Computerization of Logistics Information for Improved Supply Chain Management
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Transcript of Computerization of Logistics Information for Improved Supply Chain Management
Computerization of Logistics Information for
Improved Supply Chain Management
Presentation at JSI
5 November 2009
Topics
• Background to supply chain management
• Tools review
• Discussion of challenges and successes
The Supply Chain
Courtesy: JSI/DELIVER
Proc Agents
MOH, MoF
Global Need
Courtesy: JSI/DELIVER
Global NeedFamily Planning
(including some condoms for STI/
HIV)
STI Drugs
Essential Drugs
Vaccines and
Vitamin A
TB/Leprosy
HIV/AIDS Test kits (&HepB tests)
DFID (UK)
KfW UNICEF JICAGOK,
WB/IDASource of funds for
commodities
Commodity Type
(colour coded)
MOH Equip-ment
(including Lab
supplies
Point of first warehousing
KEMSA Central Warehouse
KEMSA Regional Depots
Schenker Warehouse
Organization responsible for delivery to district
levels
KEMSA, District Hospitals, District Stores (Essential drugs kits, TB/Leprosy drugs, malaria drugs, lab supplies, reagents, HIV/AIDS test kits)
Express Kenya
(Equipment)
Procurement Agent/Body Crown
AgentsGovernment
of Kenya
GOK
GTZ
DELIVER (FPLM) and Division of RH (MOH) (Contraceptives, condoms,
STI kits, HIV/AIDS test kits)
Euro-pean Union
KfW UNICEF
KEPI Cold Store
KEPI (Vaccines
and Vitamin A)
Malaria
SIDA (6 districts)
USAID
USAID
UNFPA
DANIDA (11 districts)
EUROPA
Condoms for STI/HIV/
AIDS prevention
Belgian Gov (BTC) (2 districts)
CIDA World Bank DARE (8 districts)
UNFPA
European Union (20 Districts)
District level decisions of
quantity, type and procurement of
health commodities
De-centralization projects
US Gov
CDC
WHO (3 Districts)
NPHLS store
MEDSPrivate Drug
sources
Dutch
Dutch Gov
Agent
Government
NGO/Private
Bilateral Donor
Multilateral Donor
World Bank loan
Organization Key
Japanese Private
Company
JICA (5 districts)
WHO
GAVI
ADB (5 districts)
Courtesy: JSI/DELIVER
Supply Chain SoftwareFunctional Overview
Nat
iona
lR
egio
nal
Ser
v ic e
D
eliv
ery
I nt e
rnat
iona
l
Manufacturer International DistributorDelivers to
National Warehouse
Sub-national warehouse
Service Delivery Point
Orders fromOrders from
Delivers to
Delivers to
Health Program Manager
Reports to
Delivers to
Procurement Service Requests
Deliveries
Orders from
Delivers to
Logistics Management Unit
Reportsto
Reports to
Reports to
ORION
Global Procurement Information
SystemReports forecasts
and orders
Reproductive Health Interchange
PipeLine,
ProQ
Supply Chain Manager
Last Mile Technologies
,
Mobile Tech
Topics
• Background to supply chain management
• Tools review
• Discussion of challenges and successes
Website: http://rhi.rhsupplies.org
RHI Inputs and Outputs
RHIUSAID My Commodities
IRH Excel
Crown Agents (DfID)RAP
IPPF SunBusiness
UNFPA ATLAS
Other, future…
(Govts., PSI)
Summary of Shipments
Value Summary
Quantity Summary
Geographic Summary
Shipment History
Shipment Details
MSI
Excel
Govt. of Nepal
Excel
Govt. of Uganda
Excel
DKT/Ethiopia
Excel
Users and Uses• TA Providers: preparation for country-specific TA
for forecasting, procurement, financing context• MoH RH Program Mgrs: planning & budgeting• Commodity Managers: monitoring of shipments• Donors: coordination• Contraceptive Security Committees: share
information, strategize, mobilize resources• Advocates & Researchers: advocacy, support for
campaigns and research questions
DistributionCenters
Information Goods
Vendors /Manufacturers
ORION
ORION™ Version 10.3.0 – 3i Infotech
Supply Management
http://deliver.jsi.com/dhome/mycommoditieshttp://deliver.jsi.com/dhome/mycommodities
View Shipments>>View Shipments>> Shipment Summary Reports>>Shipment Summary Reports>>
