Emergency Preparedness: Return on Investment Model

Transcription

1 UNICEF/UN055427/Modolo Emergency Preparedness: Return on Investment Model Result trend analysis Prepared by PricewaterhouseCoopers January 2017

2 EXECUTIVE SUMMARY... 4 INTRODUCTION... 5 TIME SAVINGS AND FINANCIAL SAVINGS ACROSS PHASE 1 AND 2 INVESTMENTS... 7 TIME SAVINGS... 8 FINANCIAL SAVINGS... 8 GHG SAVINGS APDS AND APDSPD SIR AND TIME HORIZONS CAPACITY STRENGTHENING INVESTMENTS CONCLUSIONS AND RECOMMENDATIONS ANNEX 1 LIST OF INVESTMENTS ANALYSED ANNEX 2 SUMMARY DATA The RoI Methodology Result trends, March 2017 PwC 2

3 Acknowledgements This document was authored by Pasquale Mari and Lorenzo Newman, with contributions from Fiona Christine Arnone and Giorgio Garbasso. The authors would like to thank all members of the inter-agency Return on Investment Working Group (ROI WG) that was established as part of the DFID funded Ready to Respond project. These were John Long from OCHA, Anna Dmitrijewa and Barb Wigley from UNHCR, Mari Denby from UNICEF, Danilo Delfini, Marlies Lensink, and Karine Strebelle from WFP. We would also like to thank Mel Schmidt as inter-agency coordinator for the ROI WG and Charlotte Jourdain, technical expert working with the inter-agency Climate Change Working Group under the same project. The authors also wish to recognise the work of all the representatives of UN agencies who participated in field interviews and data collection in, Myanmar, and in order to describe the investments on which this document is based. Disclaimer The views set out in this report represent those of the authors acting on behalf of PwC. They do not necessarily reflect the official views of OCHA, UNHCR, UNICEF, WFP, or any other UN entity PricewaterhouseCoopers Advisory SpA. All rights reserved. In this document, PwC refers to PricewaterhouseCoopers Advisory SpA, which is a member firm of PricewaterhouseCoopers International Limited, each member firm of which is a separate legal entity. The RoI Methodology Result trends, March 2017 PwC 3

4 Executive Summary The ROI Methodology is a toolkit for providing evidence of returns on investment in emergency preparedness (EP) with respect to four types of indicators: contribution to the quality of the response, financial savings, response time reduction, and carbon footprint reduction. It was developed during the course of Phase II of the DFID funded Ready-to-Respond project, involving four UN Agencies: UNICEF, WFP, UNHCR, UNOCHA. UNICEF and WFP had also participated in Phase I of the project, supported by the Boston Consulting Group (BCG). As part of this project, we examined 49 preparedness initiatives in Myanmar,, and. The findings in this document reflect all quantifiable results collected with PwC over the course of research, excluding two of UNHCR s four quantifiable investments due to concerns regarding the reliability of these individual investments results. PwC added 35 investments to this sample, those that had been examined during Phase I of the project for two already existing indicators (SIR 1 formerly ROI, and Time Saving). The Phase I projects were from Chad, Madagascar and Pakistan. Although the initiatives were chosen to help develop the methodology, not to demonstrate performance, they can provide information on the level and type of return that may be expected from the different types of investment. An aggregate analysis of these investments shows that: An Emergency Preparedness (EP) investment can decrease response times by 14 days; For every $1 invested in EP: o o o o 15 affected person-days of improved humanitarian outcomes; $0.50 is saved following the first emergency to occur; $1.50 is saved over the entire lifecycle of the investment; 0.24 kg of CO2 emissions are saved. Emergency preparedness investments have been categorised according to six types, each with specific mechanisms and types of return. The following table summarises, in terms of the median value of the key indicators, the return of each type of investment 2 : Type of investment Time savings (days) Net savings after the first emergency to occur For every $ 1 invested Net savings over investment lifecycle KGs of CO2 equivalents emissions saved Affected person-days receiving better assistance Data systems 18 $0.9 $ Infrastructure/ 3 $0.5 $ process pre-positioning LTA/PCAs 16 $1.2 $ Skills 9 $6.6 $ Supply pre-positioning 14 $0.2 $ All 14 $0.5 $ SIR= (Cost without -Cost with )/Investment means that SIR-1= (Cost without -Cost with - Investment)/Investment=Net Cash Flow/Investment. Note that with SIR = 150% as median value, for each dollar invested, half dollar is saved. 2 Coordination type investments have no quantitative indicator The RoI Methodology Result trends, March 2017 PwC 4

