Overview
Monitoring is the routine tracking of implementation and results; evaluation is a periodic, more in-depth assessment of whether the intervention is working, for whom and why. Both depend on a clear logic of how the program is expected to create change. When that logic is vague, organizations end up counting outputs, such as people trained, without evidence on outcomes, such as changed practice.
We help you set out your results chain or theory of change, translate it into a logical framework (logframe) or results framework, and define indicators with clear definitions, data sources, frequency, baselines and targets. We then design practical data collection tools and an M&E plan that assigns responsibilities and fits your budget.
For evaluations, we help you frame evaluation questions around the OECD DAC criteria (relevance, coherence, effectiveness, efficiency, impact and sustainability), choose a proportionate design, and prepare terms of reference, inception reports or evaluation matrices. The criteria are a starting point, applied thoughtfully to your context rather than mechanically.
Who it’s for and the problems it solves
This is for you if you are…
- NGOs and nonprofits needing an M&E framework for a grant application or new program
- Universities and institutions evaluating teaching, capacity-building or outreach initiatives
- Project managers asked by a funder to strengthen their logframe or indicators
- Evaluation commissioners preparing terms of reference for an external evaluation
- Graduate students in development, public health or education learning M&E methods, through coaching
Common problems we help with
- Your indicators measure activities and outputs but not outcomes
- The logframe has gaps between levels, or assumptions nobody has checked
- Indicators are not SMART and have no baselines or data sources
- Your funder uses a specific results framework template you have not used before
- You need to plan an evaluation but are unsure which design is proportionate to your budget
- Your team collects lots of data but none of it is used for decisions
What’s included — and what isn’t
Included
- Theory of change or results chain development through a workshop or document review
- Logical framework: goal, outcomes, outputs, activities, indicators, means of verification and assumptions
- Indicator design: definitions, disaggregation (for example by gender, age or disability), baselines, targets and data sources
- Selection of standard indicators from sector frameworks where they fit, and custom indicators where they do not
- M&E plan: data collection methods, frequency, responsibilities, quality assurance, reporting and learning processes
- Data collection tools: surveys, observation checklists, interview guides and mobile forms
- Baseline study design and support
- Evaluation design: evaluation questions mapped to OECD DAC criteria, evaluation matrix, methods and sampling
- Terms of reference for external evaluators, or inception report support for evaluation teams
- Dashboards or reporting templates for tracking indicators over time
Not included
- Reporting results that were not measured, or adjusting data to meet targets
- Acting as the independent evaluator of a program we helped design, where independence is required
- Guaranteeing that a funder will approve your framework or proposal
- Writing graded M&E assignments for students to submit as their own
What you receive
- Theory of change
- A diagram and narrative showing pathways from activities to long-term change, with explicit assumptions and external factors.
- Logframe or results framework
- A complete matrix in your funder's format, with coherent levels, indicators, means of verification and assumptions.
- Indicator reference sheets
- One sheet per indicator with definition, calculation, disaggregation, data source, frequency, responsibility, baseline and target.
- M&E plan
- A practical plan covering data collection, quality checks, reporting, review meetings, learning and budget.
- Tools and templates
- Data collection instruments, including KoboToolbox or other mobile forms, and a reporting template or dashboard.
- Evaluation design or terms of reference
- Evaluation questions, criteria, matrix, methods and timeline, ready for commissioning or implementation.
How it works
Understand the program
We review your proposal, program documents and funder requirements, and talk with key staff about how change is expected to happen.
Map the logic
We develop or refine the theory of change and results chain with your team, often in a facilitated online workshop.
Build the framework
We draft the logframe and indicators, testing each for measurability and usefulness.
Plan data collection
We design tools and the M&E plan, matching methods and frequency to your capacity and budget.
Review and handover
You review with your team and funder; we revise and provide a short orientation for staff who will run the system.
Frameworks and evaluation approaches
- Theory of change
- Mapping causal pathways and assumptions, used both for planning and as the basis for theory-based evaluation.
- Logical framework approach
- The four-level matrix still required by many funders, with a vertical logic of results and horizontal logic of indicators and verification.
- SMART indicators
- Specific, measurable, achievable, relevant and time-bound, with attention to validity and data availability, not just format.
- OECD DAC evaluation criteria
- Relevance, coherence, effectiveness, efficiency, impact and sustainability, as revised in 2019 and explained in the OECD's guidance on applying the criteria thoughtfully.
- Evaluation designs
- From pre-post and comparison group designs to contribution analysis, outcome harvesting and most significant change, chosen according to the questions and resources.
- Mixed methods data collection
- Surveys, administrative data, interviews, focus groups and observation, combined to explain both whether and why results occur.
