Supply Chain Modeling: Analysis of Demand Variability and Volumetric Capacity Needs for Contraceptives and MCH Products James Gibney Anabella Sánchez Carlos

Supply Chain Modeling: Analysis of Demand Variability and Volumetric Capacity Needs for Contraceptives and

MCH Products

James GibneyAnabella SánchezCarlos Lamadrid February 20, 2009

Agenda

Introduction: Overview of Unmet Need and Areas of Interest

Part A: Volumetrics of Guatemala’s Integrated Supply Chain

Part B: Effect of Demand Variability on Contraceptive Logistics

Introduction: Low Unmet Demand in 2007 For Contraceptives – But Analysis Still Needed to Ensure Success in 2008/9

Observation:

No significant stock-out problems existed in 2007 for contraceptives

Areas of Interest:

A. Given the integrated supply system, what are the volume requirements needed to ensure full supply for contraceptives and MCH products?

B. What is the effect that variability has on the system? Are stock-outs being avoided due to high level of emergency orders?

99% 97% 98% 97%100% 100% 100% 99% 100% 100% 100% 100% 99%

94%99% 97%

1% 2% 1% 1% 1% 3%3%3%6%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Con

do

ms

IUD

Inje

ctab

les

Ora

ls

Con

do

ms

IUD

Inje

ctab

les

Ora

ls

Con

do

ms

IUD

Inje

ctab

les

Ora

ls

Con

do

ms

IUD

Inje

ctab

les

Ora

ls

Guatemala Total Jutiapa Totonicapán Sololá

Consumption Unfulfilled Demand

Source: MSPAS National RH Program, “Real Demand for Contraceptive Methods (2007)”

Part A: Volumetrics of Guatemala’s Integrated Supply Chain

Background: With little exception, the distribution network (warehousing and transport) of products in Guatemala’s public health system is integrated. To better understand the volume capacity needs of this system, data on all products from Jutiapa and Totonicapán was analyzed. A special focus was placed on contraceptives and MCH products.

Questions this section answers:1. In terms of volumes, what does the average monthly demand for all products that flow

through a DAS warehouse look like? How does this differ for health centers, health posts, NGO’s, and hospitals? What are the products that take up the most space?

2. What are the space requirements needed for the family planning products? How do these products compare to each other? What are the different requirements per SDP site type? How to they compare to non family planning products?

3. What are the space requirements needed for the MCH products? How do these products compare in space needs to each other? How to they compare to non MCH products?

• Contraceptives represent less than 1% of volume for Totonicapán and 3% for Jutiapa

• Difference is attributed to

higher demand of condoms in Jutiapa

• MCH accounts for approximately 1/3 and other products take 2/3 of volume capacity

Volumes of Product Types in the Integrated System

Volume by % of Average Monthly Demand -- All Products

66.6% 68.5% 67.6% 69.9%60.8%

65.8%

32.0% 28.4% 30.1%29.5%

38.4%33.6%

1.3% 0.5% 0.8% 0.6%

2.3%3.1%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Health Posts Health Centers Health Postsand Health

Centers

Health Posts Health Centers Health Postsand Health

Centers

Jutiapa Totonicapán

Other Products Maternal & Child Health Contraceptives

Source: MSPAS Logistics Module (January 2007 to April 2008)

Volumetric Composition of Average Monthly Demand By Products (Combined Average Monthly Real Demand for Totonicpán and Jutiapa)

• Table provides 105 products

• Contraceptives are highlighted blue, Condoms take 1.3% of total

• Volume composition follows 80/20 rule

• Acetaminofen syrup and Bromexina take approx. 20% of volume

80% volume

Volume (cubic cm) Requirements of Average Monthly Demand

• Jutiapa has double the capacity need at SDP’s than Totonicapán

• In Totonicapán Health Posts require more volume capacity than health centers for MCH and Other Drugs, but not Contraceptives

• In Jutiapa, the Health Centers require more volume capacity for all product types, with Contraceptives requiring significantly more volumetric capacity (approx. 3x)

4,540,039

5,565,604

2,814,298

2,035,063

2,182,770

2,309,746

1,187,586

1,286,735

27,321 14,177 15,984 3,287

253,399

89,559

21,660

25,633

-

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

7,000,000

8,000,000

Health Posts Health Centers NGOs Hospital Health Posts Health Centers NGOs Hospital


