Innovation pushes the bounds of human capability. Technology such as medical devices, communication software and applications of new methods and new techniques help us to understand the world around us. Bright and shiny is what the world of research often seems to want. In recent years, field research in Southeast Asia has seen a steady integration of innovation. More than ever before new software tools and hardware kits have been made available to reshape how data is gathered and used. But with every new leap forward in innovation come striking gaps in who uses it and to what ends.

Scattered throughout internet development blogs, academia, and tweets are discussions on the equity of innovation in field research. Equity of innovations can be distilled into three categories: simply having knowledge of the innovation’s existence (locked behind pay-to-access schemes), gaining access to innovation (such as cost of tech, language availability, or skills to use it), and ease of use. A fourth, and often overlooked question, is whether the innovation is appropriate.

The appropriateness of innovation is not just about a single measure of benefit – for example, does the innovation expand how data is collected? Or, does the innovation grant access to more data but without added tools for interpretation? For instance, Thailand’s “innovative” method of displaying real time air quality data in raw figures assumes that raw data is useful, while the end users may not understand well what a certain number means for their health. A good idea – implemented poorly.

Narrowly defining the measures of benefit can lead to any innovation being accepted as appropriate. Instead, appropriateness of a new research tool or method should be a collective measure of benefit to the researchers and the target audience including accessibility and ease of use.

In other words, is the over-all use of the innovation beneficial?

In many situations, the answer is yes. Innovation, after all, is spurred forward by the need to overcome some type of challenge – say a community’s innovative use of geographic information systems (GIS) to map water/food access and deduce geopolitical or socioeconomic obstacles to the resource. These innovations have been used throughout urban spaces in the Americas and countries throughout Africa (another article here). Another example is the heavy reliance on a new, or often new-to-user, software or hardware device, say, for instance the Airbeam technology. Airbeam has been employed by activists, communities, and individuals as a way to monitor air quality and challenge government policies around the globe. In instances like these, yes innovation and its use may be appropriate.

However, in recent discussions and indeed in past experiences, I have seen and heard of cases where the appropriateness of an innovation being pushed into the field is second to the newness of it. In some instances, donors become so driven by a new innovation that organizations must shift to incorporate the innovation or risk losing donor support. In the past this has happened with the heavy reliance on GIS that saw donors suddenly shift to projects that produced GIS data regardless of whether GIS data was even appropriate or necessary for the project. The push for GIS and other complex data has also forced organizations to try to gather data without the proper capacity and has led to outsourcing those jobs almost exclusively to consultants, drawing resources away from the local organization and missing an opportunity to build capacity and produce locally-owned research.

Is it enough to simply find the newest tools and hand them out like candy?

Pressure to gather specific kinds of complex data is not on its own an entirely bad thing. In fact, in the case of GIS this innovation has led to increased data availability in hard-to-research regions of the world. However, this has also lead to exclusivity in access to the technological innovation itself.  GIS is still often exclusively used by well-funded international organizations and western-educated academics, furthering the divide between local and external specialists. While local organizations can access GIS data about the areas in which they work, and may work in partnership with a larger organization that can collect the data, they are unable to collect and interpret the data on their own. This leads to smaller organizations being left out of funding opportunities based on their access to technology that may not even be necessary for their purposes.

Equally problematic is when organizations or researchers become fixated on a single tool despite the impracticality of implementing the tool in projects. An example of this is the often-required gathering of statistical data that is perceived to be authoritative when engaging with donors, INGOs, and government agencies. This in turn facilitates the push to use sophisticated statistical analysis programs like SPSS to analyses the data (despite Excels’ sufficiency for most NGO purposes). Having studied SPSS in graduate school and used it occasionally in a professional setting, I have found it to be powerful but not the most practical in some situations. For one, it often requires external experts unfamiliar with the data sets or cultural context to come in and manipulate the data. This adds an ever-increasing barrier between local users and the technology. Additionally, many experts spend years learning the tools and then many more practicing it while the transfer of knowledge to local groups is expected to happen in a few days of training.

Innovative technologies are an important part of field research and equally important is giving access and skills to local groups. But, is it enough to simply find the newest tools and hand them out like candy? We must continually ask ourselves and the groups we work with the ever-important questions – is this innovation appropriate for those expected to use it? Will short trainings in the technology be enough for the users to benefit from it? Will the innovation simply be a one-off that only benefits the donors or external researcher? If we can’t give good answers to these questions, perhaps the innovation needs a little more innovating.