Cam Anderson is a systems engineer and managing principal at Climate & Waste Systems Advisory and chief technology officer at Compoz.
U.S. cities are running more waste reduction and diversion pilots than ever before.
Smart composting trials, food-scrap separation programs, contamination monitoring and data-driven reporting systems are being launched with urgency and good intent.
Many of these pilots show early promise. And then, quietly, they stall.
This is rarely because the technology fails. More often, it is because pilots are designed around an assumption that turns out to be incorrect: that once the right tools or reporting systems are in place, better diversion will follow.
In practice, the biggest constraints appear long before the collection trucks roll.
The upstream reality most pilots underestimate
Most municipal waste pilots focus downstream. They measure contamination rates, track participation, optimize routes and report diversion metrics.
But in food-waste programs especially, a large share of the variability that determines success is introduced upstream — inside homes and multifamily buildings — long before anyone collects the waste.
Participation is inconsistent. Sorting behavior varies. Storage conditions differ. In apartments, space and odor constraints reshape resident engagement. By the time material reaches the curb, the outcome has largely been determined.
The U.S. Environmental Protection Agency has repeatedly identified food waste as one of the largest contributors to landfill methane emissions while also noting wide variability in contamination and participation across housing types. Yet most municipal interventions occur after this variability has already entered the system.
That gap — between where behavior is set and where policy intervenes — is where many pilots begin to lose control.
Why data alone can’t solve diversion challenges
Cities have made meaningful investments in measurement. Dashboards are more sophisticated. Reporting is more standardized. Diversion estimates are more precise. But visibility does not equal control.
When upstream conditions are unstable, data tends to describe problems after they occur rather than prevent them. Operators can see contamination spikes or declining participation, but they often have limited leverage to influence the behavior that caused them. Municipal staff then face rising operational costs, public pressure and political scrutiny when pilot results drift from initial projections. The technology may work. The reporting may be accurate. But the system feeding the program remains unpredictable.
A pilot works in a controlled trial. Participants are motivated. Conditions are carefully managed. Results look encouraging. Then the program expands.
As it moves into broader neighborhoods — including multifamily housing, mixed-use buildings and diverse household types — variability reappears. Participation fluctuates. Inputs degrade. Operational costs increase.
In some cases, cities pause expansion not because the concept failed, but because upstream conditions were never stabilized.
This pattern is not unique to one jurisdiction. It reflects a structural mismatch between how pilots are designed and how household waste systems actually behave.
Designing for how cities actually operate
What if diversion pilots treated upstream stabilization as part of the intervention itself?
Instead of assuming predictable participation, pilots could explicitly test mechanisms that reduce variability at the source, before optimizing collection routes, reporting dashboards or enforcement systems.
This does not require heavier mandates. It requires acknowledging that predictability is not a given, it is an outcome that must be built.
Energy and infrastructure research consistently shows that advanced optimization performs best when underlying systems are stable. Waste diversion programs are no different.
Stabilize inputs first. Optimize second.
Municipal waste departments operate under tight budgets, staffing constraints and political oversight. Pilots that succeed long-term reflect these realities.
That means for success, scaling such programs must:
- Recognize the limits on municipal control of how residents act inside their homes.
- Treat participation variability as a design variable, not a footnote.
- Use pilots as learning environments, not as proof-of-concept marketing
Cities do not lack innovation. They lack upstream alignment.
Until diversion pilots account for the conditions that shape waste behavior before collection, scaling will remain fragile — no matter how sophisticated the downstream technology becomes.
