Transcript Computerization of Logistics Information for Improved

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
MOH, MoF
Proc Agents
Courtesy: JSI/DELIVER
Global Need
Commodity
Type
Family
Planning
(colour coded)
Global Need
STI
Drugs
(including some
condoms for STI/
HIV)
Vaccines
and
Vitamin A
Essential
Drugs
TB/
Leprosy
HIV/AIDS
Test kits
(&HepB
tests)
Malaria
Condoms
for STI/HIV/
AIDS
prevention
MOH
Equipment
(including
Lab
supplies
Organization Key
Government
World Bank loan
Bilateral Donor
Multilateral Donor
NGO/Private
Source of
funds for
commodities
U
S
A
I
D
KfW
U
N
F
P
A
DFID
(UK)
European
Union
W
H
O
G
A
V
I
GOK
C
I
D
A
UNICEF
D
u
t
c
h
JICA
De-centralization projects
US
Gov
GOK,
WB/IDA
DANIDA (11 districts)
European Union (20 Districts)
World Bank DARE (8 districts)
SIDA (6 districts)
Belgian Gov (BTC) (2 districts)
EUROPA
Procurement
Agent/Body
Point of first
warehousing
Organization
responsible
for delivery
to district
levels
U
S
A
I
D
K
f
W
KEMSA
Regional
Depots
U
N
F
P
A
WHO (3 Districts)
Crown
Agents
Government
of Kenya
Dutch
Gov
Agent
UNICEF
KEMSA Central Warehouse
KEMSA, District Hospitals, District Stores
(Essential drugs kits, TB/Leprosy drugs, malaria
drugs, lab supplies, reagents, HIV/AIDS test kits)
NPHLS store
Japanese
Private
Company
KEPI Cold
Store
DELIVER (FPLM) and Division of
RH (MOH) (Contraceptives, condoms,
STI kits, HIV/AIDS test kits)
GTZ
JICA (5 districts)
C
D
C
ADB (5 districts)
Schenker
Warehouse
KEPI
(Vaccines
and Vitamin
A)
Express
Kenya
(Equipment)
Courtesy:JSI/DELIVER
JSI/DELIVER
Courtesy:
District level
decisions of
quantity, type and
procurement of
health
commodities
MEDS
Private
Drug
sources
Supply Chain Software
International
Functional Overview
Global
Procurement
Information
System
Reproductive
Health
Interchange
Reports forecasts
and orders
Delivers to
Manufacturer
Delivers to
International
Distributor
Delivers to
ORION
Orders from
National
Procurement
Service
,
PipeLine
Requests
Deliveries
ProQ
Health Program
Manager
Reports
to
Supply Chain
Manager
Logistics
Management Unit
Reports
to
National
Warehouse
Regional
Delivers to
Sub-national
warehouse
Reports to
Delivers to
Last Mile
Technologies
,
Service
Delivery
Mobile Tech
Orders from
Reports to
Orders from
Service Delivery
Point
Topics
• Background to supply chain
management
• Tools review
• Discussion of challenges and
successes
Website: http://rhi.rhsupplies.org
UNFPA
ATLAS
IPPF
SunBusiness
RHI Inputs
and Outputs
Crown Agents (DfID)
Summary of
Shipments
RAP
Value Summary
IRH
Excel
Quantity
Summary
USAID
My Commodities
MSI
RHI
Geographic
Summary
Excel
Govt. of Nepal
Excel
Govt. of Uganda
Excel
DKT/Ethiopia
Excel
Other, future…
(Govts., PSI)
Shipment
History
Shipment
Details
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
ORION™
Version 10.3.0 – 3i Infotech
Supply Management
ORION
Distribution
Centers
Vendors /
Manufacturers
Information
Goods
View Shipments>>
Shipment Summary Reports>>
Account Information>>
Inventory>>
Shipping Information>>
Product Catalogue>>
Support>>
http://deliver.jsi.com/dhome/mycommodities
PipeLine Monitoring and
Procurement Planning
Inputs
Outputs
