Bihar kosi flood report-Importance of Relief Chain Management in Disaster Response
Distribution Network Designs in Relief Chain Management: Government’s response to Kosi Floods 2008<br />A project report submitted in partial fulfillment of the requirements for the degree of Master of Arts in Disaster Management<br />Submitted by<br />Animesh Prakash<br />2009DM007<br />Under the Guidance of <br />Dr. Janki Andharia<br />Jamsetji Tata Centre for Disaster Management<br />Tata Institute of Social Sciences, Mumbai<br />February, 2011<br />CERTIFICATE<br />This is to certify that the dissertation titled “Distribution Network Designs in Relief Chain Management: Government’s response to Kosi Floods 2008” is the record of the original work done by Mr. Animesh Prakash under my guidance. The Results of the research presented in the dissertation have not previously formed the basis of the award of any degree, diploma or certificate in this or any other university.<br />Dr. Janki Andharia 28th February, 2011<br />Professor<br />Jamsetji Tata Centre for Disaster Management<br />Malati and Jal.A.D Naoroji Campus<br />Tata Institute of Social Sciences<br />Post Box No. 8313, Deonar<br />Mumbai-400 088<br />India<br />DECLARATION<br />I, Animesh Prakash, hereby declare that this dissertation titled “Distribution Network Designs in Relief Chain Management: Government’s response to Kosi Floods 2008” is the outcome of my own study undertaken under the guidance of Dr. Janki Andharia, Jamsetji Tata Centre for Disaster Management, Tata Institute of Social Sciences, Mumbai. It has not been previously formed the basis for the award of any degree, diploma or certificate of this institute or any other institute or university. I have duly acknowledged all the sources used by me in the preparation of this dissertation.<br />Animesh Prakash Date: 28th February, 2011<br /> Place: Mumbai<br />ACKNOWLEDGEMENT<br />I owe my sincere thanks to Dr. Parama Bhattacharya, who, in the role of my faculty supervisor during my internship in Bihar, helped me to conceive the idea for this study.<br />The thesis would never have evolved without the contribution of Dr. Janki Andharia. She has been extremely patient in going through my numerous drafts and bringing out even the minutest points of corrections. She, deserves a special mention for her constant support and advice during the entire period of research. I consider myself extremely fortunate to have completed the thesis under her supervision. I owe my sincere reverence and gratitude to Dr Andharia.<br />Dr Samrat Sinha, kept motivating me throughout the process of this study. Faculty Members at Jamsetji Tata Centre for Disaster Management, Tata Institute of Social Sciences have constantly reviewed this study and provided their valuable inputs. I convey my sincere thanks to all of them.<br />Thanks to Dr Anshu Sonak from University of Delhi, Ms. Shivangi from SEEDS, India and Mr. Naval Kishore Yadav, District Provident Fund Officer, Madhepura for their immense help with the data collection. Thanks to Mr. Surender Yadav from Rampur Lahi who took me to the most inaccessible places in the village for the data collection.<br />Thanks to my colleagues, for enriching the quality of the study through debates and discussions. <br />Special thanks to my school teachers, Mr. H.P. Bhatt, Late Mr. B.N. Khanna, Dr Sanjay Dubey, Mrs V Juyal and all others who have worked hard in shaping my personality. Their principles have always guided us to sail through the most difficult paths in life with courage and strength. Demise of Mr. Khanna in 2010 was a great loss for me. Undoubtedly, you were the best teacher I have ever seen and will ever see. <br />I convey my reverence to my parents, for their unmatched efforts in bringing the best opportunities in my life. Thanks to my brothers for loving me always. <br />Finally, thanks to Pakhi for being the most important source of inspiration in my life. <br /> <br />For those who lost their lives in Kosi…..<br />CONTENT<br /><ul><li>Chapter One: Introduction………………………………………………………………12
Importance of relief chain management in disaster response…………….....................12
History and an Overview of floods in Bihar…………………………………………….15
Government’s Relief and Response efforts: Analysing the Distribution Network…...96
State of disaster preparedness in Bihar…………………………………………………96
Government’s Strategy for relief and response after the floods………………………99
Chapter Seven: Towards an enhanced distribution framework……………………...120</li></ul> Appendices…………………………………………………………………………………….130<br />References……………………………………………………………………………………..149<br />List of Figures<br /><ul><li>Madhepura; Political Map………………………………………………………………….09
Summary of findings……………………………………………………………………………...…119
NGOs and Flood Relief Intervention;District – MadhepuraDate of Reporting: 29-09-08……..126</li></ul>Fig 01, Madhepura; Political Map<br />Figure 02, Madhepura, map showing inundation.<br />Figure 03, Madhepura, Road Network<br />CHAPTER 01<br />INTRODUCTION<br />Importance of relief chain management in disaster response<br />An important characteristic of a powerful disaster is infrastructure collapse in the affected region which could severely impact the coping capacity of the affected community. Further it could make the function of Relief Chain Management extremely challenging in a disaster response. A prompt disaster response requires rapid deployment of aid and assistance to the affected area within a shortest possible time, while surpassing, immense dynamic hurdles posed by the collapsed infrastructure. The two components, of the relief chain on which its success relies are logistics and distribution. The challenges increase in severity as aid goes closer towards the real beneficiaries. In many post-disaster situations, aid could not reach the true beneficiaries. <br />Logistics has always been an important factor in humanitarian aid operations, as logistics efforts account for 80% of disaster relief (Turnick, 2005). However in India, the significance of disaster logistics is not acknowledged. “The speed of the humanitarian aid after disaster depends on the ability of logisticians to procure, transport and receive supplies at the site of a humanitarian relief effort” (Thomas 2003, p. 04).Distribution of aid is a vital aspect of relief chain management. Disaster relief operations struggle with very special circumstances, as they often have to be carried out in an environment with destabilized infrastructure, (Cassidy, 2003; Long and Wood, 1995) ranging from a lack of electricity supplies to limited transport facilities. Furthermore, since the magnitude of most natural disasters are unpredictable, the demand for goods in these disasters is also unpredictable (Cassidy, 2003; Murray, 2005). Logisticians in this sector often have to work with fragmented technology and poorly defined manual processes. There are greater issues of safety as they may be operating in a politically volatile climate. Thus it is evident that humanitarian logistics is challenging as it has to be more flexible, and has to function under severe constraints. The biggest hurdle faced by the humanitarian logistics teams is the sheer complexity of the operating conditions within which they have to work in order to supply aid to those who have been affected by disasters. <br /> Transparency and accountability also has gained its importance with the donors, pledging millions in aid and goods, being more inquisitive regarding the relief distribution. Inventory management itself becomes an extremely challenging task in humanitarian logistics. According to Iain Logan, former Operations Manager at IFRC, the Balkan crisis unleashed an overwhelming response from the donor community to the point that IFRC decided not to unload planes carrying unsolicited goods. Richardson (1995) did a comprehensive study on challenges that come across a logistician’s way after a disaster. <br />Ptashkin (2008) recognizes another challenge, i.e., to synchronize network plans, operations, technologies and data to accomplish two objectives: manage, monitor and deliver supplies and services to citizens, service providers and survivors, and enable adaptation and response to alerts and recovery from daily operating events and catastrophic incidents. Lack of co-ordination amongst various governmental and nongovernmental organization working in disaster response. This lack of coordination often leads to confusion at last mile (Murray, 2005).<br />Managing logistics while responding to a disaster is extremely challenging particularly in cases of floods. Normally, floods of great magnitude cripple the existing infrastructure and people may be marooned in large numbers. Evacuation and relief distribution in cases of flood would urgently require all possible sources of conveyance, i.e. from boats to buses to helicopters. Therefore, logistics while responding to floods are expected to pose more varied challenges as compared to other disasters like earthquakes, cyclones etc.<br />The importance of humanitarian logistics was recognized belatedly by several organizations, particularly after the Indian Ocean Tsunami. The Fritz Institute conducted a survey of the response to the Tsunami and found that humanitarian organizations were struck by the scarcity of trained and experienced logisticians in the field. The survey found that 88% of the aid agencies had to recall their most experienced logisticians from other organizations (such as Darfur) to be redeployed to staff the Tsunami relief efforts. <br />In another study by Lee Wassenhove (2006), it was observed that exclusion of logistics in planning leads to fire fighting mentality which makes the logistics management during a disaster- a complex and challenging task. He states that, “It is only recently that, humanitarian organizations such as the International Federation of Red Cross and Red Crescent Societies (IFRC) and the World Food Programme (WFP) have tried to pin-point logistics and supply chain management as key to a relief operation. Other organizations in the sector are beginning to follow suit and raise the profile and professionalism of logisticians.” <br />Other authors have also emphasized on the need of the logistics in disaster response. Logistics serves as a bridge between disaster preparedness and response, between procurement and distribution and between headquarters and the field. It also provides a rich source of data, since it is this department that handles the tracking of goods, which could be used to analyse post-event effectiveness (Thomas and Mizushima, 2005).