Other Products Maternal & Child Health Contraceptives


Contraceptive Volumes – Monthly Demand Averages For SDP Types

•Percentages show relative capacity needs for storage and transport

•Commonalities between Jutiapa and Totonicapan:

•Same order of magnitude (Hospitals, then NGO’s, then Health Posts, then Health Centers)

•Hospital percentages most similar

•Health Post percentages are 2nd most similar

•Differences between Jutiapa and Totonicapan

•Totonicapan higher relative flow to NGO’s

•Jutiapa higher relative flow to Health Centers (almost 2 times that of Totonicipan)

65.9%

38.5%

23.3%

32.5%

7.1%

24.0%

3.7% 4.9%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


Health Centers Health Posts NGOs Hospital


For the contraceptives part of the integrated order (1%-3% of total volume, what is the volumetric composition by product?

Volume by % of Average Monthly Demand -- Contraceptives

48.7%

79.3%71.3%

43.4%

31.6%

67.4%

55.4%

31.8%

42.6%

13.4%

32.5%38.7%

39.7%

12.4%19.6%

27.4% 51.1%

22.1%

19.0%

22.7%

21.0%

37.6%

30.6%24.1%

11.6% 7.7% 8.8%

25.7%

17.3%10.0%

25.6%

36.3%

31.4%

42.1%

36.9%33.2%

0.0% 0.0% 0.0% 0.0%9.2% 5.0% 6.9% 3.9%3.5%0.6% 0.4% 0.5%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

HealthPosts

HealthCenters

HealthPostsand

HealthCenters

Hospital NGOs AllSites

HealthPosts

HealthCenters

HealthPostsand

HealthCenters

Hospital NGOs AllSites


CONDOM LOFEMENAL DEPO PROVERA IUD


What is the Average Monthly MCH Demand By Volume?

Totonicapan - MCH Average Monthly Demand by Volume

34.3% 31.5%36.8%

11.6%13.0%

10.3%

11.0% 12.6% 9.6%

7.5%10.1%

5.1%

6.7%5.2%

8.0%

6.6%7.6%

5.6%

6.1%7.7%

4.6%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Health Postsand Health

Centers

Health Posts HealthCenters

LIDOCAINA CLORHIDRATO (SIMPLE) 2 %Vial

ACIDO FOLICO 5 mg Tableta

ALBENDAZOL 200 mg Tableta

HARTMAN (RINGER LACTATO) 1000 mlBolsa/Frasco

ALBENDAZOL 200/5 mg/ml Frascosuspensión

AMOXICILINA 500 mg Tableta

AMOXICILINA + ACIDO CLAVULANICO 125/5 mg/ml Frasco suspensión

ACETAMINOFEN 500 mg Tableta

AMOXICILINA + ACIDO CLAVULANICO 250+62.5/5 mg/ml Frasco suspensión

PRENATALES 0 Sin ConcentraciónGragea

SALBUTAMOL 2/5 mg/ml Frasco Jarabe

TRIMETROPRIMA SULFAMETOXAZOL 40-200/5 mg/ml Frasco suspensión

ACETAMINOFEN 125/5 mg/ml FrascoJarabe

ERITROMICINA 250/5 mg/ml Frascosuspensión

AMOXICILINA 250/5 mg/ml Frascosuspensión

SALES DE REHIDRATACION ORAL 55.8 gSobre


Jutiapa - MCH Average Monthly Demand by Volume

30.5% 30.8% 30.2%

13.5% 12.5% 14.4%

11.6% 11.5% 11.8%

11.1% 13.3% 9.1%

9.1% 8.7%9.5%

4.5% 5.2%3.8%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Health Postsand Health

