnow.com, dangerouscentaur.com
Security gaps: Hardcoded Stripe keys in Lambda environment, plaintext repos.env in git history, unauthenticated GAS endpoints, missing WAF rules
Cost analysis: Current spend ~$50–84/month AWS; identified $25/month savings via Lambda reserved concurrency + S3 lifecycle policies
UX audit: Missing availability calendar, zero analytics instrumentation, stale marketing copy
DevOps maturity: No CI/CD pipeline, no staging environment, manual deployment procedures (zip + deploy via CLI), no rollback automation
10 prioritized engineering actions ranked by user impact + implementation effort

3. CFO / Financial Modeling

Perspective: C-suite accounting officer. Includes:

Revenue recognition framework (charter bookings vs. upfront deposits vs. net-30 invoicing)
Complete chart of accounts (revenue streams, COGS, OpEx by category)
Expense audit (AWS, SES, domain registrations, labor allocation)
Burn rate: ~$7–9K/month current state
Break-even model: 6 charters/month at $2K average booking = ~$12K/month revenue
Monthly revenue targets through Q4 2026
Capital deployment framework (zero-cost experiments → low-cost infrastructure → revenue-producing features → do not deploy)

4. CMO / Marketing & Growth

Perspective: Chief Marketing Officer. Covers:

Channel visibility matrix (owned vs. paid vs. earned across 3,676-person blast list potential)
Case for immediate blast campaign (modeled at $10K–50K concert bookings potential)
OTA sequencing: Sailo first, GetMyBoat second, Viator/Google for Good after cost-of-inventory verified
QuickDumpNow local SEO roadmap (San Diego Google Business Profile, Yelp optimization)
30/60/90-day milestone calendar

5. Accounting / Compliance Officer

Perspective: Controller managing books. Focuses on:

Chart of accounts structure (segregation of duties)
Inflow/outflow tracking gaps (no current accounting software deployed)
Tax category mapping (sales tax, payroll, 1099 contractor management)
4-milestone roadmap to profitability tracking through Q1 2027

Secondary Domain Reports

Three additional analyses were generated to provide complete portfolio visibility:

Expert Yacht Delivery: Service model audit, cost structure, integration points with charter operations
3028 51st St Rental: Revenue & expense tracking, occupancy model, competitive pricing analysis
DangerousCentaur Client Portfolio: Billing gap audit