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.

Importance of using digital data gathering

The main reasons why organizations are resorting to digital data collection are as below:

  1. Data Quality

Perhaps the most important reason why organizations should consider DDG is for data quality purposes. Digital data collection ensures strict data collection measures are enforced, an important feature to control data quality. Several restrictions can be enforced including:

  1. Skip patterns

Several times in a survey, a researcher has questions with skip patterns. For example, for a WASH questionnaire, you may only want to ask a respondent if their toilet is internally lockable, if their response to a previous question on whether they have a toilet is “yes”. These types of skip patterns can only be enforced on digital surveys, with a conditional question only appearing based on the response to a previous question. An example of a skip pattern question is as below

Do you own Land? [ ] Yes / [ ] No

If Yes, to question above, how many acres [Number Entry_____]

For paper based questionnaires, proper recording of such skip pattern kinds of questions are entirely reliant on the enumerator skills, knowledge of the questionnaire and keenness, leaving plenty of room for error.

  1. Entry limits

This kind of restriction is usually vital especially for numeric types of questions. For digital surveys, it is possible to restrict entries, by having minimum and maximum values. For example, when taking the ages of children in a household survey, say for Children between 0 and 5 months, one can restrict age entry to a maximum of 5. Any entry above 5 is therefore rejected.

  1. Type questions (e.g. Numeric vs Text)

Questions are of different types. There are numeric entries, alpha-numeric entries, and date entries, among other types. Digital data gathering ensures that entries are limited to their type, so you don’t have a text response for a numeric question, for example. The researcher is also able to control such things as date formats, such as DD/MM/YYYY or MM/DD/YYYY or DD/MM/YY, depending on requirements or preferences

  1. Optional vs mandatory questions

For digital data collection, a researcher has control over whether a question is mandatory or optional. In this case, he/she does not miss responses for questions that are considered essential for the survey.

In short, using technology for data collection helps to eliminate data collection and entry related errors as much as possible. This means that the data available for analysis is usually pretty clean and ready for analysis.

  1. Time

Using DDG can be quite time saving to a project. Time for data entry is usually cut out completely, which depending on the number of surveys, can be quite time consuming. If a project constantly experiences time constraints, especially for its monitoring and evaluation activities, then digital data gathering may be the way to go. Even for organizations that do not collect large scale data, in the short term, it might not appear as though a lot of time is spent on data entry. However, over a longer period, data entry does consume a lot of time. One day of data entry a month translates into twelve days in a year. For a five year development program, that would translate into 60 days (two months) of data entry.

  1. Short term and Long term costs

In close association with time saving, digital data gathering saves on data entry costs. Data entry costs are a short term cost that an organization is able to save on for adopting digital data collection. Even when there are no direct costs associated with data entry, plenty of personnel time is saved when using DDG in the long run. Longer term costs include the costs of printing questionnaires, purchasing stationary for data entry among others. Printing and stationary costs, for example, constitute a large proportion of most M&E budgets

  1. Data Storage and Retrieval

Yet another advantage of using DDG for M&E is data storage and retrieval. Data that is collected digitally is free from regular damage, as opposed to paper-based surveys which can be easily destroyed by water, rain, fires among others. Data is usually freely accessible for download since it is stored in the clouds. Paper-based surveys also consume plenty of storage space, which may not be available in the modern office. Costs associated with storage of numerous files may be prohibitive as well.

  1. Environmental conservation Issues

In an age where environmental issues are a sentimental topic, saving the environment is yet another plus for the use of DDG for data collection. Needless to say, paper comes from trees, and the lesser and lesser paper we use, the better for the environment.

  1. Geo-tagging of the unit of sampling (capturing GPS locations)

Recent developments in monitoring and evaluation have enhanced the need for geo-tagging the sampling units, be it individual or household locations. Other important elements that can be geo-tagged include physical infrastructure that may have an impact on a project. For example, hospitals for a health project, schools for an education project and VCTs for a HIV/AIDs project. Digital data gathering platforms allow for collection of GPS coordinates of the sampling units, ensuring that it is possible to link attribute data to their corresponding spatial data.

Limitations for organizational adoption of Digital data Gathering

Of course, like any other good thing, digital data gathering has its own set of challenges. These are discussed below:

  1. Prohibitive initial costs

Although DDG saves a lot in terms of costs as mentioned earlier, its prohibitive set up costs may be viewed by many as a reason for shelving any adoption plans. Initial costs will include the cost of purchasing both hardware and software (although several open-source software options exist. These will be discussed in my next article). Training costs are usually that usually have to be incurred immediately following adoption. The brighter side to this is that these are just initial costs and are mostly only incurred at startup.

  1. Data Security breaches

As is the case with most cloud computing options, hosting data on the cloud may expose the data to security breaches. Hackers are a real threat and as such, data needs to be backed up on hard drives and other localized storage. All in all, there are numerous anti-hacking measures out there which can be used in case an organization is dealing with very sensitive data.

  1. Staff capacity

Staff capacity, in terms of their ability to implement or even use DDG techniques is yet another hindrance to the adoption of technology for data collection. Knowledge of building surveys on the digital platforms is as vital, if not more, as knowledge of using them. Where this capacity is absent, there may be need to hire capable staff or outsource the function.

  1. IT Support

IT support is critical for troubleshooting issues that may arise as a result of using technology for data collection. However, since most organizations already have a functioning IT department, this might not be a huge hindrance. However, for those organizations without one, or those whose capacity is already stretched, this may be a hindrance. In the end, consideration needs to be made on how IT support will be provided.



Titus Batson is a Programmer, Humanitarian innovation technologist, internet entrepreneur, Web app developer, consultant and Blogger

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