1. Pritam Banerjee
Internship – Espirito Santo,
Investment Banking
Shubhra Ghosh Internship –
CEB, Mgmt. Strategy
Consulting
Somwrita Biswas Internship –
Credit Suisse, Investment
Banking
Nitesh Sinha
Internship – Accenture,
Management Consulting
Priyadarshan Gupta
Internship – RBS,
International Banking
PLUGGING THE LEAKS
Improving reach and efficiency of the Public Distribution System

2. CURRENTSTANDINGOFPDS(INDIA)
CURRENT CHALLENGES
APPALLING FACTS
Inefficient Targeting is the major
challenge of PDS. PDS is targeted to the
bottom of the pyramid. However there is
a lot of inclusion and exclusion errors.
Corruption is rampant in Public
Distribution System. The corruption takes
place in all the parts of the supply chain.
However most of the diversion of the
food grains takes place in the fair price
shop followed by in transit transaction.
It is mostly prevalent in States of UP,
Bihar, West Bengal. This is the most
degrading factor for the PDS.
A lot of Fair Price Shops are in very bad
condition raising the problem of viability
of FPS. In some cases we found that
there is lack of variety and packaging is
poor leading to a lot of wastage. High
Inventory carrying costs is eating up
margins and plaguing the system.
RESEARCH METHODOLOGY
Secondary Research
An extensive secondary research on
the public data was carried out. The
data published by the Planning
Commission, Ministry of Agriculture,
PDS Portal of India was consulted.
Also research papers by eminent
economists like Dr Reetika Khera, Dr
Jean Dreze were referred.
Primary Research
We did an extensive research
meeting experts (academicians,
policy makers, researchers) on Public
Distribution System. A visit to one
Fair Price Shop was done The
secondary research along with the
primary data collection has helped us
to find the root cause of the problem
and propose a robust solution.
• States like Chhattisgarh & AP has reduced leakages
• While Chhattisgarh has made some indigenous innovation,
AP relied on Technology
Source: “Trends in diversion of PDS Food grain” by Reetika Khera, Primary Research
PDS in India is a mixed success. While States like Chhattisgarh, Andhra
Pradesh are fairing high, States like Bihar, Rajasthan are languishing. The
main problems in PDS are mainly due to wrong targeting and corruption
• PDS diversion is at 40% for Food Grains, 37% for Rice & 50% for Wheat
• FPS owners deceive beneficiaries by giving false information
• There are very high estimates of the number of ghost beneficiaries
• In Bihar diversion of more than 80% is observed
It becomes very apparent that there is a need for computerization of the PDS system

