Data & The False Promise of Simplicity
Humanitarians are historically and notoriously overburdened. While some recognise that collecting and analysing data can be helpful, they still want the final analysis distilled into a single number with a “stoplight” rating: red, yellow, or 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, saving 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 provide an adequate analysis of the problems we face, day in and day out, in the world's most complex operating environments. 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 essential. They can provide theories that may guide our analysis or explain what we do, provided they have 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 types of experts can interrogate for the narratives that underpin what’s really going on. The data provides a glimpse into the patterns within the chaos. Data drives operations.
This is the promise of data. It enables us to gain a much better understanding of the complexity that shapes the contexts of the people we serve and the impact of the interventions we make on their behalf. Simple, it is not.
This is not new. Private sector enterprises invest in large data stores to decipher a range of trends, from consumer behaviours to supply chains to raw material costs. Big data did not emerge from international development and humanitarian action. It came from companies like Google and Palantir, which could corral massive 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 by 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 to use the data to aggregate 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 questioning expertise and the ability to conduct sound analysis to producing compelling arguments outside of degrees and laudations is a mistake. “Uppity, arrogant students "or "conceited overbearing millennials" are a sign of a new generation that 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 in an increasingly frightening place —our earth —and are evolving toward a siren call for better practice. Don’t tell people like Raj Chetty that he was arrogant 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 lightning 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 wiser than we are. Give them their room.
I digress . . .
Data is not supposed to be simple. It is believed 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 quickly scan and synthesise vast arrays of data. It is intended to be displayed in multi-coloured, column-wide and row-deep tables, where trends can be spotted, anomalies investigated, and gaps in service addressed. Front-line operational humanitarians should have access to multiple screens that let them scan what’s going on in any given context, based on real, deep 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 investments, and in some cases, hefty ones.
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.
Dorian LaGuardia
