Evaluating Alternative Supply Chain
Models for the Provision of
Tarpaulins Supplies
to Africa
Dr David Taylor
Senior Research Fellow
Logistics and Operations Management Section
Cardiff University Business School
UK
Reltex/ Cardiff University
Value Chain Analysis Project
To use a value chain analysis techniques to
compare
Conventional methods of supplying NFI aid
items from sources external to Africa
With
The local production model of manufacture in
Africa combined with pre-positioned
stockholding
Value Chain Analysis

VCA - the method of applying ‘Lean Principles’ to
supply chain improvement

‘Lean’ originated at Toyota

Now applied in many sectors beyond automotive

First application in humanitarian aid
Major stock locations outside Africa
Stock locations in Africa
Spaghetti Map
Value Chains Analysed
Value Chain Analysis
Assumed Area of Beneficiary Need
Uganda
Value Chain One
China Manufacture - NGO Warehouse Nairobi – Surface Transport
Qingdau
Mombasa
Singapore
Value Chain Two
China Manufacture – Regional Warehouse Dubai - Surface Transport
Dubai
Mombasa
Qingdau
Singapore
Value Chain Three
India Manufacture – Trading Company Nairobi - Surface Transport
Mumbai
Mombasa
ValueChain
ChainFour
Four
Value
China Manufacture – European Warehouse – Sea
Transport
Copenhagen
Qingdau
Entebbe
Singapore
Value Chain Five : Advance Aid Model
Manufacture Nairobi – PP Stock Entebbe
Nairobi
Entebbe
Value Chain
Current State Maps
Value Chain One :
China Manufacture – NGO Warehouse Nairobi -- Surface Transport
Whole
Chain KPI’s
Qingdao
China
Tarpaulin Factory
Production
15-20k Units
Capacity /day
Beneficiaries
Region North of
Kampala
50000 tarps
12
days
27
days
2
days
Supply Chain
Structure
( & Risk Factors)
70 kms
Supply Chain
Structure &
Operations
Singapore
Qingdao
4947 kms
6400 kms
Port Transit
2-3
Nairobi
Mombassa
days
NGO
Warehouse
481 kms
Transport legs
5
.
4-14
5-14
Inventory
range
3-9 k tarps
Border
crossings
3
.
days
days
daily
Container
6000 tarps
days
Aver Transport
time
3
days
Variability
5-14
day
Variability
2-8
days
Frequency
?
day
Frequency
daily
.
6000 tarps
Container
5500 tarps
Container
8 day
( 10 - 12 )
( 4-14)
( 24- 30)
( 5-14)
$0.66
$0.33
Cost per container $4000
Tarps per container 6000
Cost per tarp
$0.66
( 2 – 4)
( 5 - 14 )
(3 - 8)
Cost / container $2000
Tarps / container 6000
Cost / tarp
$0.33
$1.30
Unit value
$13.00
Holding cost pa 10%
Hold cost / tarp $1.30
(Tonnes of Co2
per container with 6000 tarps)
0.2
1.82
2.54
0.29
days
days
days
Min Time
57
day
Max Time
126
day
$0.73
Cost / container $4000
Tarps / container 5500
Cost / tarp
$0.73
Tarp Costs
Manufacture
cost
Transport
costs
Warehousing
cost
Cost
Per tarp
Carbon Footprint
6
71
Whole
77
Chain
3 days
8 days
$1
2
$12
Lead Time
From Nairobi
stock
To replinish
Nairobi stock
3 days
26 days
$1
2
Cost
.
8
.3
0
( 2-3 )
Frequency
days
Aver Transport
time
$1
3
( 2 - 27 )
24 -30 days
4 day
11 days
days
2-4
$1
4
.
2 day
0.25 day
(Min -Max)
6000 tarps
Variability
26
.6
6
12 days
Aver Transport
time
.0
0
Lead
Times
Average
Container
.
3500 tarps
10 - 12 days
daily
.
