Ease of Living Index to Empower Citizens in Aspiring for a Better Quality of Life from their City Authorities

  • Current Samachar
  • August 16, 2018
  • Comments Off on Ease of Living Index to Empower Citizens in Aspiring for a Better Quality of Life from their City Authorities

Ease
of Living Index launched by the Ministry of Housing and Urban Affairs on 13th
August 2018 has attracted wide public enthusiasm and provided an opportunity to
Urban Planners, Municipal Authorities and public at large a baseline data for
wider public debate. It is expected that the baseline data will fulfill the
demands of cross section of people in aspiring for a better quality of life
form their city administration. This is a unique exercise and is based on an open
and participatory assessment of cities along with physical audit of urban
metrics in a transparent manner.
The assessment, certainly, is more than just a ranking
exercise. It marks the beginning of the creation of arobust baselinealong 78
urban metrics and seeks to drive evidence-based thinkingon urban planning and development.It
has also initiated an healthy competition between the cities based on the
rankings and generated acute interest, comparisons, critiques and analysis by
citizens and experts in the public domain.

Process
Overview

Through an international bidding process, M/s IPSOS Research Private
Limited in consortium with M/s Athena Infonomics India Private Limited and
Economist Intelligence Unit (EIU)were selected for assessment of liveability
indices. The implementation of the assessment commenced formally on 19 January,
2018.
Transparency and neutrality are critical
attributes that define the success of this exercise.The assessment is open and
participatory and started with a nation-wide drive to encourage cities to
provide data online through a dedicated data entry portal.

Two
rounds of quality control and excel-based audit were performed on the data
provided by the cities and errors were identified. Every city was given an
opportunity to fix the errors and update their data sheets.This was followed by
a round of document-based audit by a set of independent professionals to
validate the veracity of the data. This was done by comparing data from supporting
documents (in the form of published plan documents, administrative reports etc.)
with the information presented by cities in the data entry portal.

Finally,
a physical audit was conducted for selected parameters which could be
physically verified (for example, availability of passenger information
systems) through a network of trained field staff.

Defining
features that influence the assessment outcomes and Rankings:

1.   
Indicators and Weightages

The
foremost aspect that influences a city’s performance is the set of indicators
that the city is being assessed on and weightages assigned to them.  In the
current assessment, the physical infrastructure pillar receives the highest
weightage of 45%, with several of the indicators focusing on universalization
of services(Sanitation, Power, Water, Sewer,Transport, Public Services etc.Thus,
cities that are observed to be doing better in terms of service coverage stand
to gain significantly.

The
other feature is the differential weights associated with indicators based on whether
they are classified as supporting or core. A core indicator receives a
weightage of 70% while a supporting indicator only receives a weightage of 30%.
For example, a city that has taken significant efforts to restore ecologically
sensitive areas (core indicator) within its jurisdiction stands to gain more on
the theme of ‘identity and culture’ vis-à-vis its performance on an indicator
such as number of cultural/sports events hosted (supporting indicator).

 

2.   
Quantum of Data Available with Cities

Every
city was invited to participate in a data collation exercise through an online
data entry portal. Multiple departments participated to provide data on over
500 questions, cutting across 78 indicators. Cities that had strong systems for
data generation and reporting and/or a history of planning that was evidence
based (City Sanitation Plan, Mobility Plans etc.) were observed to perform
better as they are simply better equipped to provide data. Cities that have
inadequate systems of record keeping were observed to be at a disadvantage.

 

 

3.   
Quality of Data Provided

 

To
encourage cities to provide sound data, an incentive in the form of higher
weightages has been deployed for indicators that are backed by supporting
documents. Cities that could support the data provided with strong secondary
documents (ex: SLIPs, DPRs, City Mobility Plans etc.) were given due weight-age
in their score.

 

4.   
Relative benchmarks

 

To
ensure that the assessment offers a level playing field to all cities, relative
benchmarks are assigned for 22 of the 78 indicators in which cities are
evaluated against their comparable peers, defined by the population. Cities
were classified into 4 categories namely:

Group Sl No.

Population

Group 1

Below 0.5 Million

Group 2

0.5 to 1 Million

Group 3

1 to 4 Million

Group 4

Above 4 Million

 

 

 

 

 

 

For
example, Karimnagar (a city that is in the ‘below 0.5 million’ category) is
observed to be performing better than Hyderabad as its benchmarks on several
such indicators are fundamentally different. For example, the benchmark value
(best performing city’s data) for Karimnagar on surveillance density is 1.76
(number of CCTV cameras per km of road length) while for a city like Hyderabad,
the benchmark is 19.2.

 

RJ/SB

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