<br />William B. Cassidy (2010) highlights the impact of relief chain debacle in Haiti earthquake as well as Hurricane Katrina through experiences of Dr. Holguin Veras who has been working with Dominican and Haitian officials to determine ways of expediting relief efforts. Haiti is a classic example of disasters gone worse due to the chaotic relief chain management, similar to the Hurricane Katrina, although it was on a much larger scale. <br />In India, the importance of relief chain management has been gradually realized more and more strongly after major disasters, like the Bhuj earthquake (2001), the Indian Ocean Tsunami (2004), the Kosi floods (2008) and the recent flash floods at Leh in August, 2010. However, disaster logistics remains in its nascent form in India. This study highlights the fact that a vast country like India should be far more prepared for humanitarian logistics to ensure effective deployment of aid and relief interventions.<br />This study focuses on the Kosi floods of 2008, caused due to the breach of the eastern embankment near Kusaha village in Nepal (about 12 kms upstream of the Kosi barrage. A total population of 33,45,545 people living in 993 villages of 412 panchayats of 35 blocks of 5 districts were affected in the flood. About 3,40,742 houses were damaged and 7.12,140 animals were affected. A total of 239 humans and 1232 animals lives were lost. (Department of Planning and Development, Government of Bihar, 2009) However, the lives lost after the subsequent epidemics were exponentially high. Most of the people died due to lack of basic commodities which could not reach them on time due to several reasons. Logistics failure might be one them. This study explores how the government in Madhepura district organized its supply chain during the Kosi floods in 2008 and analyses its strengths and weaknesses.<br />History and an overview of floods in Bihar<br />A famous Albanian proverb says that, “fire, water and government, know nothing of mercy.”<br />Floods in Bihar have placed 8.28 crore people from the state in a perfect position to accredit this saying as most of these floods can be seen rooted to be in human actions.<br />Bihar is the twelfth largest state of India. It accommodates 8,28,78,796 people and has a population density of 880 people/ Sq Km. The state has an extensive river system. It is divided into two parts by the Ganges, which flows from west to east. The region lying in the north of Ganga is drained by Ghaghra, Gandak, Burhi Gandak and Mahananda. All these rivers are tributaries of the Ganges. The district lying to the north of Ganges forms North Bihar. It has been cursed by recurring floods and in particular Kosi has been the sorrow of this region. About 76% of the total population of the North Bihar is reported to be flood prone.<br />Rashtriya Barh Aayog in its report in 1980 has assessed that 4.26 million hectares of area in Bihar is flood Prone. Only the state of Uttar Pradesh (7.336 million hectares) had larger flood prone area than Bihar. This implies that the number of persons hit by flood per unit area in Bihar is the largest as compared to other states in the country. Stating that the causes of floods in Bihar are purely natural would not be appropriate. Several scholars have fiercely debated over the issue, and many argue that floods in Bihar are human induced. <br />During the promulgation of the First National Policy on Floods in 1954, only 25 lakh hectares of area in Bihar was flood prone. According to the reassessment of the Second Irrigation Commission of Bihar, in 1994, 68 lakh hectares were deemed to be flood prone. This itself suggest that there is something much more than nature itself which has resulted into increase in flood incidents in Bihar. Mishra (2010) identifies shortsightedness exhibited by the expert technical opinion, which, he believes, has taken diametrically opposite stances in pre an post independence period. “It opposed construction of embankments during the British rule, as the colonial rulers desisted spending on rehabilitation operations. While in independent India, the technical opinion under the political compulsion to do welfare of the people, has wholeheartedly supported construction of embankments and big dams. As a consequence, not only have flood control projects not performed according to the initial expectations but have in fact created a worse scenario”, (Mishra, 2010) <br />The Kosi Blunder<br />River Kosi is one of the most vibrant and notorious rivers of India. From its origin to its confluence with Ganga at Kursela, it travels 729 kms and drains a total area of 69,300 sq. km. The river is formed by the confluence of seven streams, namely, Indravati, Sun Kosi, Tam Kosi, Likhu Kosi, Dudh Kosi, Arun Kosi and Tamar Kosi. Besides this, major tributaries of Kosi, in India are Kamla, Baghmati, Budhi Gandak and Bhutahi Balan. <br />Like a young child, who desists being disciplined, Kosi moves at her own will, explores new paths and behaves unpredictably. According to a popular hindu legend, it is believed that Kosi cannot be contained by bunds or embankments. The myth goes like this, “Once a demon got attracted by the beauty of Kosi and proposed to marry her. Kosi agreed on a condition that she would marry the demon if he could contain her between the Himalayas and her confluence with Ganga in a night’s time, and if the demon fails, he will have to pay with his life. The demon agreed and set on his work. Seeing the pace of his work, Kosi feared that he would accomplish the task before the set time. She sought help from her father, Lord Shiva, who took the garb of a cock and roosted before dawn could set in. The demon got nervous at this. Thinking he might not be able to finish the job in time and will have to pay with his life, he fled away from the place.”<br />Historically, an embankment on Kosi was constructed in 12th century by the king Lakshman II. The embankment was named Bir Bandh and its remains can still be seen along the eastern bank of Kosi at Bhimnagar in Supaul district.<br />During the British rule, particularly, in the 19th century, a possibility of construction of bunds and embankments on Kosi as flood prevention strategy was extensively reviewed. However, experts opinion oscillated between two groups. One group considered construction of embankments and bunds as inevitable flood control measure. The other group believed that taming the Kosi river through structural measures would accelerate floodings in this region.<br />By the end of the 19th century, signing of Sugali pact between India and Nepal, led to several studies, to explore the possibilities to embank the river Kosi. A futile attempt was made to construct marginal embankment along its course. This could not be made due to heavy rains (Choudhary, 1960). W.A. Inglis toured the Kosi region in India and Nepal in 1893 and suggested against interference with the natural flow of the river. Shillingford in 1895 also questioned the practicality of taming the river’s course. He writes that, “the Kosi after reaching its westernmost limit will go back near easternmost of its abounded channels and then begin the work of moving westwards all over again” (Mishra 2010 quoting Shllingford date unavailable). Shillingford was criticized by Charles Elliot (1895) who opined otherwise. He states that, “there seems to be no evidence adduced to show that the river has reached its westernmost position or to show that if it has, it will return violently from a direct southern to an extreme eastern course, instead of doing so gradually” (Elliot, 1895).<br />On Feb 24th, 1897, on the Calcutta flood conference, means were suggested to build short length embankments to prevent floods in isolated regions. This prompted local authorities, and indigo planters to construct several such embankments. Its repercussions were severe (O’Malley, 1911). even after such severe follies, authorities were unclear about a solution to this recurring problem. Captain F.C. Hirst in 1908, strongly held the opinion that embanking rivers was dangerous as was the case with Hwang Ho river in China. He argued that through structural measures, a river can be forced to follow a particular path. However, containing and taming rivers flow through such human actions are against nature. He states that, “in the nature’s face, it’s an insult, which is not yet known to leave unavenged (Hirst, 1908) W.A. Inglis, in 1909, strongly refuted Hirst. He was of the opinion that embankments designed with discretion and proper understanding of the case are of good service (Inglis, 1909). <br />Amidst the debate over merits and demerits of these structural measures, goovernment’s dilemma persisted and they strived hard to arrive at a solution to the flood problems in Bihar. In relation to this, Patna Flood Conference was held in 1937. In the conference, governor Hallet; G.A.Hall and Dr. Rajendra Prasad all in one voice spoke against the construction of embankments on rivers (Proceedings of Patna Flood Conference, 1938, Pg 2, 8, 9 and 11). Of all the embankments, Rajendra Prasad held responsible, the railway embankments and district board roads, for floods (Proceedings of Patna Flood Conference, 1938, Pg 8, 9). <br />At the Patna Flood Conference first attempt to dam the Kosi in Nepal was given by Jimut Bahan Sen. He suggested it as the only measure to check the Kosi (Proceedings of Patna Flood Conference, 1938, Pg 29). In 1942, Rai Bahadur PC Ghosh studied rivers of North Bihar. He along with WL Murrel, the then superintending engineer were of the opinion that improper maintenance of Tiljuga Bandh (dam) would result in embankment collapse, thereby, drowning thousands of people in Darbhanga district itself (Bahadur and Ghosh, 1942, printed 1949).<br />Figure 04, Map showing date wise inundation in Bihar<br />Suggestions to embank Kosi started coming in more frequently after 1940s. the Kosi Plan of 1945 recommended construction of marginal embankments built 16 kms apart from Nepal foothills to Ganges (Mishra 2010 quoted from Post War Plan of Bihar, 1945). Construction of 229 mts high dam in Barhkshetra was suggested in 1947. However, the project got repeatedly postponed until it was dropped in 1951 on recommendation of Majumdar committee (Mullick, Date not available). The committee sighted the reason that the benefits of flood control would come only in the later stages of the project. The committee came up with an alternative plan called the Belkha Reservoir Scheme (Mullick, Date not available). Under this scheme, 19.2 Km long, 20mt high earthen dam was to be constructed, 14.4 kms downstream of Belka hills.