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Research Issues
Research Opportunities for Supporting Humanitarian Operationsby Aruna Apte, The Naval Postgraduate School In 2009 there were "335 natural disasters reported worldwide that killed 10,655 persons, affected more than 119 million others, and caused over $41.3 billion in economic damages" (Vos et al., 2009). The back-to-back disasters in 2010 (Haiti and Chile earthquakes, Pakistan floods, and the Icelandic volcano eruption) have had significant impact on the academic interest in the area of humanitarian operations and disaster response. The recent triple disasters in Japan and the subsequent crises have added further interest to the topic of crisis management as well. Some of the reasons behind this heightened level of interest are: a genuine wish to help in some way; the research opportunities presented by these complex and messy problems involving conflicting objectives through all the phases of the response supply chain; realization of the gravity of the situation amongst humanitarian as well as military communities; and, more importantly, the need to squeeze the last drop of value for humanitarian assistance from ever-diminishing budgets. In response to the challenges faced in mitigating the disaster impact, and due to the interest of the academics as well as practitioners in private and public sectors, several research articles and case studies have been written describing different situations, challenges, and decisions. An informal survey including a list of citations can be found in Apte (2009). It offers a contrast between the somewhat theoretical and simplified but specific concepts of the prescriptive academic research and the broader and complex situations through the descriptive case studies in the field. The case studies help uncover the processes underlying humanitarian logistics and the lessons learned. They also describe the response to the disasters by various organizations. But equally importantly they direct us towards the needs of the community for more effective and efficient response. Analytical models try to simplify the real-world situations and quantify the tangible as well as intangible impacts of the disasters in order to offer solutions for better outcomes. However, by describing the actual practice and events, the case studies present what works and what does not. These case studies of the past and the challenges of today as experienced by the humanitarian officials set an agenda for research in the field of humanitarian logistics. Arguably, the knowledge about the realities of humanitarian assistance and disaster relief in the academic world is somewhat limited. Therefore, by grounding the research in 'real' data, academics can play an important role in addressing the challenges and issues in humanitarian operations and disaster response. Before suggesting a way forward for research in this area we provide some background information. Challenges in the Lifecycle of a Disaster It is believed that being prepared in the pre-disaster phase will lead to better response operations during and after the disaster. In fact, the United Nations estimates that for every dollar spent in prepositioning, seven dollars can be saved in disaster response. However, the specific strategies will differ based on the type of the disaster since the nature of a disaster influences the operational difficulty of the entire humanitarian assistance. A classification of disasters based on manmade versus natural disasters does not offer substantial inference for research in humanitarian operations. However, a classification based on time and location can be very helpful in assessing the operational difficulty (Apte 2009). As seen in Figure 1, disasters can be classified as localized versus dispersed in terms of location and slow-onset versus sudden-onset in terms of time. Some examples of recent disasters are provided in the resulting 2x2 matrix in the figure. Effectiveness and efficiency of transportation and distribution of critical supplies and services suffer if the disasters are dispersed and sudden-onset, such as the 2004 tsunami in the Indian Ocean which affected many countries. On one hand, we have localized and slow-onset disasters (such as the 2011 floods of Mississippi), and on the other hand, there are dispersed and sudden-onset disasters. In between are the rest, localized and sudden-onset (such as the 2010 earthquake in Haiti) or dispersed and slow-onset (such as the 2009 H1N1 flu pandemic). Figure 1: Classification of disasters.
The other concept particularly useful for conducting research in humanitarian operations is Lifestyle of a Disaster (Apte 2009). The lifecycle of a disaster can be divided into three phases (Figure 2): preparedness in the pre-disaster phase, response immediately after the disaster strikes, and recovery in the post-disaster phase.
Figure 2: Lifecycle of a disaster.