3
Inventory
days
Frequency
12
No of Ports
Port Transit
.0
0
Variability
11
541 kms
12439 kms
No of links in
chain
Port Transit
W/h response
Aver Transport
time
Distance
Uganda
Rub hall
.0
2
Aver Factory
Leadtime
Max factory
leadtime
Min Factory
Leadtime
$1
5
Inventory
1.53
12.00
$
1.73
$
1.30
$
15.02 $
Carbon Footprint
Carbon 6.38
tnns
Supply Chain Structure
& Operations
Tarpaulin Factory
Qingdao China
Production
15-20k Units
Capacity /day
Inventory
Aver Factory
Leadtime
Max factory
leadtime
Min Factory
Leadtime
The links in the chain
50000 tarps
12
days
27
days
2
days
70 kms
Qingdao
Port
Port Transit
2-3
Mombassa
Port
Singapore
Port
4947 kms
6400 kms
days
Aver Transport
time
Variability
11
days
10 - 12 days
Port Transit
Port Transit
4-14
5-14
days
Aver Transport
time
Variability
26
days
24 -30 days
Frequency
daily
.
Frequency
daily
.
Container
6000
tarps
Container
6000
tarps
Key Performance Indicators (KPI’s)
for each link in the chain
days
Value Chain One :
Supply of Tarpaulins from China to Africa using Surface Transport
Whole
Chain KPI’s
Qingdao
China
Tarpaulin Factory
Production
15-20k Units
Capacity /day
Inventory
Aver Factory
Leadtime
Max factory
leadtime
Min Factory
Leadtime
Beneficiaries
Region North of
Kampala
50000 tarps
12
days
27
days
2
days
Supply Chain
Structure
( & Risk Factors)
70 kms
Supply
Chain
Structure
Singapore
Qingdao
4947 kms
6400 kms
Port Transit
2-3
Nairobi
Mombassa
days
481 kms
Variability
11
Container
6000 tarps
Lead
Times
12 days
Transport legs
5
.
4-14
5-14
Inventory
range
3-9 k tarps
Border
crossings
3
.
days
Aver Transport
time
Variability
.
2 day
0.25 day
Min -( 2Max
- 27 )
(Min -Max)
26
days
days
24 -30 days
Frequency
daily
Container
6000 tarps
4 day
11 days
( 2-3 )
.
2-4
days
Aver Transport
time
8
days
Aver Transport
time
3
days
Variability
5-14
day
Variability
2-8
days
Frequency
?
day
Frequency
daily
.
6000 tarps
Container
5500 tarps
Container
8 day
Lead Time
From Nairobi
stock
To replinish
Nairobi stock
( 4-14)
( 24- 30)
( 5-14)
$12
$0.66
3
$1
$0.33
Cost per container $4000
Tarps per container 6000
Cost per tarp
$0.66
( 2 – 4)
( 5 - 14 )
Cost / container $2000
Tarps / container 6000
Cost / tarp
$0.33
(3 - 8)
0
.0
$
$1.30
Unit value
$13.00
Holding cost pa 10%
Hold cost / tarp $1.30
0
5.
$1
0
.3
14
$0.73
Cost / container $4000
Tarps / container 5500
Cost / tarp
$0.73
(Tonnes of Co2
per container with 6000 tarps)
0.2
1.82
2.54
0.29
1.53
days
days
2
days
Min Time
57
day
Max Time
126
day
Tarp Costs
Manufacture
cost
Transport
costs
Warehousing
cost
Cost
Per tarp
Carbon Footprint
6
71
Whole
77
Chain
3 days
8 days
66
2.
$1
00
2.
$1
Cost
3 days
26 days
( 10 - 12 )
.
3500 tarps
Average
Average
.
3
Inventory
10 - 12 days
daily
12
No of Ports
Port Transit
days
Frequency
541 kms
12439 kms
No of links in
chain
Port Transit
W/h response
Aver Transport
time
Distance
Uganda
Rub hall
NGO
Warehouse
12.00
$
1.73
$
1.30
$
15.02 $
Carbon Footprint
Carbon 6.38
tnns
Value Chain One :
Supply of Tarpaulins from China to Africa using Surface Transport
Whole
Chain KPI’s
Qingdao
China
Tarpaulin Factory
Production
15-20k Units
Capacity /day
Beneficiaries
Region North of
Kampala
50000 tarps
12
days
27
days
2
days
Supply Chain
Structure
( & Risk Factors)
70 kms
Supply
Chain
Structure
Singapore
Qingdao
4947 kms
6400 kms
Port Transit
2-3
Nairobi
Mombassa
days
481 kms
Transport legs
5
.
4-14
5-14
Inventory
range
3-9 k tarps
Border
crossings
3
.
days
days
( 2-3 )
daily
Container
6000 tarps
days
Aver Transport
time
3
days
5-14
day
Variability
2-8
days
Frequency
?
day
Frequency
daily
.