Centers

Health Posts HealthCenters

LIDOCAINA CLORHIDRATO (SIMPLE) 2% Vial

ALBENDAZOL 200 mg Tableta

ACIDO FOLICO 5 mg Tableta

PRENATALES 0 Sin ConcentraciónGragea

AMOXICILINA 500 mg Tableta

ALBENDAZOL 200/5 mg/ml Frascosuspensión

ACETAMINOFEN 500 mg Tableta

HARTMAN (RINGER LACTATO) 1000 mlBolsa/Frasco

ERITROMICINA 250/5 mg/ml Frascosuspensión

TRIMETROPRIMA SULFAMETOXAZOL40-200/5 mg/ml Frasco suspensión

SALBUTAMOL 2/5 mg/ml Frasco Jarabe

AMOXICILINA 250/5 mg/ml Frascosuspensión

SALES DE REHIDRATACION ORAL 55.8g Sobre


Acetaminofen takes up over 30% in both Departments

Effect of Demand Variability on Contraceptive Logistics

Background: Given the complexity of large logistical networks, such as the MSPAS system, the effect of high variability on a supply chains can be both significant and hard to measure. Accordingly, it is necessary to measure the variability levels and use advanced analysis methods, such as modeling, to determine the effect.

Questions this section answers:1. Does the use of 3 months historical averages in making orders reduce the

variation to insignificant amounts?2. How does variability effect service levels? Can there still be a stock-out even

if 1/3 min/max levels are followed? Does an increase in variability increase the propensity for emergency orders? Does it increase the propensity to be overstocked?

Variability in Contraceptive Monthly Real Demand

Observations:• Real demand changes

significantly on a monthly basis• Jutiapa shows lowest variability in

all products• High IUD variability partially

attributed to low order amounts (ie. change from 4 to 8 represents 100%)

Ramifications:• Variability levels can

significantly effect service rates of logistics system, even if system follows the min/max ordering system

• Causes of Variability should be addressed

– Are reporting procedures being followed

– or are there really high swings in real demand?

Average Change in Monthly Real Demand for 2007

15%

91%

14%

30%

29%

99%

39%

37%

28%

101%

18%

31%

10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 110%

condones

tdecobre

inyectable

orales

Jutiapa Totonicapan Solola

Does Using 3-Month Historical Average Smooth-away Variability?

• Table below compares projected demand based on 3 month historical averages to the actual demand for 2007

• Red highlights represent projected under-estimating by more than 20%• Yellow highlights represent projected demand over-estimating by more than 20%• Results: 50% of the time the projected was either over or under by more than 20%. Using projections

based on 3-months historical data does not necessarily remove variability. Complexity of system requires the use of advanced supply chain modeling software.

Projected Demand as Percentage of Actual Demand For Aggregated 2007 Quantities

MA

RZO

AB

RIL

MA

YO

JUN

IO

JULI

O

AG

OS

TO

SE

PTI

EM

BR

E

OC

TUB

RE

NO

VIE

MB

RE

DIC

IEM

BR

E

Jutiapa condones -13% 3% 5% -12% -23% -5% 5% -21% 13% 46%tdecobre -38% 0% 33% 183% 22% -63% 44% -64% 0% 700%inyectable -11% 5% -7% 7% 3% -10% 2% -8% 1% 64%orales -40% 51% 2% 13% -8% -22% 8% -13% 13% 104%

Totonicapan condones -17% -12% 7% 4% 35% -18% -26% -47% 171% 88%tdecobre -47% 11% 33% 22% -70% -41% 267% -22% 67% 67%inyectable -24% 12% -17% -10% 28% -23% 19% -13% 32% 19%orales -50% 27% -4% -5% 10% -19% -6% -8% 29% 32%

Solola condones 52% -3% 9% 18% 7% 50% -39% -20% 8% 10%tdecobre -70% 33% -33% 0% -10% -61% -37% -77% 157%inyectable -11% 31% 24% -9% -14% 22% -5% 27% 6% -23%orales -8% 44% 31% -10% -31% 97% -12% -17% 4% 4%

*Projected amounts calculated using average of previous 3 months

Modeling The Department of Sololá

Structure• 1 National Warehouse• 1 Department

Warehouses• 10 District

Warehouses• 33 Health Centers• 10 NGOs• 1 Hospital

Rules• Products• Inventory Policies• Sourcing Policies• Transportation Policies

Effect of Variability on Sololá Health Center Condom Stock Outs and Emergency Orders

Scenario OutputsStock Out Periods

– no variability scenario – 0– 25% variability scenario – 1 – 50% variability scenario – 5

Instances Crossing Above Max (overstocked)– No variability scenario – 0– 25% variability scenario – 5– 50% variability scenario – 2