3. ENSURINGBETTERTARGETING
CURRENT SITUATION RECOMMENDATIONS
Analysis of the data published by Ministry of Rural Development reveals
that both Type I and Type II errors are significant in India. The type I
error pan India is pegged at 26.3% and 60.4% respectively.
The Ministry of Rural Development (MORD) used self reported income as
the parameter to identify poor households. This has led to many
inclusion errors. In 1997, BPL census used food expenditure rather than
income as a criterion. Now this has led to exclusion errors. The exclusion
criteria was too stringent.
BPL census in 2002 sued the following formula
Si = ∑ Hij <= Sp
cut-off where i = 1………….to n and j = 1 ………….13,
Si= aggregate score of the ith household,
Hij = ith household on jth indicator, Sp
cut-off = State specific cut-off score
CHALLENGES OF THE CURRENT CRITERIA
As a one-point gain in one dimension can be compensated by an
equivalent decrease, in another dimension it would make it irrelevant.
For instance, the situation of a family eating only once a day gets nullified
if it has quite a few items of clothing or is doing well across any other
dimension not as serious as not getting food.
Equal weights of dimensions can be treated as a poor description of
poverty. For instance, not having one square meal a day throughout the
year is treated equivalent to open defecation or not possessing electrical
appliances
The poor often has no access to credit market because of their inability
to offer any acceptable collateral. But the highest score of “4” has been
assigned to household who is not indebted. Thus, the score attached to
“type of indebtedness” might have ruled the poor out of the BPL category
Use vulnerability criteria approach for determination of
poor. Give scores (0 if non vulnerable & 1 if vulnerable) to
households for each dimension & add to get composite
score. Include all households in vulnerable list. A
household is vulnerable if it bears at least one of the
following criteria:
 Households do not own a dwelling unit
 Households with no land or employment in non-
agriculture & whose no member is regular salaried
 Where members of the households primarily work as
agricultural and other labor having only homestead
land with no regular salary earner
 Households that hold <=2 ha of standardized cultivable
land with no regular salary earner & primarily engaged
in agriculture & other labor activities
 Households belonging to SC and ST
 Households which spend less than Rs 216.29 per
capita on clothing during a year
Apart from the above list add households with single
woman member, disabled person who is the sole
breadwinner of casual work, no member above 14 years of
age, households bearing destitute characteristics
Estimate the weights of each of the vulnerability factor
using logistic regression.
If P is the probability of a household being poor, then
P = [1+e{–βX}]–1 where “β” is a vector of the unknown
coefficients and “X” is a vector of covariates that affect
the probability of household being poor.
Source: :Identification of poor: Errors in Inclusion and Exclusion” – Motilal Mahamallik, Gagan Bihari Sahu, Economic and political Weekly
The problem with targeting comes from the fact that the formula used is
not a good estimator of the BPL population. A more robust method of
targeting using vulnerability criteria is proposed.

4. LEAKAGESINPDS
Root Cause Analysis of Diversion
Source:”Trends in Diversion of Food Grains” – Reetika Khera,
DIVERSION (%) OF PDS FOODGRAINS AND ESSENTIAL COMMODITIES
State Rice Wheat Food grain
Assam 73.0 97.5 77.5
Bihar 92.4 85.1 89.5
Gujarat 73.0 53.3 63.1
Haryana 61.8 48.8 51.1
Himachal Pradesh 12.9 14.3 13.6
Jammu and Kashmir 7.6 59.1 24.3
Jharkhand 83.3 85.2 84
Karnataka 42.2 33.4 41.0
Kerala 3.5 55.6 16.2
Madhya Pradesh 20.8 39.9 35.5
Maharashtra 40.7 44.1 42.5
Odisha 46.2 97.1 50.2
Punjab 17.6 18.4 18.4
Rajasthan 75.7 82.0 81.2
Uttaranchal 33.3 70.9 48.5
West Bengal 70.8 77.9 74.8
The first level of PDS diversion
takes place in transit. The trucks
which transport PDS commodities
are stopped and leakages start
from this point.
 The diverted food is then sold
in the black market at higher
price
 The next level of leakage takes
place at the Fair Price Shops. The
FPS owner tells that the food
grains has not reached the FPS
Shop.
 Only a fraction comes for his
share the next time. This excess is
then sold for higher prices.
 Finally another level of leakage
takes place when the FPS shop
owners blatantly deceits the
beneficiaries and gives them less
quantity.
He also inflates the quantity
taken by beneficiaries while
recording, thus diverting the grain
The root cause analysis of diversion of PDS commodities reveal that
leakages takes three forms. The magnitude of leakage is till very high in
India and is appalling in some States.