6000 tarps
Container
5500 tarps
Container
( 4-14)
( 24- 30)
( 5-14)
$0.33
Cost per container $4000
Tarps per container 6000
Cost per tarp
$0.66
( 2 – 4)
( 5 - 14 )
(3 - 8)
Cost / container $2000
Tarps / container 6000
Cost / tarp
$0.33
$1.30
Unit value
$13.00
Holding cost pa 10%
Hold cost / tarp $1.30
(Tonnes of Co2
per container with 6000 tarps)
0.2
1.82
2.54
0.29
days
days
days
Min Time
57
day
Max Time
126
day
$0.73
Cost / container $4000
Tarps / container 5500
Cost / tarp
$0.73
Tarp Costs
Manufacture
cost
Transport
costs
Warehousing
cost
Cost
Per tarp
Carbon Footprint
6
71
Whole
77
Chain
3 days
8 days
$1
2
$0.66
Lead Time
From Nairobi
stock
To replinish
Nairobi stock
3 days
26 days
( 10 - 12 )
$12
Per tarp
8
Variability
8 day
$1
2
Cost
.
Aver Transport
time
$1
3
( 2 - 27 )
Frequency
4 day
11 days
days
days
.3
0
6000 tarps
26
24 -30 days
2-4
$1
4
.
2 day
0.25 day
(Min -Max)
Container
Variability
.6
6
12 days
Aver Transport
time
days
daily
.
3500 tarps
10 - 12 days
Frequency
.
3
Inventory
.0
0
Lead
Times
Average
11
12
No of Ports
Port Transit
.0
0
Variability
541 kms
12439 kms
No of links in
chain
Port Transit
W/h response
Aver Transport
time
Distance
Uganda
Rub hall
NGO
Warehouse
.0
2
Aver Factory
Leadtime
Max factory
leadtime
Min Factory
Leadtime
$1
5
Inventory
1.53
12.00
$
1.73
$
1.30
$
15.02 $
Carbon Footprint
Carbon 6.38
tnns
Value Chain One :
Supply of Tarpaulins from China to Africa using Surface Transport
Whole
Chain KPI’s
Qingdao
China
Tarpaulin Factory
Production
15-20k Units
Capacity /day
Inventory
Beneficiaries
Region North of
Kampala
50000 tarps
Aver Factory
Leadtime
Max factory
leadtime
Min Factory
Leadtime
12
days
27
days
2
days
Supply Chain
Structure
( & Risk Factors)
70 kms
Supply
Chain
Structure
Singapore
Qingdao
4947 kms
6400 kms
Port Transit
2-3
Nairobi
Mombassa
days
481 kms
Variability
Lead
Times
Average
12 days
daily
Container
6000 tarps
( 2 - 27 )
Transport legs
5
.
4-14
5-14
Inventory
range
3-9 k tarps
Border
crossings
3
.
days
Aver Transport
time
Variability
.
26
days
Frequency
daily
Container
6000 tarps
.
( 24- 30)
days
Aver Transport
time
3
days
Variability
5-14
day
Variability
2-8
days
Frequency
?
day
Frequency
daily
.
6000 tarps
Container
5500 tarps
Container
$0.66
( 5-14)
( 2 – 4)
( 5 - 14 )
3
$1
Cost / container $2000
Tarps / container 6000
Cost / tarp
$0.33
(3 - 8)
0
.0
$
$1.30
Unit value
$13.00
Holding cost pa 10%
Hold cost / tarp $1.30
0
5.
$1
0
.3
14
$0.73
Cost / container $4000
Tarps / container 5500
Cost / tarp
$0.73
(Tonnes of Co2
per container with 6000 tarps)
0.2
1.82
2.54
Per container ( 6000 tarps)
0.29
1.53
days
days
2
days
Min Time
57
day
Max Time
126
day
Tarp Costs
Manufacture
cost
Transport
costs
Warehousing
cost
Cost
Per tarp
Carbon Footprint
6
71
Whole
77
Chain
3 days
8 days
$0.33
Cost per container $4000
Tarps per container 6000
Cost per tarp
$0.66
Lead Time
From Nairobi
stock
To replinish
Nairobi stock
3 days
66
2.
$1
$12
days
8
26 days
( 4-14)
2-4
Aver Transport
time
8 day
00
2.
$1
Cost
days
24 -30 days
4 day
( 10 - 12 )
.
3500 tarps
11 days
( 2-3 )
.
