Beyond Data: Leadership, Values, and the Data Revolution

October 13, 2015
Development Gateway
Data Use

Much has been made recently of the return on character – that core leadership values, like integrity, responsibility, forgiveness, and compassion, have a big impact on organizational results.

This is a great reminder for the global development community as the Data Revolution takes shape – what are the core values and attitudes that should guide Data Revolutionaries?

It’s tempting to think of data as this dispassionate, mechanical thing to be collected and released. The reality is that behind the data are people – people being counted (or not counted!), people with their own experiences, cultures, biases, and wishes – choosing whether, when and how to convert data into something useful and useable.

For me, this Revolution is about data as a catalyst for change and not just a means to measure it; building government (especially National Statistics Office) capacity to achieve national objectives; disrupting the relationship between citizens and government; and getting smarter about the tricky human-centered elements of data use, demand, and uptake.

Are values and attitudes the X factor that might help get us there?

What values should guide the institutions and people who are diving head first into this uncharted data abyss? What organizational – and personal – ethos best equips us to wrestle imperfect data sets into something useful and usable; to fill critical data gaps, such as the gender data gap; to mobilize political support to make investments that take time to bear fruit?

Here’s a starting list of core values to guide the kind of Data Revolution I’d like to see:

Remembering “Why”. Simon Sinek famously observed that “people don’t follow what you do, they follow why you do it.” We may each be energized by different elements of the SDGs or Data Revolution, and it’s our responsibility to share what gets us fired up. My colleague Susan Stout, a great example of this, frequently expresses her passion for “cultivating the quality and use of local data, and not overemphasizing the international extraction of data.” Sticking to our passions, and calling out hot air when we see it is crucial for keeping the Data Revolution honest and on track.

Listen to culture and personal experience. In the ICT world, we’ve learned how important it is to understand how people feel about using technology: have their experiences been positive, or are their computers so riddled with viruses that they expect the worst? Data is similar – feelings, experiences, and cultural norms around data matter. For instance: is rolling up one’s sleeves and diving into the data considered a desirable or loathsome activity? The answer will change depending on where you are and whom you ask, and making headway on data uptake requires getting this right.

Collaboration. New technologies and the Open Data movement have created the unprecedented ability to mash up data that were once siloed. The huge side-benefit? Mashing up data has the potential to bring new groups together – across sectors, functions, geographies, agencies, and more. Breaking out of homogenous siloes and collaborating in multi-disciplinary teams is key to unlocking insights from newly joined data and to putting diverse skills and expertise to best use.

Patience. John McArthur, crediting his mom’s wisdom, notes that the odd and large number of SDGs and indicators matches the complexity of the global challenges at hand. At a recent event, he had two pieces of advice: “Respect the need to explain to people why this is important, and embrace the complexity.” It will take patience and stamina to advocate for investments across the data lifecycle, and just as much patience to accept the complexity of the challenges we face, without oversimplifying, missing the big picture, or becoming disheartened.

Listening. Overcoming the barriers to data use and uptake will require more than a technical lift to address issues of data formatting, standards and accessibility. We’ll have to take a holistic look at organizational culture(s) of data use and decision-making. By putting ourselves in the shoes of different potential data users, by listening and observing how decisions are currently made, we can better understand how, where, and when data can be used to underpin policy decisions.

Be inquisitive and discerning. Ruth Levine reminded a group at the Global Partnership for Sustainable Development Data Community Event that statistics sometimes reflect the biases of those who created them. In the case of the gender data gap, less than a third of countries produce sex-disaggregated statistics on informal employment and entrepreneurship. Since women’s participation in the informal economy is often very high, the statistics don’t capture the participation of women in these areas, which has implications for policies to support women. Being inquisitive and discerning about the data we’re diving into, the new data we aim to collect, and how this data will ultimately be used is essential.

Humility and empathy. The difficult reality is that, to date, data-driven decision-making has been slow to take root in the public sector such that it’s ubiquitous and woven into day-to-day processes and interactions. There are exceptional divisions and departments across agencies, but we all have a long way to go. The good news is that we can all learn from the tireless champions who are getting it done.

It may be easy to think that the Data Revolution is primarily the responsibility of statisticians and data scientists. After all, these folks have been tirelessly advocating for better data and smarter approaches to data use long before it was en vogue. For sure, these data lovers are at the heart of the Data Revolution, but they shouldn’t be revolutionaries alone.

It will take outspoken, courageous leadership across the development community to model, cultivate, socialize and put into practice the values and attitudes that will guide us through a human-centric, action-focused and impactful Data Revolution.

Image credit: PopTech CC BY-SA 2.0.

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