humanitarian network and partnership week- geneva - 2020€¦ · layers - option 1 humanitarian...

Humanitarian Network and Partnership Week- Geneva - 2020

ESUPS session HNPW 2020 - Agenda

9h00-9h30 Opening

Introduction to ESUPS

David

David

9h30 - 10h00 Data Collection Florent - Sue

10h00 - 10h30 Data Anaylsis Jason

10h30 - 11h00 BREAK BREAK

11h00 - 11h30 Advocacy Burcu

11h30 - 12h00 Communications Sofia

12h00 - 12h30 Wrap up Florent


What is ESUPS?


Data Collection

Data Analysis Advocacy

What youhave?

What youshould have?

Data Sharing/ Loan& Borrowing/

branding

ESUPS…. How/ Where?

Pilots Asia Haiti



9h00-9h30 Opening


David

David








Pillar 1 - Data Collection

On registration only access

2 types of users

Ownership by users once

organisation registered


Data Collection- STOCKHOLM Platform

ESUPS approves PALM as the Data

Collection Tool

PALM No longer available

Engagement with new countries put

on hold

Identification seed funding for new

platform development

STOCKHOLM Tender launched

STOCKHOLM Tender finalised

PHASE 1: Visuals

PHASE 2 : Back to PALM functionalities

PHASE 3 : New Functionalities

consultation and definition + roll out

Final Phase Hand-Over to neutral and independent body

Feb 2018

May 2019

June 2019

Aug 2019

Dec 2019

Jan 2020

Feb 2020

Apr 2020

May 2020 to Dec 2021

Dec 2021


STOCKHOLM Layers - Discussion

Global

Regions

National

Economiczone

Provinces

Districts

City

Community


Data Collection


Examples

Levels Philippines Nepal Indonesia Notes

Global No change, all agencies use the same term Agree these are the

generic terms, very

little to no change

across the agencies

and governments

Regional No change, all agencies use the same term

National No change, all agencies use the same term

Provincial Island group Provincial Provincial Some discussion required to agree with

recommendation made

Districts Regions Districts Cities regencies

Communities provinces Municipalities District Where stuff actually is Agreement to be made on terms and how deep do we go

Barangyas Village

Layers - Option 1


Option 1 - Map the structure to a set of agreed terms

Agreed Terms: 1 - Global, 2 - Regional, 3 - National– all similarSuggested: 4 – District, 5 – Sub District (provinces and communities would sit here)

Pros

• Simpler to set up

• See the goods at a relatively

low level with comparison

on location

• Easier identification of stock

and location

Cons

• May result in more work for

the CO to follow the

mapping

• Pressures governments to

use our systems

• Limited flexibility

Option 2


Pros Cons

Option 2 - Each organisation or country to define their own structure providing them with “level 1, level 2, level 3 etc… they (collectively at country level or under the direct responsibility of each government) would decide what level attribute works for them

• Relatively easy system that allows CO to decide on what levels regions, provinces fit into

• Simple to produce reports for oversight of stock

• If levels are too low and too many, could cause confusion

• Potentially difficult to program into the system unless a max level is set

• More difficult to see where stock is with a variety of locations under 1 descriptor

Option 3


Pros Cons

Use a system similar to the example of the government health structure, with 3 key levels (National, Regional and Local) and Local would cover sub locations

• Simple and easy to follow, with Countries having flexibility as to where lower locations are

• More difficult to see where stock is with a variety of locations under 1 descriptor

• The word “region” could then be confused with the level up over National

Option 3


Government Health Structure (Example)

Next Steps


• Short discussion Q & A on the options• Decide on an options which best suits the majority• Start the development of the structure agreed• Test


9h00-9h30 Opening


David

David









Disaster data

Warehouse data

Distances data

Items data

Em-Dat data(2013- 0576)

Affected districts per disaster(FLOODS)

Affected people per district per

disaster(4320 ppl)

Manual Typing

Census Data

Of 101 disasters, 34 have NULL

“Affected”

Warehouse Name(from stock data)

Biratnagar 56613, Nepal

Cleaning

List of Warehouses & provinces

BiratnagarBiratnagar (with space) Biratnagar Sub-metropolitan- 10, Tintolia, MorangBiratnagar, ward-12

Driving Distances

Via Google Maps

Reality adjustment

Field cross check

Stock report

BlanketBlankets

BLANKET

Cleaning

Other Issues

Pillar 2 - DATA ANALYSIS: collect &

clean


Disasters Summary

90% disasters < 250,000 affected > 10% disasters 102 disasters affecting more than 100 people since 1980

0

2

4

6

8

10

12

14

Ho

w m

any

dis

aste

rs

People Affected (Scale doubles at each bucket)

Sum of people affected by disaster type Count of disasters by type


Warehouse locations

20 Depot Locations from Stock ReportOnes in circles I combined to make easier to interpret


Warehouse locations

(Potential)

77 Provinces we assume are disaster distribution points


Model and Metrics.. How does it

work?