Being prepared is the first step in the right direction for mitigating the impact of a disaster or conflict. Therefore, readiness is rated high in any military operation where uncertainty is the name of the game. Some of the principal challenges in being prepared are planning for and establishing adequate capacity and resources, installing critical infrastructure, and investing in technology that will enable the flow of information. Military organizations routinely face many such challenges and therefore they have policies and procedures in place that have been tested through events of war or other disasters. Commercial supply chains have also been dealing with similar challenges. Some of the effective policies utilized in the private sector enterprises such as agility, adaptability, and alignment of the global supply chains (Van Wassenhove 2006) can help in meeting the challenges of the response operations in a disaster. In the pre-disaster phase, critical issues such as location of emergency facilities and allocating resources can frequently be dealt with using classic analytical models such as facility location, capacity constrained network optimization models proven to be useful in military and private sector. However, certain challenges associated with needs assessment and information management require innovative methodologies due to their unique nature and place in a humanitarian response supply chain. There exist many other challenges in a response supply chain. Varying demand in scope and scale, as well as mixed sourcing of supplies contributing to lack of visibility into the supply flows are some of the more formidable obstacles in effective and efficient distribution of critical supplies and services. Throughout the response phase, managing relations and developing trust to facilitate collaboration in the supply chain is a key to achieving smooth flow of relief to the affected population. Even if the infrastructure exists, a phenomenon commonly observed in case studies is that if the host community is not willing to collaborate, humanitarian operations cannot succeed. The collaboration may be within the local community or among the players in the supply chain, but it can be improved by building trust. Trust may be especially harder to achieve in a response supply chain of transient suppliers and volunteers. The existing infrastructure may consist of the actual roads and utility networks, or distribution and transportation processes of the supply chain. Infrastructure can also be in the form of education of the community and awareness within the community towards disaster leading to the swift formation of trust and collaboration. Post-disaster phase predominantly involves recovery operations. After the recovery, the state of the affected community may or may not reach or exceed the initial condition of the community before the disaster. One of the key points in the recovery phase is acquiring the knowledge, maintaining it, and learning from the lessons. The information gathered in the post-recovery phase enables being prepared and responsive for future disasters. In general, information and knowledge management facilitate all phases of the disaster. Research Opportunities Having discussed issues related to different types of disasters and different phases of the response supply chain, we now propose four specific research opportunities: prepositioning for humanitarian operations, needs assessment, information and knowledge management, and collaboration. Prepositioning for humanitarian operations. Until recently, emergency planners and researchers have primarily focused on tactical and operational aspects of humanitarian logistics. However, agility and adaptability, which are vitally important characteristics of the humanitarian response supply chain, cannot be supported without being prepared or pre-positioned for adequate capacity and resources. Being prepared in anticipation of a disaster entails prepositioning of assets and resources in addition to ensuring adequate capacity. In the absence of adequate capacity and resources, rapidly increasing capacity, such as expanding warehouses or creating infrastructures such as ramp-space at airports, becomes extremely difficult. In private sector as well as in military logistics, prepositioning is one of the most important strategies. Readiness translates to prepositioning and planning of resources and having sufficient capacity at the organizational level. Prepositioning of war reserves and contingency stocks has always been important in case of a conflict in the military. Positioning of spare parts and reserve equipment in post-sales support at conveniently located warehouses and distribution centers is a standard operation process in private sector and so is the placement of seasonal inventory. There are substantial commonalities and differences among all these supply chains—humanitarian response supply chains, military as well as commercial supply chains—that need to be studied and analyzed further. Researchers have available fairly rich set of issues to study in the context of humanitarian operations. For example, one of the complexities in humanitarian operations is facility location. This topic has been studied extensively for warehousing and to some extent for locating emergency services in the past. However, the uncertainty, scope, and classification of the disaster (Figure 1) add further complexities to the classic facility location problem. Another example could be incorporating different objectives of minimizing 'cost' (definition of cost is in itself an interesting challenge) or monetary budgets for a desired level of performance. Adding the context of public policy and ethics to the constraint of budget offers a realistic perspective in the humanitarian space (Tomasini & Van Wassenhove, 2009). This is especially relevant for prepositioning budget. Organizations are hesitant in allocating funds for prepositioning since the results are not immediate. On the other hand, investing in prepositioning can save large expenditures in response operations. Needs assessment. Even if prepositioning has been accomplished by considering all possible scenarios of the response, understanding the needs on the ground after the disaster constitutes one of the critical factors for the 'success' of humanitarian operations. The relief items in demand are normally from a short list and yet they can be diverse in kind and quality based on the type of disaster. In addition, different Non-Government Organizations (NGO) have different means of measuring the demand. World Food Program measures food in terms of size and scope of the affected population whereas International Federation of Red Cross believes that such assessment cannot be done, in the beginning phase, without the involvement of the donors. Which one has the right idea? Can both be integrated to assess the correct needs? What is the 'correct' need? How should it be defined? The military generates needs for deployment or a conflict to provide a better operational picture. Can the processes utilized in such situations better evaluate the requirements at remote locations? Private sector also estimates forecasted demands remotely and this has proven to be effective in converting a forecasted demand into a customer order for the supply