5 Introduction Building an evidence base around emergency preparedness As humanitarian actors increase their emergency preparedness activities, they must be able to estimate these investments contribution to improved humanitarian outcomes. The ROI (Return on Investment) Methodology developed in 2016 by Pricewaterhouse Coopers (PwC) provides a tool for doing this on a case-by-case basis, by describing improved humanitarian outcomes as ROI return on investment. Indicators show the differential benefit of investing (the with scenario) in comparison to not investing (the without scenario). Specifically, the ROI Methodology provides tools for assessing ROI in terms of financial savings, savings in response time, GHG (greenhouse gas) savings, and newly developed humanitarian indicators such as APDS (Affected Person-Days Saved) and APDSPD (APDS per Dollar). The key indicator of financial return is the SIR (Saving to Investment Ratio). This equals the difference between the cost, in the event of an emergency, of the without scenario compared to the cost of the with scenario 3. The key humanitarian return is the APDSD, calculated by dividing the APDS by the Investment value. APDS is obtained by calculating the number of days that an affected person is better assisted thanks to the investment 4. By aggregating ROI results, it is possible to build an evidence base that, in turn, can be used to inform future investments in emergency preparedness. By doing so, this document contributes to the growing literature on the expected humanitarian return of preparedness activities. How these results were calculated These results were computed by aggregating a wide variety of ROI indicators for those investments that were examined, and that produced quantitative results. 49 investments, located in, Myanmar, and, were examined by PwC. Indicators, such as GHG savings and APDS, were introduced through PwC s analysis 5. For the SIR (Savings to Investment Ratio) and Time Savings indicators, the sample of investments also includes 35 investments, located in Chad, Pakistan, and Madagascar, examined during Phase I of this project by the Boston Consulting Group (BCG) in Investment types include LTA/PCAs; Skills; Data systems; Infrastructure/Process pre-positioning 6 ; and Supply, equipment, and capacity pre-positioning. Coordination investments were also analysed but they rarely yielded quantifiable indicators. 3 For example: Let us assume that to pre-position goods entails a $ 95,000 investment (procurement and transport costs) and $ 5,000 in warehousing costs at the distribution point until the first emergency happens. Let us also assume that, in the event of an emergency, without prior investment, $ 150,000 must be spent to get the same quantity of goods at the same distribution point. The Saving equals $ 150,000 (because in the with scenario the goods are already available); the SIR = 1.50 = $ 150,000/($ 95,000+$ 5,000), if no discount rate is applied. In the analysis, a 10% yearly discount rate is applied; if the emergency happens in year 1, then both warehousing cost and Saving must be discounted by dividing them by 1.1. Therefore, the actualised SIR = For example: Let us assume that the pre-positioned goods are relief items (e.g. blankets) for 20,000 people and that, if the investment is not made, 10 days will be required to get the same quantity of items. This means that, in the event of a sudden onset emergency, thanks to the investment, 20,000 people are better protected for 10 days, i.e. 200,000 affected person-days = 20,000 people x 10 days of receiving better assistance. 5 BCG operated in Phase 1, and PwC in Phase 2, of an ROI Project funded by DFID. Phase 1 involved UNICEF and WFP; Phase 2 involved OCHA, UNHCR, UNICEF, and WFP. 6 The ROI Methodology explains how Infrastructure (fixed assets improving the speed, quality, and reliability of, and reducing the costs of, humanitarian response) and Process (More efficient and effective operational processes, systems and standards) investments should be treated differently in modelling. Here they are aggregated for analysis purposes. The RoI Methodology Result trends, March 2017 PwC 5

6 The full list of investments is provided in Annex 1. In most cases, this document features median and dispersion values, indicated by the first and third quartiles as represented by the variation bars. Results are broken down by investment type in order to gauge whether there are significant differences between investment opportunities. All statistical values per indicator and per investment type are provided in Annex 2. How to interpret results As sample sizes are small, results should be interpreted with caution. Also, the investments are not a representative sample of the agencies emergency preparedness activities, as they were selected for methodological development, not for empirical purposes. Nonetheless, the insights that follow are informative on the level and type of return that can be expected from the different types of investment. Further application of the methodology will increase the evidence base and help expand it to include additional investment categories. Please note that, in some cases, outliers have been removed from the samples in order to better represent dispersions graphically. The RoI Methodology Result trends, March 2017 PwC 6

7 Time savings and financial savings across Phase 1 and 2 investments Adding Phase 1 investments to our sample confirms BCG s findings: Skills and LTA/PCA investments offer high potential for financial and time ROI; Supply and infrastructure pre-positioning investments are safe choices. The chart below demonstrates this by plotting the distribution of each investment type s 1 st and 3 rd quartile SIR and time savings ROI scores. The RoI Methodology Result trends, March 2017 PwC 7

