This report presents the findings of the Solid Waste Management data collection survey conducted in Cluster 6 of Kathmandu Metropolitan City (KMC), which comprises Wards 10, 31, 32. The primary objective of this study was to collect structured, ward-level data to support evidence-based planning and decision-making for local governance and solid waste service delivery.

The data collection was carried out using a digital mobile application by trained surveyors selected through the KMC Shram Bank system. The survey was organized into two major data modules — Waste Management and Garbage Vulnerable Points (GVP) — supplemented by auxiliary data on road networks, religious sites, parks, and water bodies gathered from respective local authorities.

Each module captured specific, measurable indicators relating to local infrastructure, waste generation patterns, management practices, and community-level conditions. Where required, local officers and police personnel accompanied survey teams to facilitate community coordination and verify data authenticity. The resulting dataset provides a comprehensive baseline for identifying service gaps, prioritizing interventions, designing waste collection routes, and establishing an equitable fee structure across all wards of Cluster 6.

This report is organized into five major modules, each addressing a distinct dimension of the waste management survey. The table below summarizes the scope of each module:

Table 2.1 — Report Modules and Scope

Module	Title	Description	Data Source
1	Waste Data Collection & Analysis	Structured survey of households and commercial establishments covering waste generation quantities, waste types, management practices, segregation behaviour, and socio-economic profiling. Includes both Waste Profile and Economic Profile sub-modules.	Field survey (digital app)
2	Garbage Vulnerable Points (GVP)	Identification and mapping of illegal dumping sites, open waste accumulation areas, and vulnerable public spaces that require priority intervention and monitoring.	Field observation & community reporting
3	Road Network Analysis	Classification of roads by width, surface type, and pavement condition to support vehicle deployment planning and waste collection route design.	KMC GIS / field survey / OSM
4	Temples, Parks & Ponds	Inventory of religious sites, public open spaces, and water bodies requiring dedicated waste collection schedules, particularly during major festivals.	Ward office records / field visit
5	Economic Profile & Fee Schedule	Calculation of monthly waste service fees for commercial establishments (based on actual waste volume and KMC tariff schedule) and households (based on family size). Includes ward-wise revenue projections.	Derived from survey + KMC fee schedule

Table 3.1 — Abbreviations Used in This Report

Abbreviation	Full Form
KMC	Kathmandu Metropolitan City
GVP	Garbage Vulnerable Point
GIS	Geographic Information System
GPS	Global Positioning System
SWM	Solid Waste Management
IEC	Information, Education and Communication
TPD	Tonnes Per Day
HH	Household
B.S.	Bikram Sambat (Nepali Calendar)
MRF	Material Recovery Facility
TOR	Terms of Reference
PAN	Permanent Account Number
VAT	Value Added Tax
NPR	Nepalese Rupee
OSM	OpenStreetMap
EMD	Environment Management Department

Cluster 6 comprises Wards 10, 31, 32 of Kathmandu Metropolitan City. The cluster-based approach was adopted to organize data collection in a systematic and operationally manageable structure, enabling better coordination, progress monitoring, and inter-ward comparison. Enumerators were selected through the KMC Shram Bank and received structured training prior to field deployment.

Table 4.1 — Cluster 6 Key Attributes

Attribute	Value
Cluster Number	Cluster 6
Wards Covered (3 wards)	Ward 10Ward 31Ward 32
Total Cluster Area	11.300 km²
Estimated Population	246,220 residents
Estimated Households	49,244
Transfer Station Location	Ward 32, Manohara
Total Survey Records	Loading…
Households Surveyed	Loading…
Commercial Establishments Surveyed	Loading…
Estimated Daily Waste (TPD)	Loading…
Total GVP Sites Recorded	Loading…
Religious Sites / Temples	Loading…
Total Road Network Length	Loading…

Kathmandu Metropolitan City (KMC) conducted a comprehensive field survey of households and commercial businesses across Cluster 6 to collect reliable, ward-level data on waste generation quantities, waste composition, and current management practices. The data collection was carried out using a structured digital mobile application, ensuring systematic coverage, real-time GPS tagging, and consistent data entry across all wards.

In addition to waste-specific data, the survey recorded household profiles (family size, contact details) and business profiles (TypeID, PAN/VAT), which support both operational planning and the calculation of equitable service fees. Locations of irregular waste disposal sites (GVPs) were also documented during the same field visits.

