Upload
rajendra-naik
View
30
Download
1
Embed Size (px)
Citation preview
PLANNING WORKSHOP II(Infrastructure Studies)
SUBMITTED TO: Mr. PramanDept. of Urban and Regional Planning
SUBMITTED BY:13011BA01013011BA02013011BA027
BENCHMARKINGBenchmarking is a process of
Measuring ULB’s/Water Board’s Performance and practices in key areas,
Comparing them with best practice
Subsequent translation of this best practice into use,
Leading to superior performance –Performance Improvement
A process through which practices are analysed to provide a standard measurement
('benchmark') of effective performance within an organisation.
Types of Benchmarking
Generally, there are two approaches to benchmarking: metric and process.
• Metric benchmarking is a quantitative comparative assessment using
standard performance indicators that enables utilities to track internal
performance over time, compare this performance against that of similar
utilities, and establish target levels of performance.
• Process benchmarking involves first identifying specific work procedures
to be improved through a step-by-step ‘process mapping’, and then
locating external examples of excellence for standard setting and possible
emulation.
Service Level Benchmarking has been developed and released by the MoUD. It seeks to:
• identify a minimum set of standard performance parameters for the water and
sanitation sector that are commonly understood and used by all stakeholders across
the country;
• define a common minimum framework for monitoring and reporting on these
indicators; and
• Set out guidelines on how to operationalise this framework in a phased manner.
PRINCIPLES UNDERLYING THE BENCHMARKING PROCESS
The model of benchmarking process is famously referred to as the
“Deming cycle” and it includes a minimum of four phases “Plan –
Do-Action-Check”
Deming’s Benchmarking Cycle
BENCHMARKING AN APPROACH
Identify Problem or Area for review
Map the ProcessIdentify Partners & Data Sources
Collect Data
Identify Good or Best Practise
Change Existing Practice
SLB frameworkIndicators
List of service level indicators for each sector
Rationale
Why is this indicator important for the service
Definition
Objective and mathematical definition
Data Requirements
Data that is required to calculate the indicator
Reliability of measurementWhat is the reliability of data should be targetted
Frequency of measurement
How often should the indicator be measured
Level of detail
What is the level of geographical detail to which the data should be available
Target for the indicator
What is the performance level that should be targetted?
STROM WATER DRAINAGE
• Extent of the network and effectiveness of the network are emphasized to assess storm water drainage systems performance.
• As this service does not yield any direct revenues, financial sustainability is not considered.
INDICATORS:• Coverage of storm water drainage network• Incidence of water logging/flooding
SLB FOR STORM WATER DRAINAGE
Sl. No
Proposed Indicator Benchmark
1 Coverage of storm water drainage network 100 %
2 Incidence of water logging/flooding 0
1.COVERAGE OF STORM WATER DRAINAGE NETWORK
Indicator Unit Definition
Coverage of storm water drainage network
% Coverage is defined in terms of road length covered by the storm water drainage network
Data Requirements
Data Requiring for calculating the indicator
UNIT Remarks
(a)Total length of road network in the ULB
Km Only consider roads that are more than 3.5 m wide carriageway
(b)Total length of primary secondary and tertiary drains
km Only consider drains that are trained, madeof pucca construction and are covered.
Coverage of storm waterdrainage networks
% Coverage = [(b/a)*100]
RATIONALE FOR THE INDICATOR
This indicator provides an estimation of the extent of coverage of the storm water drainage network in the city. This value should be 100 percent.
Reliability of Measurement
Reliability scale Description of method
Lowest level of reliability (D) Not applicable.
Intermediate level (C) Estimated from city road maps, not updated in the past five years.
Intermediate level (B) Estimated from city road maps (that are detailed and to scale), whichhave been updated in the past five years.
Highest/preferred level of reliability (A)
Actual ground level surveys are carried out to measure drain and road length. Surveys are carried out to verify that drains are of puccaconstruction and covered.
Minimum frequency of measurement of performance indicator
Smallest geographical jurisdiction forof performance indicator measurement of performance
Measurement Annually Measurement Ward level
2.INCIDENCE OF WATER LOGGING/FLOODING
Performance IndicatorIndicator Unit Definition
Data Requirements
Data required for calculatingthe indicator
Unit Remarks
a. Identification of flood pronepoints within the ULB limits. Thepoints may be named as A1, A2,A3,….An
Number Flood prone points within the city should beidentified as locations that experience waterlogging at key road intersections, or along a roadlength of 50 m or more, or in a locality affecting50 households or more.
b. Number of occasions offlooding/water logging in a year
Numberper year
An occasion or incident of flooding/water loggingshould be considered if it affects transportationand normal life. Typically, stagnant water for morethan four hours of a depth more than six inches.
