In early 2022, the Greater Amman Municipality (GAM) faced a growing waste crisis. Given its population of 4.5 million people generating approximately 3,000 tons of solid municipal waste daily, half of Jordan’s total, the city’s rapid growth had significantly outpaced its waste management infrastructure. In response to this challenge, a remarkable two-year transformation using Problem-Driven Iterative Adaptation (PDIA) took place that not only improved waste collection efficiency, but also fundamentally changed how departments collaborated across GAM’s large bureaucracy.
When the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) suggested using PDIA as part of their Solid Waste Management in Jordan (SoWas) project, the idea was met with initial resistance. Having experienced previous reform efforts with mixed results, many officials were skeptical that this new approach could help the city overcome entrenched issues. Strong leadership ultimately made the difference. The active involvement of the Mayor and City Manager in PDIA meetings demonstrated the administration’s serious commitment to the work and boosted team morale regarding the initiative.
Using a systematic approach to problem deconstruction using fishbone diagrams, a cross-departmental team identified six root causes of their waste management inefficacies. However, instead of attempting to solve all issues simultaneously, the team used a change space analysis to identify two targeted entry points: Addressing decision-making hesitation due to lack of data and improving needs-based training. This selective approach allowed for meaningful progress despite limited resources.
The implementation process was distinguished by its emphasis on iteration and learning. Starting from a pilot in Zahran district, the team mapped container location and collection routes before methodically expanding to all 22 districts. By April 2024, they had mapped more than 41,000 containers across Amman, with comprehensive data on locations, types, and collection schedules that was previously unavailable to decision-makers. The project resulted in a 65% reduction in fuel costs and 35% lower unit costs for waste collection in the pilot area.
Perhaps most remarkably, this initiative spurred broader organizational transformation. Interdepartmental collaboration improved massively through changes in working practices rather than formal restructuring. Direct communication channels replaced lengthy approval chains, reducing tender processing time from three months to one month. In fact, a survey found that 74% of staff experienced improved cross-departmental collaboration, signaling a more responsive organization.
The implementation wasn’t without challenges, however. There were delays due to leadership changes, scheduling conflicts, and bureaucratic hurdles. Indeed, the meta-problem of long processes that the Task Force had identified as a root challenge impacted the PDIA implementation itself. Nonetheless, persistence and support from senior leadership helped the team move ahead.
Today, the GAM Task Force has become a model for public sector reform. In April 2024, a survey found that 84% of Task Force members believe PDIA will continue to be used within GAM, which suggests a lasting cultural shift toward iterative problem-solving.
APRIL 2024
This case offers several key implementation lessons for practitioners of adaptive policy work:
- The importance of selective entry points based on the systematic analysis of authority, acceptance, and ability.
- The power of iteration in building workable solutions in complex policy environments.
- The need for leadership buy-in and support throughout implementation.
- The potential for targeted improvements to encourage broader organizational change.
- The effectiveness of using local systems and resources rather than relying on external consultants.
To learn more, read the case Using PDIA to Improve Waste Management in Amman.
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