5. ELIMINATINGCORRUPTION(1/3)
THE EFFECT OF LEAKAGES IN PDS
The main problem plaguing the PDS is the amount of leakages. Leakages vary across States and is more than 70% in some
States of the country. By merely plugging these leakages, the Government can not only make PDS leaner, but can also save
a lot of money.
BEST PRACTICES IN VARIOUS STATES IMPLEMENTING PDS
CHHATTISGARH
ANDHRA PRADESH
The PoS machines, and the fully transparent MIS
system does not leave room for pilferages to take
place
 Aadhar enrolment in the district is as high as
99%
 Almost 95% Gram Panchayats (GP) are serviced
by the Banking Correspondents
 Aadhar number seeding of bank accounts is
fairly high at 80%. This is mainly due to door to
door organic seeding done by the Government.
There is a high level of digitization of data and
complete transparency in the flow of commodities.
High level of technology infrastructure and
support and proximity of the PDS shops to district
collectorate office has enabled better monitoring of
the scheme
Computerization and Proper Monitoring of the
PDS system is the key to success. This shows that
strong political will is necessary for the success of
the scheme
• Lorries are painted bright yellow so that they can be easily
identified by villagers if they were to be unloaded elsewhere.
• Each FPS has GPRS linked Point f Sales Device which gives
a printed receipt for each transaction.
• Chip enabled ration cards are issued. These ration cards are
validated from the central sever. Handouts a receipt receives
each month is logged.
• The centralized food server monitors the entire food supply
chain
• Central server monitors the entire food supply chain.
• UIDAI based validation is done at each FPS
• Each Fair Price Shop is equipped with a point of Sales Device
which use biometric fingerprinting to validate beneficiaries.
• All ration cards are digitized and high level of seeding in the
region leads to efficient implementation of the scheme
• SMS is sent to recipients when the FPS receives stock, thus
making the FPS owner as a mere distributor . This prevents
leakage.
CRITICAL SUCCESS FACTORS (CSFS)
In order to reduce the level of corruption there is a need to use the latest
technology. The use of technology coupled with political will, thorough
preparation has contributed to the success of the AP PDS.

6. Commodities reach
PDS shop under auth.
from go-downs and
delivery is
authenticated by
route officer.
Send SMS to all the
beneficiaries that
the PDS shop now
has the required
stock
A family
member of the
beneficiary goes
to the Fair Price
Shop to collect
ration.
POS
Machine
validates
ration
/Aadhar
Card No.
PoS device sends
encrypted XML file to
Authentication User
Agency (AUA). AUA
forwards to Auth.
Service Agency
ASA invokes Central
Data Repository of
UIDAI & transmits
auth. packets.
PoS device
receives the
results of the
authentication.
FPS owner keys the
details of
commodity,
quantity, amount
details
All transactions are
recorded with the
timestamp and sent
to central server.
PoS device
gives a printed
receipt.
ELIMINATINGCORRUPTION(2/3)
RECOMMENDATIONS
 Use Unique Identification for validating the beneficiaries
 Have high level of Aadhar Enrolment in all States
 Use NPR and UIDAI in tandem to generate more Aadhar
enrolment
 Incentivize States and districts to work on Aadhar
 Start working on computerization of the PDS data now.
 Use point of Sales device in every Fair Price Shops
 Plow back some savings generated after plugging the leakages
in the PDS as incentives to the FPS owners
 Set up a central control center for monitoring PDS shops
 Use route officers and monitor the route information and
capacity data of the PDS trucks
 Tie-up with ISPs for efficient data transfer
 The proposed solution is sustainable and is a proven method. It
is indeed scalable and once the infrastructure is in place, it
will take only -2 months to scale up.
 The model will create win-win situation for all the stakeholders
- beneficiaries, FPS shop owners, State Government and the
Centre. This will make the solution sustainable.
PROPOSED FLOWCHART
SUSTAINABILITY AND SCALABILITY
BENEFITS OVER EXISTING METHODS
The solution uses all existing architecture for which cost will be
low. The time to roll out will also decrease due to the sharing of
existing infrastructure. This is a cost effective way of ensuring
food security to the people.
Taking the best practices from the already existing system will not only be
cost effective but will also be deployed at much faster rate. The proposed
solution uses the current infrastructure to reduce Go to market time.