PipeLine - 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
ProQ
Quantification Software
for HIV Tests
Current Uses of testing:
•Blood Safety
•VCT
•PMTCT
•Testing HIV-exposed babies
•Clinical Diagnosis
•Sentinel Surveillance
•Other
ProQ: Advocacy Tool for Resource Mobilization and Funding
Allocations
ProQ - Users and countries
–
–
–
–
–
Logistics Advisors
Program Managers and Planners
Product Managers
Procurement Officers and Agents
Donors
– Ghana
– Zambia
– Zimbabwe
Main Menu
Main inputs & features
Inputs:
•
Quantities issued to facilities or dispensed to users
•
Quantities received
•
Losses/adjustments
•
Stock on hand
Main features:
- Supply status and distribution of stocks at each SDP and storage facility
- Quantities of products dispensed to user
- Trends in commodity consumption for program evaluation and procurement planning
- Service statistics, such as new and continuing users
- Couple years of protection (CYP), calculated for family planning products dispensed
- Percentage of facilities reporting, names and locations
Delivery Planning Screen
Delivery Planning Screen
Supply Chain Manager:
Users and countries
Program staff and MOH counterparts
• Malawi
• Zambia
• Nigeria
Technologies & trends
• Mobile technology for capturing data
• Web based Logistics Information System
• Open source development
• Network analysis
Supply Chain Guru™
LLamasoft, Inc.
Supply Chain Network Design
• Network Modeling through
- Network Optimization
- Inventory Optimization
- Enterprise Simulation
Baseline Network
Optimized Network
Does using 3-month historical average smooth away
variability?
BR
E
E
IEM
BR
VIE
M
RE
TU
B
SE
PT
IEM
B
-12%
183%
7%
13%
-23%
22%
3%
-8%
-5%
-63%
-10%
-22%
5%
44%
2%
8%
-21%
-64%
-8%
-13%
13%
0%
1%
13%
46%
700%
64%
104%
Totonicapan
condones
tdecobre
inyectable
orales
-17%
-47%
-24%
-50%
-12%
11%
12%
27%
7%
33%
-17%
-4%
4%
22%
-10%
-5%
35%
-70%
28%
10%
-18%
-41%
-23%
-19%
-26%
267%
19%
-6%
-47%
-22%
-13%
-8%
171%
67%
32%
29%
88%
67%
19%
32%
Solola
condones
tdecobre
inyectable
orales
52%
-70%
-11%
-8%
-3%
33%
31%
44%
9%
-33%
24%
31%
18%
0%
-9%
-10%
7%
-10%
-14%
-31%
50%
-39%
-61%
-5%
-12%
-20%
-37%
27%
-17%
8%
-77%
6%
4%
10%
157%
-23%
4%
22%
97%
AB
DIC
5%
33%
-7%
2%
NO
3%
0%
5%
51%
OC
AG
OS
TO
JU
-13%
-38%
-11%
-40%
LIO
NIO
JU
condones
tdecobre
inyectable
orales
MA
Jutiapa
RIL
YO
O
RE
Projected Demand as Percentage of Actual Demand For Aggregated 2007 Quantities
RZ
•
•
•
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.
MA
•
*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
•
•
•
25% Variability in Monthly Demand for
Condoms
500
Inventory
•
•
(Settings: 106 condoms/month; 1/3 month min/max;
2 year period, reorder quantity based on previous 3 month
demand)
400
300
200
100
0
Aug-07 Nov-07 Feb-08 May-08 Aug-08 Nov-08 Feb-09 May-09 Aug-09
50% Variability in Monthly Demand for
Condoms
500
500
400
400
300
200
100
0
Aug-07 Nov-07 Feb-08 May-08 Aug-08 Nov-08 Feb-09 May-09 Aug-09
Inventory
Inventory
No Variability in Monthly Demand for
Condoms
300
200
100
0
Aug-07 Nov-07 Feb-08 May-08 Aug-08 Nov-08 Feb-09 May-09 Aug-09
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?