Course Overview

How can we determine whether a program contributed to meaningful change when multiple factors influence the results?

In complex programs, establishing causality is rarely straightforward. Outcomes may be influenced by other interventions, policy changes, organizational dynamics, and external conditions. Traditional approaches to measuring impact are not always feasible or sufficient to explain how and why change occurs.

Contribution analysis offers a systematic, evidence-based approach to developing and testing credible causal explanations, even when experimental or quasi-experimental designs are not practical.

This interactive, two-module course introduces participants to the principles and practical application of contribution analysis. Participants will learn how to develop and test a contribution story, examine causal pathways, assess the strength of evidence, and consider alternative explanations for observed outcomes.

Through real-world examples, guided exercises, and a practical case study, participants will build skills to assess and communicate how programs contribute to results while recognizing the influence of other factors.

What You Will Learn

By the end of this course, participants will be able to:

• Distinguish attribution from contribution and explain how contribution analysis supports credible causal reasoning.
• Apply the key steps of contribution analysis to investigate how and why programs contribute to outcomes.
• Develop a contribution story grounded in a theory of change, identifying causal pathways and underlying assumptions.
• Assess the strength of evidence supporting causal explanations and identify important evidence gaps.
• Examine alternative explanations and determine how they affect the credibility of a contribution claim.
• Communicate defensible conclusions about program contributions, including uncertainties and limitations.

Course Format

This course includes two live, instructor-led sessions, each lasting three hours (or one day in-person). Participants will engage in guided exercises, practical examples, and a case study that builds across both modules. A certificate of completion will be provided to all participants who successfully complete both modules.

Module Breakdown

Module 1: Building a Credible Contribution Story

This module introduces the foundations of contribution analysis and its role in understanding program results. Participants will explore the differences between attribution and contribution, examine the key steps of contribution analysis, and learn how to use a theory of change to identify causal pathways and underlying assumptions.

Through a guided case study, participants will develop an initial contribution story that explains how an intervention is expected to influence outcomes.

Module 2: Testing Evidence and Strengthening Causal Explanations

Building on the first module, participants will examine how to test and refine a contribution story using available evidence. They will explore approaches to assessing evidence quality, identifying gaps, and examining alternative explanations.

Using the same case study, participants will evaluate competing explanations, strengthen their contribution story, and practice communicating credible conclusions that reflect both the evidence and its limitations.

Who Should Attend

This course is ideal for:

• Evaluation professionals and researchers seeking to strengthen their causal reasoning skills
• Monitoring, evaluation, and learning (MEL) specialists
• Program managers responsible for assessing program effectiveness
• Policymakers and decision-makers seeking to understand how interventions contribute to results
• Professionals working on complex programs, systems-change initiatives, and capacity-building interventions

Prerequisites

Prior experience with evaluation or familiarity with theories of change is recommended. No previous experience with contribution analysis is required. All course materials will be provided.