Account Information>>Account Information>>
Inventory>>Inventory>>
Shipping Information>>Shipping Information>> Product Catalogue>>Product Catalogue>>
Support>>Support>>
PipeLine Monitoring and PipeLine Monitoring and Procurement PlanningProcurement Planning
InputsInputs OutputsOutputs
PipeLine - Users and countriesPipeLine - Users and countries
Program managers and consultants in:
Bangladesh, Burkina Faso, Dominican Republic, El Salvador, Ghana, Honduras, Liberia, Malawi, Mozambique, Nepal, Nicaragua, Paraguay, Rwanda, Tanzania, Uganda, Zambia, Zimbabwe
ProQQuantification Software
for HIV Tests
Current Uses of testing:Current Uses of testing:
•Blood SafetyBlood Safety
•VCTVCT
•PMTCTPMTCT
•Testing HIV-exposed babiesTesting HIV-exposed babies
•Clinical DiagnosisClinical Diagnosis
•Sentinel SurveillanceSentinel Surveillance
•OtherOther
ProQ: Advocacy Tool for Resource Mobilization and Funding ProQ: Advocacy Tool for Resource Mobilization and Funding AllocationsAllocations
– Logistics Advisors– Program Managers and Planners– Product Managers– Procurement Officers and Agents– Donors
– Ghana– Zambia– Zimbabwe
ProQ - Users and countriesProQ - Users and countries
Main Menu
Main features:Main features:
- Supply status and distribution of stocks at each SDP and storage facility - Supply status and distribution of stocks at each SDP and storage facility
- Quantities of products dispensed to user- Quantities of products dispensed to user
- Trends in commodity consumption for program evaluation and procurement planning - Trends in commodity consumption for program evaluation and procurement planning
- Service statistics, such as new and continuing users - Service statistics, such as new and continuing users
- Couple years of protection (CYP), calculated for family planning products dispensed - Couple years of protection (CYP), calculated for family planning products dispensed
- Percentage of facilities reporting, names and locationsPercentage of facilities reporting, names and locations
Inputs:Inputs:
• Quantities issued to facilities or dispensed to usersQuantities issued to facilities or dispensed to users
• Quantities receivedQuantities received
• Losses/adjustmentsLosses/adjustments
• Stock on handStock on hand
Main inputs & featuresMain inputs & features
Delivery Planning Screen
Delivery Planning Screen
Supply Chain Manager:Supply Chain Manager:Users and countriesUsers and countries
Program staff and MOH counterparts
• Malawi
• Zambia
• Nigeria
Technologies & trendsTechnologies & trends
• Mobile technology for capturing data
• Web based Logistics Information System
• Open source development
• Network analysis
Supply Chain Guru™Supply Chain Guru™LLamasoft, Inc.LLamasoft, Inc.
• Network Modeling through
- Network Optimization
- Inventory Optimization
- Enterprise Simulation
Supply Chain Network DesignSupply Chain Network Design
Baseline Network Optimized Network
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
Effect of Variability on Solola Health Center Condom Stock Outs and Emergency Orders
• Scenario Outputs• Stock 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
Aug-07 Nov-07 Feb-08 May-08 Aug-08 Nov-08 Feb-09 May-09 Aug-09
Inv
en
tory
25% 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
Topics
• Background to supply chain management
• Tools review
• Discussion of challenges and successes
Discussion Questions• How has your program used information
technology to improve supply operations in a global health setting?
• What continue to be the most important hurdles to applying information technology in our context?
• What information gaps continue to hamper our ability to assure a transparent and equitable distribution of medical resources?