8 Note that in this case PwC and BCG s investments were all assessed for SIR accrued after the first emergency to occur over the time horizon. Thus, SIRs for PwC s investments are somewhat lower than when analysed on their own. Sensitivity to time horizons is discussed in section 7. Time savings As shown in the chart below, 28 out of the 49 Phase II investments analysed yielded significant time savings. Results varied within and across investment types. LTA/PCA and skills investments saved the most time. Financial savings For those 43 investments with a clear investment cost, the combined total investment value equals $30,881,864. The average investment cost is $718,182. The chart below shows the total investment cost by investment type. The RoI Methodology Result trends, March 2017 PwC 8

9 Investment costs per investment vary significantly within and across investment types. 33 of these investments generated a combined $64,957,411 in total savings. This total is broken down by investment type in the chart below. As can be seen from the category breakdown below, Skills investments generate the highest median SIR, although results varied significantly. The RoI Methodology Result trends, March 2017 PwC 9

10 GHG savings 32 investments yielded GHG savings totalling 43,666 MTCO2e 7. Four Infrastructure investments accounted for most of savings. The char below shows median GHG savings for each investment type. Median savings for infrastructure/process investments are over 14 times higher than the next most emissions reducing category supply pre-positioning. 7 Metric Tonnes of CO2 equivalents emissions saved The RoI Methodology Result trends, March 2017 PwC 10

11 APDS APDSPD APDS and APDSPD The Affected Person Days Saved indicator (APDS) is a new way of quantifying humanitarian results. It attempts to quantify ROI uniformly as the cumulative number of days during which people affected by an emergency are better assisted thanks to the investment. The formula varies according to the emergency risk profile and the risk time profile. As shown by the following charts, APDS and APDSPD (APDS per dollar invested) were calculated for 18 investments, generating a total of 81,580,558 affected person-days saved, over half of which came from supply pre-positioning investments. Median APDS and APDSPD values where highest for Data system investments. LTA investments generated the second-highest APDSPD but lower APDS values than infrastructure/process prepositioning investments. Median APDS and APDSPD (by investment type, n=18) Median APDS Median APDSPD The RoI Methodology Result trends, March 2017 PwC 11

12 These results should be interpreted with caution. They do not account for the ways in which different emergencies and the intensity of time savings affect individual people. When looking at individual investments, the APDS indicator should be supplemented by an explanation of how affected people benefit from faster emergency response. These results are also highly contingent on assumptions made about the affected people in each emergency scenario. SIR and time horizons As shown in the chart below, longer investment time horizons are correlated with increased financial returns, with the notable exception of supply pre-positioning investments. Capacity Strengthening investments 28 of the investments analysed involved elements of capacity strengthening. These investments included simulations, training, and contingency planning, and often involve a variety of institutional actors (Government, NGOs, UN agencies). The investments analysed share one or more of the following features, all indicators of high returns: A high level of diversity amongst the institutions represented; A high level of influence amongst the individuals involved; The activities conducted relate directly to emergency preparedness and response (e.g. solving management issues occurring during past emergencies); The investments produce outputs that can be used in future emergencies or in preparedness activities (e.g. contact lists, early warning systems). The RoI Methodology Result trends, March 2017 PwC 12

13 Conclusions and recommendations The following conclusions can be drawn from this sample of investments: Pre-positioning of emergency relief items and infrastructure procured internationally demonstrates consistently strong financial, time, and carbon savings; Pre-positioning of locally procured items has roughly neutral financial and carbon impact but saves time towards emergency response; Investments related to human capacity (skills, training) show very high proportional returns, partly because they re relatively inexpensive and their use is repeated without further investment; Infrastructure investments generally require longer payoff time horizons due to high upfront costs, but can generate the greatest financial savings in absolute terms, as well as generating significant carbon savings; Newer types of emergency preparedness investments related to information management and data systems show very significant returns in terms of cost and time savings, particularly if they serve the wider humanitarian community, as they also result in important improvements in the quality of response through the rapid availability of more reliable data; Emergency preparedness investments that have a joint character, rather than targeting just one agency, do pay off: they show good returns in terms of quality of response and financial and time savings. In addition, numerous contextual factors may impact an investment s ROI, as detailed below. For Coordination investments: The pre-investment level of maturity of the emergency management capacity and/or of the coordination processes and/or of shared approaches; The likelihood of the actual implementation of the actions decided in the context of the investment or of behaviours of the participants/partners. For Data systems investments: The uncertainty implicit in the decision to be taken using the collected information; The importance of the consequences of not taking the right decision. For Skills investments: The turnover of the staff; The demand for the skills in the geographic area where the trained staff members are expected to be deployed; the demand must be evaluated in terms of frequency and duration of the deployments. For Process and infrastructure investments: The duration of the emergency, which should be sufficiently lengthy as to justify the implementation of the solution; The demand for the solution after the emergency, at least for a period equal to or higher than the payback period; The RoI Methodology Result trends, March 2017 PwC 13

