Why Fragmentation Caps Uptime Before Technology Does
In most charging organizations, reliability improvement is framed as an operational exercise. If uptime stalls, the instinct is to add effort: more technicians, more dashboards, more monitoring, more escalation paths, more analytics. When uptime rises, the strategy is validated. When it plateaus, the assumption is that execution needs tightening.
But reliability systems do not behave like mechanical systems. They behave more like capital systems. They exhibit diminishing returns.
At some point, each additional point of uptime becomes harder to achieve than the last, and disproportionately more expensive. Not because the workforce has become less competent or the hardware more fragile, but because the remaining failures are structurally different from the early ones. The easy reliability—the misconfigurations, the obvious resets, the procedural gaps—has already been captured. What remains are ambiguous, cross-boundary, multi-party problems that resist clean diagnosis.
This is what I mean by an economic governor.
The phrase “cost per unit uptime” is not an accounting term; it is a way of describing the marginal cost required to increase uptime by one percentage point. Moving from 95% uptime to 97% often involves operational hygiene: better triage discipline, clearer ownership boundaries, improved dispatch sequencing. Moving from 97% to 99% is another matter entirely. At that margin, the failures that remain are typically cross-vendor, data-constrained, warranty-sensitive, and politically entangled. Resolving them may require multiple truck rolls, engineering escalation at the manufacturer, coordination with site hosts, reconstruction of incomplete telemetry, and negotiation across contractual lines.
The overall improvement of reliability is smaller, but the effort required to produce it is materially larger. The marginal cost curve bends upward. The governor begins to assert itself.
When I was at UCLA’s Anderson School, one of the earliest lessons they taught us young, aspiring MBAs was the concept of opportunity cost. Every allocation of capital implicitly rejects an alternative. A dollar spent in one direction is a dollar not deployed somewhere else. In practice, this idea is easy to accept in theory and uncomfortable to apply in operations. Charging networks face this tradeoff continuously. Capital deployed to push uptime from 97% to 99% is capital not deployed toward new site expansion, grid upgrades, software improvement, site amenities, or customer acquisition. The real decision is not whether uptime can be improved further; it is whether the incremental improvement is worth more than the next best alternative use of that capital.
If the marginal effort required to secure the next uptime point requires disproportionate coordination across fragmented vendors, incomplete telemetry streams, and ambiguous ownership boundaries, then the opportunity cost of that improvement rises sharply. Eventually, leadership encounters a ceiling: spending increases, but the incremental reliability gain shrinks. The governor is not technological. It is economic.
Fragmentation is what tightens that governor.
Fragmentation is often described as a technical inconvenience—different hardware vendors, different CSMS providers, different firmware baselines, different data exposure models. But its more consequential impact is economic. When data lives in silos, when telemetry exposure varies across EVSE manufacturers, when warranty ownership is unclear and SLA accountability spans organizational boundaries, coordination cost increases. Each reliability event must be negotiated across entities that do not share a single operational truth.
None of this is malicious. It is structural. The ecosystem evolved in layers with Tier 3 field service evolving last, and those layers do not align cleanly. But the effect is predictable: as uptime targets rise, the coordination burden rises with them. Dispatch becomes slower to authorize. Escalations become harder to resolve. The remaining failures demand cross-organizational alignment rather than simple technical intervention.
The industry is not unaware of this problem. Cross-industry initiatives have emerged specifically to reduce fragmentation at foundational layers. Organizations such as CharIN have worked to harmonize charging standards and certification processes, improving interoperability at the vehicle-to-charger interface. Collaborative efforts like the ChargeX Consortium subject multi-vendor combinations to structured validation, recognizing that interoperability must be tested, not assumed. These efforts have meaningfully reduced certain classes of incompatibility and raised the floor of baseline reliability across the industry.
But it is important to be precise about what these initiatives accomplish. Standards bodies and interoperability consortia reduce fragmentation at the protocol and certification layer. They ensure that components can speak to one another in defined ways. They do not eliminate operational fragmentation across data access rights, warranty boundaries, escalation authority, or dispatch accountability. They raise the baseline. They do not remove the governor.
If reliability improvement is constrained by rising marginal cost, then the strategic objective is not simply to exert more effort. It is to lower the marginal cost curve itself. That requires reducing the coordination overhead that makes the last few points of uptime so expensive. It requires clearer responsibility boundaries, better alignment between telemetry exposure and service authority, significantly increased cyber protections, and operational layers that reduce reconciliation friction without requiring every participant to abandon their existing systems.
Reliability does not plateau because chargers stop breaking less frequently. It plateaus because the system required to resolve the remaining failures becomes economically irrational to operate at scale. Until fragmentation is addressed not only at the protocol layer but at the operational and contractual layers, the final increments of uptime will continue to demand disproportionate capital.
The governor, in other words, is not mechanical. It is structural.
And structural limits do not move unless the structure itself changes.
