Value for Money Assessment
Quantified Value for Money Assessment AI-Optimized Health Supply Chain Framework - Uganda Pilot Implementation
Version 1.0 | November 2025
Document Information
Project
Optimizing Aid Supply Chain with Local Insights in Uganda
Lead Organization
International Foundation for Recovery and Development (IFRAD)
Funding Source
Elrha Humanitarian Innovation Fund (UK FCDO)
Status
Phase 1 Complete - Awaiting MOH/NMS Financial Data for Phase 2
Next Version
Version 2.0 (with quantified calculations) expected May 2026
Executive Summary
This document provides the quantified value for money (VfM) assessment framework for the offline-first AI supply chain optimization system piloted across 10 health facilities in Karamoja and Southwestern Uganda.
The assessment follows the 4E Model:
Economy (Spending Less)
Efficiency (Spending Well)
Effectiveness (Spending Wisely)
Equity (Spending Fairly)
Data Availability Status
The baseline assessment captured operational performance metrics but encountered significant financial data gaps:
Budget utilization
Unavailable for 5 of 10 facilities
Commodity expiry costs
Not tracked at facility level
Emergency delivery costs
District level only, no facility breakdown
Health worker wages
Held centrally by MOH
This Document Provides
Complete VfM calculation methodology with worked formulas
Verified baseline operational metrics from pilot facilities
Clearly marked placeholders for MOH/NMS financial data
Data collection guide for government partners
Sensitivity analysis framework for scenario modeling
Key Findings from Available Data
Baseline operational metrics demonstrate substantial improvement potential:
Facilities experiencing stockouts
100% (10 of 10)
Average stockout duration (remote facilities)
Up to 120 days (Nakivale)
Connectivity reliability
Unreliable at 89% of facilities
Storage capacity-stockout correlation
r = -0.695 (strong negative)
Emergency procurement frequency
Quarterly to monthly at HC III facilities
Baseline Performance Data
Data collected from 10 pilot facilities (2 regional referral hospitals, 8 spoke health centers) across four districts: Moroto, Amudat, Mbarara, and Isingiro.
Data Collection Period: August 25 - September 6, 2025 Source: IFRAD Baseline Assessment Report (October 2025), 33 quantitative surveys, 31 key informant interviews
Projected Improvements
Based on the offline-first AI framework design with three-tier forecasting architecture:
Stockout duration reduction
40% reduction
Needs Assessment Report Dec 2024
Delivery delay reduction
30% reduction (rainy season)
Needs Assessment Report Dec 2024
Forecast accuracy (Tiers 2-3)
≥85% prediction accuracy
Needs Assessment Report Dec 2024
Ordering cycle time
From 2 weeks to 2 days
Technical Validation Report
Equity target
≤5% accuracy disparity urban/rural
Needs Assessment Report Dec 2024
Financial ROI Calculation
Financial ROI measures cash-releasable savings through reduced waste (expired commodities) and avoided emergency logistics costs.
Formula
Variable Definitions and Data Status
Expiry Savings
(Baseline Expiry Rate - Current Rate) × Unit Cost × Annual Volume
MOH/NMS REQUIRED
Logistics Savings
(Baseline Emergency Runs - Current Runs) × Cost per Run
MOH/NMS REQUIRED
Operating Cost
Annual server hosting + maintenance + technical support
PROJECT DATA: £50,000 GBP
Worked Example
Baseline annual expiries (value)
[PLACEHOLDER - MOH/NMS DATA]
Projected expiries with AI (40% reduction)
[AUTO-CALCULATED]
Expiry Savings
[AUTO-CALCULATED]
Baseline emergency runs/year
[PLACEHOLDER - MOH/NMS DATA]
Cost per emergency run
[PLACEHOLDER - MOH/NMS DATA]
Logistics Savings
[AUTO-CALCULATED]
Annual operating cost
[UGX equivalent of £50,000]
FINANCIAL ROI
[CALCULATED UPON DATA INPUT]
Social Return on Investment (SROI)
SROI monetizes efficiency gains by valuing staff time freed from manual ordering processes.
Formula
Time Calculation Basis
Time per ordering cycle
2 weeks (80 hrs)
2 days (16 hrs)
64 hours
Rationale: Staff currently spend ~1 week collecting data from paper records, preparing orders, and entering into multiple systems (DHIS2, eAFYA, CSSP). AI system reduces this to 2 days for data review and order approval only.
Worked Example (10 Pilot Facilities)
Hours saved per ordering cycle
64 hours
Ordering cycles per facility per year
[PLACEHOLDER - assume 12]
Number of pilot facilities
10
Total hours saved annually
64 × 12 × 10 = 7,680 hours
Average hourly wage (UGX)
[PLACEHOLDER - MOH PAYROLL]
SROI (Monetized Time Value)
[CALCULATED UPON DATA INPUT]
Interpretation: This monetized value represents health system efficiency gains. Staff can redirect freed time to direct patient care.
This is classified as 'time-releasable' rather than 'cash-releasable' value.
Data Collection Guide for MOH/NMS
National Medical Stores (NMS) Data Requirements
Commodity Expiry Value
Total UGX value of expired medicines at 10 pilot facilities (Aug 2024 - Aug 2025)
NMS invoices matched to facility expiry reports
Top 10 Expired Commodities
Most frequently expired items with unit costs
NMS procurement database
Emergency Delivery Costs
Average cost per emergency delivery (fuel, per diem, vehicle)
District fuel logs and vehicle manifests
Ministry of Health Data Requirements
Health Worker Wages
Average gross hourly wage for pharmacists/clinical officers in ordering
MOH payroll (annual salary / 2,080 hours)
Ordering Cycle Frequency
Number of ordering cycles per facility per year
District procurement schedules
System Operating Costs
Annual hosting, maintenance, support in UGX
MOH budget office
Data Validation Protocol
Verify expiry data against facility-level stock cards (avoid double-counting)
Cross-reference emergency delivery costs against district fuel logs
Calculate blended hourly wage including benefits
Document assumptions for any estimated values
Use Bank of Uganda midpoint exchange rate (Dec 31, 2025) for GBP→UGX
Obtain district health office sign-off before finalizing
Sensitivity Analysis Framework
Given uncertainty in baseline financial data, sensitivity analysis models how VfM outcomes vary under different scenarios.
Key Variables for Scenario Modeling
Stockout reduction
20%
50%
Expiry reduction
15%
40%
Emergency delivery reduction
20% fewer
40% fewer
Time savings per cycle
40 hours
80 hours
Break-Even Analysis
A neutral Financial ROI (0%) indicates the system pays for itself through waste reduction without generating additional cash savings.
Glossary
4E Model
Framework: Economy (spending less), Efficiency (spending well), Effectiveness (spending wisely), Equity (spending fairly)
Cash-releasable
Savings that could be returned to budget (e.g., reduced expiries, fuel costs)
Time-releasable
Staff time freed from admin tasks, redirected to patient care
MAPE
Mean Absolute Percentage Error - forecast accuracy metric
Offline-first
Systems function fully without internet, syncing when available
Three-tier forecasting
Tier 1: Rule-based (offline), Tier 2: Statistical (intermittent), Tier 3: ML (district/central)
Tracer commodities
Key essential medicines monitored for stockout tracking
Document Information
Version
1.0 (Methodology Complete)
Date
November 2025
Author
IFRAD
Contact
Audience
Elrha HIF Program, Uganda MOH, NMS, District Health Offices
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