Tag Archives: data visualization

Four Reflections on the 2019 MERL Tech Dashboards Competition

by Amanda Makulec, Excella Labs. This post first appeared here.

Data visualization (viz) has come a long way in our MERL Tech community. Four years ago the conversation was around “so you think you want a dashboard?” which evolved to a debate on dashboards as the silver bullet solution (spoiler: they’re not). Fast forward to 2019, when we had the first plenary competition of dashboard designs on the main stage!

Wayan Vota and Linda Raftree, MERL Tech Organizers, were kind enough to invite me to be a judge for the dashboard competition. Let me say: judging is far less stressful than presenting. Having spoken at MERL Tech every year on a data viz topic since 2015, it felt novel to not be frantically reviewing slides the morning of the conference.

The competition sparked some reflections on how we’ve grown and where we can continue to improve as we use data visualization as one item in our MERL toolbox.

1 – We’ve moved beyond conversations about ‘pretty’ and are talking about how people use our dashboards.

Thankfully, our judging criteria and final selection were not limited to which dashboard was the most beautiful. Instead, we focused on the goal, how the data was structured, why the design was chosen, and the impact it created.

One of the best stories from the stage came from DAI’s Carmen Tedesco (one of three competition winners), who demoed a highly visual interface that even included custom spatial displays of how safe girls felt in different locations throughout a school. When the team demoed the dashboard to their Chief of Party, he was underwhelmed… because he was colorblind and couldn’t make sense of many of the visuals. They pivoted, added more tabular, text-focused, grayscale views, and the team was thrilled.

Carmen Tedesco presents a dashboard used by a USAID-funded education project in Honduras. Image from Siobhan Green https://twitter.com/siobhangreen/status/1169675846761758724

Carmen Tedesco presents a dashboard used by a USAID-funded education project in Honduras. Image from Siobhan Green: https://twitter.com/siobhangreen/status/1169675846761758724

Having a competition judged on impact, not just display, matters. What gets measured gets done, right? We need to reward and encourage the design and development of data visualization that has a purpose and helps someone do something – whether it’s raising awareness, making a decision, or something else – not just creating charts for the sake of telling a donor that we have a dashboard.

2 – Our conversations about data visualization need to be anchored in larger dialogues about data culture and data literacy.

We need to continue to move beyond talking about what we’re building and focus on for who, why, and what else is needed for the visualizations to be used.

Creating a “data culture” on a small project team is complicated. In a large global organization or slow-to-change government agency, it can feel impossible. Making data visual, nurturing that skillset within a team, and building a culture of data visualization is one part of the puzzle, but we need champions outside of the data and M&E (monitoring and evaluation) teams who support that organizational change. A Thursday morning MERL Tech session dug into eight dimensions of a data readiness, all of which are critical to having dashboards actually get used – learn more about this work here.

Village Enterprise’s winning dashboard was simple in design, constructed of various bar charts on enterprise performance, but was tailored to different user roles to create customized displays. By serving up the data someone needs filtered to their level, they encourage adoption and use instead of requiring a heavy mental load from users to filter to what they need.

Village Enterprise’s winning dashboard was simple in design, constructed of various bar charts on enterprise performance, but was tailored to different user roles to create customized displays. By serving up the data someone needs filtered to their level, they encourage adoption and use instead of requiring a heavy mental load from users to filter to what they need.

Village Enterprise’s winning dashboard was simple in design, constructed of various bar charts on enterprise performance, but was tailored to different user roles to create customized displays. By serving up the data filtered to a specific user level, they encourage adoption and use instead of requiring a heavy mental load from users to filter to what they need.

3 – Our data dashboards look far more diverse in scope, purpose, and design than the cluttered widgets of early days.

The three winners we picked were diverse in their project goals and displays, including a complex map, a PowerBI project dashboard, and a simple interface of bar charts designed for various user levels on local enterprise success metrics.

One of the winners – Fraym – was a complex, interactive map display allowing users to zoom in to the square kilometer level. Layers for various metrics, from energy to health, can be turned on or off depending on the use case. Huge volumes of data had to be ingested, including both spatial and quantitative datasets, to make the UI possible.

In contrast, the People’s Choice winner wasn’t a quantitative dashboard of charts and maps. Matter of Focus’ OutNav tool instead makes the certainty around elements of theory of change visual, has visual encodings in the form of colors, saturation, and layout within a workflow, and helps organizations show where they’ve contributed to change.

Seeing the diversity of displays, I’m hopeful that we’re moving away from one-size-fits-all solutions or reliance on a single tech stack (whether Excel, Tableau, PowerBI or something else) and continuing to focus more on crafting products that solve problems for someone, which may require us to continue to expand our horizons regarding the tools and designs we use.

4 – Design still matters though, and data and design nerds should collaborate more often.