<br />In 1953, another committee of experts was constituted after Nehru’s aerial survey of North Bihar on October 31st and November 1st. The committee proposed construction of 1150 mts long barrage, 5 kms upstream of Hanuman Nagar town. The embankment on kosi was approved in December 1953. The Barrage was built at Bhimnagar between 1959 and 1963, and was inaugurated in 1963-64. An 1149 mt long barrage was constructed along with 46 gates. Two canals were built on either side of the barrage. These canals are Eastern and western Kosi canals. However, this has not brought any respite from the vagaries of Kosi. Rather, it has proved to be a nightmare in flood management. In 1954, Bihar had 160 kms length of embankment, which rose to 3465kms by 1992 (Various annual reports of the Department of Water Resources, Government of Bihar). The Flood prone region in 1954 was 25 lakh hectares which rose to 68 lakh hectares in 1994. <br />Vulnerability to Floods and Earthquakes<br />Structural interventions for flood control on Kosi are also challenged by numerous geographical complexities. The river has one of the world’s largest river built alluvial fan. The Kosi mega fan is 180km long and 150km wide. It cuts across Himalayas and Shiwalik ranges carrying huge quantities of sediments. The upper catchment of Kosi experiences heavy soil erosion due to very high rainfall in these areas (mean 1451.8 mm/yr) the silt load in kosi is largest in the rivers of Indian subcontinent. It averages 80 million tones/year (Aggarwal and Bhoj, 1992). After the river reaches the North Bihar plain, the silt load is deposited leading to aggradation of the river bed. This offers resistance to the flow of water thereby forcing the river to change its course. Precisely, due to this reason containing the river within embankments from both side could be a disastrous step in the long term. The silt would be deposited within the embankment itself and gradually the river bed would rise to such a level that the purpose of constructing embankments would have no meaning. Apart from this shifting of the river is also a natural evolution process. It can be induced by several factors like earthquakes, landslides and neotectonic activities (Aggarwal and Bhoj, 1992). The Kosi flood plains are constantly being influenced by the compressive tectonic regime resulting from the collision of the Indian and Eurasian plates. Besides the presence of various active subsurface structures like East Patna fault, Begusarai fault, Monghyr-Saharsa ridge, Bhawanipur fault, Malda-Kisahnganj fault, Madhubani Graben with sediment thickness of about 6 km and the shallow Purnea Depression underneath the vicinity of Kosi and North Bihar flood plains may result in uplift or subsidence of the surface, causing changes in the river course (Aggarwal and Bhoj, 1992).<br />The flood management on Kosi is therefore far more challenging. The loopholes in Kosi flood management became more and more evident with time. Bihar experienced several devastating floods, even after the construction of the barrage and the embankments. In most of the cases, and particularly in the recent floods of 2008, the reason for flooding was breach of the embankment itself. Of the numerous floods that struck Bihar after 1950, some of the most destructive were the floods of 1953, 1954, 1963, 1971, 1984, 1987, 1991,1995, 2004 and the most recent flood of 2008. The highest flood recorded in the recent history of the river Kosi is reported to be 850,000 cusec (as against the average discharge of 55,000 cusec) on 24th August 1954 (Reddy et. Al, 2008). In 2008, due to the breach of embankment at Kusaha, the discharge of water rose to 1.66 lakh cusec as against 25,744 cusec in the usual course. Kosi started flowing on a new course, where at places it was 15- 20kms wide. Length of the Kosi, flowing north to south on this new course, was 150kms. (Department of Planning and Development, Government of Bihar, 2009)<br />Objectives: Kosi floods saw excessive loss of life and damage to property. The role of disaster logistics and distribution networks has not been explored in the context of these floods. The focus of this study is to explore government’s management of relief logistics and how it can be improved.<br />The specific objectives of this study are:-<br /><ul><li>To identify the district government’s mechanisms of managing logistics while responding to Kosi floods 2008.
To evaluate the efficiency of these mechanisms with respect to its outreach to flood affected people.
To review and analyse the strengths and weaknesses of the adopted distribution network design for relief management with reference to strategic locations of the relief camps, during the first month of the kosi floods in 2008.
To suggest ways of improving disaster logistics at district level in Bihar.</li></ul>The research will primarily examine government’s response during the first month of the Kosi floods in terms of logistics. It will also examine if the government had a plan for the flood response or whether the response was mainly adhoc. The study would also try to explore, if logistics was given enough priority or significance during the flood response. For this people from government responsible for managing logistics during Kosi floods would be identified. Process of managing logistics and relief distribution by these logistics service providers would be captured and analysed. The study would look into the difficulties faced by these logistics service providers. It will also examine how evacuation and relief distribution was managed, how many people were reached by the responders for evacuation and how many people could not be reached. The study will look into the relief provisions made by the government for those who were evacuated by their aid as well as those who could not be evacuated.<br />CHAPTER 02<br />METHODOLOGY<br />Methodology<br />This is an exploratory study that it aims to explore the specific distribution strategies in releif and its effectiveness for people affected by floods.<br />The broad methodology of the research is qualitative. The study draws significant qualitative data from the people affected by the floods and also relies on some secondary sources for data collection. <br />It examines the response, perspectives and insights of the logistics service providers, the agencies of disaster management in India and Bihar, the academicians and practioners engaged in disaster response and the flood affected people in Bihar. In order to analyse the consequences of the adopted strategies in distribution of relief, during the Kosi floods response, this study compares the different situations in which the affected people found themselves at the time of the floods. Since very little is known about distribution network designs in humanitarian logistics, an exploratory, qualitative method is used.<br />The research design:<br />The study examines relief distribution from various perspectives. First, the perspective of the logistics service providers from the state government was considered to understand the situations and circumstances which determined the adoption of specific strategies. What consequences these strategies have? They will be evaluated by examining the consequences on people placed in different situations. Whether these strategies were capable or not capable of directly/indirectly benefitting the affected people would be examined.<br />The three different sets of respondents, for the study were; (a) the officials from various governmental departments who were engaged in evacuation, relief distribution and other activities of relief chain management, during the flood response, (b) the flood affected people who were benefitted by the relief chain management strategies adopted by the authorities. (c) the flood affected people, to whom the benefits of these strategies could not reach, thereby, influencing them adversely. <br />Questions addressed under each objective are as follows:- <br /><ul><li>To evaluate the efficiency of these mechanisms with respect to its outreach to flood affected people.
For this objective, field data collection was guided by following questions:-
Was logistics given enough priority or significance during the flood response? If not:-
What difficulties were faced by the responders due to this?
How many people could be reached by these responders for evacuation?
How many people could not be reached by the government responders for evacuation?
Where were the people evacuated through government’s aid taken?</li></ul>Interviews were conducted with villagers who were either reached by the Government logistics service providers (LSPs) or were not reached by them. Further, interviews were conducted with LSPs who worked during the first month of the floods. <br /><ul><li>To review and analyse the strengths and weaknesses of the adopted distribution network design for relief management with reference to strategic locations of the relief camps, during the first month of the Kosi floods in 2008.
All the research questions listed above (under subsection 1) helped in analysis of the strategies with which the LSPs handled the distribution of the relief goods at various places in Madhepura. The situation that existed during the Kosi response were then reviewed and evaluated with reference to the existing distribution network designs.
To suggest ways of improving disaster logistics at district level in Bihar.
After the detailed analysis of the data collected, the study identifies scope of improvement and offers practical suggestions that could be implemented at the district level in disaster management.</li></ul>Sample:- Managing Humanitarian logistics while responding to a disaster like floods is extremely challenging. Floods of great magnitude cripple the existing infrastructure and people are marooned in large numbers. Evacuation and relief distribution would urgently require all possible sources of conveyance, i.e. from boats to buses to helicopters. Therefore, logistics while responding to floods are expected to pose more varied challenges as compared to other disasters like earthquakes, cyclones etc. Therefore, floods were preferred over other disasters, for the purpose of this study.<br />The specific reasons for selecting Kosi floods as the case were:<br /><ul><li>In April, 2009 it had been only 18 months since Kosi floods had swept Bihar. Its devastation was still visible and people could easily recollect the experiences of the disaster. Moreover, several families still living in ad hoc settlement established during the flood. Hence , research expected to retrieve the data with much accuracy as the event was still fresh in their memories.
