piratesofvastrapur
TRANSCRIPT
Pritam BanerjeeInternship – Espirito Santo,
Investment Banking
Shubhra Ghosh Internship –CEB, Mgmt. Strategy
Consulting
Somwrita Biswas Internship –Credit Suisse, Investment
Banking
Nitesh SinhaInternship – Accenture,
Management Consulting
Priyadarshan GuptaInternship – RBS,
International Banking
PLUGGING THE LEAKSImproving reach and efficiency of the Public Distribution System
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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 onthe public data was carried out. Thedata published by the PlanningCommission, Ministry of Agriculture,PDS Portal of India was consulted.Also research papers by eminenteconomists like Dr Reetika Khera, DrJean Dreze were referred.
Primary Research
We did an extensive researchmeeting experts (academicians,policy makers, researchers) on PublicDistribution System. A visit to oneFair Price Shop was done Thesecondary research along with theprimary data collection has helped usto find the root cause of the problemand 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, AndhraPradesh are fairing high, States like Bihar, Rajasthan are languishing. Themain 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
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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 anequivalent decrease, in another dimension it would make it irrelevant.For instance, the situation of a family eating only once a day gets nullifiedif it has quite a few items of clothing or is doing well across any otherdimension not as serious as not getting food.
Equal weights of dimensions can be treated as a poor description ofpoverty. For instance, not having one square meal a day throughout theyear is treated equivalent to open defecation or not possessing electricalappliances
The poor often has no access to credit market because of their inabilityto offer any acceptable collateral. But the highest score of “4” has beenassigned 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 ofpoor. Give scores (0 if non vulnerable & 1 if vulnerable) tohouseholds for each dimension & add to get compositescore. Include all households in vulnerable list. Ahousehold is vulnerable if it bears at least one of thefollowing 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 homesteadland with no regular salary earner
Households that hold <=2 ha of standardized cultivableland with no regular salary earner & primarily engagedin 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 singlewoman member, disabled person who is the solebreadwinner of casual work, no member above 14 years ofage, households bearing destitute characteristics
Estimate the weights of each of the vulnerability factorusing logistic regression.If P is the probability of a household being poor, thenP = [1+e{–βX}]–1 where “β” is a vector of the unknowncoefficients and “X” is a vector of covariates that affectthe 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.
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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.
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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.
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 /AadharCard 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.
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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.
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SYSTEM REQUIREMENTS
• All Fair Price shops shouldhave a board stating thecommodities that can befound in that shop and thecorresponding prices in thelocal language
• Give printed receipt ofeach transaction in locallanguage to the customers
• Validate users based onAadhar Number ordigitized ration card no
• Co-ordinate with UIDAIand National PopulationRegister for UID
• Use Point of Sales deviceto validate users. It shouldbe equipped to carry outbiometric validation. Toovercome the challenges ofa good fingerprinting, usethe Best Finger DetectionTechnology. It records thefinger prints of all thefinger of the beneficiariesand finds out the bestfinger which an be used forproper validation
• PoS device Cost Rs 20,000with a life of over 4 yearsmaking them extremelycost effective
• Digitize all transactions andstore the data in acentralized server. This willhelp forecast demand andmonitor FP Shops.
• The PoS device should alsohave a voice over facility tosay out the commoditiesentered in the device andthe corresponding price andthe total amount to be paidby the beneficiary. All theabove should take place inlocal language.
• This facility will protect thebeneficiary from dishonestshop owners and will plugleakages in the PDS
• Online tracking of thevarious points in the Supplychain will prevent thepossibility of leakage of foodgrains during the transfer ofcommodities fromwarehouse to the shops.
• Assign responsibilities of aroute to specific person andmake him liable for anypilferage.
• At the same time track theamount of food grainstransferred from eachlocation. This an be done bysending the inventory dataof each FPS to the centralserver.
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.
