Data-drivien optimization of OFDA's disaster response capacity: Phase II - Workshop III

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Data-driven optimization of OFDA’s

disaster response capacity

Phase II – Workshop III

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Agenda

• Recap

• Target beneficiaries and OFDA’s mandate

• Inventory optimization

• Recommendations

• Discussion

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Beneficiaries served vs target TAP

18 Sample size 1 16 8 31 21

Cap based on current ops

Recap

➢ We created a function to scale TAP to a target TAP using past service rates.

➢ Considering current inventory levels, the resulting disaster portfolio is featuring relatively high

targeted TAP, resulting in rather low service rates, and consolidated inventory allocations.

➢ Using the current inventory distribution in the network, we scaled the target TAP down with a “flat” cap on all disasters.

➢ To have a diversified network as in OFDA’s current operational footprint and at current inventory levels, the results of our modelling suggests that OFDA seeks to meet a disaster portfolio with lower target TAP!

Served with current inventory Max cap

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Disaster portfolio scenarios

18 Sample size 1 16 8 31 21

Cap based on current ops

Suggested analysis

➢ To develop inventory allocation recommendations, we create product-specific disaster-portfolio

scenarios.

➢ Comparing the resulting inventory allocation

recommendations and service metrics will provide OFDA with options to consider.

➢ In the following we focus our analysis on hygiene kits to showcase how it works.

Served with current inventory Max cap

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A three-step process

• Optimize the current inventory level

• Determine performance against different mandates • Decide if inventory levels

have to be adjusted • Collect past disaster

information.

• Create OFDA’s risk portfolio with target beneficiaries • Create scenarios, i.e. vary

OFDA’s mandate

• Define objective

• Adjust inventory levels • Identify optimal allocation • Recommend actions

OFDA’s mandate Inventory optimization Recommendations

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Step 1: OFDA’s mandate

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Disaster portfolio and OFDA’s mandate

• Disaster responses in the past

• TAP and location • Adjust TAP according to OFDA’s disaster response activities • Use past activities to estimate

mandate

Disasters OFDA’s responses in the past Risk portfolios: hygiene kits

Medium-Large Large

Small-Medium Current Small

• Creating different item-specific scenarios = OFDA’s future mandate • Characterize different exposure to

disaster sizes 30,000 3,200 60,000 9,400 130,000 29,700 Small Small _-Med . Lar ge Mean Std. Dev. 100,000 23,900 Med . -Lar ge 80,000 Current _14,800

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Step 2: Inventory optimization

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Metrics – current mandate

Balance metric

Inventory allocation

80 - 100%

0 - 2

Results

• Reallocating inventory benefits OFDA • Response time reduction: 3% • Cost reduction: 5%

• 69% of beneficiaries served

• 93% of all disaster scenarios served

➢ Current inventory levels result in mixed service levels.

➢ Current inventory allocation is close to optimum. 97% 69% 93% 1.1 - 3% - 5% 16.0h $13,800 Medium-Large Large Small-Medium Current Small

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Metrics – large mandate

Balance metric

80 - 100%

0 - 2

Results

➢ Current inventory levels result in lower service and strong consolidation.

89% 54% 79% 1.73 - 11% - 17% 16.5h $14,500 Medium-Large Large Small-Medium Current Small

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Metrics – small mandate

Balance metric

80 - 100%

0 - 2

Results

- 2% - 3% 14.5h 98% 94% 99% 0.33 $11,800

➢ Current inventory is sufficient to run a diversified response network effectively.

Medium-Large Large

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Metrics – comparing mandates

Balance metric Inventory allocation 80 - 100% 0 - 2 Medium-Large Results

• At current inventory levels, with increasing mandates the inventory allocation should be consolidated more.

• Service levels drop.

• Cost and lead time increase.

➢ Which mandate is capturing OFDA’s future activities appropriately?

Large Small-Medium Current

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Inventory allocation

Today Small Small-Med Current Med-High High

Inv. Allocation Metric 1.1 0.3 1.0 1.1 1.4 1.7 Dubai, UAE 15,000 8,831 12,400 17,000 21,000 25,000 Miami, USA 10,000 7,000 12,400 8,000 4,000 0 Pisa, Italy 0 6,000 200 0 0 0 Subang, Malaysia 0 3,168 0 0 0 0

• A larger mandate means that OFDA expects to serve more beneficiaries in each disaster and the variation of beneficiaries increases. • At current inventory levels OFDA should

consider to consolidate the inventory if they expect a larger mandate.

Results

Medium-Large Large

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Step 3: Recommendations

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Inventory decision to fit OFDA’s mandate

Medium-Large

Problem

• OFDA seeks to serve the medium-large mandate. • The rather low service (% TAP served) is of

concern.

• Strong inventory consolidation resulting in higher response times and higher cost, are not

acceptable.

➢ Increasing total number of hygiene kits inventory can address these concerns.

➢ How much inventory should OFDA hold, and where should they locate it?

Large Small-Medium Current

Small

1. Set a target, e.g. min. 85% service level 2. Evaluate inventory scenarios

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Inventory and its allocation to increase service

85%

56k

Current inventory level

+ 100%

64%

37%

26% 37%

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Results of increased inventory

Balance metric*

80 - 100%

0 - 2

Medium-Large @ Current Inv.

OFDA’s optimized network

• Approximately doubling hygiene kits

inventory allows OFDA to increase service level to 85%.

• Because OFDA can choose a diversified

network, response times drop by up to 15%. • Cost can be reduced by up to 12%.

Medium-Large @ Higher Inv. Current 85% 85% 15h $12,600 _97% 0.61

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Summary

• By exploring different disaster risk scenarios, OFDA can

explore various mandates.

• Various scenarios allow OFDA to discuss future

mandates, and what service levels they would achieve

with current inventory.

• Evaluating varying inventory levels, then enables OFDA

to choose appropriate service levels, cost, and response

times.

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