Research
Impact Measurement
Programs’ Objectives
Developing and scaling up proprietary methodologies and tools allowing a rigorous measurement and reporting of the expected and realized impact of sustainable investments (Signature Impact Frameworks).
The program develops in 2 Flagship Projects:
- Signature Impact Theme Coverage
- AI-Augmentation Of The Signature Impact Framework
Flagship Project 1.
Signature Impact Theme Coverage – Scaling up SIF across IRIS+ impact themes
Objective 1.1 – Data Collection
Construct corresponding Signature Impact Databases
- Collect literatures of different intervention types & beneficiaries in recent years, in the MEASA region
- Categorise main intervention types in each IRIS+ theme
- Identify different dimensions for each IRIS+ theme to
organise KPIs and prepare Impact Intensity Metrics
Deliverable 1.1 – Databases
Databases
1 Database per IRIS+ theme covered
● Signature Impact Database consisting of rigorous literature review of each article/journal
● Data analysis & visualization of main intervention types, beneficiaries, geographies,
and associated Probabilities of Impact
Objective 1.2.
Impact Analysis
Analyse applicability of SIF in IRIS+ themes
● Construct case studies to demonstrate feasibility of the framework in each IRIS+ theme
● Apply the SIF framework to existing projects/portfolios for impact assessment
Deliverable 1.2
Publications
1 White paper per IRIS+ theme covered
● Signature Impact Framework White Paper to detail the content of the database, relevant KPIs and benchmarks for each IRIS+ theme, and applications of the metrics to projects in each theme
Flagship Project 2.
AI-Augmentation Of The Signature Impact Framework
Objective 2.1
Process Standardization
- Streamline process to extract appropriate KPI for impact measurement across impact themes
- Identify sources & to collect country-level benchmark
- Develop methodology to estimate project-specific impact
Deliverable 2.1
Framework Guideline Methodological Guide
- A methodology paper clearly outlining the theoretical frameworks of SIF and guidelines for KPI selection and target outcome computations
- A repository of pre-mapped country-level benchmarks for covered IRIS+ Impact Verticals
Objective 2.2
Data Extraction Automation
Complement the Signature Impact Database with AI
- Train Large Language Models (LLMs) for data extractions to decrease human-based biases
- Leverage Natural Language Processing (NLP) frameworks to create aggregate analytics (e.g. intervention type)
Deliverable 2.2
NLP Classifier Tool
AI-assisted Signature Impact Database
- An NLP classifier trained to categorize projects by type and beneficiary based on predetermined rule-based logic
Objective 2.3
Platform Development
Automate the Calculation of Ex-Ante Metrics
- Explore potential of using a Retrieval Augmented Generation (RAG) system to let machines conduct the calculation of impact metrics (e.g. Expected Impact & Impact Intensity)
- Develop automated platform to output impact metrics by inputting basic project profile information
Deliverable 2.3
Ex-Ante Metrics Calculator
Automated Interface for the Calculation of Ex-Ante Metrics
- Interactive tool with a front-end user interface allowing users to input basic project profile, which is fed into back-end RAG logic to retrieve relevant Expected Impact and Impact Intensity figures
newsletter
Learn more about Transition Investment.
Join our mailing list to receive news and updates about our exclusive events and workshops.