01
Survey design
and data
collection
Impact & Learning uses last advances in digital data collection to collect the data you need. We have extensive experience in collecting household data, samples collection, use of sensors or leveraging additional sources of data (remotely sensed images, public domain datasets). We can find the most cost-effective way for obtaining the necessary data, design survey instruments, program the questionnaires, and establish the server infrastructure and analyses collected data for reporting
We take advantage of satellite images to compute relevant metrics
02
Remote
sensing
03
Impact
Evaluation
We help organizations to demonstrate the value of what they do, deliver better outcomes for development and improvements into future programming. Born from academic research, we have extensive knowledge of impact evaluation methods, adapted to a wide range of topics.
Digital monitoring, tailored to your needs. Starting with project-based indicators and matrices of results, Impact & Learning help project leaders design and take advantage of an insightful tracking system. We bring Monitoring & Evaluation (M&E) to the 21st century using digital data collection, automation, analytics and machine learning.
04
Dashboard
and reporting
We design real-time dashboard and
automated notebooks for tracking and
sustaining progress
05
Analytics &
Machine Learning
We use analytic to uncover patterns and gain insights into your most important decisions. Our services include predictive modelling, web scrapping and recommender systems.
Data collection
Design of survey instruments for monitoring
project outputs
Database management
We establish server infrastructures and manage
database access
Dashboard and reporting
From real-time dashboard to automated notebooks, all the data you need available for better decisions
Analytics & Machine Learning
We use analytic to uncover patterns and gain insights into your most important decisions. Our services include predictive modelling, web scrapping and recommender systems.
Making predictions
This neural network from a past project determines the likelihood of water contamination with E. coli bacteria by running every new data point through the branches.
Input variables:
A – Handwashing place reported
B – Type of water source
C – Distance to water source
D – Mean annual rainfall