Data on needs (people affected)

Transportation times/costs

Disaster scenariosInventory data

Inputs The model

(A bunch of math)

Objectives:- Allocates inventory minimizing time or cost to respond- Optimizes average response time over all possible scenarios

Output

Assessment

Guidance


ANALYSIS – Current Stock - BLANKETS

Item

Number

Units

People

served

per item

People

Served

Fraction of

Disasters Served

with OnHand

inventory

People affected

by 90% of

disasters

Can current stocks

handle 90th

percentile disaster

Receommended

Stocks

Increase

stocks by

BlanketGen 111,637 2.2 244,100 0.92 225,000 Yes 102,899 0%

HygieneKit 43,619 1 43,600 0.69 225,000 No 225,000 416%

KitchenSetGen 3,864 5 19,300 0.61 225,000 No 45,000 1065%

PlasticSheet4x6 104,960 2.5 262,400 0.92 225,000 Yes 90,000 0%

ShelterKit 19,627 5 98,100 0.83 225,000 No 45,000 129%

SleepingMats 6,806 1 6,800 0.45 225,000 No 225,000 3206%

Tent 829 5 4,100 0.35 225,000 No 45,000 5328%

WaterCollectStorageVessel_Bkt62,574 2.5 156,400 0.84 225,000 No 90,000 44%


1.00 1.05 1.10 1.15

BlanketGen

HygieneKit

KitchenSetGen

PlasticSheet4x6

ShelterKit

SleepingMats

Tent

WaterCollectStorageVessel_Bkt

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Kathmandu 44600

Janakpur

Pokhara

Bharatpur 44200

Hetauda

Dhangadhi

Bhimdatta

Dasharathchanda

Value (in hours) of adding invenotry to warehouse

Best Place to add Blankets

Best place to move blankets

FROM


Blankets: Actual Vs Optimum

0 20,000 40,000 60,000 80,000 100,000 120,000

Actual Inventory

Optimal Inventory

Biratnagar 56613, Nepal Hetauda, Nepal Janakpur, Nepal Bharatpur 44200, Nepal Kathmandu 44600, Nepal

Siddharthanagar, Nepal Nepalgunj, Nepal Phidim 57400, Nepal Dipayal Silgadhi 10800, Nepal Bhimdatta, Nepal

Birgunj, Nepal Pokhara, Nepal Dhangadhi, Nepal Dasharathchanda, Nepal Besisahar 33600, Nepal

Biratnagar Hetauda Janakpur Bharatpur Kathmandu Siddharthanagar


OPTIMUM locations - BLANLKETS



Performance


Timeline


Stock data gathering

Logistics informationcollection

Cleaned data analysed

Presentation HNPW

Presentation Nepal partners

Integration in STOCKHOLM

platform

Dissemination of the Results

July 2019

October 2019

Dec 2019

Jan 2020

Feb 2020

March 2020

June 2020

Dec 2021

Start Em-Dat data cleaning


9h00-9h30 Opening


David

David








The impact of loan-borrowing and postponement on prepositioned relief stocks

Pillar 4 – Advocacy & Comm’s


Burcu BalçıkAssociate Professor, Özyeğin University (OzU), İstanbul, Turkey

Joint work with: Marie-Eve Rancourt (HEC Montréal)

Lamia G. Kasap (OzU)Florent Chane (ESUPS)

The Team

Burcu BalçıkAssociate ProfessorOzU

Marie-Ève RancourtAssociate Prof.HEC Montréal

Lamia G. KasapPhD StudentOzU


➢ Working with ESUPS since May 2019

➢ Related projects: Collaborative Prepositioning

▪ Researchers: Selene Silvestri, Jessica Rodríguez-Pereira, Hani Zbib, Gilbert Laporte

▪ Collaborators:

Florent ChaneESUPS

❖ Prepositioning

– A vital and widely-implemented disaster preparedness strategy

– Expensive (Sleeping money)

❖ Improve preparedness via collaborative practices

– Resource pooling

– Improve cost efficiency

– Improve/Maintain time efficiency

❖ Collaborative logistics

− Well-established in traditional supply chains

− Increased recent attention in humanitarian practice and research

− What? How? When?

− How to share savings, costs and risks?

Motivation

Collaborative prepositioning in the Caribbean


Can the efficiency of prepositioned stocks be improved by loan-borrowing (stock sharing) and postponement of branding?

Purpose of the Study


Qb1

Qu1

Amount of unbranded stock held by agency 1

Amount of branded stock held by agency 1

One Warehouse Multiple Warehouses (Regional and Country)

Demand points

Country warehouse

Regional warehouse

❖ In private sector, postponement (a.k.a. delayed product differentiation) has been widely implemented.

➢ For example, computer production (DELL)

Benefits of postponement for DELL:

▪ Reduced lead times: 4 weeks to 1 week

▪ Reduced finished goods inventory: 30-45 days to 4 days

Benefits of Postponement


Product differentiation at the manufacturing stage

Product differentiation after customer order

are received

1. Evaluate the impact of collaborative prepositioning via loan-borrowing and postponement of branding on response performance (cost and time)

▪ 100% Branded stocks

▪ 100% Unbranded stocks

▪ Partially branded stocks

2. Develop a decision support tool to optimize the use of resources (maximize response performance)

▪ Given a fixed target inventory level of each agency, what percent of prepositioned stocks must be kept in branded versus unbranded form?