3
Inventory
10 - 12 days
Frequency
12
No of Ports
Port Transit
days
2 day
0.25 day
(Min -Max)
11
541 kms
12439 kms
No of links in
chain
Port Transit
W/h response
Aver Transport
time
Distance
Uganda
Rub hall
NGO
Warehouse
12.00
$
1.73
$
1.30
$
15.02 $
Carbon Footprint
Carbon 6.38
tnns
Value Chain One :
Supply of Tarpaulins from China to Africa using Surface Transport
Qingdao
China
Tarpaulin Factory
Production
15-20k Units
Capacity /day
Beneficiaries
Region North of
Kampala
50000 tarps
12
days
27
days
2
days
Supply Chain
Structure
( & Risk Factors)
70 kms
Supply
Chain
Structure
Singapore
Qingdao
4947 kms
6400 kms
Port Transit
2-3
Nairobi
Mombassa
days
481 kms
Transport legs
5
.
4-14
5-14
Inventory
range
3-9 k tarps
Border
crossings
3
.
days
days
( 2-3 )
daily
Container
6000 tarps
8
days
Aver Transport
time
3
days
Variability
5-14
day
Variability
2-8
days
Frequency
?
day
Frequency
daily
.
6000 tarps
Container
5500 tarps
Container
8 day
( 10 - 12 )
( 4-14)
( 24- 30)
( 5-14)
$0.66
$0.33
Cost per container $4000
Tarps per container 6000
Cost per tarp
$0.66
( 2 – 4)
( 5 - 14 )
(3 - 8)
Cost / container $2000
Tarps / container 6000
Cost / tarp
$0.33
$1.30
Unit value
$13.00
Holding cost pa 10%
Hold cost / tarp $1.30
(Tonnes of Co2
per container with 6000 tarps)
0.2
1.82
2.54
0.29
days
days
days
Min Time
57
day
Max Time
126
day
$0.73
Cost / container $4000
Tarps / container 5500
Cost / tarp
$0.73
Tarp Costs
Manufacture
cost
Transport
costs
Warehousing
cost
Cost
Per tarp
Carbon Footprint
6
71
Whole
77
Chain
3 days
8 days
$1
2
$12
Lead Time
From Nairobi
stock
To replinish
Nairobi stock
3 days
26 days
$1
2
Cost
.
Aver Transport
time
$1
3
( 2 - 27 )
Frequency
4 day
11 days
days
days
.3
0
6000 tarps
26
24 -30 days
2-4
$1
4
.
2 day
0.25 day
(Min -Max)
Container
Variability
.6
6
12 days
Aver Transport
time
days
daily
.
3500 tarps
10 - 12 days
Frequency
.
3
Inventory
.0
0
Lead
Times
Average
11
12
No of Ports
Port Transit
.0
0
Variability
541 kms
12439 kms
No of links in
chain
Port Transit
W/h response
Aver Transport
time
Distance
Uganda
Rub hall
NGO
Warehouse
.0
2
Aver Factory
Leadtime
Max factory
leadtime
Min Factory
Leadtime
$1
5
Inventory
Whole
Chain
KPI’s
1.53
12.00
$
1.73
$
1.30
$
15.02 $
Carbon Footprint
Carbon 6.38
tnns
Whole Chain Key Performance Indicators
Supply Chain
Structure
( & Risk Factors)
Lead Time
From Nairobi
stock
To replinish
Nairobi stock
Whole
Chain
6
days
Distance
12439
kms
59
days
No of links in
chain
12
.
No of Ports
3
.
Transport legs
5
.
Border
crossings
3
.
