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EPISODE 6 OF MS PRESIDENT SEASON 2 ON PERIOD POVERTY

Some thoughts on research, data analysis and evidence based decision making

About three weeks ago, I was in a #SalzburgGlobalSeminar discussing “Global innovations on youth violence, safety, and justice.” Two of the sessions that I sat through were on community-based research and on data. As a firm believer and practitioner of evidence-based policy decision-making, I was challenged to think about these issues more deeply, hence these personal reflections.

Data in evidence-based decision-making is often used to measure performance, structure incentives, and allocate resources while informing public courses of action. Setting up an anti-corruption agency (i.e., allocation of resources and course of action) with the hope of deterring high-end corruption (structure incentives) because corruption is too rampant (performance) is one such example. Determining the course of action and allocation of resources is often political. On the other hand, the process of measuring performance, while political, is often hierarchical as the data is generated by international agencies, bureaus of statistics, and researchers. Even when the research process is done in consultation with community members, the ultimate interpretation and presentation of the analysis are often from the researchers’ cultural nuances, definitions, biases, or vested interests.

 

Bribery, for example, is the primary consideration when designing the bribery index and, in turn, is a primary determinant of the corruption rankings among countries in the world. In cultural contexts where it is informally acceptable to give money or gifts for a public service rendered, as a way of expressing gratitude, bribery as a measure of corruption becomes very problematic. It means that, as long as corruption is measured using the bribery index,  some countries will never exonerate themselves from being the most corrupt countries in the world because their way of life integrates “transfer of value in the context of an official action.” 

 

Selecting an indicator or a set of indicators to measure performance also means that many factors that perhaps make more sense to a community or tell the whole story as experienced by community members are also left out. Corruption seen through the prism of bribery or another definition like nepotistic appointments to public positions may not be a significant or a relevant measure of corruption in a communal culture like the Somalis in my country who select leaders based on clans. However, personal experiences of denial of essential services like access to health facilities or misuse of resources that cause harm to community members while unfairly enriching others may be a more relevant, tangible, and relatable definition of corruption to them. Therefore, in measuring corruption, the latter indicators should matter more than the former indicators to validate these lived experiences and contexts, whether I agree with them or not from a research point of view. 

 

It is therefore important to remind ourselves that data is never neutral. Data can create illusions of rationality, yet beneath it, mask underlying fundamental differences of interpretation, purpose, and power among the various stakeholders situated on both sides of the spectrum, such as researchers (with an academic outlook) and communities (with lived experiences). Scarcity of resources is at the root cause of relying on other people’s data, hence depending on their interpretation of what is or is not important. This means that the real experts – those with lived experiences and whose perspectives should matter most in giving meaning to the data or indicators to measures performance are often ignored.

 

As a researcher, I must be committed to presenting the community’s outlook with honesty and respect. Taking human-centered approaches to data and research that: truly regards multiple community definitions and perspective; that seeks to have a collaborative as opposed to an extractive data relationships; that considers lived experiences as equally important as academic perspectives; that is empathetic to community welfare above researcher interests, and; that promotes social trust and community realities, must be embedded within research and data analysis if it is to lead to mutually benefiting and just evidence-based decision-making processes.

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Dr. Katindi Sivi - Complexities surrounding youth involvement in violence

Freedom in foresight – the reason why children make the best futurists!

I am in the business of futuring, and I am glad that in my part of the world, it is catching on and with a lot of excitement. One of the greatest difficulties I have encountered as I facilitate these processes is what it entails for people or organizations to fully utilize the available intelligence - especially the non-mainstream, seemingly obscure gut feeling or ostensibly disparate information – to effectively increase insights. 

The inability to do so is orchestrated by the fact that all human beings have a particular worldview they use to filter things, including information. The tendency is to reject whatever is not congruent with those filters. These relatively narrow mental constructs are based on past and the conventional lenses they use to view the world. However, one other crucial reason is that they come to these processes with self-serving biases that incline them to gather and process information to advance their perceived self-interest or support their pre-existing views. To be politically correct, they seldom voice all their standpoints, cynicisms, fears, or assumptions, without which the process short-circuits the creation of robust futures that enable strategic decision making.

To guard against these blind spots, it is imperative to consider:

1. Joining these processes from a place of complete honesty, awareness, reflection, and the openness to learn just like children view the world with wide-open eyes and a sense of wonder and curiosity
2. More honest analyses of the data we collect, including the emerging weak signals we often dismiss to re-conceptualize our ideas and get multiple views, just like children are open to having more than 'the right answer' to a question 
3. The effective use of human intelligence tacked away in gut feelings just like children bluntly say what they think, however illogical
4. Inviting those people we rarely interact with, the ones who are not like us – the authentic dissenters or devils advocates - with the intention to value those outside views just like children are un-inhibited and open to playing with everyone
5. Highly abstracting sensitive situations and role-playing them to literary 'put oneself in another's shoes' and increasing empathy while creating a much more open interaction, just as children often experiment with anything in their context to imagine different fantasies, aka possibilities!