7. ELIMINATINGCORRUPTION(3/3)
SYSTEM REQUIREMENTS
• All Fair Price shops should
have a board stating the
commodities that can be
found in that shop and the
corresponding prices in the
local language
• Give printed receipt of
each transaction in local
language to the customers
• Validate users based on
Aadhar Number or
digitized ration card no
• Co-ordinate with UIDAI
and National Population
Register for UID
• Use Point of Sales device
to validate users. It should
be equipped to carry out
biometric validation. To
overcome the challenges of
a good fingerprinting, use
the Best Finger Detection
Technology. It records the
finger prints of all the
finger of the beneficiaries
and finds out the best
finger which an be used for
proper validation
• PoS device Cost Rs 20,000
with a life of over 4 years
making them extremely
cost effective
• Digitize all transactions and
store the data in a
centralized server. This will
help forecast demand and
monitor FP Shops.
• The PoS device should also
have a voice over facility to
say out the commodities
entered in the device and
the corresponding price and
the total amount to be paid
by the beneficiary. All the
above should take place in
local language.
• This facility will protect the
beneficiary from dishonest
shop owners and will plug
leakages in the PDS
• Online tracking of the
various points in the Supply
chain will prevent the
possibility of leakage of food
grains during the transfer of
commodities from
warehouse to the shops.
• Assign responsibilities of a
route to specific person and
make him liable for any
pilferage.
• At the same time track the
amount of food grains
transferred from each
location. This an be done by
sending the inventory data
of each FPS to the central
server.
The System requirements for the proposed solution is a tried and tested
method which has been proved to have worked for a pilot implementation.
The solution is cost effective and can be rolled out quickly.

8. IMPROVINGFAIRPRICESHOPS
INTRODUCE VARIETY
VARY ALLOCATION BASED ON DEMAND
COMPUTERIZE TRANSACTION
USE SURPRISE VISITS AND OTHER MONITORING
Introduce more variety in
the FPS shops.
This will not only provide
choice to the people but will
also help in improving the
level of commission.
The PDS System in Andhra
Pradesh has included an array
of products to the portfolio of
Fair Price Shops.
This will improve control of
the Fair Price Shop
Will help in knowing the
level of inventory accurately
Will give an idea of the
demand of the Fair Price Shop
From the data some low
performing shops may be
closed and some shops may
be opened in high demand
regions.
Allocate the Fair Price
Shops according to the
demand of the previous
period
This dynamic allocation of
products will not only reduce
wastage but will also save
money in terms of lost
inventory
Inventory carrying cost will
also come down
Use Strong monitoring of
the conditions of the Fair
Price Shops
Use surprise visits to the
stores to make it
unpredictable for the shop
owner
Take suitable actions (in
terms of penalty) against
those FPS which doesn't
comply to standards & reward
those FPS which does well
With more computerization and more competition the condition of the fair
price shop will increase. Surprise checks and strong quality control will also
prevent the owners of FP shops to slack off in terms of quality.

9. ROADMAPANDSTRATEGY
Timeline for rollout of the improved PDS scheme
PHASE I : ENROLMENT
(3 MONTHS)
PHASE II : SEEDING
(2 MONTHS)
PHASE III : ROLLOUT
(6 MONTHS)
Enrolment Phase:
Set up Central and State level Action
plan Use both NPR and UIDAI
Give slots to people for UID
generation
 Mobilize people within the
Government
Set up Control rooms and monitor
progress
Educate people about Aadhar and
how it can be used
Demonstrate benefits of Aadhar
Use TV ads and radio ads
Database Seeding Phase:
Coordinate with different
departments to digitize data
Use inorganic as well as organic
seeding.
Launch camps pan India to generate
organic seeding. Hire volunteers from
local institutes for this.
Use back end inorganic seeding from
existing ration cards / PAN cards and
other proof of address
Perform de-duplication and other
processing techniques on the data.
Roll out Phase:
Procure Po device for rollout
Roll out in a small scale in those
places where the progress can be
monitored easily.
Monitor the progress and optimize
the process with the local constraint in
mind. Use local customization ad
address issues.
Roll out in all the districts
simultaneously
Monitor results and use proper
feedback loop
Funds and HR Requirements
Human resource is required mainly for
promotional activities and setting up
of amps. Approximately 5 personnel
per 100 beneficiaries will be required.
The funds required will be mainly for
advertisements. W e believe that
approximately Rs 100 Crore will be
required for advertisement purposes.
Funds and HR Requirements
In this phase back end HR will be
required. This will typically be in the
tunes of 1 person per 100 data
entries. Highly skilled data entry
operators can be hired.
The additional cost to the Government
is almost negligible. Most of the costs
have already been sanctioned.
Funds and HR Requirements
Minimal Human resource needed for
control purposes. Need some
supervisors for monitoring.
From the cost perspective, the costs of
the PoS devices will be incurred. This is
very small compared to the opportunity
costs of the welfare schemes of the
Government.
Keeping in mind the inherent urgency and the severity of the problem, the
solution uses only existing technology and system. It is a matter of political
will that is needed for successful implementation of the solution.