The Kosi river in 2008 flooded those regions mostly which had not seen major floods in past several years. Most of the people (from all generations) had never experienced floods in their lives. Even the administration was caught unawares. Therefore, researcher expected to come across various complexities and learnings which would be rather unique and enriching.</li></ul>In Madhepura district, the severely affected blocks were Madhepura, Singheshwar, Shankarpur, Murliganj, Kumarkhand, Udakishunganj, Aalamnagar, Bihariganj, Chausa, Puraini and Gwalpada. The worst affected village during the floods, in terms of loss of life and damage to property was Jorganwa in Murliganj block. <br />At the same time there were villages like Rampur Lahi which were placed in extreme complex situations. During floods Shankarpur block headquarter was unreachable due to inundation and destruction of REO road at Maujma. It was proposed to immediately reconstruct Baily Bridge for effective relief distribution. During that period the region was accessible only through boats. Moreover, in Rampur Lahi a very large number of people were trapped between two rivers, one of which was created only in the floods. Thus, the situation at Rampur Lahi required more attention towards effective logistics for evacuation and relief distribution. <br />Of all the affected areas, Rampur Lahi of Shankarpur block in Madhepura district in Bihar was selected as the study area. People from Rampur Lahi, either stayed in Singheshwar Mega Camp or in the ad-hoc settlement, established at the MVC embankment. Only those people who stayed in either of the camps were selected as respondents for this study.<br />.Although, Rampur Lahi was one of the badly affected regions, it was not the worst affected area in the district. The worst affected Blocks were Murliganj, Kumarkhand, Udakishanganj etc. Jorganwa village in Murliganj was, Particularly, the most affected village. However, inspite of this Rampur Lahi of Shankarpur block was preferred over Jorganwa panchayat due to the following reasons :-<br /><ul><li>I had an opportunity, on an earlier occasion to work for flood rehabilitation for one month. This made me well acquainted with the topography and social structure of the village. I had established good relations and contacts during his stay in the village. In the limited time and budget it would have been impractical for me to collect a comprehensive set of data from Jorganwa.
As stated earlier, due to destruction of REO road at Maujma and creation of a new river at Rampur Lahi during the flood, such situations were created that provided a good base for a study pertaining to disaster and logistics.
Since, I belong to Bihar; I had an advantage of understanding the vernacular languages, culture, customs and practices of the region. This became an important point of consideration for giving preference to Kosi floods over other recent floods in other parts of the country.</li></ul>MVC camp and the Singheshwar Mega Camp were selected for the case study because people of Rampur Lahi, who took refuge in camps, stayed in either of the two camps.<br />After selecting the study area, next task involved selection respondents from Humanitarian logisticians who were involved in Kosi disaster response. At first it was proposed to select the respondent both from NGOs and Governmental organization. After the initial study various NGOs which worked at Rampur Lahi were selected. However, it was later discovered that these NGOs worked at different timeframes for brief periods and would have possibly faced different challenges altogether because the dynamic nature of the then situation. On the other hand, government worked right from the beginning with various departments and their presence was expected uniformly which can be stretched on a temporal platform. Hence the study focuses only on governmental departments. <br /> <br /> In order to get proper representation from various regions within the village, and in order to equally capture different situations that emerged within the village, it was stratified on the following basis:-<br /><ul><li>On the basis of administrative boundaries. (This classification helped in wardwise representation)
On the basis of severity of affected areas. This was further sub classified into:-
Area with limited access to safe route but having accessibility
Area with no access to safe route neither safe location.
This classification and subclassifications helped in considering the severity of the situation in relation to the different situations in which the people were placed in.</li></ul>On the basis of this the village, Rampur Lahi was divided into the following categories (see figure 05):-<br /><ul><li>Ward no 01 and 02 - Least affected areas.
Ward no 03, 04, 05 and 06 – Moderately affected areas with access to safe route. ( exception – some parts of ward no 05 and 06 had limited access to safer route) Shown with red boundary
Ward no 07, 08 and 09 – Moderately affected areas with limited access to safe route but with access to safe location. Shown with blue boundary
Ward no10, 11 and 12- severely affected areas with no access to either safe route or safe location. Shown with yellow boundary</li></ul>Fig 05 Sketch of Rampur Lahi, Stratification for Sampling<br />Figure 06 PRA being conducted in Ward no 01.Source: SEEDS India; 2010, Photograph by Animesh Prakash<br />Figure 07 Group discussion being conducted at ward no 12.Source: SEEDS India; 2010, Photograph by Ankit Jaiswal<br />On the basis of this stratification:-<br />Ward no 01 and 02 were excluded from the sample as relatively these were the least affected regions with only knee deep inundation. Most sof the people were not compelled to evacuate by the forces of water.<br />Thus, I could arrive at the final region from where the respondents were interviewed. This is defined below:-<br /><ul><li>Ward No. 03, 04, 05 and 06
Most of the areas in these wards lay between the MVC canal and the Bariyahi Dhar. Which is the new river, that was created in the floods. This river intersects the village into approximately two equal halves and it has a north south gradient. This region had three strongly built pukka houses which were used as a safer temporary shelter. These houses were
Trisum Bhawan</li></ul>MVC embankment which became the site for large ad hoc settlement during the flood is also next to this region.<br /><ul><li>Ward No 07, 08 and 09. </li></ul> As a new river suddenly swelled, intersecting the village into two halves, people of this region found themselves trapped between two rivers – Bariyahi Dhar and the Jogiya Chahi river. For them it was difficult to escape but most of them had access to safe place i.e., Chhoti Nahar (small canal embankment) which passes through this region.<br /><ul><li>Ward No.10, 11 and 12</li></ul> This was a severely affected region with neither the safe route nor the safer location. People were trapped between two rivers and chhoti nahar embankment was at some distance. People of mahariji tola, ward no 12 were so badly trapped that they had to precariously cross two mighty rivers in order to reach a safer location. People had no alternative, but to build long bamboo platforms in order to escape drowning. Respondents were selected from this area and were classified into the following category:-<br /><ul><li>Respondents who stayed in Singheshwar Mega Camp</li></ul>1-a) Respondents who lost atleast one family member during the flood<br />1-b) Respondents who did not experience any death in family during the flood<br /><ul><li>Respondents who stayed in MVC ad hoc settlement.</li></ul> 2-a) Respondents who lost atleast one family member during the flood<br /> 2-b) Respondents who did not experience any death in family during the flood<br />Sample Size<br />The total population of Rampur Lahi village is 10,500 people. During initial visit group discussions were conducted. Villagers reported that 20 people amongst those who lived in MVC camp died within three months of the flood. Government’s record were silent on this aspect as data was not maintained. Singheshwar Mega Camp incharge stated that it is extremely difficult to maintain such records at this highly crowded ad hoc settlement where every day hundreds of people came in and left and there was no systematic registration mechanism.<br />After the pilot study, 20 no. of deaths from Rampur lahi was considered as the base on which sample was developed. A sample size of 14 respondents from Rampur Lahi was proposed. Out of these the 14, 07 respondent should be from MVC camp and the rest from the Singheshwar Mega Camp. Atleast 40% of 20 deaths were targeted to be covered from each camp. The other three respondents were selected from the families who have not experienced any death. However, while interviewing the people from Singheshwar Mega Camp it was realized that there has been only a one death from the camp, hence other 06 respondents included those respondents who have not experienced any deaths in the family during the flood. <br />Although 50% of the total deaths were covered through the interview of the relatives of the victims, only 5 of them i.e., 25% were included in the final sample as it was decided that from a sample size of 07 from each camp not more than 04 should be from those who have not experienced deaths in a family. <br />Data started showing saturation after 4th and 5th interview in Singheshwar mega camp. In case of MVC camp data started showing saturation after 6th and 7th interview.<br />Considering the vast area to be covered in the village with physical infrastructure collapse in floods and with motorcycle being the only mode of transport( which was difficult to arrange) mobility was difficult. <br />The proposed and the final sample is listed below:-<br />Table 01 Categorisation of RespondentRegionSample Category1-a1-b2-a2-bProposed SampleActual SampleProposed SampleActual SampleProposed SampleActual SampleProposed SampleActual SampleWard No. 03,04.05 and 0601-01-01-0102Ward No. 07, 08, and 0901-01-020301-Ward No.10, 11 and 120201010601010101Total (Actual Sample)01+ 06= 0704+03=07<br />1-a - Respondents who have experienced death in family during the flood while staying in the Singheshwar mega camp.<br />1-b -Respondents who have not experienced death in family during the flood while staying in the Singheshwar mega camp.<br />2-a- Respondents who have experienced death in family during the flood while staying in the MVC camp.<br />2-b- Respondents who have not experienced death in family during the flood while staying in the MVC camp<br />Please note that:- <br /><ul><li>In sample category 1-a and 1b all the actual sample were collected from the third region only. This is because of ward no.12, only people living in ward no Maharaji Tola were evacuated with government’s aid and were taken to Singheshwar Mega Camp.
