TeslaGrid — Supercharger Network & Fleet Reliability
TeslaGrid is an internal-facing reliability cockpit designed for Tesla's charging and fleet operations teams. It surfaces real-time network health, predicts congestion and outages, and ranks work so teams fix what hurts drivers the most.
Primary Problem
Unpredictable charging experience
Outages and congestion erode trust in the Supercharger network.
Who I Designed For
Charging & Fleet Ops
Network ops, maintenance schedulers, and regional leads.
My Role
Product Manager
Discovery → framing → flows → success metrics; built as a live demo.
This app is built as a portfolio artifact. Names and numbers are illustrative, but the product thinking and flows reflect how I would approach an internal reliability tool at Tesla.
Context
The charging reliability and network ops problem
Tesla's brand promise is built on confidence: drivers trust that the car will get them from A to B without drama. But that promise depends on a global Supercharger network that can quietly fail—through outages, congestion, or slow repairs. When reliability is opaque, teams are stuck firefighting instead of strategically managing the network.
Pain points today
- Network health is fragmented across monitoring tools, tickets, and spreadsheets.
- Maintenance prioritization is reactive instead of driven by customer impact and fleet behavior.
- Congestion is discovered after the fact, not forecasted around holidays or events.
- Ops teams can't easily answer "What's breaking the experience this week?"
What TeslaGrid aims to do
- Provide a single, ranked view of network health and incidents across the Supercharger network.
- Predict congestion and outages before they materially impact driver experience.
- Prioritize work orders by "customer minutes saved" instead of first-in-first-out.
- Give ops, regional leads, and support a shared source of truth when things go wrong.
Users
Who TeslaGrid is for
Network Operations Lead
Owns overall Supercharger reliability metrics.
Needs
- Single view of station health and trends.
- Confidence that teams are fixing the right work.
What TeslaGrid gives them
A ranked backlog of incidents by customer impact, with forecast overlays for upcoming risk.
Maintenance Scheduler
Plans field technician routes across regions.
Needs
- Clarity on which sites matter most today.
- Tools to sequence work without guesswork.
What TeslaGrid gives them
A prioritized job list with customer-minutes-saved, travel constraints, and SLAs baked in.
Regional & Fleet Leads
Own experience in a geography or fleet segment.
Needs
- Answers to “what broke and where?” in minutes.
- Evidence for prioritizing investments across stations.
What TeslaGrid gives them
Regional dashboards showing reliability, congestion, and incident history for their territory or fleet.
Solution
An opinionated reliability cockpit for the Supercharger network
TeslaGrid is designed around a few clear product pillars. Instead of being "just a dashboard," it encodes how Tesla should reason about reliability: from the network level, down to a single station, with customer impact as the default lens.
Network Health
Real-time "stoplight" view of every station, with trends on sessions, failures, and throughput.
Impact-Based Prioritization
Incidents and maintenance tasks ranked by customer-minutes at risk, not just severity codes.
Forecasting
7/30-day projections of load vs capacity, with events and seasonality layered in.
Shared Source of Truth
A single workspace where ops, maintenance, and regional leads see the same story.
Flows
Key flows I designed the demo around
The live demo focuses on three flows that illustrate how TeslaGrid changes day-to-day work for operations teams.
1. Morning network stand-up
Goal: Align on what is breaking the experience today.
Outcome: Teams start the day with a clear, shared idea of the most critical work, grounded in impact not anecdotes.
2. Prioritizing maintenance routes
Goal: Sequence field technician visits to maximize impact.
Outcome: Technicians spend more time fixing the worst problems and less time driving to low-impact jobs.
3. Holiday congestion forecast
Goal: De-risk upcoming spikes in demand.
Outcome: Instead of being surprised by holiday congestion, teams proactively mitigate the worst hotspots.
Demo
What the live demo actually shows
In the demo, these flows are represented as simple, opinionated screens — enough to show thinking without pretending this is a production system.
Network Health Overview
A table or map-style view of Supercharger stations with status, utilization band, and trend arrows. Filters for region, severity and forecasted risk.
Incident & Work Order Queue
Ranked list of incidents with impact scores, suggested priority, and a simple drill-down panel for station details and history.
Demand & Capacity Forecast
Lightweight chart of sessions vs capacity over time, with highlighted windows where thresholds are exceeded and callouts for events.
Outcomes
Target impact and how I’d measure it
Because this is a portfolio artifact, the numbers here are modeled — but the measurement mindset is the same as I'd use in production.
Target reduction in downtime
15–25%
Decrease in customer-facing downtime hours at high-criticality stations.
Faster time-to-fix
20–30%
Reduction in median time from incident detection to first technician touch.
Congestion risk coverage
80%+
Share of projected congestion events with a mitigation plan in place.
Execution
How I approached TeslaGrid as a product manager
- Framed the problem in terms of driver trust and brand promise, not just internal ops metrics.
- Defined personas and responsibilities across network ops, maintenance, and regional leads to avoid "dashboard for everyone" bloat.
- Chose three anchor flows (morning stand-up, route planning, holiday prep) that tell a complete reliability story in a short demo.
- Scoped the UI intentionally small — enough screens to show judgment and tradeoffs, without pretending this is a full production tool.
- Anchored on measurable outcomes (downtime, time-to-fix, congestion coverage) so the app reads like a product, not just a visualization.
In a real engagement, this artifact would sit alongside discovery notes, data architecture, and an incremental rollout plan. For the portfolio, the goal is to make those decisions legible in a single, navigable experience.