Impact assessment

Testing the strength of evidence (TestE)


Our evaluations shall be real-time, the design of the evaluation is done as the programme is designed, baseline data collected prior to implementation and then we benefit from all opportunities for evaluation, while implementing. During the evaluation design we agree on  how to collect, compile and analyse monitoring data, when and by whom. Lessons learned are  compiled and addressed real-time.

We identify the study sample and the control, prior to implementing the programme, we reflect over sample size and external validity to meet the requirements of the selected statistical method, and benefit from simple randomized evaluation, whenever possible. We base the evaluation topics on Outcome Challenges, the quantification on Progress Markers and then measure against Baseline, and if randomization against Control.

Micro data Survey guide

Study sample

Set sample size  & who to include.
External validity: i) Ensure that the person asked is representative for the group, and that we would expect the same answer if we asked someone else, ii) reflect over if the results of our randomized evaluations is generalizable to other contexts.


Simple randomized evaluations : Randomized evaluations are a type of impact evaluation that use a specific methodology for creating a comparison group—in particular, the methodology of random assignment. Thus, impact evaluations that are scientifically sound usually compares outcomes of those (individuals, communities, etc.) who participated in the programme against those who did not participate. They generate a statistically identical comparison group, and therefore produce the most accurate (unbiased) results. Moreover, randomized evaluations produce results that are very easy to explain.
Conducting a randomized evaluation may change the selection process, but not the number of participants served. Randomization may be a fairer way of choosing who will have access to the programme than other selection methods e.g. first-come, first-served.
Without denying access: It can be possible to conduct a randomized evaluation without denying access to the intervention. For example, we could randomly select people to receive encouragement to enrol without denying any interested participants access to the intervention.
Pilot-phase randomization method: An ideal time to conduct a randomized evaluation is during the pilot phase of a programme or before scaling up. During the pilot phase, the effects of a programme on a particular population are unknown. The programme itself may be new or it may be an established programme that is targeting a new population. In both cases programme heads and policymakers may wish to better understand the impact of a programme and how the programme design might be improved. Almost by definition, the pilot programme will reach only a portion of the target population, making it possible to conduct a randomized evaluation. After the pilot phase, if the programme is shown to generate impact, the aim must be that the programme is replicated or scaled up to reach the remaining target population.
What is the appropriate level or unit of randomization?  What is the appropriate method of randomization?  How would we implement the randomization? Sample size & Who

Survey questions

Use semi-structured questions.
Quantitative: Outcome Challenges, Progress Markers & Baseline, Sustainable economy, Activites & Milestones.
Qualitative: Strategy for Change, Cost- benefit, Team operations, as it needs driven, Equal partnership, Unexpected effects, Other survey questions.

Survey team

Assign a data collection team and ensure they have access to the tools required; transportation, camera, recorder, notebook. Ensure they are comfortable with the assignment.
The team includes; interviewers, photographers, vdeo camera staff,  staff recording the interviews, person taking notes in a dedicated notebook about everything that happens.

Written survey manual

Develop written survey manual, including;  number of interactions, who to interact with and in which setting, a set of semi-structured interview questions. Describe how, where, when and by whom.

On-site interactions

Equipment: Apps on cell phones, or recorder, camera, video camera. Notebooks and pens for all team members. Written copies of the Semi-structured interview guide.
Interaction with the respondents: With the support of a semi-structured interview guide, recording devices, cameras, and other resources the survey team team interact with the respondents. Interview after interview, community after community, the exercise shall progress smoothly and a lot of interesting evidence – videos, photos, documents, recordings, etc. – shall be gathered. At the end of a data collection exercise, it will be obvious that a data collection team has learned several lessons. This is one of the reasons why HR&S programmes have to scale-up slowly, as we have to ensure water-tight communication with our partners and customers. We are continuously collecting data as we work on-site and surveys are carried out.

