Geo-Referenced Utility
Benchmarking System: A tool
supporting the Global WOPs Alliance
Presentation for the Global Water
Operators’ Partnership Alliance
Foundation Meeting
by Dr. Graham Alabaster at Safari Park Hotel, Nairobi, Kenya, January 29th-, 2009
Integrating household data and geographic
information
Input HH data
Digitize Features
from satellite
images
GIS
System
UrbanInfo/Lake
Victoria Info
Monitoring/Policy
Digitize EA
boundaries
Field verification/
Quality Control
maintainance the
GIS and the
database
Total Population of Selected Secondary Urban Centres,
Kenya 2006
Town
Total Population, 20061
Migori Municipality
56,700
Kisii Municipality
88,400
Homa Bay Municipality
59,528
Siaya Municipality
49,343
Bondo Township
36,229
1Estimated
from the Kenya Population and Housing Census, 1999
Access to improved water source, Kenya 2006 (JMP data)
100
Percentage
80
70
71
76
68
60
52
40
20
0
Migori
Kisii
Homa Bay
Siaya
Bondo
Access to improved water decreases dramatically when quantity is
considered,
Kenya 2006 (less than 20L/day)
Percent
100
80
76
71
70
68
61
60
50
53
52
52
39
40
20
0
Migori
Kisii
Homa Bay
Improved water (source only)
Siaya
Bondo
Improved water but not sufficient
Access to improved water decreases dramatically when quantity and cost
are considered, Kenya 2006 (more than 10% of income)
Percent
100
80
76
71
70
68
60
52
40
26
20
20
20
10
15
0
Migori
Kisii
Homa Bay
Siaya
Improved water (source only)
Improved water but not sufficient and not affordable
Bondo
Access to improved water decreases much further when quantity, cost, and
the burden of fetching water are considered,
Kenya 2006 (collection time >1 hr)
Percent
100
80
76
71
70
68
60
52
40
20
21
18
9
9
2
0
Migori
Kisii
Homa Bay
Siaya
Bondo
Improved water (source only)
Improved water but not sufficient, not affordable and burdensome to fetch
Access to Improved Water
Migori, Kenya
Access to Improved Water
(in %)
0
0.01 - 20
20.01 - 50
50.01 - 80
80.01 - 100
Access to Pipe Water
Migori, Kenya
Household Access to pipe water
(%)
0
1-10
10-30
30-50
50-100
The h2.0 Inform and Empower Initiative
Several attempts to improve current monitoring approaches but
lack of good local, disaggregated data mask the true picture of
what is happening on the ground. This project will therefore
address three key themes:
• Coverage data in addition to health, environment and socioeconomic data, (based on UN-HABITAT Urban Inequities
Survey)
• benchmarking service providers - coverage and quality, but
also accountability to customers
• Development of citizen-based participatory monitoring
techniques to support and empower communities
• Use of GIS & Google products to compare/contrast data from
different sources
Introduction to GRUBS
Concurrent advancements in benchmarking, monitoring, GIS, and telecom
technologies are multiplying the possibilities for new utility-centred
analytical and problem solving applications.
•
•
Some Potential Applications:
a geo-referenced utility benchmarking system (GRUBS) to track utility
performance and to enable utilities to search and identify potential
peer-support partners
a web-enabled, GIS-based databases of utility coverage areas that
would enable water operators to understand and act upon variation in
performance within their service areas & prepare utility mapping tools
GRUBS Workshop
Nairobi, November 24h-25th, 2008
• UN-HABITAT, Google, IB-NET, h20 partners, utility
representatives
• Objectives: to understand how utilities use
benchmarking and how GRUBS could add value
• Outcome: UN-HABITAT Partnership with GWOPA, IBNet and Google to develop a tool to address needs
and new potentials.
Basic Concept
The envisaged tool would give water service providers,
regulators and consumers easily accessible and
readily interpretable (mapped) information about
WSPs customer responsiveness, particularly to the
poor. The tool will show how WSPs are performing in
different parts of their coverage area, and,
secondarily, give an overall ‘rating’ for the utility as a
whole.
The tool’s Key Functions would be to:
• understand current WSP performance variability within a service area
• highlight the location and “watsan realities” of the unserved population
• help utilities and regulators develop appropriate pro-poor policies and
planning strategies
• allow better planning and evaluation of investment strategies
• enable target setting to reduce pro-poor performance gaps – such as the
basis for performance improvement contracts and staff incentive
structures
• help consumers to demand improved service and hold WSPs accountable
• provide compelling data to attract funds and political support to improve
service
• highlight the potential market base among un-served areas of the city
The Key Users would be:
•
•
•
•
utilities
consumers
regulators
wops and utility associations
How the tool would work
The tool would first bring together select sets of data from the
following sources:
– digitized utility network information(piped water and sewerage networks,
connections)
– household data (from national census, urban inequity surveys,)
– customer feedback information, where available (ie. Citizen Report Carding)
With these available datasets, the tool would use GIS to facilitate the calculation of
aggregate indicators and analysis of customer responsive performance. For
example, it might be programmed to answer:
– which areas have the greatest unmet demand for services?
– which areas suffer most from water-borne diseases?
– which areas pay most for watsan services relative to income?
– How does land tenure relate to water access?
The (most relevant of) the analysed information would then be made available in a
clear, readily understandable, interactive map formats and tables online, facilitated
by Google
Why is such a tool relevant?
• Currently, there is no simple way of understanding and demonstrating
water and sanitation service inequities within urban areas. Statistics on
access may exist, but are not commonly integrated with other socioeconomic data to enable analysis of relationships. Furthermore, these
statistics are rarely in a mapped format where spatial analysis can be
conducted. Finally, such information does not exist in a format that is
readily understandable to users and accessible to the public.
• Being able to demonstrate spatial inequities in access to water and
sanitation within urban areas is extremely important for creating the
awareness, building the political support, and planning to improve the
situation for the poor. The tool would aim to highlight the realities of the
poor and underserved in urban areas that are normally hidden behind
spatially-aggregated data.
• The partnership with Google enables low-cost tools to be available event
othe smallest utilities
Developing and Piloting the Tool
• Development and testing of CRC and GRUBS in
Lake Victoria (17 Towns) with exisitng UIS data
• Zanzibar h20 pilot
• Expressed interest by ZAWA, ONEP, Nairobi,
NWSC of Uganda, Senegalaise des Eaux to
pilot, but not limitied