65
days
Tarp Costs
Manufacture
cost
Transport
costs
Intermediary
Costs
Cost
Per tarp
8.80
$
1.28
$
6.02
$
Carbon Footprint
Carbon
16.10
$
5.5
tnns
Comparative Analysis
Value Chains Selected for Analysis
VC 1
From China
via NGO
Nairobi
warehouse
VC 2
From China
via warehouse
in Dubai
VC 3
From India via
Nairobi trading
company
VC 4
From China
via European
warehouse
VC 5
Mombasa
Port
Manufacture
China
Aid Agency
Warehouse
Nairobi
Uganda
Distribution point
Mombasa
Port
Manufacture
China
Dubai
Warehouse
Mombasa
Port
Manufacture
India
Manufacture
China
Africa manufacture
& pre-positioned stock
Aid Agency
European
Warehouse
Uganda
Distribution point
Nairobi
Trading Co &
Warehouse
Uganda
Distribution point
Kampala
Uganda
Distribution point
Airport
Nairobi
Manufacture
Entebbe
Ware/h
Uganda
Distribution
point
Lead Time
From order placement to delivered Uganda
VC1: From China via
Nairobi
71
VC2: From China via
Dubai
6
48
29
VC3: From India via
Nairobi
59
VC4: From China via
Europe
59
VC5: From Nairobi via
Entebbe
6
0
6
4
2
10
20
30
40
50
60
70
80
days
Stock replenishment LT
LT from stock
90
Supply Chain Vulnerability
Risk of Disruption
Distance: Entire Supply Chains
VC1: China via Nairobi
12439
VC2: China via Dubai
16697
VC3: India via Nairobi
7642
VC4: China via Europe
30066
VC5: African manufacture
641
0
5000
10000
15000
20000
kms
25000
30000
35000
Supply Chain Vulnerability
Factors with Potential for Disruption
VC1: China via Nairobi
VC2: China via Dubai
VC3: India via Nairobi
VC4: China via Europe
VC5: Afric an manufac ture
0
2
4
6
8
10
12
14
16
18
N u mb e r
Transport legs
Ports
Border crossings
Total supply-chain cost
Cost per Tarp - delivered Uganda ($ US)
VC1: China via Nairobi
12
VC2: China via Dubai
12
VC3: India via Nairobi
8.8
1.72 1.3
$ 15 .0 2
2.52 1.35
1.28
6.02
$ 15 .8 7
$ 16 .10
$ 3 8 .0 3
VC4: China via Europe
12
24.83
11
VC5: Afric an manufac ture
0
5
0.351.65
10
1.2
$ 13 .18
15
20
25
30
35
$ (U S )
Manufacture
Transport
Warehousing
40
Environmental Impact
Carbon Footprint
Entire Supply Chains - delivered Uganda
6.4
VC1: China via Nairobi
9.1
VC2: China via Dubai
5.5
VC3: India via Nairobi
104
VC4: China via Europe
1.8
VC5: Afric an manufac ture
0
20
40
60
80
T on n es Co2 p er sh ip men t of 6000 tarp s
100
Summary & Conclusions
Summary
Total Lead Time :
From order placement to delivered Uganda
VC1: From China via
Nairobi
Cost per Tarp - delivered Uganda ($ US)
71
VC2: From China via
Dubai
6
48
VC3: From India via
Nairobi
59
VC4: From China via
Europe
59
VC1: China via Nairobi
12
29
VC2: China via Dubai
12
6
VC3: India via Nairobi
1.72 1.3
$ 15 .0 2
2.52 1.35
8.8
1.28
6.02
$ 15 .8 7
$ 16 .10
$ 3 8 .0 3
VC5: From Nairobi via
Entebbe
6
0
VC4: China via Europe
4
12
11
VC5: Afric an manufac ture
2
10
20
30
40
50
60
70
80
0
90
24.83
0.351.65
5
10
1.2
$ 13 .18
15
20
25
30
35
40
$ (U S )
d a ys
Stock replenishment LT
Manufacture
LT from stock
Transport
Warehousing
Carbon Footprint
Supply Chain Vulnerability
Entire Supply Chains - delivered Uganda
Factors with Potential for Disruption
VC1: China via Nairobi
6.4
VC1: China via Nairobi
VC2: China via Dubai
9.1
VC2: China via Dubai
VC3: India via Nairobi
5.5
VC3: India via Nairobi
VC4: China via Europe
104
VC4: China via Europe
VC5: Afric an manufac ture
0
2
4
6
8
10
12
14
16
18
1.8
VC5: Afric an manufac ture
N u mb e r
0
Transport legs
Ports
Border crossings
20
40
60
80
T on n es Co2 p er sh ip m en t of 6000 tarp s
100
The Reltex Aid Model
v
Conventional Supply Chains
Advantages




Avoids long, costly & unreliable supply chains
Reduces Carbon Impact
Quicker & more responsive
Creates local employment in Africa - sustainability
The Potential Benefits of Lean and VCA in
Humanitarian Aid

Comparison of strategic alternatives

Analysis, measurement and improvement of
existing supply chains
Evaluating Alternative Supply Chain
Models for the Provision of
Non-Food Aid Products
to Africa
Dr David Taylor
Senior Research Fellow
Logistics and Operations Management Section
Cardiff University Business School
UK