From sample category 1-a , actual sample was only 01 as against the intended 04. This is because there was only one death in singheshwar mega camp from the village.</li></ul>Selection of Respondents<br />As I was unsure of how respondents in the category 1-a and 2-a would be distributed in the village and as the total number of people in this category was not very large, I have adopted a snowball sampling method for data collection. In order to avoid collecting data from a single concentrated region, the village was divided into three zones (as mentioned earlier). Snowball sampling method was adopted in each of these regions. Address of the first respondent was obtained from Mr.Nawal Kishore Yadav who was incharge of the Singheshwar mega camp. Subsequently, respondents were reached with the reference of the previous respondent interviewed.<br />Data Collection – Tools and Methods<br />The data collection period were divided into two stages, i.e.,<br /><ul><li>Initial stage of data collection and
Final stage of data collection.</li></ul>The initial stage of data collection also being the first stage of exploration, I preferred to have a wide view of the subject without any prior assumptions. At this stage I collected all the information that might have some connection with the subject of the study and maintained detailed notes. For eg, risk perception of the people during the time time of flood, safe routes in the villages, class segregation in the village based on social and economic structure, indigenous knowledge of people etc. The following tools of data collection were used:-<br /><ul><li>Transect walk and observation
Unstructured Interviews</li></ul>During my first four visits to the village, all the places in the village were covered. Simultaneously, I also met with the villagers and explained my purpose of visit. These conversations were crucial as it allowed me to build rapport with the people. This has greatly helped me later too during subsequent data collection. People were requested to congregate at Mukhiya’s place in ward no 01 on the 5th visit. Social Mapping was done with them. Safe routes and locations were identified during this process. It was followed by group discussions using a discussion guide on the floods. People who represented different classes, communities and wards participated equally throughout the process.<br />Table 02 Group discussions conducted during initial stage of data collection.SNCommunity/Group of peopleWardsPlace of FGD01People of Rampur LahiAll WardsWard no 0102People with physical and mental handicapWard no 05 & 09Ward no 05 & 0903Women and old peopleAll WardsWard no 0104People who lived at SMC during floodWard no 12 (Maharaji Tola)Ward no 12 (Maharaji Tola)05People who experienced death of a family member while living at MVCAll WardsWard no 05, 06 and 08.06Sardar families living on chhoti nehar embankment since floodsWard no 12Ad-hoc settlement on the chhoti nehar embankment07Mushar and sardar communityAll wards except 01 & 02Ward no 05, 06, 09 and 1208Muslim CommunityWard no 12 Ward no 12 (Maharaji Tola)09Jha and YadavAll wardsWard no 05, 06,08, 09 and 12<br />In subsequent visits, group discussions were conducted in each tola of each ward of the village with an exception of Maharaji Tola of ward no 12. As it was inaccessible due to two rivers on the way with broken bamboo bridges on them ,this was not even safe for a motorcycle to cross. The region was visited after two months when the water in the rivers receded and crossing them through motorcycles became possible. Areas, which were inaccessible during earlier visits were covered in these visits.<br />During these visits, three more PRAs in ward no 09, ward no. 03 and ward no 05 were conducted to verify the data that were collected on the 5th visit at the mukhiya’s place.<br />Table 3 PRAs conducted during initial stage of data collection.S.NPlace of main activitiesTarget area01 Ward No. 01Rampur Lahi02Ward No. 02Ward No. 0203Ward No. 03Ward No. 0304Ward No. 05Ward No. 0505Ward No.09Ward No. 08,0906Ward No.12Ward No. 12<br />Plans for the data collection for the final stage were made after reviewing the of data collected during the first stage. Subsequently, tools for final stage of data collection were designed.<br />In the final stage of data collection, both primary and secondary sources of data were collected. Main stool of data collection was personal interviews. These interviews were both structured and unstructured. Unstructured interviews were conducted with journalists and TV correspondents, bearing in mind that they had extensively covered Kosi Floods and Structured interviews might just prevent or restrict them to share certain information of substance. Other governmental officials were interviewed through structured interview schedule at their offices.<br />Respondents from villages were also interviewed. Questions were mostly open ended. <br />Each person was individually interviewed at home at a time convenient to his/ her schedule. Interviews generally lasted from 30 to 90 minutes.<br />All of these questions were easily understood by the people. However, some questions like question no 08 in set of questions intended for respondents from singheshwar mega camp needed additional explanation. These questions were asked either in hindi or in the local language. Knowledge of the local language added to the advantage of the researcher in conveying and receiving correct messages.<br />Secondary Sources of data were mainly gathered from the district information officer at the Madhepura Collectorate. He also gave references of websites from where related information could be retrieved. <br />The Scope and Limitations of the Study:- The study focuses only on floods. Although during other natural disasters like earthquake and landslide , similar problems might be faced, it is outside the scope of the study. It can be a prospective research area to test the findings of this study in context of other disaster.<br />Only governmental supply chain and governmental officials of various departments taking up the role of humanitarian logisticians are considered. Non Governmental Organizations and its logistics fall outside the scope of the study primarily because different NGOs kept coming in the region at different time and went out after the intended intervention during their brief stay. Due to the extremely dynamic situation after the floods and magnitude of the challenge the time of the study is limited to the first three months after the floods.<br />CHAPTER 3<br />REVIEW OF LITERATURE<br />Comparison between Humanitarian and Commercial Supply Chain<br />In last few decades, level of comfort has tremendously increased atleast in some fragments of the settlements, particularly the urban settlements. Our daily Ration, cooked and ready to eat food, clothes, medicines, luxury items like jewelry, car, T.V., refrigerator, you name them and you will find them in a store near you, in most of the cases, at walking distance. If you don’t feel like walking upto the store, just make a phone call and the desired product will be delivered at your place within no time. Captions like, ‘delivery in 30 minutes or free’ must have caught your attention. All these comforts which we experience today is result of years of research and innovations that has gone into commercial supply chain.<br />However, many a times certain adverse conditions significantly reduce the outreach of an existing supply chain. This adversities can arise from situations like man made or natural disasters or a massive accident blocking communication routes, or political decisions like impositions of sanctions etc. Under such a situation where the reach of the existing commercial supply chains is limited to such an extent that life and well being of people is threatened, role of Humanitarian Supply Chain becomes significant. <br />In a massive flood, a man is marooned on a tree for several days and an agency brings the commodities essential for his survival at that place itself. But just like him, there are several thousands of people stranded at various places with absolute needs for basic commodities. Non fulfillment of these requirement would make it difficult for them to survive. This gives an idea about how important could be the operations of Humanitarian supply chain. It also explains the basic differences between a commercial and a humanitarian supply chain. Where commercial supply chain generally operates under normal conditions, the humanitarian supply chain faces challenging conditions like collapsed infrastructure, lack of information etc.<br />Inspite of this, unlike its commercial counterpart, Humanitarian logistics is starved of research studies. “The field of humanitarian logistics is relatively new with significant research only having begun to be undertaken within the last five years.” (Maspero and Ittman, 2008). Beamon (2003) differentiated commercial supply chain and humanitarian relief chain on the basis of 07 criteria, i.e., Demand pattern, lead time, Distribution network configuration, inventory control, information system, strategic goals and performance measurement system.<br />Definitions of the factors listed by Beamon in the table 04 is listed below:-<br />Demand Pattern is the pattern of a particular good or service that a consumer/ group of consumer want at a given time.<br />Lead Time is the amount of time between the placing of an order and the receipt of the goods ordered.<br />Distribution Network is the network of intermediaries between the producer of goods and or services and the final user.<br />Inventory control is the supervision of supply and storage and accessibility of items in order to insure an adequate supply and storage and accessibility of items in order to ensure an adequate supply without excessive oversupply.<br />Information System is a system consisting of network of all communication channels used within an organisation.<br />Strategic Goal is the overall goal of an organisation in terms of its market position in the medium or the long term.<br />Performance measurement system is a set of a measureable criteria and methodology to enable performance to be measured objectively.<br />Table 02, Difference between Commercial and Humanitarian Supply Chain (Beamon, 2004, quoted from Maspero and Ittman, 2008)<br />Table 4 Differences between Commercial and Humanitarian Supply Chain, Beamon, 2003<br />In the above table Beamon has highlighted crucial differences between commercial and the humanitarian supply chain. A careful examination of the table suggests that basic differences between the two primarily exist because they operate under different conditions and in different circumstances.<br />The major and perhaps the most important difference between Humanitarian relief chain and commercial supply chain is the different strategic goals they desire to achieve. A commercial supply chain aims at providing high quality products at low cost to maximize profitability and achieve higher customer satisfaction. However, humanitarian relief chain aims at minimizing loss of life and alleviating sufferings (Thomas, 2003). In order to achieve, this strategic goal, a relief chain has to respond in approximately zero lead time. As lead time increases, so the chances of deaths and sufferings also increase. Hence, it is required to respond to the most urgent demands of the affected community within no time.<br />Unlike commercial supply chain, humanitarian relief chain which normally operates in response to a crisis situation or a disaster does not have the advantage of proper demand predictability. This is because demand is generated from sudden random events which themselves are unpredictable in terms of timing, location, type and size. Demand requirement can be estimated only on the basis rapid damage assessments or needs analysis. There is every possibility that outcomes of these rapid assessments would give highly inflated or deflated figures or would altogether omit some important immediate demands of the affected community. As a result, misleading demand pattern could lead to inappropriate intervention.<br />A well defined information flow, as in commercial supply chain, can possibly guide the respondents to establish correct demand pattern. However, establishment of proper information system is itself jeopardized in a post disaster situation, due to massive destruction of the community infrastructure.