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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 accuratelyWill 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 periodThis dynamic allocation of products will not only reduce wastage but will also save money in terms of lost inventoryInventory carrying cost will also come down
Use Strong monitoring of the conditions of the Fair Price ShopsUse surprise visits to the stores to make it unpredictable for the shop ownerTake 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.
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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
generationMobilize people within the
GovernmentSet up Control rooms and monitor
progressEducate people about Aadhar and
how it can be usedDemonstrate benefits of Aadhar Use TV ads and radio ads
Database Seeding Phase: Coordinate with different departments to digitize dataUse 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 addressPerform de-duplication and other processing techniques on the data.
Roll out Phase: Procure Po device for rolloutRoll 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 simultaneouslyMonitor results and use proper feedback loop
Funds and HR RequirementsHuman resource is required mainly forpromotional activities and setting upof amps. Approximately 5 personnelper 100 beneficiaries will be required.The funds required will be mainly foradvertisements. W e believe thatapproximately Rs 100 Crore will berequired for advertisement purposes.
Funds and HR RequirementsIn this phase back end HR will berequired. This will typically be in thetunes of 1 person per 100 dataentries. Highly skilled data entryoperators can be hired.The additional cost to the Governmentis almost negligible. Most of the costshave already been sanctioned.
Funds and HR RequirementsMinimal Human resource needed forcontrol purposes. Need somesupervisors for monitoring.From the cost perspective, the costs ofthe PoS devices will be incurred. This isvery small compared to the opportunitycosts of the welfare schemes of theGovernment.
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.
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THE PROPOSED SOLUTION WILL GENERATE SUBSTANTIAL SAVIINGS TO BOTH CENTER AND STATE
CommodityTotal No of cards saved
Total Quantity
Saved
Avg. No of cards for which ration is
not withdrawn
Avg. Qty saved per
shop
Central Subsidysaved 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 GodavariDistrict. The pilot has been a success and has reduced leakages in the system. Oursolution 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
CommodityAvg. No. of cards
per FP ShopAvg. 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 ahigh IRR. It is easily scalable andsustainable due to the win-winsituation created. Overall the solutionwill 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.
= High = Medium = Low
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RISK REGISTER FOR THE PROPOSED SOLUTION
RISK EVENT DESCRIPTOR
Risk Event Type of RiskProbability 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_002R_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
PR
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*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.
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TEAM PROFILE
Nitesh SinhaEducation: B.Tech, ECE, IIT GuwahatiWork 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 publications in international journals and has undergone internship in Germany. He was placement representative of ECE at IITG and organizer of several national level competitions.
Pritam BanerjeeWork Experience: Consulting, Deloitte, MumbaiSummer Internship: Equity Research, Espirito Santo Investment Bank, MumbaiA meritorious student from BESU, and an internationally rated 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 management of various companies.
Shubhra GhoshSummer Internship: CEB, Management Strategy Consulting, GurgaonWork 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 million project with a Fortune 500 client delivering high degree of Management Satisfaction. He loves Singing, painting & public speaking.
Priyadarshan GuptaEducation: B.Tech, Electrical Engineering, IIT BombayWork Experience: Tensilica Technologies India Pvt. Ltd. (now Candence) (47 months)Summer Intern: The Royal Bank of Scotland (International Banking)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 BiswasFresh Graduate, B.Tech, IIT KharagpurSummer Internship: Investment Banking, Credit Suisse, MumbaiAn NTSE Scholar, Somwrita has an excellent academic record. She has a fair taste of working in different sectors having interned at Credit Suisse, General Electric and Central Glass & Ceramics Research Institute. She was Head of Asia’s largest techno-management fest Kshitij & the Coordinator of a Youth Summit on Climate Change.
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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 PritamBanerjee, 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_System
http://pdsportal.nic.in/main.aspx
http://www.apscsc.gov.in/pds.php
http://planningcommission.nic.in/plans/planrel/fiveyr/10th/volume2/v2_ch3_4.pdf