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How to Manage Data and Measure Our Success in International Development

By Guest Writer on March 29, 2018

measure data

If the last ten years are an indicator of what to expect in the coming ten years, data will be one of the most sought-after commodities for measuring success in development work. To measure accurately, however, data must be of high quality. They must be managed by skilled staff and processed using interoperable information systems to assure the right data quality and quantity.

In the decade ahead, data collection and management technology will mature, and issues of cyber security and related ethical practices will be on the rise. These will shake the development sector and shape the way we manage data.

Let’s look at each of these elements – skilled staff, interoperability, and responsible data practices in the context of low-and middle-income countries – and what they portend for the development sector in the decade ahead.

Digital Data Workforce

In the last decade, demand in the development sector shifted from more data to intersectoral, accurate, and granular data. Collecting and processing data across sectors, in sufficient disaggregation, and with a high level of accuracy would be almost unimaginable without technology.

But data are only one part of the equation. With data systems shifting from paper to digital, we have learned that without corresponding improvement in data management, broad-based, accurate, and granular data will remain an aspiration.

My project, MEASURE Evaluation, funded by USAID, has worked across more than 50 developing countries over two decades. We’ve seen an increasing demand for people with varied data management capabilities, many of which are “skills,” plus a combination of behaviors, expertise, know-how, work habits, character traits, and dispositions.

One lesson learned is that when technology gets ahead of staff skills, the chances those data systems will survive are slim.

Building these skills, however, needs care. Last December, I attended the Global Digital Health Forum in Washington, DC. One session concerned digital health and gender and the message was stark: in many aspects of digital development, the scales are tipped in favor of men.

More men than women own technology tools in general, and mobile phones in particular. New data shows this digital gender gap growing wider. This trend, if left unchecked, can further entrench a gender digital divide, thereby perpetuating inequalities that technology ought to overcome.

We can change this trend if we are intentional in encouraging women, and providing them incentives to acquire information technology-type skills. Importantly, the leadership of development programs at various levels need to have a fair representation of women so that their voices and views are integrated in digital development.

At a national level, governments must enact policies and programs aimed at removing barriers that stand in the way for women to fully enjoy technology benefits like their male counterparts such as cost, skills and access to the internet.

Open Data Management

The development sector is known for data collection. I have been part of the health sector for more than a decade and I know we live in data bubbles, holding data in closed systems. I know too well how cumbersome it is to exchange data between sectors, even in the same government. One of my colleagues compared this process to “blowing air into a sack” – a futile effort.

Principle six of the nine Principles for Digital Development states that we should be open: Use open standards in developing information systems, share data openly, and use open-source and open innovation approaches. In practice, however, it is the polar opposite.

Why? Because actors in each sector collect and horde their data. The result is siloed data, which prevents us from seeing the big picture. Siloed data for health. Siloed data for agriculture. Siloed data for the education, energy, and transport sectors. And even within these sectors, there are further data fragmentations.

The solution to this problem is interoperability. That is, using and reusing existing data exchange standards; deploying data across development sectors; using common classifications wherever possible; and ensuring that data standards serve the users.

When I see the current national and global efforts to create re-usable open public goods developed through Communities of practice, it gives me hope that interoperability between systems is within reach.

Sustainable interoperability thrives, not when information systems can exchange their information, but when organizations and their leadership can sit around the table and agree to harmonize their business process and create common tools for data stewardship and governance.

Responsible Data Practices

Wide-scale use of technology raises data security and privacy concerns. Principle eight of the nine principles for digital development underscores the importance of privacy and security of information systems.

To sustain current data and technology growth, we need to institutionalize responsible data practices that address and go beyond data security and privacy. Practices such those aimed at mitigating biases in both data practice and consumption.

These biases arise when we collect and analyze data for places that are better served by technology, and leaving out inconvenient places without technology, thereby blacking-out marginalized communities. Importantly, we need to treat data as a public good — one that is easily accessible and used to direct development. 

Enforcement of these practices will alleviate fears that data will be lost or misused – which is a main argument against interoperability. Adherence to these practices will increase transparency in the development sector and encourage wide participation of other actors especially the risk-averse private sector.

Technology has the potential to accelerate the wheels of development—but that can happen only if we train a digitally dynamic workforce, break the walls that limit data sharing, and adopt ethical data management practices.

By Sam Wambugu, MPH, PMP, Senior Health Informatics Specialist, MEASURE Evaluation and this was first given as a lightning talk at the USAID Digital Development Forum

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One Comment to “How to Manage Data and Measure Our Success in International Development”

  1. Ali says:

    Data is valuable & tracking always does wonder regardless whatever environment we are in.