Data & The False Promise of Simplicity
Humanitarian actors are historically and notoriously overburdened. While some recognise that the collection and analysis of data can be useful, they still want the final analysis to be distilled into a single number with a “stoplight” rating: red, amber, green.
Unfortunately, this is not what data promises. First, it moves us toward empiricism and away from the best intentioned but evidence-dry theory-base for action. Second, it gives us the ability to track what’s working and what’s not at a micro-level and to adjust in near “real-time” to ensure the highest levels of efficiency and effectiveness. Data gives us the tools to manage resources in complex contexts so that we can save more lives. That is simple. Using and interpreting the data is not.
The data revolution is premised upon a recognition that historical models of expertise are flawed. We can no longer expect any one expert, no matter how prolific and profound, to give an adequate analysis of the problems we face, day in and day out, in the most complicated operating environments in the world. Somalia, Syria, Afghanistan, South Sudan, DRC. Simply the political economies and clan dynamics that exist in countries like these are enough to make any one mere mortal's head spin. Academics, the writers of heavy tomes, are important. They can provide theories that may guide our analysis or explain what we do given a strong empirical base. They cannot give us insights into what’s working, how to become more efficient and effective, how to maximise adaptive programming, and how to ensure continuous improvement. They are not performance oriented.
Data has risen from the failure of the lionised expert to provide indisputable trends that new type of experts can interrogate for the narratives that underpin what’s really going on. The data provides a glimpse into the patterns that exist in the chaos. Data drives operations.
This is the promise of data. It enables us to get a much better understanding of the complexity that influences the contexts of the people we serve and of the impact of the interventions we make on their behalf. Simple it is not.
This is not new. Private sector enterprises invest in huge data stores to decipher a range of trends, be they related to consumer behaviours, supply chains, or raw material costs. Big data is not something that emerged from international development and humanitarian action. It came out of companies like Google and Palantir who could corral mass streams of data into rational analytical frameworks. We are, as so often, catching up. It is also not confined to ranty blogs like this one. The United Nations held a World Data Forum in January 2017 (http://undataforum.org) where an emerging group of donors led by the U.K.’s Department for International Development and the World Bank is calling for greater data disaggregation — a breakdown of figures based on characteristics such as sex, age, disability status, and geography. DFID has set out a plan to do this. https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/582315/Data-disaggregation-action-plan-Jan-2017.pdf
Yet, we still get prodded and cajoled into using the data to aggregate up toward one all-defining number. This is as bad as the pompous professor from lore whose words we were to take without a glance of curiosity or suspicion.
Don’t get me wrong. I come from a family of such professors and I hear their laments about the uppity arrogance of students "these days" who have no respect for expertise. Shit, I went to Harvard. I understand the implications of veritas. Yet, the leap from a questioning of expertise and the ability to conduct sound analysis and to produce compelling arguments, outside of degrees and laudations, is a mistake. “Uppity, arrogant students" "or "conceited overbearing millennials" are a sign of a new generation who is seeking much better evidence, much stronger arguments, than those that can be provided by limp theories that have been passed around the academies ad infinitum.
The post-millennials are being left an increasingly frightening place, our earth, and they are evolving toward a siren call for better practice. Don’t tell people like Raj Chetty that he was arrogant and uppity when he wanted to dig into the actual data that underpins the American Dream. http://www.equality-of-opportunity.org/
They can consume, synthesise, and order data at lightening speeds and when they see those who grew up without the Internet unable to do so, they scoff. They are right. They are faster and smarter than we are. Give them their room.
I digress . . .
Data is not suppose to be simple. It is suppose to upend the simple ways that we have used to understand complexity. It is a gift from the convergence of technology, telephony, and these bright young things who can scan and synthesise vast arrays of data quickly. It is intended to be displayed in multi-coloured, column wide and row deep tables, where trends can be spotted, anomalies can be investigated, and where gaps in service can be addressed. Front-line operational humanitarians should have access to multiple screens where they can scan what’s going on in any one context as based on deep and real numbers.
Of course, this takes a new skill set. Of course, the younger amongst us will have a natural talent at this level of analysis and “real-time” synthesis given the access they’ve had to mass information flows since childhood. Of course, this type of data collection and representation will require new and, in some cases, hefty new investments.
Yet, the promise is that we will be able to serve more people, with higher quality and at less cost. We have a moral obligation to make this so.