10. ECONOMICIMPACT
THE PROPOSED SOLUTION WILL GENERATE SUBSTANTIAL SAVIINGS TO BOTH CENTER AND STATE
Commodity
Total No of
cards saved
Total
Quantity
Saved
Avg. No of cards
for which ration is
not withdrawn
Avg. Qty
saved per
shop
Central Subsidy
saved per Shop
(Rs.)
Rice 4041 52505 86 117 15305
Sugar 4655 2369 99 50 1260
Palmolive Oil 4632 4628 99 98 1443
Kerosene 7502 24074 160 512 14342
Total 32349
The Analysis is the data from the pilot implementation of this solution in Andhra Pradesh.
The Andhra pilot has been implemented in 47 Fair Price Shops of the East Godavari
District. The pilot has been a success and has reduced leakages in the system. Our
solution is based on that. This analysis is from the research data.
COMMMODITIES USED FOR ANALYSIS
Commodities Subsidy
Rice 13.70
Sugar 25.00
Palmolive Oil 14.65
Kerosene 28.0
INCREASED INCENTIVES FOR FP SHOP OWNERS WILL CREATE A WIN-WIN SITUATION
Commodity
Avg. No. of cards
per FP Shop
Avg. Qty
Per Shop
Existing
Earnings (Rs.)
New
Earnings
(Rs.)
Increase in
Earnings per
shop (Rs.)
Rice 702 9320 1864 9320 7456
Sugar 703 352 56 352 296
Palmolive Oil 703 703 703 1406 703
Kerosene 660 1358 340 1358 1018
Total 2963 14436 9473
NEW COMMISSION STRUCTURE
Commodity Old Subsidy New Subsidy
Rice 0.20 1.00
Sugar 0.16 1.00
Palmolive Oil 1.00 2.00
Kerosene 0.25 1.00
ASSUMPTIONS
The project has a positive NPV and a
high IRR. It is easily scalable and
sustainable due to the win-win
situation created. Overall the solution
will have a positive economic impact
The solution is based on sound economic logic. There will be substantial
savings to both the Central as well as the State Government. The proposal
of increasing the commission of FPS will create a win-win situation.

11. = High = Medium = Low
RISKMITIGATIONSTRATEGIES
RISK REGISTER FOR THE PROPOSED SOLUTION
RISK EVENT
DESCRIPTOR
Risk Event Type of Risk
Probability of
Risk (a) *
Severity of
Risk (b)
Net Score
(a x b)
R_001 Opposition from the Anti Aadhar Activists Social 3 2 6
R_002 Lack of Support from the States ruled by Opposition Party Political 3 1 3
R_003 Lack of Vendor for the Technological Requirements Technological 1 1 1
R_004 Attack from Hackers and Virus Technological 1 3 3
R_005 Loss of Data Technological 2 2 4
R_006 No Bank Accounts System 3 1 3
R_002
R_006 R_001
R_005
R_003 R_004
Risk Descriptor Risk Mitigation Strategies
R_001
• Educate people on the importance of Aadhar
• Create wide spread campaigns and Give lots of ads
R_002
• Use Political clout and power to drive improvement of PDS
• Make Opposition realize that improving PDS will help their
chances of winning. Bring them on board by negotiations
R_003 • Do Nothing
R_004
• Use good level of firewall and anti virus protection
• For critical data use Intrusion Detection System
• Apply high level of data encryption
R_005 • Take proper care of servers and take backup of all data
R_006
• Use RBIs BC model to drive banking penetration
• Act proactively with RBI an d BCs
Risk Register for the Proposed Solution
Risk Mitigation StrategiesRisk Heat Map
CONSEQUENCE
PROBABILITY
*High = 3, Medium = 2 and Low =1
The proposed solution has some risks but with proper mitigation strategies
it can be implemented. The risks will be mainly political than system or
technological risks. However a common ground may be negotiated.