The specific objectives of the waste data collection module are as follows:

1. Collect ward-level waste data — Gather accurate, granular information on the type, quantity, and daily generation of waste from households and commercial establishments in Cluster 6.
2. Document waste management practices — Record the existing disposal and management methods used by generators, including door-to-door collection vehicle use, composting, and rooftop farming.
3. Profile households and commercial entities — Collect essential background data including household size, business category, and identification numbers (PAN/VAT) required for service billing.
4. Assess waste segregation compliance — Determine the rate of source segregation at household and commercial levels against the 95% target set in the KMC service contract.
5. Support data analysis and reporting — Organize and verify collected data in a systematic manner to enable evidence-based operational planning and monitoring.

The Cluster 6 survey area was geographically divided into systematic collection zones, with each zone covering one or more wards. Each division was assigned 4–5 surveyors to ensure efficient and consistent areal coverage. GPS coordinates were recorded for each surveyed unit with an accuracy of approximately ±50 metres. The spatial distribution of collection points across Wards 10, 31, 32 confirms comprehensive coverage. Ward boundaries used in the study align with KMC administrative divisions, and data density maps were used during the collection period to monitor progress and identify uncovered zones.

Surveyors were recruited from applicants registered in the KMC Shram Bank based on predefined eligibility criteria. All selected individuals received an orientation covering survey objectives, data collection protocols, ethical guidelines, and hands-on training in the use of the mobile data collection application. Each surveyor was assigned a specific ward or zone and provided with a printed ward map and field manual.

During field visits, surveyors used the mobile application to record structured data for each household and business unit visited. Data recorded included waste generation estimates, waste type, management practices, disposal payment status, waste segregation behaviour, and GPS location. Photographs of PAN cards or household representatives were captured for identity verification. Data was submitted in real time to the KMC central server via mobile data connection.

Local ward office staff and, where necessary, police personnel accompanied survey teams during certain visits. Their presence facilitated community coordination, ensured surveyor safety, and helped access restricted premises. Ward representatives and local community leaders assisted in locating households and businesses that had unclear addresses or had recently relocated.

A dedicated data management team conducted continuous quality reviews of submitted records. This included identification and correction of: incomplete entries, duplicate records, GPS coordinate anomalies (e.g., coordinates outside ward boundaries), and multilingual inconsistencies in the TypeID and Tole name fields (Nepali/English). Errors were cross-verified with field surveyors before finalization. Records with irrecoverable data quality issues were flagged and excluded from quantitative analysis.

The digital survey form was structured into four categories of questions, tailored to the type of entity being surveyed:

Table 5.1 — Survey Question Categories

Category	Applies To	Fields Collected
6.1 Household Information	HH records	Full name of head of household; phone number; family size (number of kitchens/families including tenants)
6.2 Business Information	Commercial records	Business name; TypeID (business category); PAN/VAT registration number; mobile contact number
6.3 Location & Documentation	All records	GPS coordinates (±50 m accuracy); tole (locality) name; photograph of PAN card or household representative
6.4 Waste Management	All records	Total waste generated (weight category); type of waste (organic / recyclable / hazardous / other); current management practice; waste segregation behaviour; illegal disposal awareness; monthly payment for disposal services

All survey data for Cluster 6 (Wards 10, 31, 32) was gathered through a structured digital field survey using a mobile data collection application (ODK-based platform). Each field collector was equipped with a GPS-enabled smartphone loaded with a standardised digital form covering both Household and Commercial establishment categories. Collectors were deployed ward-by-ward under the supervision of the Kathmandu Metropolitan City — Environment Management Department.

The survey instrument captured the following information for each entry:

• Entity identification — full name, mobile number, citizenship/NID number, PAN/VAT number (commercial)
• Location — GPS coordinates (latitude/longitude) auto-recorded at time of survey; tole name entered manually
• Waste profile — average daily waste generation category, waste type, waste management method, segregation practice
• Establishment type — TypeID classification for commercial entities; family unit count for households
• Photographic evidence — photograph of premises or waste storage point captured via device camera
• Timing — form start time and end time automatically recorded, allowing per-record duration tracking

Each completed form was automatically assigned a unique Form ID and synchronised to the central KMC data server at the end of each field day. The average time taken to complete one survey record was approximately 4 minutes (range: under 1 minute for simple entries to up to 2 hours for complex commercial premises requiring detailed inspection). GPS location coverage across all wards in this cluster exceeded 96% of collected records, confirming near-complete geographic traceability of the data.

