The State of Food Security Analysis: A FEWS NET Perspective

Transcription

1 The State of Food Security Analysis: A FEWS NET Perspective Bruce Isaacson FEWS NET MORE THAN JUST DATA Charting the Road to Zero Hunger 08 March 2017 The Hague, Netherlands

2 Outline Introduction to FEWS NET Analytical Approach Fit for Purpose?? FAMINE EARLY WARNING SYSTEMS NETWORK 1

3 Introduction to FEWS NET FAMINE EARLY WARNING SYSTEMS NETWORK 2

4 To prevent famine and mitigate risks of food insecurity by providing decision makers with information that is accurate, credible, timely, and actionable. To strengthen the ability of FEWS NET countries and regional organizations to provide timely early warning and vulnerability analysis. The purpose of FEWS NET FAMINE EARLY WARNING SYSTEMS NETWORK 3

5 FEWS NET Fact Sheet A USAID-funded project, started in 1985 Field activities implemented by private sector contractor Independent, not a voice for the US Government Tracks food security conditions in 70 countries Reports monthly on 35 countries, many special reports Flexible country coverage 200 fulltime staff plus 100 field monitors in 25 countries Annual budget of approximately $25m FAMINE EARLY WARNING SYSTEMS NETWORK 4

6 2016 Presence.. 25 } 35 Reports RM3 Report RM2 Watch.. 10 RM1 Prep Countries FEWS NET Country Coverage 2015 Presence. 20 Remote Monitoring FAMINE EARLY WARNING SYSTEMS NETWORK 5

7 Our network Implementing Team USG Science Partners Private Sector Partners National governments Regional technical organizations (CILSS, SADC, COMESA, IGAD) WFP, FAO, UNICEF, UNHCR, other international agencies Non-governmental organizations Price/Market Information Systems Meteorological, statistical offices IPC working groups FAMINE EARLY WARNING SYSTEMS NETWORK 6

8 FEWS NET Analytical Approach FAMINE EARLY WARNING SYSTEMS NETWORK 7

9 A Brief History of FEWS NET Analysis ? FEWS FEWS 2 FEWS 3 FEWS NET FEWS NET 2 FEWS NET 3 FEWS NET 7 Initial focus on needs assessment Heavy reliance on satellite imagery What is good food security analysis? The theory of famine (Amartya Sen) FS dimensions, focus on production Food Security vulnerability framework FAMINE EARLY WARNING SYSTEMS NETWORK 8

10 A Brief History of FEWS NET Analysis ? FEWS FEWS 2 FEWS 3 FEWS NET FEWS NET 2 FEWS NET 3 FEWS NET 7 Started work on accessibility dimension Market/price monitoring Developed and introduced a five point vulnerability scale: same colors as IPC FAMINE EARLY WARNING SYSTEMS NETWORK 9

11 A Brief History of FEWS NET Analysis ? FEWS FEWS 2 FEWS 3 FEWS NET FEWS NET 2 FEWS NET 3 FEWS NET 7 Not much technical advancement Geographic expansion Data managers FAMINE EARLY WARNING SYSTEMS NETWORK 10

12 A Brief History of FEWS NET Analysis ? FEWS FEWS 2 FEWS 3 FEWS NET FEWS NET 2 FEWS NET 3 FEWS NET 7 Move from USAID AFR to FFP Greater focus on the network Expansion out of Africa (AF, LAC) Convergence of indicators Introduced LH-based framework FAMINE EARLY WARNING SYSTEMS NETWORK 11

13 A Brief History of FEWS NET Analysis ? FEWS FEWS 2 FEWS 3 FEWS NET FEWS NET 2 FEWS NET 3 FEWS NET 7 From classifying vulnerability to classifying food insecurity Adopted and joined IPC Emphasis on early warning Scenario development (SADC) FAMINE EARLY WARNING SYSTEMS NETWORK 12

14 A Brief History of FEWS NET Analysis ? FEWS FEWS 2 FEWS 3 FEWS NET FEWS NET 2 FEWS NET 3 FEWS NET 7 Introduced remote monitoring Network development Focus on assumption building for better scenario development Primary data collection FEWS NET Data Warehouse (FDW) FAMINE EARLY WARNING SYSTEMS NETWORK 13

15 A Brief History of FEWS NET Analysis ? FEWS FEWS 2 FEWS 3 FEWS NET FEWS NET 2 FEWS NET 3 FEWS NET 7 Multiple contract awards Global, geographically flexible Focus remains on early warning Food security dynamics Data as a product Innovation FAMINE EARLY WARNING SYSTEMS NETWORK 14

