{"id":10448,"date":"2016-11-04T00:49:25","date_gmt":"2016-11-04T04:49:25","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/is-flood-relief-pouring-into-all-the-wrong-places\/"},"modified":"2016-11-04T01:05:18","modified_gmt":"2016-11-04T05:05:18","slug":"is-flood-relief-pouring-into-all-the-wrong-places","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-flood-relief-pouring-into-all-the-wrong-places\/","title":{"rendered":"Is flood relief pouring into all the wrong places?"},"content":{"rendered":"

The International Federation of Red Cross and Red Crescent Societies (IFRC) is in the business of disasters. Needless to say, they have been very busy lately. Thanks to climate change, our new reality is that natural disasters are becoming less the exception and more the norm [1]. With such a scary prognosis, one might assume that a company in the disaster business is ripe for expansion – natural disasters have cost the world $1.3 trillion in damages and 1.1 million lives in the past 12 years [2].<\/p>\n

In reality, however, climate change has thrown a wrench into the operational model of IFRC.\u00a0 The culprit is not the increasing frequency of disasters per se (though frequency has strained capacity to some extent). Rather, it is the unpredictability <\/em>of such disasters. Put differently, if all that climate change affected was the average temperature, forecasting would remain predictable, and resources would arrive to the correct places at the correct times. But climate change also increases the range<\/em>, or variance, of temperatures experienced. \u00a0Variance is the catalyst of unpredictability, which can make it nearly impossible for humanitarian organizations stay on the front-end of disaster (Exhibit 1<\/strong>) [3].\"picture1\"<\/a>Exhibit 1<\/u>: Climate change increases both average temperature and temperature variance. Temperature variance leads to less predictability in climate forecasting, which in turn makes it difficult for humanitarian organizations to \u201cbeat the storm<\/em>.\u201d (SOURCE: NASA Earth Observatory)<\/p>\n

 <\/p>\n

The IFRC Approach to Disaster Management \u2013 Potential Pitfalls<\/em><\/strong><\/p>\n

Aid relief at IFRC operates under a series of relatively linear processes. As shown in Exhibit<\/strong> 2<\/strong>, the first step in disaster management is to identify areas with the most need. Of all the steps, this first one is the most vulnerable to unpredictable weather patterns \u2013 without the ability to predict where a storm or earthquake will hit, risk reduction efforts can be misdirected, leading to even higher demand downstream [4,5].<\/p>\n

\"pic-3\"<\/a><\/p>\n

Exhibit 2:<\/u> Disaster relief process map. Poor execution of Risk Reduction Step 1 can lead to worsening damage downstream. This in leads to higher costs for IFRC, as recovery is more expensive than risk reduction.<\/em><\/p>\n

 <\/p>\n

What are they doing now? <\/em><\/strong><\/p>\n

The IFRC is aware that to operate as efficiently as possible, they need to optimize Risk Reduction Step 1 – resources need to be at the right place at the right time, before disaster strikes. Consequently, in the past six years, they have \u201cmore than tripled their preparedness\u201d efforts \u2013 doubling down on their presence in existing communities, and in new, untapped areas, are \u201cstrategically pre-positioning relief items for rapid deployment\u201d [5].
\nHowever, quick deployment is useless without good measurement. \u00a0In climate science, such forecasting is by no means a new concept. However, in recent years, IFRC has partnered with the International Research Institute for Climate and Society (IRI) at Columbia University to develop a more accurate, cutting-edge tool used for long-term global forecasting (Exhibit 3<\/strong>).\u00a0 Soon after launch, the tool was put to the test in West Africa, successfully detecting a large, potentially detrimental storm before it struck. This in turn led to more effective \u2018pre-disaster\u2019 risk reduction, which generated cost savings of $18 per beneficiary [6].<\/p>\n

\"pic-4\"<\/a><\/p>\n

Exhibit 3<\/u><\/em>: New partnerships with academia have created better, more customizable forecasting for IFRC. <\/em>(SOURCE: IFRC Climate Centre)<\/p>\n

 <\/p>\n

What should they do next?<\/em><\/strong><\/p>\n

While good measurement is a step in the right direction, IFRC should adopt three additional measures to ensure that its process map (Exhibit 2<\/strong>) aligns with the growing unpredictability of our climate.<\/p>\n

1) Establish global partnerships with climate scientists to aid in forecast interpretation and information dissemination<\/em>: Decision-making chains are not always fully prepared to process the information that is being forecasted. In other words, even if a storm is detected<\/em> on time, it is difficult to translate information from Columbia to aid supplies in West Africa. Decentralizing the forecasting process to other nations and other scientists can alleviate that delay.<\/p>\n

2) Begin \u201cpre-disaster preparation\u201d even earlier than originally anticipated<\/em>. This will prevent a dangerous \u201cbacklog\u201d in the event that a disaster arrives sooner than planned.<\/p>\n

3) Adopt more aggressive internal fundraising<\/em>. 80% of IFRC\u2019s operating income comes from voluntary contributions, which usually spike in the days-weeks following a disaster [8]. Unfortunately, these spikes in revenue are not in line with the time in which IFRC needs to increase its resource utilization, namely, in the weeks-months before a disaster.<\/p>\n

In conclusion, our increasingly unpredictable climate has created an increasingly unpredictable supply chain for IFRC. Can further dissemination of forecasting technology beat storms to the punch, or are humanitarians\u00a0simply fighting an uphill battle?<\/p>\n

 <\/p>\n

(784 words)<\/p>\n

\n

Sources <\/u><\/strong><\/p>\n

[1] IPCC, \u201cClimate Change 2007: Synthesis Report, https:\/\/www.ipcc.ch\/publications_and_data\/ar4\/syr\/en\/spms1.html<\/p>\n

[2] UNISDR \u201cGlobal Assessment Report 2015,\u201d https:\/\/www.unisdr.org\/we\/inform\/gar<\/p>\n

[3] NASA Earth Observatory, \u201cThe Impact of Climate Change on Natural Disasters,\u201d http:\/\/earthobservatory.nasa.gov\/Features\/RisingCost\/rising_cost5.php. Accessed November 2016.<\/p>\n

[4] IFRC, \u201cPreparedness for Climate Change,\u201d http:\/\/www.ifrc.org\/Global\/preparedness_climate_change.pdf. Accessed November 2016<\/p>\n

[5] Jennifer Leaning, M.D., Debarati Guha-Sapid, Ph.D, \u201cNatural Disasters, Armed Conflict, and Public Health,\u201d New England Journal of Medicine<\/em>, no 19 (2013):369, via PubMed, accessed Nov 2 2016<\/p>\n

[6] Lisette Martine Braman, \u201cClimate forecasts in disaster management: Red Cross flood operations in West Africa, 2008,\u201d Disasters, no 1 (2013):37, via PubMed, accessed Nov 2 2016<\/p>\n

[7] IFRC Climate Centre, \u201cIFRC\/IRI Map Room,\u201d http:\/\/www.climatecentre.org\/climate-info-and-forecasts\/ifrc-iri-map-room. Accessed November 2016.<\/p>\n

[8] IFRC Independent Auditors\u2019 Report on Consolidated Financial Statements, 2015, http:\/\/www.ifrc.org\/Global\/Publications\/Finance\/IFRC-Consolidated-financial-statements_2015.pdf. Accessed November 2016<\/p>\n

 <\/p>\n

 <\/p>\n

 <\/p>\n

 <\/p>\n

 <\/p>\n

 <\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

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