The aggregate number ofinstances or occasions of waterlogging/flooding reportedacross the city in a year
Numberper year
Aggregate incidence = (b at A1) + (b at A2) +….. (b at An)
Rationale for the IndicatorThis indicator provides a picture of the extent to which water logging and flooding are reported in the ULB within a year, which have impacted a significant number of persons as well as normal life and mobility. This indicator provides an assessment of the impact or outcome of storm water drainage systems. The benchmark value for this indicator should be zero.
Reliability of Measurement
Reliability scale Description of method
Lowest level of reliability (D) Not applicable.
Intermediate level (C) Not applicable.
Intermediate level (B) Based on reports/complaints filed by citizens.
Highest/preferred level ofreliability (A)
Flood prone points should be first identified based on reports/complaints filed by citizens, or by direct observations, and reportedinto a central control room. Monitoring stations (in charge ofspecific jurisdictions) should regularly monitor instances of floodingin the respective wards/zones, as mentioned above. Data shouldbe captured by time, date, location and extent of flooding.
Minimum frequency of measurement of performance indicator
Smallest geographical jurisdiction for measurement of performance
Measurement Annually Measurement Ward level
Sl. No
Urban Service Frequency of Measurement by ULB/Utility
Frequency of Reporting within ULB/Utility
Frequency of Reporting to State/Central Govt.
Jurisdiction for Measurement by ULB /Utility
Jurisdiction for Reporting within ULB/Utility
Jurisdiction for Reporting to State/Central Govt.
1 Coverage of storm water drainage network
Annually Annually Annually Ward Ward ULB
2 Incidence of water logging/flooding
Quarterly Quarterly Annually Ward Ward ULB
SUGGESTED FREQUENCY AND JURISDICTION OF REPORTING
Indicator Parameter Source of data Remark
Coverage Drain length pucca or covered (road width of 3.5 m)
1. Existing drainage map (updated).
2. Data captured by infrastructure DPR (like water, sewerage, drainage or road etc).
3. Physical measurement (using bike)
•Only pucca covered drains should be considered. •Road with both side drain should be considered once.
Water Logging No. of incidence in a year 1. Complaint records.2. Other related
records.3. Physical verification
during monsoon.4. Experience of the
local people.5. Disaggregated level
(supervisors).
• Along roads (50 mt length or more)
and Locality (affecting 50 HH
or more)
Incidence of storm water mixing in the sewerage
Capacity of storm water drains.
1. Disaggregated level (supervisors).
2. Complaint records.
Summary of SLB Indicators – Storm Water Drainage
Source: MoUD SLB performance data.
Average of Storm Water Drainage in Pilot Cities
Indicator Benchmark Pilot Cities Average
1. Drainage network coverage
100% 31.3
2. Incidence of water logging 0 66.7
STORM WATER DRAINAGE (case study of Bangalore)
Observations/Comments
•Exact length of tertiary drains needs to be assessed. •Lack of regular updation of information on drains, water stagnation points etc. •No centralized monitoring system is in place. •Ward level road history is to be maintained. This is to be linked GIS.
Performance Indicator Benchmark Status Reliability
Coverage 100% 5 CIncidence of water logging 0 number 135 number B
SWD: Areas identified for improvementIndicator Reasons for low
reliabilityISIP
Coverage No comprehensive records on drains
• Ward level road history register to be updated
• Developing a GIS based road database
• Maintenance of recordsIncidence of water logging
No records are being updated on occurance of flooding
• Identification of flood prone areas• Integration of traffic data and GIS
based data• Updation of records on occurance
of flooding• Participatory reporting for flooding
incidence• Establishmet of rain gauge
recording system & integration of rain fall data
Key issues and possible solutions
Key Issues Likely Difficulties Possible Solutions
Choice of Indicators and Definitions
Difficulties in arriving on a universally accepted setof indicators
•Choose number and type of indicators carefully based on relevance and usefulness to a broad majority of utilities, ease of understanding and measurability, their likelihood to be monitored, and so on•Customize global indicators to suit the local context while, at the same time, retaining the flexibility to allow international comparisons•Communicate indicators and their definitions to utilities clearly
Data Collection
Availability and reliability of data can be limited
•Communicate indicator definitions, interpretations and their calculation to utilities clearly•Devise methods to arrive at broad indicators within the existing data Constraints•Include robust quality assurance mechanisms to grade the reliability and accuracy of data•Improve accounting practices and put in place incentives for utilities to collect and report accurate data
Thank you