12. APPENDIX-1
TEAM PROFILE
Nitesh Sinha
Education: B.Tech,ECE, IIT Guwahati
Work Experience: Strand Life Sciences Pvt. Ltd. (22 months)
Summer Internship: Accenture
A DAAD and CBSE merit scholar, Nitesh ranked 153 among 4,80,000 candidates in AIEEE. He has 2 publicationsin international journals and
has undergone internship in Germany. He was placement representative of ECE at IITG and organizer of several national level competitions.
Pritam Banerjee
Work Experience: Consulting, Deloitte, Mumbai
Summer Internship: Equity Research,Espirito Santo Investment Bank, Mumbai
A meritorious student from BESU, and an internationallyrated Chess player, Pritam has worked for Deloitte Consulting as a functional
domain Analyst and is appreciated for his high quality deliverable.His summer internship report on Direct Cash Transfer is widely discussed in
Press and has been appreciated by Senior managementof various companies.
ShubhraGhosh
Summer Internship: CEB, Management StrategyConsulting, Gurgaon
Work Experience: Software R&D, Samsung India Software Operations
CBSE merit scholar (Class X) from MSRIT & Bangalore region topper (Class XII), Shubhra was 2nd in his dept. at MSRIT. At CEB, his work was
rated as 'Exceeds Expectations' where he worked on a US $40 millionproject with a Fortune 500 client deliveringhigh degree of
ManagementSatisfaction. He loves Singing, painting & public speaking.
Priyadarshan Gupta
Education: B.Tech,Electrical Engineering, IIT Bombay
Work Experience: Tensilica TechnologiesIndia Pvt. Ltd. (now Candence)(47 months)
Summer Intern: The Royal Bank of Scotland (InternationalBanking)
AIR 44 in IIT JEE, Priyadarshan has semiconductor industry experience. He was member of the recruitment team and was ‘Student Intern
Mentor’ in Tensilica. He has also worked with “Teach For India” and takes keen interest in football and puzzles.
Somwrita Biswas
Fresh Graduate, B.Tech,IIT Kharagpur
Summer Internship: Investment Banking,Credit Suisse, Mumbai
An NTSE Scholar, Somwrita has an excellent academic record. She has a fair taste of working in different sectors having interned at Credit
Suisse, General Electricand Central Glass & Ceramics Research Institute. She was Head of Asia’s largest techno-managementfest Kshitij &
the Coordinator of a Youth Summit on Climate Change.

13. APPENDIX-2
References
References
Identification of the Poor: Errors of Exclusion and
Inclusion, by Motilal Mahamallik, Gagan Bihari Sahu
Trends in Diversion of Food Grains by Reetika Khera
Revival of the public distribution System by Reetika
Khera
Direct Cash transfer: A game changer? by Pritam
Banerjee, Deepali Bhargava
The task of making the PDS work by Jean Dreze
The PDS Turnaround in Chhattisgarh by Jean Drèze,
Reetika Khera
India's Public Distribution System: Utilization and
Impact by Reetika Khera
http://en.wikipedia.org/wiki/Public_Distribution_Sy
stem
http://pdsportal.nic.in/main.aspx
http://www.apscsc.gov.in/pds.php
http://planningcommission.nic.in/plans/planrel/five
yr/10th/volume2/v2_ch3_4.pdf