That said, there remain huge opportunities for more design in our data displays. Last year, I gave a MERL tech lightning talk on why no one is using your dashboard that focused on the need for more integration of design principles in our data visualization development, and those principles still resonate today.

Principles from graphic design, UX, and other disciplines can take a specific visualization from good to great – the more data nerds and designers collaborate, the better (IMHO). Otherwise, we’ll continue the an epidemic of dashboards, many of which are tools designed to do ALL THE THINGS without being tailored enough to be usable by the most important audiences.

An invitation to join the Data Viz Society

If you’re interested in more discourse around data viz, consider joining the Data Viz Society (DVS) and connect with more than 8,000 members from around the globe (it’s free!) who have joined since we launched in February.

DVS connects visualization enthusiasts across disciplines, tech stacks, and expertise, and aims to collect and establish best practices, fostering a community that supports members as they grow and develop data visualization skills.

We (I’m the volunteer Operations Director) have a vibrant Slack workspace packed with topic and location channels (you’ll get an invite when you join), two-week long moderated Topics in DataViz conversations, data viz challenges, our journal (Nightingale), and more.

More on ways to get involved in this thread – including our data viz practitioner survey results challenge closing 30 September 2019 that has some fabulous cash prizes for your data viz submissions!

We’re actively looking for more diversity in our geographic representation, and would particularly welcome voices from countries outside of North America. A recent conversation about data viz in LMICs (low and middle income countries) was primarily voices from headquarters staff – we’d love to hear more from the field.

I can’t wait to see what the data viz conversations are at MERL Tech 2020!

New Report: Global Innovations in Measurement and Evaluation

All 8 innovationsOn June 26th, New Philanthropy Capital (NPC) released its “Global Innovations in Measurement and Evaluation” report. In it, NPC outlines and elaborates on eight concepts that represent innovations in conducting effective measurement and evaluation of social impact programs. The list of concepts was distilled from conversations with leading evaluation experts about what is exciting in the field and what is most likely to make a long-lasting impact on the practice of evaluation. Below, we feature each of these eight concepts accompanied by brief descriptions of their meanings and implications.

User-Centric

The key to making an evaluation user-centric is to ensure that the service users are truly involved in every stage of the evaluation process. In this way, the power dynamic ceases to be unidirectional as more agency is given to the user. As a result, not only can findings become more compelling to decision makers because of more robust data collection, but also those responsible for the program now become accountable to the users in addition to the funders, a shift that is both ethically important and that is important for the trust it builds.

Shared Measurement & Evaluation

Shared measurement and evaluation requires multiple organizations with similar missions, programs or users to work together to measure their own and their combined impact. This involves using the same evaluation metrics and, at a more advanced stage, developing shared measurement tools and methodologies. Pooling data and comparing outcomes creates a bigger dataset that can support stronger conclusions and provide more insights.

Theory-Based Evaluation

The central idea behind theory-based evaluation is to not only measure the outcome of a program but to also get at the reason why it does or does not work. Typically, this approach begins with a theory of change that proposes an explanation for how activities lead to impact, and this theory is then tested and accepted, refuted or qualified. It is important to apply this concept because without an understanding of why programs work, there is a risk that mistakes will be repeated or that attempts to replicate a program will fail when attempted under different conditions.

Impact Management

Impact management is the integration of impact assessment into strategy and performance management by regularly collecting data and responding to it with course corrections designed to improve the outcomes of a program. This method contrasts with assessment strategies that only examine a program at the end of its life cycle. The objective here is to be flexible and adaptive in order to produce a more effective intervention rather than waiting to evaluate it until there is nothing that can be done to change it.

Data Linkage

Data linkage is the act of bringing together different but relevant data about a specified group of users from beyond a single organization or sub-sector dataset. One example could be a homelessness charity that supports its users in accessing social housing linking its data with the local council to see if its users ultimately remained in their homes. In essence, this method allows organizations to leverage the increasing quantities of data to create comparison groups to track the long term impacts of their programs.

Big Data

Big data is typically considered as the data generated as a by-product of digital transactions and interactions. It is a category that includes people’s social media activity, web searches and digital financial transaction trails. New technology has expanded the human ability to analyze large datasets, and consequently big data has become a powerful tool for helping identify trends and patterns, even if it does not provide explanations for them.

Remote Sensing

Remote sensing uses technology, such as mobile phones, to gather information from afar. This method is useful because it allows one to collect data that may not be typically accessible. Additionally, remote sensing data can be highly detailed, accurate, and in real time. Finally, one of its great strengths is that it is generated passively, which reduces the possibility of introducing researcher bias through human input.

Data Visualization

Data visualization is the practice of presenting data in a graphic form. New technology has made it possible to create a broad range of useful visualizations. The result is that data is now more accessible to non-specialists, and the insights produced through analysis can now be better understood and communicated.

For more details and more examples of real-world applications of these concepts, check out the full “Global Innovations in Measurement and Evaluation” report here.