Context
SmartAccess was my capstone project for the Kellogg Professional Certificate in Product Management (2024), a solo project developed over 6 months of coursework, culminating in a full venture plan for a smart-building platform: "Intelligent Habitats for a Green Future." The core idea: make commercial buildings measurably more efficient by layering AI on top of existing infrastructure and low-cost sensors, rather than requiring buildings to rip out and replace what they already have.
Challenge
Commercial buildings waste a significant share of the energy they consume, and existing "smart building" technology doesn't actually close that gap: it can't measure usage, take automated action, or apply modern AI/ML, and what does exist is often too expensive for most buildings to adopt. (The two anchor stats behind this, 40% of US energy consumption comes from buildings and 30% of energy in commercial buildings is wasted, were sourced from public research, not originated by me.)
Role & Constraints
Solo project, full ownership end to end: market sizing, product vision, technical architecture, business model, MVP scope, and go-to-market roadmap, developed over 6 months as the capstone deliverable for the certificate program.
Approach
Market sizing: rather than sizing the broadest possible global market, I narrowed the serviceable-obtainable market to C40 Climate Pact cities in North America (LA, SF, Toronto, Vancouver, NYC), deliberately choosing progressive, climate-forward cities where building owners would already be primed to adopt this kind of technology, rather than chasing total addressable market size for its own sake.
Build vs. buy on hardware: the core design principle was making existing buildings more efficient cost-effectively, not requiring a hardware overhaul. I chose to build on top of what a building already had (existing WiFi, cameras) and supplement only where needed with additional low-cost IoT sensors, rather than designing proprietary hardware from scratch. This kept the cost and adoption barrier low for the customer.
Business model: that build-vs-buy decision directly shaped the business model: a SaaS-plus-lease structure, rather than an upfront hardware sale, since leasing lowered the cost and commitment for a building that already had most of the needed infrastructure in place.
Execution
The capstone scoped, rather than built, an MVP: a SaaS analytics dashboard for building managers, a tenant mobile app, and monitoring on existing WiFi/IoT sensors, positioned as the proof-of-concept layer ahead of the fuller roadmap (edge controller, camera integration, AI/ML-based add-ons like predictive maintenance and facial recognition). No product was built; this was product strategy and planning, not implementation.
Outcome
This was a fictional venture built entirely for the capstone: no real product was built, no customers were onboarded, and no revenue was generated. (The "outcomes" language in the deck itself, such as onboarding, deployment, and revenue generation, describes the plan's projected future state, not anything that actually happened; this is flagged explicitly here so it's never mistaken for a real result.) The concrete outcome: the full plan was presented to a broader audience and received a full grade for both the project and the course.
Reflection
If I rebuilt this today, I'd push the "use what's already there" principle even further: designing the whole platform around off-the-shelf signals (WiFi, existing IoT devices, thermostats, cameras) and cheap sensors plus AI, with effectively no proprietary hardware investment at all. That would make the product more attainable and lower-friction for a building to adopt, rather than asking them to invest heavily in new hardware even in a supplementary role.