From outputs to outcomes
The most common weakness in M&E frameworks is a jump from activities to impact with no measurable steps between. Training 200 teachers is an output. Teachers using the new method in class is an intermediate outcome. Improved student learning is a longer-term outcome. Each level needs its own indicators and each link needs a stated assumption that can be checked.
We work through the chain with you, asking 'what has to happen next for this to lead to that?' until each step is plausible and measurable. This also strengthens grant applications, where reviewers look for a coherent logframe or theory of change.
Indicators your team can actually collect
An indicator is only useful if someone can collect it reliably at the planned frequency and cost. We test each indicator against practical questions before it goes into the framework.
- Is there an unambiguous definition and calculation, including numerator and denominator?
- What is the data source, and does it exist now or must it be created?
- Who collects it, how often, and with what tool?
- Can it be disaggregated by sex, age, disability or location as your funder requires?
- Is there a baseline, or a plan to establish one before activities start?
- Will anyone use the result to make a decision?
Using the OECD DAC criteria thoughtfully
The six criteria provide a shared vocabulary for evaluation questions, and many funders expect them. The OECD itself encourages applying them flexibly: not every evaluation needs to address all six equally, and the questions should reflect what stakeholders need to know. We help you prioritize the criteria and write questions that are answerable with your data and budget, then link each to methods and sources in an evaluation matrix.
Proportionate evaluation design
Not every program needs a randomized trial. Small or complex programs may be better served by theory-based designs such as contribution analysis, or by participatory approaches such as outcome harvesting. Larger programs with clear treatment and comparison groups may support quasi-experimental designs. We explain the trade-offs between rigor, cost, timing and ethics so you can choose a design you can defend.
What the work can look like
Illustrative example — fictional data
An M&E framework for a youth digital skills program
A fictional NGO is applying for a three-year grant to deliver digital skills training to 1,200 young people in two cities, aiming to improve employment. The funder requires a logframe, indicators with baselines and an evaluation plan.
Results chain
The workshop added an intermediate outcome that was missing, 'participants apply for jobs or freelance work using new skills', and an assumption about local employer demand, which led to a new employer engagement activity.
Indicators
Fourteen indicators were drafted and then reduced to nine. For example, 'improved employability' became 'percentage of graduates in paid work or self-employment six months after completion, disaggregated by sex and disability status', measured by a follow-up phone survey.
Evaluation plan
A mid-term review focused on relevance and effectiveness, and a final evaluation added efficiency and sustainability, using a comparison with waitlisted applicants and interviews with employers.
Illustrative, invented scenario and figures. Real frameworks depend on your program, funder and context.
What you’ll need to provide
- Program proposal, concept note or strategy document
- Funder guidelines, results framework templates and any mandatory indicators
- Information on your team's M&E capacity, data systems and budget
- Existing data, baseline studies or previous evaluations
- Availability of staff and, if appropriate, stakeholders for a theory of change workshop
You don’t need everything ready to ask for a quote — tell us what you have and we’ll say what’s missing.
What affects price and turnaround
Price depends on
- Size and complexity of the program, including number of outcomes, sites and partners
- Whether a facilitated theory of change workshop is included
- Number of indicators and data collection tools to develop
- Funder template requirements and review rounds
- Whether evaluation design, terms of reference or baseline support is needed
Turnaround depends on
- Grant deadlines or program start dates
- Availability of staff and stakeholders for workshops and review
- Speed of funder feedback on draft frameworks
Every project is quoted individually. How we price our work.
Questions people ask before starting
What is the difference between a logframe and a theory of change?
A theory of change describes how and why change is expected to happen, including pathways and assumptions, often as a diagram. A logframe is a structured matrix summarizing the results, indicators, verification and assumptions. Many programs use both: the theory of change for thinking, the logframe for management and reporting.
Do we have to use the OECD DAC criteria?
Only if your funder or evaluation policy requires them, although many do. Even when optional, they help structure evaluation questions. We help you use them selectively and appropriately.
Can you be our external evaluator?
If we designed your framework, we would not normally serve as the independent evaluator where independence is required. We can help you write the terms of reference and select evaluators.
We have no baseline. Is it too late?
Not necessarily. Options include a rapid baseline at the start of activities, using existing administrative or secondary data, or reconstructing a baseline through recall questions, each with limitations we explain.
Can you set up our data collection on mobile phones?
Yes. We can design forms in KoboToolbox or similar tools, with logic and validation, through our online survey setup service.
Is this help available for students?
Students can use coaching on M&E concepts and feedback on their own frameworks. Assessed work must be your own.