16 FEWS NET Analytical Approach Livelihoods-based early warning analysis Knowledge Base Effective decision support Livelihoodsbased analysis Efficient Monitoring Comparable classification Scenario Development FAMINE EARLY WARNING SYSTEMS NETWORK 15

17 FEWS NET Analytical Approach Knowledge Base 1. Build and use knowledge bases to understand the context Effective decision support Livelihoodsbased analysis Efficient Monitoring Comparable classification Scenario Development FAMINE EARLY WARNING SYSTEMS NETWORK 16

18 FEWS NET Analytical Approach 2. Monitor key risk factors Knowledge Base Field Assessments Market/Price monitoring Effective decision support Livelihoodsbased analysis Efficient Monitoring Rainfall Forecasts Nutrition Surveys/ Surveillance Comparable classification Scenario Development Conflict Remote sensing FAMINE EARLY WARNING SYSTEMS NETWORK 17

19 FEWS NET Analytical Approach 3. Use scenarios to estimate projected food security Knowledge Base STEP 1: Set scenario parameters Effective decision support Livelihoodsbased analysis Efficient Monitoring STEP 2: Describe and classify current food security STEP 3: Develop key assumptions STEP 4: Describe impacts on HH income sources STEP 5: Describe impacts on HH food sources Comparable classification Scenario Development STEP 6: Describe and classify projected HH food security STEP 7: Describe and classify projected area food security STEP 8: Identify events that could change the scenario FAMINE EARLY WARNING SYSTEMS NETWORK 18

20 FEWS NET Analytical Approach Knowledge Base 4. Use a common language for describing food insecurity Effective decision support Livelihoodsbased analysis Efficient Monitoring West Africa Food Security Outcomes, May 2015 Comparable classification Scenario Development Source: FEWS NET FAMINE EARLY WARNING SYSTEMS NETWORK 19

21 FEWS NET Analytical Approach Knowledge Base 5. Communicate analysis to decision-makers Effective decision support Livelihoodsbased analysis Efficient Monitoring Comparable classification Scenario Development FAMINE EARLY WARNING SYSTEMS NETWORK 20

22 FEWS NET Products Agro- Climatology Markets and Trade Livelihoods Nutrition Integrated Analysis Global Weather Hazards Seasonal Monitor Monthly Seasonal Forecast Review Knowledge Base Products: rainfall estimation; drought metrics; vegetation and crop conditions; surface water monitoring Analysis tools Market Fundamentals Report Price Watch Price Bulletin Regional Supply and Market Outlook Cross border trade monitoring systems Market monitoring bulletin Production and trade flow mapping Livelihood Zone Map Livelihood Zone description Livelihood Baseline Household Economy Approach (HEA) Outcome analysis SMART Surveys Nutrition Causal Analysis Nutrition Context Document Food Security Outlook Food Security Outlook Update Food Security Alert Special Report Food Assistance Outlook Brief FAMINE EARLY WARNING SYSTEMS NETWORK 21

23 Fit for Purpose? FAMINE EARLY WARNING SYSTEMS NETWORK 22

24 Fit for Purpose?? FEWS NET s forward looking analysis currently meets the needs of our client. But does it meet the needs or add value for other users? How does expert judgment fit in? Greater emphasis on consensus? Is there a better way to build consensus amongst partners? FAMINE EARLY WARNING SYSTEMS NETWORK 23

25 FAMINE EARLY WARNING SYSTEMS NETWORK 24

26 There is almost certainly some value in the idea that different members of a group can learn from one another s expertise. But this introduces the possibility of groupthink and herding. Some members of a group may be more influential because of their charisma or status and not necessarily because they have the better idea. Empirical studies of consensus-driven predictions have found mixed results, in contrast to a process wherein individual members of a group submit independent forecasts and those are averaged or aggregated together, which can almost always be counted on to improve predictive accuracy. FAMINE EARLY WARNING SYSTEMS NETWORK 25

27 A better approach to consensus building? 1. Everyone s data is shared in real time and available to everyone. (e.g., FEWS NET s CHIRPS data) 2. Different partners run independent analyses. Common language and analytical concepts, standards and protocols should be followed but no constraints on methods 3. The consensus process is centered around presentations and discussions of these different analyses rather than getting a group of people together and starting from scratch. FAMINE EARLY WARNING SYSTEMS NETWORK 26

28 FAMINE EARLY WARNING SYSTEMS NETWORK 27

29 Questions? Bruce Isaacson Chief of Party FEWS NET FAMINE EARLY WARNING SYSTEMS NETWORK 28