<br />All these factors make timely dissemination of relief in the affected community, an extremely difficult task. Due to lack of information flow, proper demand pattern is not established. As a result, delivering appropriate aid in close to zero lead time becomes extremely difficult. An alternative solution to this problem can be rooted to better preparedness. Establishing large inventories as preparedness towards disaster response might lead to timely and improved aid delivery. Although the strategy involves high costs, considering the stakes involved, the expenses may be considered necessary. Determining inventory levels based on the demand, demand locations and lead times are some of the problems that are expected to emerge while planning for proper disaster preparedness.<br />Beamon and Balcik (2008) have made comparison between For-profit supply chain and humanitarian relief chain They have stated broad differences between the two supply chains on the basis of strategic goals, demand characteristics and customer characteristics.<br />Strategic Goals:- As put in by Ballon (2004, p 35-37), three prime objectives for firm’s logistics strategy are: (a) Cost reduction, (b) Capital reduction and (c) Service improvement. Based on this, the strategic objective of a commercial supply chain system is producing profit and high quality goods or services corresponding to customer goals or values.<br />The Humanitarian relief chain operates with ultimate goal of saving lives and reducing human sufferings. NGOs, however, have two major bottom lines: Mission effectiveness and financial sustainability (Moore, 2000, Lindenberg and Bryant, 2001). Although, cost is common consideration in both the supply chains, it is slightly lower on a priority in a relief chain when compared to time. Van Wassenhove (2006) points out, “the pressure of time in the relief chain is not a question of money but a difference between life and death.”<br />Demand Characteristics: Demand in a commercial chain are products and services. In a relief chain demands are supplies (aid) and people (Beamon, 2003). More prominent variations are seen in demand patterns. Commercial chain has a predictable and relatively stable demand pattern, whereas, demand pattern in relief chain is highly unpredictable. This is because, demand is generated suddenly due to random events like a disaster. Information regarding location, type or size of disaster or demand requirements and its volume are not known very clearly.<br />Beamon and Balcik (2008), have also described the unique characteristic of the order fulfillment process for the relief chain responding to quick onset emergency. Following factors make process different than that in a commercial chain:-<br />Zero Lead Time: Disaster strikes usually without warnings and creates sudden demands. The lead time, ie, the time between the moment disaster strikes and the time supplies reaches should be close to zero.<br />Transportation unreliabity: Uncertainity in demand location, damages incurred to infrastructure and various other dynamic factors that emerges after a disaster makes it to establish reliable transportation routes for relief distribution.<br />Pricing: As disaster creates abnormal demands, suppliers are lured to raise their prices in response. For most non commodity commercial industries pricing is relatively static over reasonable time horizon (Beamon, Balcik, 2008).<br />Customer Characteristics:- There are significant differences between commercial chain customers and aid recipients. “Unlike the commercial chain, the aid recipient does not have the luxury of market choice for supply (relief supplies). Thus, the aid recipient operates in an unregulated monopoly, where the stakes associated with supplies are often life or death (Beamon, Balcik, 2008).<br />Another significant problem in the field of humanitarian relief chain is determining a well defined distribution network system. As a disaster creates sudden and unpredictable conditions and timely information on the location, type and size of events, state of existing infrastructure are not known, the task of distribution of aid is perhaps the most difficult one in a humanitarian relief chain.<br />Distribution Network Designs<br />From the discussions over differences between the two supply chains in the previous section, some of the factors that emerged time and again, indicated, how challenging could be the task of establishing a distribution network in a humanitarian supply chain. Maspero and Ittmann have quoted Beamon in their paper, ‘The rise of humanitarian Logistics,’ that ‘ Distribution network configuration in a relief chain is challenging due to the nature of the unknowns (Locations, type and size of events, politics and culture) and last mile considerations.’<br />The importance of a proper distribution network in relief chain was emphasized by Balcik and Beamon’s statement that, ‘The stakes associated with relief supplies are often life or death.’ Inspite of this there are very few studies published in the field of distribution network in humanitarian relief chain. Anna Nagurney and Qiang Patrick Qiang in their book, “Fragile Networks: Identifying vulnerabilities and synergies in an uncertain world” describes methodological approaches that both capture and measure network vulnerabilities and performance. This book formalizes concept of network robustness, an important aspect associated with network vulnerabilities.<br />Anna Naguerney et al, in their paper titled supply chain network models for humanitarian logistics: Identifying synergies and vulnerabilities,’ have spoken about the benefits of integration of multiple supply chains for two organisations.<br />Ali Ekici et al, in their paper, ‘Modeling influenza pandemic and strategies for food distribution,’ attempts to comprehend, geographically, the spread of diseases and construct a food distribution network.<br />Each of these papers have made a significant contribution in the field of network in supply chain. However, unlike the commercial supply chain, Humanitarian relief chain still lack studies that directly deals with distribution network models. The focus of this research is to analyse the existing Distribution network models in a commercial supply chain and to construct a distribution network model for the relief chain by adapting the merits of commercial chain that can be workable in uncertain conditions under which a relief chain operates.<br />Role of distribution in a post disaster situation<br />The word ‘Distribution’ in a humanitarian supply chain, ideally refers to the steps taken to move and store relief goods and services from a donor’s end to the beneficiaries end.<br />Section 2 (d) of the Disaster Management Act, 2005 defines disaster as a “catastrophe, mishap, calamity or grave occurrence in any area arising from natural or man made causes, or by accident or negligence which results in substantial loss of life or human suffering or damage to, and destruction of property, or damage to, or degradation of environment, and is of such a nature or magnitude as to be beyond the coping capacity of the community of the affected area.”<br />Going by this definition of a disaster, it is apparently clear that the community hit by the disaster is incapable of coping up with its impact. In order to mitigate its impact, the community largely relies on help from external agencies. Furthermore, the definition also highlights that a disaster leads to loss of life and property. Hence, the significance of distribution of relief goods and services can be understood by the fact that:<br /><ul><li>The local community hit by a disaster requires help from external agencies to cope up with its impact.
Proper and timely distribution of relief goods and services can prevent further loss of lives and property and can bring respite to the affected community.</li></ul>Examples from the recent disasters in India clearly indicate the significance of a proper relief distribution in a post disaster situation. In Kosi floods of 2008, approximately 1300 people from Maharaji tola in Rampur Lahi, were trapped between two flooding rivers. With no safe location to hide, they prepared several bamboo platforms and stayed on it for as long as 90 days. They had no access to safe drinking water, food, sanitation or medical facilities. By the first week, the little food stock they had (maize, sattu, choora etc) had been consumed. Majority of them were sick and needed medical attention. Government’s aid arrived after 10 days. People were given the much needed bottled water, food packages and medicines. Most of them (800 people) were eventually evacuated in a phased manner.<br />In another example from cloudburst and flashflood of August 2010 in Leh district, 1431 houses were either completely destroyed or received substantial damages (Damage Assessment Report; TATA-LAHDC). Leh district has a very harsh climate. In winter, the temperature goes as low as -30 degree centigrade. In an immediate relief and response work, 12 various organisations provided temporary shelters (camps, tents and huts) to the affected community. Around 35 various governmental and nongovernmental organisation were engaged in distribution of blankets and beddings to these affected people. <br />In both the cases, various organisations responded quickly to the immediate needs of the affected communities. Distribution of relief goods like food medicines, blankets etc during a disaster response is a significant but neglected area of planning and in order to prevent secondary threat and bring down further fatalities.<br /> <br />Factors affecting distribution network designs<br />In this section, broader goals in a commercial supply chain are identified. Further, cost and service factors which determines adoptions of distribution network designs keeping in mind the broader goals of a firm is dealt with. This section provides a platform to study that how the similar factors from the commercial supply chain, when operational in humanitarian relief chain is prioritized and subsequently on the basis of this prioritization a distribution network design is adopted in a humanitarian relief chain. After discussing the broader goals, service and cost factors in commercial supply chain, the same factors are studied in respect of humanitarian supply chain. The various distribution network designs as present in the existing commercial supply chains are then evaluated on the similar parameters to determine an appropriate distribution network design, in the last mile and immediately after the floods (as the study is centered in the last mile and during the first three months). This section, thus provide the basis on which the analysis of government’s distribution process during first three months of Kosi floods, is done in the later sections of the study.<br />Factors affecting distribution network designs<br />Performance of distribution network is evaluated broadly along two dimensions:-<br /><ul><li>Customer needs that are met
Cost of meeting customer needs.</li></ul>These broad goals, guides a company to adopt a distribution network design which in turn also determines the strategies for, the inventories, transportations, facilities and handling and information.<br />Structure of a distribution network also influences key service factors which are essential to achieve better customer services and ensure customer satisfaction. Some of these factors are:<br /><ul><li>Response Time
Returnability</li></ul>Apart from these service factors, there are four main cost factors, which are also considered as the main drivers in a supply chain. These factors are:<br /><ul><li>Inventories
Information</li></ul>Distribution network designs are adopted in such a way that it affects the above stated factors (cost and services) to achieve its strategic goals. In a commercial supply chain, companies driven by profitability, decides on adopting a distribution network design that would decrease its cost and increase its revenues. In humanitarian supply chain, service factors like Response time, product availability etc are prioritized before cost factors while determining distribution network designs.<br />Response Time is the time between placing an order and receiving the delivery.Product Variety is the different number of products that a distribution network has to offer.Product Availability is the probability of having a product in stock when order arrives. Customer experience includes the ease with which a customer can place and receive their order. The ability to track the order from placement to delivery is order visibility and the ability to return unsatisfactory merchandise is the returnability.<br />Same factors when operate in a relief chain behave differently. Some of these differences have been elaborately dealt with, in earlier sections. The reasons for emergence of these differences are discussed below:<br /><ul><li>Strategic Goals :- The ultimate goal of a relief chain is to save lives and reduce human sufferings. The stakes of supplies, in a relief chain are human life and health.