Compile monitoring data

Compile survey related infromation from audited financial reports, signed programme reports, implemented Output & achieved Outcome, testimonies,  and microdata survey results.
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Quantitative analysis – Statistical method

Basic statistics: The basic assumption to be made is that a set of data, obtained under the same conditions, has a normal or Gaussian distribution. The primary parameters used are the mean (or average) and the standard deviation, and the main tools F-test for precision, t-Tests for bias, Linear correlation and regression and Analysis of variance (ANOVA).
Simple comparison: With randomized evaluations, the simplest method is to measure the average outcome of the targeted group and compare it to the average outcome of the control group. The difference represents the programme’s impact. To determine whether this impact is statistically significant, one can test the equality of means, using a simple t-test. One of the many benefits of randomized evaluations is that the impact can be measured without advanced statistical techniques.
Propagation of errors: The final result of a Programme is calculated from several activities (outputs) performed during the implementation and the total error in a programme is an adding-up of the sub-errors made in the various steps. The bias and precision of the whole Programme are usually relevant parameters.

Qualitative assessment – probability methods

With qualitative assessments, and contrary to statistical methods, the quality of the evidence is not judged by the sample size (the number of observations) but rather the probability of observing certain pieces of evidence. Qualitative impact evaluation includes assessing the contribution made by a particular intervention in achieving one or more outcomes, commonly referred to as a ‘contribution claim’. TestE benefit from process tracing to assess our Strategy for Change and from Contribution tracing to examine the contribution by external stakeholders . We also address Team operations, Cost- benefit, Needs driven, Equal partnership and Unexpected effects.

Testing the Strength of Evidence
Personal stories: Personal stories are not easily classified, categorised, calculated or analysed. More recently, software programmes are available to facilitate categorisation of story fragments, which allows for analysis of patterns that can lead to quantitative information.
Strategy for Change:  A reasonable contribution causal claim can be made if: there is a reasoned Strategy for Change for the intervention, in the sense that the key assumptions behind why the intervention is expected to work, make sense, are plausible, may be supported by evidence and/or existing research, and are agreed upon by at least some of the key stakeholders. The activities of the intervention were implemented as set out in the Strategy for Change. The Strategy for Change (or key elements thereof) is supported by and confirmed by evidence of observed results and underlying assumptions, thus, the chain of expected results occurred.  The Strategy for change has not been disproved. Other influencing factors have been assessed and either shown not to have made a significant contribution or their relative role in contributing to the desired result has been recognized.

Macro data Survey guide

Compile & analyse monitoring data

Compile survey related infromation from
broad-trend data and literature reviews.
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Compile results

Impact reports are shared with all partners and uploaded on our web-site. The Lessons learned are compiled and addressed real-time.

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Definitions by HR&S

Ambition The need and ambitions as expressed by the local stakeholder, the Target partner.
Outcome challenge Challenges hindering the Target partner to reach her ambitions, as expressed by the Target Partner.
Activity Activities arranged by the Programme management Partner, addressing the Outcome challenges identified by the TP and that generates a specific Output.
Expected Output The Expected Outputs are quantified results from the Activities. The PP are in control over Outputs. It can for example be the number of active participants in a certain number of workshops that lasted a certain period of time.
Input Resources required to arrange the Activities.
Expected Outcome Actions taken by the Target partners as a results of the Activities. The programme managers do not have control.
Progress markers Measurable indicators of progress or non-progress. They are linked to the expected Outcome and are categorised at Level 1, 2 and 3.

Expected Impact We define Expected Impact as Expected Outcomes that have become sustainable over time and does not require backup from the Programme to be sustainable. The expected impact is quantitatively measureable as a result of our progress markers and we are accountable for the Expected Impact. The Expected impact is measured at the time of closing the programme.  We may in addition aim to measure if our impact is still sustainable some period after we have closed the programme, maybe one, two, five and event ten years after.
Possible Impact The possible Impact is often a wide and qualitative statement, something that is desired and that may or may not happen as a consequence of our interaction, and often long after we have closed the programme.  We are not accountable for the possible Impact, and we can also not claim it as goal that we strategically work towards achieving. If it actually happens, then we do often not have evidence for to which extent it was actually cause as a result of our programme.

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