Instances Crossing Below Min (emergency order)– No variability scenario – 0– 25% variability scenario – 8– 50% variability scenario – 6

(Settings: 106 condoms/month; 1/3 month min/max; 2 year period, reorder quantity based on previous 3 month demand)

No Variability in Monthly Demand for Condoms

0

100

200

300

400

500

Aug-07 Nov-07 Feb-08 May-08 Aug-08 Nov-08 Feb-09 May-09 Aug-09

Inv

en

tory

50% Variability in Monthly Demand for Condoms

0

100

200

300

400

500


Inv

en

tory

25% Variability in Monthly Demand for Condoms

0

100

200

300

400

500


Inv

en

tory

How variable is the data? Examples of condom real demand - JutiapaAgua Blanca - Health Center

0

50

100

150

200

250

300

350

400

450

Jan-

07

Feb-0

7

Mar

-07

Apr-0

7

May

-07

Jun-

07

Jul-0

7

Aug-0

7

Sep-0

7

Oct-

07

Nov-0

7

Dec-0

7

Jan-

08

Feb-0

8

Mar

-08

Apr-0

8

Asunción Mita - Health Center

0

500

1000

1500

2000

2500

3000

3500

4000

4500

Jan-

07

Feb-0

7

Mar

-07

Apr-0

7

May

-07

Jun-

07

Jul-0

7

Aug-0

7

Sep-0

7

Oct-

07

Nov-0

7

Dec-0

7

Jan-

08

Feb-0

8

Mar

-08

Apr-0

8

Atescatempa - Health Center

0

200

400

600

800

1000

1200

1400

1600

1800

Jan-

07

Feb-0

7

Mar

-07

Apr-0

7

May

-07

Jun-

07

Jul-0

7

Aug-0

7

Sep-0

7

Oct-

07

Nov-0

7

Dec-0

7

Jan-

08

Feb-0

8

Mar

-08

Apr-0

8

Jutiapa - Health Center

0

500

1000

1500

2000

2500

3000

3500

4000

Jan-

07

Feb-0

7

Mar

-07

Apr-0

7

May

-07

Jun-

07

Jul-0

7

Aug-0

7

Sep-0

7

Oct-

07

Nov-0

7

Dec-0

7

Jan-

08

Feb-0

8

Mar

-08

Apr-0

8

Mean: 214Standard Deviation: 103 (48% of mean)

Mean: 2,564Standard Deviation: 826 (32% of mean)



Source: MSPAS Logistics Module data

How variable is the data? Examples of depo real demand - JutiapaMoyuta - Health Center

0

50

100

150

200

250

300

Jan-

07

Feb-0

7

Mar

-07

Apr-0

7

May

-07

Jun-

07

Jul-0

7

Aug-0

7

Sep-0

7

Oct-

07

Nov-0

7

Dec-0

7

Jan-

08

Feb-0

8

Mar

-08

Apr-0

8

Yupiltepeque - Health Center

0

10

20

30

40

50

60

70

80

90

100

Jan-

07

Feb-0

7

Mar

-07

Apr-0

7

May

-07

Jun-

07

Jul-0

7

Aug-0

7

Sep-0

7

Oct-

07

Nov-0

7

Dec-0

7

Jan-

08

Feb-0

8

Mar

-08

Apr-0

8

Comapa - Health Center

0

20

40

60

80

100

120

140

160

180

200

Jan-

07

Feb-0

7

Mar

-07

Apr-0

7

May

-07

Jun-

07

Jul-0

7

Aug-0

7

Sep-0

7

Oct-

07

Nov-0

7

Dec-0

7

Jan-

08

Feb-0

8

Mar

-08

Apr-0

8

El Adelanto - Health Center

0

20

40

60

80

100

120

140

Jan-

07

Feb-0

7

Mar

-07

Apr-0

7

May

-07

Jun-

07

Jul-0

7

Aug-0

7

Sep-0

7

Oct-

07

Nov-0

7

Dec-0

7

Jan-

08

Feb-0

8

Mar

-08

Apr-0

8




Mean: 79Standard Deviation:21 (26% of mean)

Source: MSPAS Logistics Module data

Questions?

Documents

Supply Chain Modeling: Analysis of Demand Variability and Volumetric Capacity Needs for Contraceptives and MCH Products James Gibney Anabella Sánchez Carlos