Solutions for MEL & Programme Teams
Dots connects participant voices and field feedback to your program data as it comes in, so your team can see the why behind the numbers.
The challenge MEL & programme teams face
Quantitative data leads
MEL and program teams collect data throughout a program, but quantitative data often becomes the primary lens for measuring program performance, reporting, communications, and fundraising.
Qualitative evidence used sparingly
Qualitative evidence is used sparingly as anecdotes or not at all, leaving teams without important context behind the metrics.
Scattered across tools
With qualitative data scattered across tools and documents, it is also difficult to assimilate.
Insight arrives too late
By the time all the data has been cleaned, synthesized, and analyzed, the opportunity to use it for improving implementation may have passed.
Practical ways MEL & programme teams use Dots
Analyze participant feedback
Bring together interviews, surveys, focus groups, feedback forms, and other qualitative data to understand how participants experience a program, what is working, and where they are facing challenges.
Connect quantitative and qualitative data
Provide a more complete picture by bringing program metrics and qualitative evidence into one view, so teams can understand not just what is happening but why.
Monitor implementation
Analyze field feedback and program data to identify recurring implementation challenges, unexpected outcomes, and differences across locations, cohorts, or delivery partners.
Prepare evaluations and reports
Organize and synthesize qualitative evidence for evaluations, donor reports, learning products, and program reviews. Bring participant voices and field evidence into reporting without hours of manual analysis.
Compare findings across programs
Analyze qualitative data across projects, locations, cohorts, or reporting periods to identify patterns, similarities, and differences that may not be visible within individual datasets.
How Dots helps MEL & Program teams scale insight
1
Bring qualitative evidence into the bigger picture
Connect participant voices, field observations, and qualitative findings with the wider program data. Understand not just what is happening, but why.
2
Spend less time preparing data and reports
Automate repetitive work like organizing, tagging, synthesizing, and summarizing qualitative data. Spend more time interpreting findings and facilitating meaningful learning.
3
Make learning happen while programs are running
Surface emerging themes and patterns as new data comes in. Give program teams timely evidence they can use to course-correct instead of waiting for the end of a reporting cycle.
4
Make funder reporting easier
Find the evidence you need for funder reports without going back through spreadsheets, transcripts, and folders. Quickly pull together relevant findings, participant perspectives, and supporting evidence when it is time to report.
5
Build knowledge across programs
Keep findings and evidence accessible beyond individual reports and projects. Compare what teams are learning across programs, locations, and time, and build on what you already know
Make A Difference
See how volunteer reflections and feedback can be brought together with program data to create a more continuous feedback loop across the organization.
Project Nanhi Kali
Explore how Project Nanhi Kali uses qualitative and quantitative data across 180,000+ girls and 3,000+ schools to assess program quality, speed up reporting, and support ongoing program learning.
Noora Health
See how Noora Health uses Dots to capture and organize on-ground experiences across countries and teams, making it easier to identify patterns, share learning, and improve program delivery.
Connect to the tools you use
01
ODK, KoboToolbox, and SurveyCTO
Bring structured and open-ended responses from your existing data collection tools into Dots. Combine quantitative responses with qualitative feedback to build a richer picture of participant experiences and program outcomes.
02
WhatsApp Chatbot
Bring participant and field feedback collected through WhatsApp into your analysis workflow. Turn conversations into structured qualitative evidence without losing the context behind them.
03
Google Sheets & MS Excel
Bring program data and open-ended responses from Google Sheets into Dots. Connect structured information with qualitative evidence to understand not just what is happening, but why.
04
Sarvam & ElevenLabs
Transcribe and translate interviews, field recordings, and other audio data across 22+ Indian and other international languages. Bring multilingual field data into Dots in a form teams can analyze and use across contexts.
05
Custom Integrations
Dots can support custom integrations based on the tools and systems your team uses.
Frequently Asked Questions
What’s the difference between AI tools like Claude or ChatGPT and Dots?
Why should MEL & program teams use Dots instead of building internal AI workflows?
How can MEL & program teams use Dots to identify what needs attention?
What types of program data can I analyze in Dots?
Can Dots combine qualitative and quantitative data?
How secure is our program and participant data?
Can I collect data directly in Dots?
Can Dots support multilingual programs?
How can stakeholders access the data and insights?
Bring your qualitative evidence into the bigger picture.
Data is most useful when it provides a complete picture that helps your team learn, adapt, and improve.