Data collection for Cluster 6 was carried out from 24 Poush 2082 B.S. to 12 Falgun 2082 B.S. (January 2026 – February 2026). Collection duration varied by ward depending on geographic area, population density, number of establishments to be surveyed, and collector availability. Each ward was assigned a dedicated team of collectors who worked systematically through their designated zones, following pre-mapped tole boundaries to ensure complete coverage.

Table 5.2 — Ward-wise Data Collection Timeline

KMC's waste stream consists predominantly of organic/biodegradable materials from residential and market sources, with a significant but smaller fraction of recyclables (plastics, paper, metals) and a minor hazardous component. Commercial areas generate higher proportions of organic and plastic waste relative to household areas. A critical systemic challenge is the absence of source segregation at the point of generation, which reduces recycling efficiency and increases treatment costs. Some records are coded as N/A where respondents were unavailable, unwilling to participate, or lacked information.

KMC has published a standardized fee schedule specifying minimum waste volume parameters and service charges for each business TypeID. During the survey, waste quantity was recorded in kilograms (kg). To align with KMC tariff parameters, kg values are converted to litres using type-specific density values provided by the KMC Environment Department. Once the volume is established, it is compared against the base volume for the business type; if actual daily volume exceeds the base allocation, an additional charge is applied for each increment of excess volume.

For households, the fee is not based on waste quantity but on the number of family units (kitchens) residing at the premises — a larger household generates more waste and therefore pays a higher service charge.

The following table and charts present the ward-level breakdown of surveyed entities in Cluster 6, including household counts, commercial establishment counts, total records, and estimated daily waste generation (TPD).

Table 5.3 — Ward-wise Survey Summary

The distribution of waste generators by daily weight category reveals that the majority of surveyed entities — both household and commercial — fall within the 0–5 kg/day range, consistent with small household units and small retail establishments. Higher-volume generators (15 kg/day and above) are predominantly commercial entities such as restaurants, hotels, and large businesses.

Table 5.4 — Waste Generation by Weight Category and Ward

The composition of waste varies significantly between household and commercial generators, and between wards. Organic waste dominates the overall stream, but recyclable waste contribution is proportionally higher in commercial zones. Statistical testing confirms that both ward location and entity type are significant predictors of waste composition (chi-square tests, p < 0.001).

Table 5.5 — Waste Type Distribution by Ward

This section documents the primary waste disposal method used by each surveyed entity. The two main categories are: (i) collection by KMC-authorized vehicles (door-to-door service), and (ii) self-managed composting or rooftop farming. A significant proportion of records did not capture this field, which represents a data quality gap to be addressed in follow-up surveys.

Table 5.6 — Waste Management Method by Ward

Waste segregation at source is a contractual requirement under the KMC Solid Waste Management service agreement, with a target compliance rate of ≥95%. The survey assessed whether each household and commercial establishment currently segregates waste before disposal.

Table 5.7 — Waste Segregation by Ward

Tole (locality) level analysis identifies the highest-concentration areas within each ward, which are critical for optimising collection routes and prioritising service interventions. The table below lists the top tole by record count for each ward in Cluster 6.

This section analyses the distribution of surveyed entities by type — Household (HH) and Commercial — across each ward. Understanding entity composition is critical for targeted service delivery, differentiated fee schedules, and ward-level resource planning.

Table 5.14 — Entity Type Breakdown by Ward

Data quality assessment was conducted with conditional field logic: fields not relevant to a given entity type are excluded from that type's missing-value calculation. CompanyName and PAN_VAT are assessed for Commercial records only; FamilyCount and Fullname for Household records only.

Table 5.15 — Missing Value Analysis by Field and Entity Type

The heatmap below visualises the spatial density of survey records across all wards of Cluster 6, plotted using GPS coordinates captured automatically by the ODK mobile application during field data collection. High-intensity zones indicate areas with the greatest concentration of surveyed establishments.

The chart and table below present the distribution of commercial establishments by TypeID across all wards of Cluster 6. TypeID classification is used for fee schedule assignment and waste density factor selection.

Table 5.18 — Commercial Establishment Type Distribution

This section compares waste generation weight categories between Household (HH) and Commercial entities. Understanding how generation differs by entity type is critical for designing appropriate fee structures, planning vehicle capacity, and targeting awareness campaigns.