Objectives


❖ Compare the required level of stock needed in one warehouse when 100% branded (no sharing) versus 100% unbranded (sharing)

Benefits of Postponement:

An Example


Data

• 10 years of dispatch data from IFRC Panama warehouse for five agencies

• Product: Hygiene kit

Savings from sharing stocks

• Reduction in inventory for the same response level

# of

agencies

❖ Advocacy

– Demonstrate the benefits of loan-borrowing and postponement of branding strategies to the humanitarian stakeholders

– Adapt the best collaborative strategies from the private sector to facilitate implementation in the humanitarian sector

❖ Implementation

– Develop tools that will support agencies to evaluate the benefits of collaborative strategies and implement them in different settings

• Optimize resource utilization by pooling resources

• Maximize the impact of future responses (reach more people in need)

❖ Partnerships

– Contribute to the reinforcement of partnerships (SDG 17) among humanitarian agencies and also practitioners and academics

Potential Impact


Steps of the Study


Step 1.

• Understand the system

• Specify the objectives

• Define the scope

Step 2.

• Data Gathering & Analysis• Agency data• Historical disasters

• Realistic setting

Step 3.

• Modeling

• Simulation

• Optimization

• Analysis

Effective and efficient collaborative prepositioning via loan-borrowing and postponement of branding

Data Gathering & Analysis


❖ Agency data▪ Warehouses

• Locations & Capacities

• Operating regions

• Agencies in the same warehouse

▪ Relief items • Target inventory levels

• Historical requests

• Amounts, Locations

• Historical dispatches

• Amounts, Origin/Destination

▪ Costs, lead times

➢ Challenges▪ Limited data

▪ Different document/table formats

▪ Different terminology

▪ Different item specifications

❖ Historical disaster data▪ Generate a disaster database

• Region: Caribbean, Central America, South America

• Disaster types: Earthquakes, storms, floods, landslides, volcanic activity

▪ Generate disaster scenarios for the focus region

Modeling


Input❑ Disaster scenarios

▪ location, timing, impact▪ Demand

❑ Supply network ▪ Regional and country

warehouses▪ Agencies▪ Relief items

• Target inventory levels• Proportion of branded

items

❑ Lead times▪ Transportation, supplier

and branding

Simulation

OutputPerformance measures

❑ Response time

❑ Proportion of demand satisfied

❑ Inventory costs

Timeline


Kick-off

Step 1: System Description

Step 2: Data Gathering

Step 3: Simulation model

Step 3: Analysis & Results (Simulation)

Step 3: Optimization Model

Step 3: Analysis & Results

(Optimization)


June 2019

September 2019

March 2020

May 2020

August 2020

December 2020

April 2021

Dec 2021

Step 2: Data Gathering & Analysis

Thank you!

Questions/Comments?

Feedback



9h00-9h30 Opening


David

David








Communications


Objective: Inform about ESUPS and improve project visibility

WHATis ESUPS

- Mandate

WHO

- The Steering group

- Partners

- HLA- Log Cluster- HELP Logistics- IAPG- World Vision- German Preparedness Group

HOWcan ESUPS help?

- Engage various audiences

- Advocate research findings

- Tools: open, accessible and easy

to navigate

HOW?


Website

Social Media

Promotional material and Guidelines

Objective: Inform about ESUPS and improve project visibility

https://esups.org

https://www.facebook.com/ESUPS/

https://www.linkedin.com/company/esups

https://esups.org/


- Build online presence- Optimise website- Implement Communications plan

- Monitor results- Revise

Communications strategy

Mar 2020

Jun 2020

Mar - June 2020

- Collect Communications material from partners

- Finalise guidelines and SOPs- Identify fora and events to

present project and findings

2019

- Develop promotional material- Update website- Set up Communications plan

Timeline


9h00-9h30 Opening


David

David








Next Steps - summary

PHASE 1: Visuals

PHASE 3 : New Functionalities

consultation and definition

+ roll out

Feb 2020May 2020

to Dec 2021

Dec 2021


- Presentation Nepal partners

- Step 2: Data Gathering & Analysis

- Build online presenceOptimise website

Implement Communications plan

Integration in STOCKHOLM platform

Monitor resultsRevise Communications

strategy

Mar 2020 Jun 2020

Step 3: Simulation

model

Step 3: Analysis &

Results (Simulation)

Step 3: Optimization

Model

Step 3: Analysis &

Results (Optimization)


Final Phase Hand-Over to neutral and independent

body

May 2020

Aug 2020

Dec 2020

Apr2021

STOCKHOLM DATA ANALYSIS ADVOCACY COMMUNICATIONS

Apr 2020

PHASE 2 : Back to PALM functionalities

- Collect Communications material- Guidelines and SOPs-Identify fora and events to present project and findings

Questions/Comments?

Feedback


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