14 Shared interest in using infrastructure; the timing of when numerous actors use infrastructure is very important. For LTA/PCA investments: The quality of the services that can be assured at a local level by partners/providers; The prices that can be negotiated in the market context of the country. For Supply pre-positioning investments: The cost of transport to the country and country customs rules; In-country transport times and reliability; Security issues in the expected deployment area; Synergies with regular programmes. Lessons learned from applying the methodology during the project include: Scenario-building is essential for defining both the risks and the with and without scenarios when the methodology is being used to build a business case. The user must accept that ROI results refers to the future; The user is advised to use the risk scenarios developed through existing country processes, such as contingency planning with the government and risk analysis and planning work by the Humanitarian Country Team (HCT). The ROI relies on planning processes and best estimations; Risk scenarios should be specific to the geographic area where the investment could potentially be deployed; Data must fully cover all the investment components in the with and without scenarios. However, recognising that data collection may be impossible in some cases, reasonable assumptions are often sufficient. The ROI Methodology Excel Workbook parameters can be changed to simulate different assumptions. The RoI Methodology Result trends, March 2017 PwC 14

15 Annex 1 List of investments analysed Category Investment Country Coordination Increasing/Strengthening Coordination with Local Authority (Chin) Myanmar Coordination Diffusion of standards on emergency and temporary Shelters Myanmar Coordination Multi-sectoral Initial Rapid Assessment (MIRA) Process improvement Myanmar Coordination Simulation exercises at National and State (Rakhine) level Myanmar Coordination Protection workshops and consultations for non-protection sectors Myanmar Coordination Establishment of a Rapid Response Mechanism (RRM) Coordination SET (Situational Emergency Training) workshop with government, agencies and partners Coordination Contingency planning with government, agencies and partners Coordination Government Capacity strengthening: early warning systems and contingency planning Data systems 72H food assessment process set up Myanmar Data systems CBI assessment Myanmar Data systems Introduction of Mobile VAM system Data systems Establishment of an Information Management (IM) system Data systems Gov. Capacity Building: Sites Sentinels and SIMA Data systems Introducing a biometrics registration system Data systems Data systems Infrastructure/proce ss pre-positioning Infrastructure/proce ss pre-positioning Infrastructure/proce ss pre-positioning Infrastructure/proce ss pre-positioning Infrastructure/proce ss pre-positioning Infrastructure/proce ss pre-positioning Infrastructure/proce ss pre-positioning Infrastructure/proce ss pre-positioning Coordination of an Information Management (IM) Working Group EUMS (End-User Monitoring System) to monitor local supply chain Shallow well drilling instead of water trucking Increase in logistics capacity to enable strategic prepositioning Increased security through establishment of ICT services and guesthouse Deep well drilling instead of water trucking Cooking energy in Diffa Strengthening institutional capacity (urbanization) Hybrid pumps (for WASH) in place of fuel pumps APC (Advanced Positioning Center) LTA/PCAs Local Framework Agreements to procure and inspect CRI Myanmar LTA/PCAs Emergency contingency agreements Myanmar The RoI Methodology Result trends, March 2017 PwC 15

16 Category Investment Country LTA/PCAs LTAs for fleet LTA/PCAs Emergency contingency agreements Skills Emergency staff rosters Myanmar Skills Emergency preparedness & response training Myanmar Skills Overall preparedness for CBT Skills Emergency preparedness & response training Skills WEM Deployment of emergency personnel (global) ICT equipment sets pre-positioning Emergency stock pre-positioning (National) Emergency stock pre-positioning (International) MSU pre-positioning HEB pre-positioning Development of minimum intervention packages for WASH sector (National) Development of minimum intervention packages for WASH sector (International) Procurement & pre-positioning of emergency stocks (National) Procurement & pre-positioning of emergency stocks (International) ICT network pre-positioning MSU pre-positioning Prefab and hybrid generators pre-positioning Regional emergency preparedness warehousing and prepositioning for CRI Supply pre-positioning (National) Supply pre-positioning (International) Myanmar Myanmar Myanmar Myanmar Myanmar The RoI Methodology Result trends, March 2017 PwC 16