Table 5.20 — Waste Weight Category by Entity Type

Family size is a significant predictor of household waste generation. This section analyses the distribution of household records by family unit count and its relationship with reported waste generation. Commercial records are excluded as family count is not applicable to businesses.

Table 5.21 — Family Size Categories and Waste Generation

This section estimates the daily waste generation tonnage per ward and projects the minimum number of collection vehicles required to service each ward effectively. Estimates are derived from the survey weight-category midpoints applied to all valid records. Vehicle capacity is standardised at 3 metric tons per trip with 2 trips per day (6 MT/vehicle/day), consistent with KMC operational standards.

Table 5.22 — Estimated Daily Waste Tonnage & Vehicle Requirement by Ward

The scorecard below consolidates key performance indicators for each ward in Cluster 6. Metrics include survey volume, entity composition, GPS data coverage, waste segregation compliance, average daily waste generation, survey duration, and number of data collectors deployed.

Table 5.23 — Ward Performance Scorecard

During the implementation of the waste data collection survey in Cluster 6, the following operational and technical challenges were encountered, affecting efficiency, coverage, and data accuracy:

Table 5.19 — Survey Challenges and Impact

Challenge	Description	Impact
Incomplete Household & Business Information	Some premises could not be located due to unclear addresses, recent relocation, or lack of proper identification. Key data fields (PAN, FamilyCount) were missing or partially recorded.	Incomplete database; gaps in fee billing
GPS Accuracy & Mapping Limitations	GPS devices achieved approximately 80% location accuracy. Signal interference from dense urban structures contributed to imprecise coordinates, making it difficult to accurately link records to service zones.	Inaccurate spatial mapping; route planning challenges
Low Response Rates	Several residents and business owners were unwilling to participate or unavailable during survey hours, particularly in the morning. Privacy concerns and busy schedules reduced response rates.	Under-coverage in certain toles
Waste Reporting Inconsistencies	Respondents often underestimated or overestimated waste quantities due to limited awareness of measurement standards, recall bias, or intentional misreporting.	Reduced reliability of TPD estimates
Time & Resource Constraints	The large number of units to survey within a fixed timeline created pressure on staffing and logistics, making thorough follow-up visits difficult.	Coverage gaps; insufficient repeat visits
Data Entry & Multilingual Inconsistencies	Manual entry errors, inconsistent formatting, and mixed Nepali/English input in TypeID and Tole fields required extensive post-processing and validation rounds.	Increased cleaning workload; delayed analysis

Garbage Vulnerable Points (GVPs) are locations in the urban environment where solid waste is irregularly dumped in public spaces, creating health hazards, environmental pollution, and aesthetic degradation for surrounding communities. These sites are typically found under bridges, along drainage channels (nalas), on open land, at street corners, in road medians, and in other unmonitored or underserved locations. Identifying, documenting, and systematically eliminating GVPs is a core component of KMC's urban waste management strategy for Cluster 6.

• Identify and map all active GVP locations within Cluster 6 (Wards 10, 31, 32)
• Assess the type, estimated volume, and illegal dumping frequency at each identified GVP site
• Prioritize sites for immediate clean-up intervention and long-term prevention measures
• Establish a monitoring and tracking framework for GVP elimination and recurrence prevention
• Provide data-driven recommendations for community engagement and enforcement actions

Table 6.1 — GVP Summary by Ward

The table below lists representative GVP sites identified during the survey. Precise GPS coordinates and photographs are maintained in the KMC spatial database.

Table 6.2 — GVP Location Registry

GVP data was collected simultaneously with the waste survey using a combination of direct field observation and respondent-reported information:

• Direct field observation by trained surveyors throughout the data collection period
• Community reporting: respondents were asked to identify known illegal dumping locations near their premises
• GPS-tagged photography at each identified GVP site for spatial documentation
• Cross-verification with ward office records and local community representative feedback
• Classification by site type (illegal dumping, licensed collection point, near temple/park) and estimated waste volume

Road network data for Cluster 6 was systematically collected and analysed to support waste collection vehicle deployment planning. A detailed understanding of road widths, surface types, and pavement conditions is essential for selecting appropriate vehicle types, designing efficient collection routes, and identifying zones that require lightweight vehicles (e-rickshaws, tricycles) versus standard compactors.