Uncertainties:- As discussed in earlier sections, relief chain operates in an extremely uncertain environment. The demand uncertainties pertaining to location, type and various demands great flexibilities in a relief chain.</li></ul>Slack (1991), Beamon and Balcik (2008) have emphasized on the importance of flexibility in a relief chain. They have discussed, the following, three flexibilities in their respective works:-<br /><ul><li>Volume Flexibility (ability to respond to different magnitudes of disasters): Volume flexibility allows an organisation to respond to different magnitudes of disaster, with a wider range of relief in less response time. Beamon and Balcik defines volume flexibility as the number of tier I supplies (individual units) an organisation can provide during the critical time period for relief, ie, the time during which the greatest number of lives is lost.
Delivery Flexibility (time to respond to disasters): Beamon (2008) defines delivery flexibility as the minimum response time, which is the elapsed time between the onset of disaster and the arrival time of the organisation’s first supplies to the disaster’s site.
Mix Flexibility: Mix flexibility for the relief chain is the ability of an organisation to provide different types of items during a particular period.</li></ul>Hence, from above discussion, it becomes apparent that unlike distribution network in supply chain whose performance is measured on the basis of customer needs and costs involved, distribution network in relief chain should be evaluated on the following parameters:-<br /><ul><li>Beneficiaries’ needs that are met.
Beneficiaries covered/Leftout by the distribution network or in other words, the reach of the distribution network.</li></ul>As the basic differences in a distribution network designs in a supply chain and a relief chain are so evident, it is also expected that key factors in a distribution network design will also be prioritized differently in the two supply chains. The key factors in a distribution design, as discussed earlier are, Response time, product variety, product availability, customer experience, order visibility, and returnability. The order in which these factors are prioritized in a relief chain are as discussed as under:-<br /><ul><li>Response Time: As stakes in a relief chain is human life and health, response time is a very crucial factor. Critical time period for relief is the time during which the greatest number of lives is lost. Efficiency of relief chain in the critical time period plays a significant role in bringing down the total death toll. In 2010, Leh flashflood, Major Neetu singh, of 740 TPT workshop, 7014 EME battalion, reported that their unit responded to the disaster within 10 minutes and saved 89 lives from a place, 3 kms away from Phyang village. Damage assessment report of the district authorities lists 248 dead and 76 people missing from the whole district. (www.ladakhflood.org). Thus, with a very quick response to the disaster, the unit has saved lives equal to 36% of the total deaths. This explains how crucial, response time in a relief chain can be.
Product Availability: Product availability is probability of having a product in stock when the demand arises. Due to, disasters being extremely random and uncertain events, to maintain the product availability for the affected area and population is rather challenging (as location, type and volume is uncertain), It requires a great deal of preparedness and planning.
The repercussions of not having the product availability can be huge. As procuring and arranging all the goods after a disaster has struck, would lead to increase in the response time which might result in increase of losses of life and property.
Product Variety: Product Variety is different number of products that a distribution network offers. In response to a disaster, a variety of products are required to be supplied in the affected area. This could range from ready to eat foods, bottled water, a variety of medicines, hygiene kits, tents, blankets, clothing etc. Group discussions conducted in Rampur Lahi, Madhepura revealed that Post Kosi flood, people taking rescue on MVC embankment survived on Khichdi (dal and rice cooked together) which was served once a day, for a month.
Customer Experience: Beamon (2008) states that aid recipient does not have the luxury of market choice for supply. Thus, the aid recipient operates in an unregulated monopoly, where the stakes associated with supplies are often life or death. Hilhorst (2002) have raised the concern that as there is no formal contract between NGOs and recipients may not have effective mechanisms for representation and often lack recourse to appeal, if their expectations are not met. All this, however, does not mean that customer experience is not important or does not have a significant part to play in success of a relief chain. A section ahead, deals with a case study which shows that how people’s refusal to accept bad relief goods have resulted in clogging of warehouses, railway godowns etc. Allthough, most of the relief goods are distributed for free, dignity of the beneficiaries should not be hurt at any cost. It is essential to ensure the beneficiaries’ satisfaction while distributing the goods to them.
Returnability: Returnability of relief goods which were dispatched with intentions of free distribution, would mean additional costs involved. In cases of NGOs returnability, which signifies failure of projects, might also have a negative impact on its functions in future projects as well. NGOs, which have two major bottom lines: mission effectiveness and financial sustainability (Moore, 2000; Lindenberg and Bryant 2001, p 218) would rather prefer to dump these goods on site rather than to return it to the source. Its repercussions could be clogging of the relief chain facilities, which would mean additional pressure on it.
Order Visibility: Order visibility is a characteristics of commercial supply chain. Its practicality in a humanitarian relief chain can be put to fierce debate. However, obtaining some sort of visibility in a relief chain can be significant particularly in the last mile distribution. For eg, visibility about date, time and place of arrival of medical assistance would help needy people to congregate at one place, thereby, making it easier for relief operations as well. However, it might come up with additional disadvantages as well. Like there can be chances of pilferages, looting or threatening socially vulnerable groups and preventing them to collect relief.</li></ul>Of the six factors, due to the reasons cited above, response time is of extreme priority as the stakes involved with it are human life and health. Product availability and product variety comes next, respectively. These two factors are essentially important as it deals with meeting up with the basic needs of the affected communities. Customer experience, with which, are associated the important issues of human rights and dignity, comes next and returnability and order visibility which can be questioned on the basis of its practicality and implications inspite of its significance are placed down in the order of priority.<br />Hence, the order of priority which determines the importance of the various factors in a relief chain are as under:-<br /><ul><li>Response Time
Order Visibility</li></ul>This sequence in priority of the above listed factors will be utilized to analyse the merits of the commercial distribution network designs and to adopt some of these merits in the distribution framework for the humanitarian relief chain, which will be discussed in the later sections. Next section deals with the analysis of distribution network designs as propounded by Peter Meindl and Sunil Chopra<br />Distribution Network Designs in a Supply Chain.<br />Meindl and Chopra, in their paper, ‘Designing the delivery network for a supply chain’, have discussed six distinct distribution network designs that can be adopted in a commercial supply chain management. These six network designs are:-<br /><ul><li>Manufacturer Storage with direct shipping
Manufacturer Storage with direct shipping and In Transit merge.
Distributor Storage with package Carrier delivery
Manufacturer/Distributor Storage with customer pick up
Retail Storage with customer pick up</li></ul>Authors have used several factors for the evaluation of the performance of these network designs. These factors are categorized broadly into:-<br /><ul><li>Cost Factor
Order Visibility</li></ul>Manufacturer Storage with direct shipping <br />In this distribution network design, a product is delivered directly from the manufacturer to the customer location. The design either bypasses retailers or restricts their role to the information flow only. All the inventories are stored at manufacturer’s end. Retailer does not hold any inventories. Diagrammatic representation is as under:-<br />Fig:08 Manufacturer Storage with direct shipping<br />Merits<br /><ul><li>Inventory: This design allows a manufacturer to centralize inventories at his end. A manufacturer can aggregate demand across all retailers, as a result, a high level of product availability is maintained with lower level of inventory.
Facilities and Handling: The design allows a supply chain to save on the fixed cost of facilities. This is because, all the inventories are centralized at the manufacturer’s end. Manufacturer also saves on additional warehouses as aggregation of inventories at Manufacturer’s end eliminates the need of additional warehousing space.
