Understanding when, where, and how to use data is complex.
IDinsight is on-site with our clients to translate data into actionable insights. We provide rigorous evidence to improve social sector programs and help clients understand how to use data to inform decisions large and small, within time, budget, operational, and political constraints.
Every IDinsight engagement is anchored to three principles:
Impact: What is the probability that this work will improve lives?
Demand: What are the client's highest priority questions?
Causality: What else could have/would have happened in the absence of this program?
Work with Us
We typically partner with clients in one of three ways:
An open-ended, long-term engagement in which an IDinsight team works closely with a client (often in an embedded capacity) to answer important questions as they arise using a broad methodological toolkit. Learning partnerships nearly always draw on a broad suite of services.
A time-bound engagement with a clear scope of work, usually focused on answering one or two important questions defined before the project starts.
An engagement in which IDinsight offers high-level guidance on measurement and evaluation strategy.
Client engagements may include just one of IDinsight’s services, or it may include many.
Our teams begin with a careful diagnosis of a client’s most pressing questions and a recommendation on how to how best to answer them to achieve maximum impact within the engagement’s specific context.
Our services include:
Impact evaluation to inform client decisions
Measuring whether program activities have been implemented as planned to inform programmatic decisions
Designing monitoring systems to inform client decisions
Targeted support to diagnose problems and shape program design
Data analysis, modeling and visualization techniques
Systematic and critical review of secondary sources targeted at informing client decisions
Measuring beneficiary beliefs or preferences (including willingness to pay) to inform client decisions
Training clients on how to commission, consume, generate, and/or use evidence to improve their impact
Series of approaches that are used to make accurate predictions on unseen data or automate classification of objects or outcomes