• Map and classify the road network within Cluster 6 by width category, surface type, and pavement condition
• Identify road segments accessible to different vehicle types for waste collection operations
• Determine primary, secondary, and tertiary collection zones based on road accessibility constraints
• Provide evidence-based operational recommendations for vehicle type selection and route planning

Road network data was obtained from multiple sources: KMC GIS databases, field surveys conducted by technical staff, and validation against OpenStreetMap data. Each road segment was classified by width category (<4m, 4–6m, 6–10m, >10m), surface type (Black Topped, Gravel, Earthen, Other), and pavement condition (Good, Fair, Poor). Classification was verified during field data collection.

Table 7.1 — Road Width Classification & Recommended Vehicle Types

Table 7.2 — Pavement Condition Analysis

Table 7.3 — Road Length by Width Category and Ward

Table 7.4 — Vehicle Type by Road Width and Operational Role

Road Width	Permitted Vehicle Type	Collection Role
< 4m	Electric garbage rickshaws; tricycle collection vehicles	Primary door-to-door collection in narrow lanes and alleys
4–6m	3.3 CUM 4-compartment tipper trucks	Secondary collection; transfer from e-rickshaw drop-off points
6–10m	Standard compactor; bulk waste carrier	Secondary collection routes; transport to intermediate transfer points
> 10m	Full-size compactor trucks; bulk transfer vehicles	Route to Transfer Station at Ward 32, Manohara

In addition to household and commercial waste generators, Cluster 6 contains religious heritage sites, public open spaces, and water bodies (pokhari) that require dedicated waste management plans. These facilities generate specific waste types distinct from residential and commercial sources, with significant seasonal volume surges during major festivals. This module documents the inventory of such sites and establishes collection requirements for each category.

Community gathering spaces, temple courtyards, road medians, and market areas constitute the primary public open spaces requiring regular sweeping and waste collection services. The following table specifies collection frequency requirements for each space type.

Table 8.1 — Public Open Space Collection Schedule

Space Type	Location Description	Wards	Required Collection Frequency
Temple Courtyards	All major temple and religious site premises	10, 31, 32	Daily — before morning and after evening worship
Road Medians & Green Strips	Along major roads wider than 6m	Various	3 times per week (minimum)
Community Gathering Areas	Chowks, junctions, and public plazas	All wards	Daily
School Premises	Primary and secondary school grounds	All wards	After school hours — daily on school days
Market Spaces	Open-air market areas and vegetable markets	Various	After market closure — daily
Pokhari Buffer Zones	50m perimeter around all water bodies	Where applicable	Daily sweeping — no waste disposal permitted

Table 8.2 — Temple and Religious Site Registry

The monthly waste management service fee for each generator is calculated from actual survey weight data. For commercial entities, the recorded waste weight is converted to daily litres using a type-specific density value, then compared against the KMC-published base volume for that business TypeID. When actual daily volume exceeds the base allocation, an incremental additional charge applies. For households, fees are based solely on the number of family units (kitchens) — not waste quantity — following a flat-rate progressive structure.

The table below presents the KMC standardised fee parameters for each commercial TypeID present in this cluster. These parameters are set by the KMC Environment Department. TypeIDs not listed in the standard KMC schedule are assigned the default “Other” rate (32 L / NPR 840 / month).

Table 10.1 — KMC Commercial Fee Schedule (TypeIDs present in Cluster 6)

Table 10.2 — Commercial Revenue by Ward

Fee is computed per record using the survey-reported average waste generation and the type-specific density. Rows are shaded by fee tier: high (≥ NPR 5,000/unit), medium (NPR 2,000–4,999), standard (NPR 500–1,999).

Table 10.3 — Commercial Fee Analysis by TypeID (Ward-wise)

For households, the monthly waste management fee is not determined by waste quantity but by the number of family units (kitchens) sharing the premises. This approach is administratively simple, equitable, and reflects the established correlation between household size and waste generation (r = 0.37, p < 0.001). Larger households produce proportionally more waste and therefore pay a higher service charge.

Table 10.4 — Household Fee Schedule by Family Unit Count

The table below presents the combined monthly waste management fee revenue projection per ward, aggregating both commercial establishment charges and household service fees. This provides the expected total monthly revenue that should be collected from Cluster 6 under the KMC fee schedule.

