PiratesofVastrapur

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PiratesofVastrapur

  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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

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