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M&E Systems and Data Tools

The Firdale Consulting team is experienced in:

Facilitating interactive workshops (face-to-face or on Zoom) to develop a Theory of Change and Logic Framework for your programme.

Compiling lists of SMART (Specific, Measurable, Affordable, Relevant and Time-bound) indicators linked to the Theory of Change to enable you to track change.

Theory of Change Workshop.jpg
Code to automate cleaning

Choosing the right M&E technology to suit your organisations' programme, budget and skillset.

Cleaning historical data and integrating it into new systems (using R, Python  or Stata code).

Writing code in R, Python or Stata to automate routine data cleaning to save your organisation time and reduce the risk of errors.

Developing surveys that provide data on your indicators and programming these surveys onto the relevant software.


Advising your team on best-practise for secure data storage.

Designing M&E reports with eye-catching visuals that are easy to understand so that your team, funders and external stakeholders can understand your programme's impact.

Compiling M&E Reports

Automating report generation using R, Python or Stata code to save your organisation time and reduce turnaround time for reports.


Designing customised online dashboards that empower you to analyse your own data in real-time.


Building online dashboards using R or Python code that integrate with your data collection and storage.

Evaluations, Reports and Research

The Firdale Consulting team is experienced in:

Conducting large-scale evaluations of multi-country, multi-sector programmes that span multiple years and provide a professional independent analysis.

Selecting the appropriate evaluation approach for a given programme such that the evaluation provides relevant insight and tangible recommendations.

Collecting qualitative and quantitative data through surveys, interviews or focus groups.

Firdale Consulting Analytics

Analysing data using quantitative methods including selecting the appropriate test for statistical significance, regression analysis, difference in difference model, quasi-experimental models such as propensity score matching etc.

Analysing data using qualitative methods including deductive coding, categorical coding, thematic analysis, applying reflexive techniques, researcher triangulation etc.

Conducting comparative cost-analysis to generate insight on the programme cost structure compared to alternative models.

Compiling and writing donor reports that provide regular updates on programme processes, outcomes and impact.

Compiling and writing comprehensive evaluation reports which could include impact and/or process assessments and clear recommendations that can be implemented.

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