17 Annex 2 Summary Data Investment type SIR (Phase 1+2) 1st Emergency SIR (Phase 2) 1st Emergency SIR 2 years SIR 5 years Investment Time horizon (years) N.of emergencies in time horizon Total actualized Investment (USD) SIR (in specific time horizon) Net Cash Flow (USD) (no outliers) Net Cash Flow/Without Cash Flow Time saving (Phase 1+2) (days) Time saving (Phase 2) (days) CHG saving (MTCO2e) CHG saving (MTCO2e)/Total actualized investment (USD) APDS APDSPD (person-days per USD) (no outliers) Number of cases Data systems Infrastructure/ process pre-positioning LTA/PCAs Skills Supply pre-positioning Median 148% 124% 170% 221% $250, $265,847 32% ,317, Data systems 189% 189% 429% 449% $267, $441,865 32% ,372, Infrastructure/ 146% 35% 151% 349% $371, $885,649 51% 3-1, ,840,747 7 process pre-positioning LTA/PCAs 215% 282% 1331% 2672% $6, $135,386 39% ,860, Skills 758% 1229% 2258% 3295% $56, $1,387,970 96% Supply pre-positioning 118% 115% 122% 126% $657, $88,464 17% ,013, Average 262% 311% 522% 900% $913, $1,031,238 40% , ,532, Data systems 158% 158% 392% 647% $1,744, $2,018,149 39% ,372, Infrastructure/ 251% 95% 203% 445% $1,825, $834,736 49% 8-6, ,840,747 7 process pre-positioning LTA/PCAs 301% 377% 1934% 4091% $6, $683,425 44% ,786, Skills 714% 1397% 2258% 3295% $166, $2,479,922 76% Supply pre-positioning 139% 134% 155% 160% $799, $551,927 26% ,000, Min 2% 2% 35% 80% $5, $(34,543) -15% ,050 1 Data systems 20% 20% 54% 80% $27, $(29,794) -15% ,372, Infrastructure/ 14% 14% 35% 88% $13, $28,946 10% ,840,747 - process pre-positioning LTA/PCAs 109% 109% 513% 957% $5, $34,553 15% ,476, Skills 134% 428% 2202% 2741% $8, $178,824 14% Supply pre-positioning 2% 2% 91% 91% $23, $(34,543) -10% ,050 1 Max 1595% 2702% 3958% 8644% $10,870, $7,106,669 99% , ,372, Data systems 354% 354% 748% 1634% $10,870, $7,106,669 82% ,372, Infrastructure/ 768% 318% 499% 1355% $9,875, $1,710,669 79% 26-20, ,840, process pre-positioning LTA/PCAs 663% 740% 3958% 8644% $8, $2,428,377 81% ,024, Skills 1595% 2702% 2313% 3848% $544, $5,872,974 99% Supply pre-positioning 288% 288% 306% 306% $2,402, $2,809,935 67% , ,146, st Quartile 96% 72% 104% 116% $27, $37,623 15% ,706 5 Data systems 23% 23% 77% 117% $126, $(7,746) 8% Na Na Infrastructure/ process pre-positioning 18% 16% 47% 105% $155, $39,112 22% - Na Na Na The RoI Methodology Insights, March 2017 PwC 17

18 Investment type SIR (Phase 1+2) 1st Emergency SIR (Phase 2) 1st Emergency SIR 2 years SIR 5 years Investment Time horizon (years) N.of emergencies in time horizon Total actualized Investment (USD) SIR (in specific time horizon) Net Cash Flow (USD) (no outliers) Net Cash Flow/Without Cash Flow Time saving (Phase 1+2) (days) Time saving (Phase 2) (days) CHG saving (MTCO2e) CHG saving (MTCO2e)/Total actualized investment (USD) APDS APDSPD (person-days per USD) (no outliers) LTA/PCAs 119% 109% 513% 957% $5, $42,493 18% ,476,250 Na Skills 159% 537% Na Na $17,686 Na $178,824 34% Supply pre-positioning 95% 91% 104% 105% $191, $28,852 4% , rd Quartile 267% 400% 557% 939% $523, $975,504 82% ,932, Data systems 278% 278% 689% 1278% $463, $4,832,185 74% Na Na Infrastructure/ 507% 196% 372% 650% $2,500, $1,518,917 77% 21 Na 16, Na Na process pre-positioning LTA/PCAs 568% 740% 3958% 8644% $8, $1,872,397 73% ,024,250 Na Skills 1104% 2425% Na Na $424,504 Na $5,872,974 98% Supply pre-positioning 185% 196% 207% 218% $1,129, $847,540 52% ,648, The RoI Methodology Insights, March 2017 PwC 18