As the retailer is eliminated from the product flow, some costs on handling is also saved. However if a manufacturer is incapable to develop single unit delivery, it can have significant negative impact on handling cost and response time.
Product Variety: The design allows a manufacturer to maintain a high level of product variety to its customer. Drop shipping model allows a customer to choose from any of the products, a manufacturer produces, as all of these products are aggregated at manufacturer’s end.
Product Availability: Retailers does not hold any inventory. All the products are aggregated and stocked at manufacturer’s end. This allows a manufacturer to maintain a high level of available product
Customer Satisfaction: In terms of delivery of goods, customer satisfaction is usually good. However, difficulty in handling returns might lead to customer dissatisfaction. </li></ul>Demerits<br /><ul><li>Transportation: Outbound transportation costs (costs incurred in sending material out of a facility) are high because of the average outbound distance to the end consumer is large.
Information: A retailer forms an important link, between the manufacturer and customer. As the retailer does not hold any inventory, a strong information mechanism is required to disseminate correct information about the product availability to the customers and demands to the manufacturer.
Response Time: Due to the increased outbound distances, response time is usually high.
Order Visibility: It is very important and at the same time very difficult to ensure order visibility. Order tracking is difficult as requires complete integration of information system at both the retailer and the manufacturer.
Returnability: Returnability is expensive under this design as it would require establishment of additional set ups by the retailers or a product can be directly returned by the customer which would involve high transportation and coordination costs.</li></ul>Manufacturer Storage with direct shipping and In Transit merge<br />One of the disadvantages of a drop shipping is that an end customer might get several small packages from various manufacturer directly, as products are send directly from manufacturers to the customers. Manufacturer storage with intransit merge combines pieces of the order coming from different locations so that the customer gets a single delivery. The design is illustrated below:<br /> <br /><ul><li>Fig09 Manufacturer Storage with direct shipping and In Transit merge</li></ul>Cost involved in In-transit merge is slightly higher than drop shipping as, although transportation cost is dropped due to reduction in outbound distance but investment required for setting up facilities for handling and information makes the total cost go up. <br />Service factors remain similar to that of drop shipping except that this model provides better customer satisfaction as it facilitates merging of several packages so that customer gets a single delivery.<br />Distributor Storage with package Carrier delivery<br />Under this design inventory is held, not by manufacturers but by the distributors/retailers in intermediate warehouses. In order to Transport products from the intermediate location to the final customer packaged carriers are used. The following diagram depicts the Distributor storage with package carrier delivery, distribution network:<br /><ul><li>Fig 10 Distributor Storage with package Carrier delivery
Transportation: Transportation cost is less than the cost involved in manufacturer storage designs. Intermediate warehouse decreases the outbound distance. Although, inbound distance is increased, more economic mode of transportation can be employed for inbound shipments. Hence the overall transportation cost goes down.
Information: A less complex information infrastructure is required as compared to the manufacturer storage, as the ware house serves as the buffer between the manufacturer and the customer.</li></ul>Service Factor<br /><ul><li>Response Time: As compared to the Manufacturer storage designs, response time in this design is less. This is because the intermediate warehouses, which are located closer to the customer, reduce the outbound distance.
Customer Experience: The design allows achieving better customer satisfaction as it facilitates single delivery in less response time.
Order Visibility: As a single shipment reaches the customer from the warehouse, involving one stage of the supply chain, the design offers better order visibility.
Order Returnability: An intermediate warehouse ensures better returnability as compared to the manufacturer storage as order returnability can be processed using this facility</li></ul>Merits<br /><ul><li>Inventory: Due to setting up of intermediate warehousing facilities, aggregation of demand is uncertain. The cost of maintaining inventories at the intermediate warehouses is more than storage at manufacturer’s end.
Facilities and Handling: Facilities and Handling cost is also high as compared to the manufacturer designs as this design prevents aggregation of products at one place.
Product Availability: In order to maintain the same level of availability as the manufacturer storage a higher cost would be required in this distribution network design. The design also offers less product variety as compared to the other two designs. </li></ul>Distributor storage with last mile delivery<br />Distributor storage with last mile delivery is a distribution network designed with intentions of delivering the products to a customer’s doorsteps. As the transportation cost involved is bound to high, more warehouses are required to be located in such a way that they are much closer to the customers. As a result infrastructural cost is also high in this design.<br />Fig 11 Distributor storage with last mile delivery<br />Merits and Demerits<br />This design performs, extremely good on service factors. However, better customer service comes at a higher cost. As the warehouses are setup closer to the customers, response time is very less. The design requires huge infrastructural setup and maintenance cost. Product availability requires heavy expenditure and product variety is also less as compared to distributor storage with package carrier delivery.<br />Manufacturer/Distributor Storage with customer pick up<br /><ul><li>In this design, inventory is stored at the manufacturer or distributor’s warehouse, but a customer has to come to a designated place to pick up their orders placed through internet, phone or any other medium. The figure represented below shows the functions in this distribution network design:-
Fig 12 Manufacturer/Distributor Storage with customer pick up
This network requires higher response time. However, if a product is stored at pick up sites response time is substantially reduced. Transportation cost is usually lower as more economic mode for transport can be selected for the inbound distance (Manufacturer to the pickup sites). The network requires heavy investment in the infrastructure for information which is necessary not only to aggregate demand, but also to maintain order visibility.
Retail storage with customer pickup</li></ul>Inventory is stored locally at retail stored locally at retail stores. Customers place their order and collect it from the store itself. Product is delivered almost immediately. Mainataining product availability requires heavy expenses and product variety is also least as compared to all the other designs discussed earlier.<br />Analysis<br />Dynamics of a disaster is such, that it would be illogical to use any of these distribution network designs in its totality. These designs have been framed for commercial supply chain which has significant differences when compared to the relief chain. Adoption of any of these designs for a relief chain is neither recommended nor desired. Infact, arriving at a distribution network design for a disaster response is a herculean task, as there are so many uncertainities in terms of magnitude, location, type etc. No two disaster will be same in its characteristic. Hence applicability of designing a distribution network prior to disaster will always be questioned. But one thing that goes strongly in favor of it is that a distribution network design for a disaster prone area which is constructed after extensive planning enhances the preparedness level manifolds. This is crucial for an effective disaster response. The analysis of these designs is done with a purpose to study those aspects which would hold significant merit if incorporated in any distribution network designed for a humanitarian relief chain.<br />While analyzing the applicability of drop shipping model in a disaster situation, a crucial point which emerges, is that the outbound distance is large. As a result, the model performs low in response time. As discussed earlier, response time is of extreme importance in a relief chain. Thus, the model apparently seems to be inapplicable in a disaster situation, however, not in every case. Unlike a supply chain, donors in a relief chain can be located at any distance from the site of the disaster. Infact, during the critical phase of a disaster, the greatest help comes from the local community, from and around the affected area. This pattern is seen in more or less every disasters as logically, considering the time and distance, local responders are also the first responders during the critical phase. List of NGOs that were involved disaster response in the first months during the 2008 Kosi flood and later the 2010 Leh flashflood as shown in the appendix, substantiates the fact. <br />Evaluating the model in a critical time period and for donors at shorter outbound distance from the beneficiaries/affected area, might yield interesting outputs. In the critical time period when outside help has not arrived, donors from within and around the affected area play a key role in relief work. This model can be applied successfully for this small group of donors and for a small period of the critical phase of the disaster. The diagrammatic representation is given below:-<br /> Fig 13 Distribution Network Design in Humaniatrian Logistics for local Donors<br />Due to shorter outbound distance, Response time is low. Coordinating agency plays a key role in information flow between the beneficiaries and the donors. The coordinating agency also plays an important regulation which ensures distribution as per the needs of the community and capacity of the donors. Product availability might suffice basic needs of the community for a very short period of time. That depends on the size of beneficiaries, level of disaster and help that is generated by the local donors. However, the model can ensure equitable distribution of aid generated by the local donors, through an effective coordinating agency. The model can be applied only to a small fraction of donors and in a critical phase only.<br />The Manufacturer storage with direct shipping and In-transit merge, is an improvement of direct shipping. The concept of In-transit merge can be useful in a disaster relief chain. Disaster creates sudden demand for numerous products, like, ready to eat food, bottled water, medicines, Utensils, tarpaulin, blankets, bedding, soaps, sanitary napkins etc. Various organisations prepare their relief kit and distribute it in the affected region. Most of the time, the relief kit contain several common products. As a result there is a large number of aid duplication in the time of delivery.<br />In 2010, Leh flashflood, more than 50 organisations came with their aid in the first month after the disaster. 16 organisations, distributed, blankets in leh town. Other severely affected regions like Ney, Lehdho, Skindyang, Khaltsi, and Wanla were not covered at all, even by a single organisation. As a result, in some parts, families received more than 05-06 blankets, whereas, in other parts fa