Table 10.5 — Combined Monthly Revenue Summary by Ward

Table 10.6 — Service Provider KPI Targets by Month

Performance Indicator	Weight	Month 1	Month 2	Month 3	Month 4+ Target
Door-to-Door Waste Collection	40%	70%	80%	90%	≥95%
Source Segregation Compliance	25%	50%	70%	90%	≥95%
GVP Elimination Rate	20%	50% identified	67% cleared	100% cleared	100% sustained
IEC Activities	15%	≥3/month	≥3/month	≥3/month	≥3/month

Table 10.7 — Performance-based Penalty Schedule

Achievement Level	Payment Deduction	Administrative Action
85–95% of target	−10% of monthly payment	Warning letter issued
75–85% of target	−20% of monthly payment	Formal notice + mandatory improvement plan
<70% of target	−30% of monthly payment	Flag for contract performance review
<70% for 3 consecutive months	Contract suspension	KMC retains right to terminate contract

Based on findings from all five survey modules, the following priority actions are recommended for Cluster 6. Actions are grouped by urgency and implementation timeline to support systematic, evidence-based delivery of waste management improvements across Wards 10, 31, 32.

Table 11.1 — Priority Immediate Actions

#	Action	Description & Target	Responsible Party
1	Data Gap Remediation	Collect missing PAN/VAT numbers from commercial entities (65.5% gap — critical for billing). Follow up on blank FamilyCount HH records (32.2% gap). Verify and clean 413 records with collection duration <30 seconds.	Kathmandu Metropolitan City
2	GVP Emergency Clearance	Mobilize clean-up crew to the top 3 highest-priority GVP sites identified in the survey. Install barriers and signage at cleared sites to prevent recurrence. Document before-and-after status with GPS-tagged photographs.	Service Provider / Ward Office
3	IEC Campaign Launch	Conduct ward-level awareness sessions on waste segregation (≥1 session per ward in Month 1). Distribute bilingual Nepali/English segregation guide to all surveyed households. Coordinate with ward offices to appoint local waste focal persons.	KMC EMD / Ward Office
4	Collection Route Design	Use road network data to finalise vehicle deployment plan per ward. Designate e-rickshaw zones (<4m roads) and compactor zones (>6m). Establish daily collection timetable and Transfer Station delivery schedule for Ward 32, Manohara.	KMC Operations Team
5	Award Service Contract	Finalise and award the solid waste collection service contract based on survey data, TOR requirements, and cluster-level operational plan. Ensure all KPI benchmarks and penalty clauses are formally agreed.	KMC Environment Department

Table 11.2 — Short-term Actions and Success Indicators

#	Action	Success Indicator
1	Complete 100% GVP elimination across all wards per contractual Month 3 target	Zero active illegal GVP sites in KMC monitoring dashboard
2	Deploy GPS-enabled collection vehicles with 4-compartment segregated bins (Blue/Green/Yellow/Red) on all routes	100% vehicle compliance verified by KMC field inspection
3	Achieve ≥70% source segregation compliance through continued IEC activities	Monthly field audit compliance report ≥70%
4	Install segregated collection bins at all religious sites, parks, and major public spaces	100% of registered sites equipped
5	Establish monthly KPI reporting cycle with ward-level performance dashboards	First KPI report submitted to KMC by end of Month 1
6	Activate real-time GPS fleet tracking system for all deployed vehicles	Fleet tracking dashboard live by Month 1
7	Begin fee billing for all commercial entities with verified PAN/VAT data	First billing cycle issued within 45 days

Table 11.3 — Medium-term Actions and Success Indicators

#	Action	Success Indicator
1	Achieve ≥95% door-to-door waste collection coverage across all wards	Monthly route coverage audit ≥95%
2	Complete fee billing for all commercial entities including those without initial PAN/VAT data	100% commercial entities billed
3	Scale source segregation compliance to ≥95% per contract requirement	KPI audit compliance report ≥95%
4	Conduct supplementary survey for uncovered Tole sub-areas and correct remaining data gaps	Updated database with ≥98% field completion
5	Cross-verify survey data with KMC taxpayer records and census data	Verification report produced and discrepancies resolved
6	Integrate fee billing into KMC Finance billing system	Fee collection system operational by Quarter 2
7	Conduct follow-up comparison survey to measure change from baseline across all indicators	Baseline comparison report submitted by Month 6