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The Nonprofit Data Journey

Data, data, data. At times it can feel like a four-letter word we love to hate.

June 17, 2021

Data, data, data. At times it can feel like a four-letter word we love to hate.

This little word carries as much potential for good as it does of peril. Consider that GPS coordinates can be used to rescue vulnerable people and get them to safety, but in the wrong hands those same coordinate matches can be used to speed up atrocities and loss of life.

Our use of the sudden abundance of data, and the mechanisms to produce and analyze it, are at the very core of the fourth industrial revolution. And this holds true even as we limit our focus to the nonprofit sector. Data is essential to digital transformation, but it is also very complex to tame and manage to successful outcomes.

Sometimes, the best way to delve into a complex conversation is through the use of simple questions. Questions help us work out where we are, where we are headed and whether we’re on the right path. These seven questions are ones all NGOs should ask themselves as they help illuminate the nonprofit data journey.

  1. Do you actually have the data? Collecting data seems easy on the surface, but it is hard in practice. Getting clean data in remote or hostile areas, with occasional power and connectivity, can be (and often is!) a mission in itself. When we add the complicated global framework of emerging regulations on privacy and sovereignty, it is no surprise that data collection has risen to be a top challenge for nonprofits. NGOs would be well served in allocating resources to strengthening quality data collection.
  2. Do you understand it? Understanding data and information has always been part science, part art. It requires mathematical and tech skills to extract knowledge and insights from data, particularly when there is high variability and interdependencies. Further, it requires careful and sensitive communication skills to ensure that critical nuances or dependencies are not lost in the abstraction upwards into data visuals. Trends must not become absolutes, and correlations must not become casualties. Additionally, all too often, data cannot be understood without the human experience of the work that created it. Nonprofits need to build data literacy skills to guard against these errors.
  3. Does it represent reality and is there a single version of the truth? Modern times are characterized by increased turbulence, uncertainty, novelty, and ambiguity. As data represents a sample of the past, there is a risk that it could miss the mark of the present. Because data can create different human perceptions it can lead to different interpretations. Thus, creating rapid feedback loops between data and people’s experiences is essential to ensuring coherence between the real world and its digital twin. In our fast-paced nonprofits, creating confidence about the robustness of data and contextualization on which sources it derives from are crucial.
  4. Can you trust it? If you can’t assure the integrity of your data, is it still useful? If nefarious actors manipulate it through security vulnerabilities, creating a fake version of the truth, what are the risks? With the overwhelming amount of data produced in organizations, it is becoming critical to know where the data trust gaps are and if they are narrow or wide. Agreed validation mechanisms, as well as integrity assessments to signal levels of trustworthiness, must become a core part of a nonprofit’s efforts to curate its data.
  5. Can you get it when you need it? It’s one thing to have good, relevant data and another to be able to use it at the moment it is needed. If it takes a week to crunch information needed in an emergency, data loses its value. In some cases, data that is a week old can become useless, such as infection data when a patient has recovered from a disease, but in other cases, such as forecasting pandemic propagation, that same week-old data is now precious. It is helpful to differentiate between data currency (ie, how fresh is the data?) and data timeliness (ie, how quickly can I get it to respond to events?).
  6. Is it usable? Even when data is available, it may not be useful. A large spreadsheet of numbers may just contribute to information overload as much as a graph can lead to poor decisions. How data is presented can make the difference between adoption or rejection. Consider the different social perceptions of the same data said to save 80% of people from certain death or showing that 20% are left to die. A collection of narratives can contain much more nuance about situations, but the overwhelming time it takes to read them all can make overall trends or insights almost impossible to find. A program manager and a CEO may need the same data but prepared in different ways and yet the marketing department and the government partners will still demand that data to be organized differently to be used. It is thus important to have a detailed portfolio of data use-cases and even personas who will employ it in decision making to ensure that data will be used effectively.
  7. Can you keep it safe and use it responsibly, and ethically? No nonprofit can avoid ignoring this question. Even if you can use the data you have or may collect, should you? By the nature of where and with whom nonprofits work, this data, by its very existence, could further reduce the wellbeing or endanger the safety of vulnerable people and marginalized communities now and in their future. Nonprofits must understand that holding data comes with responsibilities and burdens, and they will be expected to live up to the ethical standards, societal expectations, and laws that apply. Ensuring clear principles on data, and holding practitioners accountable to these, are essential elements for a safe digital future.

This is the first post in a new NetHope blog series dedicated to data in the nonprofit sector. Look out for the second post next week where we'll delve into data hygiene and how to achieve it.

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