chain. Humanitarian operations in a response supply chain will benefit significantly if research is carried out to answer such questions, perhaps by drawing on the practices of private sector as well as military organizations. Another important issue is to assess the capabilities of the entity which is going to fulfill the demand. Suppliers come in different shapes and sizes, local or global, pre-contracted or donors, private enterprises or military agencies. Among these, donors are the tricky bunch. The donors, most of the time, do not have access to the inventories of the humanitarian organizations. Moreover, they do not know what items may or may not be of use to the affected population (Apte 2009). There are many challenges to resolve concerning supplies and suppliers, from securing the supplies to establishing contingency contracting and from information on virtual distribution to the ever so challenging 'last mile' distribution. Information and knowledge management. Two prerequisites of understanding and assessing the needs are managing information to track demand and supply, and having the knowledge to understand the system. They both are critical through the entire life cycle of the disaster. During the lifecycle of a disaster the information also becomes available in phases, pre-disaster (a slow-onset disaster), during disaster, and post-disaster as in disaster phases (Figure 2). A well-managed information system should lead to clarity in demand, visibility in supply flows, transparency in inventory, efficiency in distribution and transportation, and accountability among the players in the response supply chain. Research in all these issues will improve humanitarian operations and will add to the quality of relief provided to the affected population. Lessons learned in disasters can be documented and discussed through case studies (Tomasini & Van Wassenhove, 2009). Moreover, the recent disasters in different geographic areas can facilitate the comparative analysis of diverse characteristics of the host countries in disaster response and relief sustainability. Capture and retention of such knowledge is critical especially since the high stress situation in this extreme supply chains bring high turnover among relief staff. Research in knowledge management will benefit the future planning of humanitarian operations. Collaboration. A disaster brings response from numerous diverse agencies from the military to governmental agencies to NGOs. To accomplish smooth humanitarian operations the responding communities need to acknowledge their interdependencies in the highly uncertain and constantly transforming environment of a disaster. Though collaboration is a generally accepted goal, achieving this objective has proved to be extremely difficult if not practically impossible. Interagency collaboration has numerous challenges and is another one of the fertile research areas for research from operational and decision-making perspective. The military often engages in the essential activity of providing security and assets during humanitarian operations. Although there has been some discussion on the topic of civil-military collaboration, there is much that needs to be researched in terms of their synergy. Organizational structures and governance are corollaries of collaboration which also need to be studied. Final ThoughtsThe research opportunities discussed above—prepositioning for humanitarian operations, needs assessment, information and knowledge management, and collaboration—have resulted from my discussions with emergency planners and first responders, military and humanitarian logisticians, and esteemed colleagues working in this area. In addition to these, there exist two broad issues that need to be pointed out: data for the research and usability of the research. There have been many articles written on the general situation of a humanitarian crisis. However, to really support humanitarian operations researchers must make an effort to learn from the actions and activities of those working in the field. Analytical models and systems form a critical methodology to support the operational issues in case of a disaster. However, contribution of such models to practice has been limited due to the lack of validation. Having said this, it is true that in certain topics of this field such as crisis management and catastrophe theory, models need to be developed whether the data is available or not. But analytical models and empirical research are of significant use only if they are based on realistic data. Therefore having 'clean,' 'accurate,' and 'relevant' data is critical. However, information gathering during the event or after the fact is difficult enough for the organizations involved. Hence, for researchers to have access to such data is even more difficult. Due to this limitation, researchers are sometimes forced to estimate parameters and related data. More often than not, such estimates are done by consulting with subject matter experts in the field which can be a good surrogate for field data. In this context, one of the immediate needs is for the researchers to create and populate accessible database containing all types of data (real and surrogate) as a disaster occurs. Creating a database like this is necessary and yet is a difficult task. One of the reasons is the lack of time and resources, and sometimes the will on the part of the players involved. Their participation is essential to obtain the information and collect the data. A caveat here is that a significant number of disasters take place in poor countries with little infrastructure and negligible resources where communication access is at best limited. Another significant concern arises from the fact that robust models that incorporate the reality of disasters tend to be large and hard to solve. Therefore solution approaches tend to be quite sophisticated. This is a double-edged sword. Sophisticated solution approaches require specialized software, which increase computational burden. Such computational complexity can move the focus from the real objective of supporting the humanitarian operations. "Computational analysis is a vital part of some other fields but humanitarian logistics will benefit more if the focus of the research is on developing models and solving them to 'near optimality' and not necessarily to optimality" (Apte 2009). In the interest of supporting humanitarian operations, academic research has a better likelihood of being applicable if it is based in robust models, grounded in real data, and the solution approaches can be implemented by those working in the field in readily available software. ReferencesA. Apte. (2009). Humanitarian logistics: A new field of research and action. Foundations and Trends© in Technology, Information and OM, 3(1), 1-100. R. M. Tomasini & L. N. Van Wassenhove. Humanitarian Logistics. New York: INSEAD Business Press, 2009. L. N. Van Wassenhove. (2006). Humanitarian aid logistics: Supply chain management in high gear. Journal of Operational Research Society, 57(5), 475-489. Vos F., Rodriguez, J., Below, R., Guha-Sapir, D. (2009). Annual Disaster Statistical Review 2009: The numbers and trends. Centre for Research on the Epidemiology of Disasters. Brussels, Belgium, 2010.
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