DIGITAL DATA GATHERING FOR MONITORING AND EVALUATION

The use of technology for data collection has gained a lot of interest from Monitoring and Evaluation professionals over the past decade. Few would argue the advantages of using digital data gathering (DDG) for M&E. However, there exist several constraints that may still play a role in the lack of its adoption. Here, the writer discusses what DDG is and the advantages of using technology for data collection. The writer also discusses some of the limitations that hinder the adoption of technology for data collection.

What is Digital Data Gathering?

Digital data gathering (or DDG) is a process of collecting data electronically through the use of existing technology such as personal digital assistants (PDAs or smart phones), tablets and net-books for data collection. In other words, it is the use of digital technology for collecting data or information from respondents.

TYPES OF MONITORING IN MONITORING AND EVALUATION (M&E)

Monitoring is the systematic and routine collection of data during project implementation for the purpose of establishing whether an intervention is moving towards the set objectives or project goals. In this case, data is collected throughout the life cycle of the project. The data collection tools are usually embedded into the project activities in order to ensure that the process is seamless. There are several types of monitoring in M&E and they include process monitoring, technical monitoring, assumption monitoring, financial monitoring and impact monitoring.

DATA VISUALIZATION

One of the constant features of M&E work is the representation of data. M&E personnel find themselves in positions where they need to or have to represent data to different audiences such as donors, local level stakeholders, and organizational hierarchy among others. Not planning how to represent or visualize data means that M&E personnel find themselves in a situation where the method they choose is inappropriate for the audience, or generally becomes misleading.

DATA QUALITY

Most organizations/ projects are faced with the data quality dilemma. Analysis of project data may leave the relevant personnel with reservations regarding the authenticity of the data, the enumerators or even the project impacts. M&E and other management staff may even contemplate the possibility of re-doing the process for the purposes of validation. Here, we take a look at what data quality is, data quality dimensions, causes of poor data and; eventually, ways of improving data quality.

DIFFERENCE BETWEEN INPUTS, ACTIVITIES, OUTPUTs, OUTCOMES AND IMPACT

Some of the most confused terminologies within the Research, Monitoring and Evaluation field are the words, “input”, “activities”, “outputs”,” outcomes” and “impact”. Within the R, M&E practice, it is important to distinguish between these terms. Understanding these terminologies not only ensures that appropriate indicators are identified, but also that they are effectively measured. Here, we will use specific project cases to demonstrate the difference between these terms.

FINAL REPORT FORMAT

An end of project report should follow the guidelines outlined below. It should include a title page, a list of abbreviations, acknowledgements, an executive summary, a table of contents, an introduction, a methodology section, a results section; conclusions, lessons learnt and recommendations section and; an annex section. The contents for each section are outlined below. 

TYPES OF EVALUATION

The major distinguishing characteristic of evaluation, unlike monitoring, is that it is only conducted periodically at particular stages of the project. As such, there are five main types of evaluation. The different evaluation types vary mainly depending on the stage of the project.  While classification could be based on different criteria such as the methodology adopted, here we look at the classification based on the time. These types of evaluation are formative evaluation, mid-term evaluation, summative evaluation, ex-post evaluation and meta- evaluation.

SAMPLE M&E WORK PLAN

An M&E Work plan is integral for any M&E personnel. Not only does the work plan enable one to organize himself or herself well, it also ensures that a timeline of activities is established well before hand. The M&E work plan, if designed in an appropriate way, guides the M&E activities, with objectively targeted timelines. Below is a sample table of an M&E work plan.

BASELINE STUDIES/ SURVEYS

Baseline surveys are an important part of any M&E process.  This discussion, takes a look at the definition of a baseline study, its importance, when to conduct one and alternatives when there is no baseline. It also includes other considerations to make when conducting a baseline study.

What is a baseline study?

A baseline study simply put is a study that is done at the beginning of a project to establish the current status of a population before a project is rolled out. The Food and Agricultural Organization defines a baseline study as:

SELECTING PROJECT INDICATORS

In M&E planning, one of the things that managers have to work out are a set of indicators that will be used to measure outputs against program goals. Understandably, questions often arise regarding what indicators are, their importance and what to consider when choosing them. Here, we will take a look at examples of indicators, their types, their importance and eventually, how to select appropriate indicators.

What is an indicator?

An indicator is a variable that is normally used as a benchmark for measuring program or project outputs. It is “that thing” that shows that an undertaking has had the desired impact. It is on the basis of indicators that evidence can be built on the impact of any undertaking. Most often, indicators are quantitative in nature, however, in some few cases, they are qualitative.