MERL Tech News

Use of Administrative Data for the COVID-19 Response

Administrative data is that which is collected as part of regular activities that occur during program implementation. It has not been tapped sufficiently for learning and research. As the COVID-19 pandemic advances, how might administrative data be used to help with the COVID response, and other national or global pandemics.

At the final event in the MERL Tech and CLEAR-Anglophone Africa series for  gLOCAL Evaluation Week, we were joined by Kwabena Boakye, Ministry of Monitoring and Evaluation, Ghana; Bosco Okumu, National Treasury and Planning, Kenya; Stephen Taylor, Department of Basic Education, South Africa; and Andrea Fletcher, Cooper-Smith.

The four panelists described the kinds of administrative or “routine” data they are using in their work. For example, in Kenya educational records, client information from financial institutions, hospital records of patients, and health outcomes are being used to plan and implement actions related to COVID-19 and to evaluate the impact of different COVID-related policies that governments have put in place or are considering. In Malawi, administrative data is combined with other sources such as Google mobility data to understand how migration might be affecting the virus’ spread. COVID-19 is putting a spotlight on weaknesses and gaps in existing administrative data systems.

Watch the video here:

Listen to just the audio from the event here:

Summary:

Benefits of administrative data include that:

  • Data is generated through normal operations and does not require an additional survey to create it
  • It can be more relevant than a survey because it covers a large swath of the entire population
  • It is an existing data source during COVID when it’s difficult to collect new data
  • It can be used to create dashboards for decision-makers at various levels

Challenges include:

  • Data sits in silos and the systems are not designed to be interoperable
  • Administrative data may leave out those who are not participating in a government program
  • Data sets are time-bound to the life of the program
  • Some administrative data systems are outdated and have poor quality data that is not useful for decision-making or analysis
  • There is a demand for beautiful dashboards and maps but there is insufficient attention to the underlying data processes that would be needed to produce this information so that it can be used
  • Real-time data is not possible when there is no Internet connectivity
  • There is insufficient attention to data privacy and protection, especially for sensitive data
  • Institutions may resist providing data if weakness are highlighted through the data or they think it will make them look bad

Recommendations for better use of administrative data in the public sector:

  • Understand the data needs of decision-makers and build capacity to understand and use data systems
  • Map the data that exists, assess its quality, and identify gaps
  • Design and enact policies and institutional arrangements, tools, and processes to make sure that data is organized and interoperable.
  • Automate processes with digital tools to make them more seamless.
  • Focus on enhancing underlying data collection processes to improve the quality of administrative data; this includes making it useful for those who provide the data so that it is not yet another administrative burden with no local value.
  • Assign accountability for data quality across the entire system.
  • Learn from the private sector, but remember that the public sector has different incentives and goals.
  • Rather than fund more research on administrative data, donors should put funds into training on data quality, data visualization, and other skills related to data use and data literacy at different levels of government.
  • Determine how to improve data quality and use of existing administrative data systems rather than building new ones.
  • Make administrative data useful to those who are inputting it to improve data quality.

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See other gLOCAL Evaluation 2020 events from CLEAR-AA and MERL Tech:

Remote Monitoring in the Time of Coronavirus

On June 3,  MERL Tech and CLEAR-Anglophone Africa hosted the second of three virtual events for gLOCAL Evaluation Week. At this event, we heard from Ignacio Del Busto, IDInsight, Janna Rous, Humanitarian Data, and Ayanda Mtanyana, New Leaders, on the topic of remote monitoring.

Data is not always available, and it can be costly to produce. One challenge is generating data cheaply and quickly to meet the needs of decision-makers within the operational constraints that enumerators face. Another is ensuring that the process is high quality and also human-centered, so that we are not simply extracting data. This can be a challenge when there is low connectivity and reach, poor networks capacity and access, and low smartphone access. Enumerator training is also difficult when it must be done remotely, especially if enumerators are new to technology and more accustomed to doing paper-based surveys.

Watch the video below.

Listen to just the audio from the session here.

Some recommendations arising from the session included:

  • Learn and experiment as you try new things. For example, tracking when and why people are dropping off a survey and finding ways to improve the design and approach. This might be related to the time of the call or length of the survey.
  • It’s not only about phone surveys. There are other tools. For example, WhatsApp has been used successfully during COVID-19 for collecting health data.
  • Don’t just put your paper processes onto a digital device. Instead, consider how to take greater advantage of digital devices and tools to find better ways of monitoring. For example, could we incorporate sensors into the monitoring from the start? At the same time, be careful not to introduce technologies that are overly complex.
  • Think about exclusion and access. Who are we excluding when we move to remote monitoring? Children? Women? Elderly people? We might be introducing bias if we are going remote. We also cannot observe if vulnerable people are in a safe place to talk if we are doing remote monitoring. So, we might be exposing people to harm or they could be slipping through the cracks. Also, people self-select for phone surveys. Who is not answering the phone and thus left out of the survey?
  • Consider providing airtime but make sure this doesn’t create perverse incentives.
  • Ethics and doing no harm are key principles. If we are forced to deliver programs remotely, this involves experimentation. And we are experimenting with people’s lives during a health crisis. Consider including a complaints channel where people can report any issues.
  • Ensure data is providing value at the local level, and help teams see what the whole data process is and how their data feeds into it. That will help improve data quality and reduce the tendency to ‘tick the box’ for data collection or find workarounds.
  • Design systems for interoperability so that the data can overlap, and the data can be integrated with other data for better insights or can be automatically updated. Data standards need to be established so that different systems can capture data in the same way or the same format;
  • Create a well-designed change management program to bring people on board and support them. Role modeling by leaders can help to promote new behaviors.

Further questions to explore:

  • How can we design monitoring to be remote from the very start? What new gaps could we fill and what kinds of mixed methods could we use?
  • What two-way platforms are most useful and how can they be used effectively and ethically?
  • Can we create a simple overview of opportunities and threats of remote monitoring?
  • How can we collect qualitative data, e.g., focus groups and in-depth interviews?
  • How can we keep respondents safe? What are the repercussions of asking sensitive questions?
  • How can we create data continuity plans during the pandemic?


Download the event reports:

See other gLOCAL Evaluation 2020 events from CLEAR-AA and MERL Tech:

Using Data Responsibly During the COVID-19 Crisis

Over the past decade, monitoring, evaluation, research and learning (MERL) practices have become increasingly digitalized. The COVID-19 pandemic has caused that the process of digitalization to happen with even greater speed and urgency, due to travel restrictions, quarantine, and social distancing orders from governments who are desperate to slow the spread of the virus and lessen its impact.

MERL Tech and CLEAR-Anglophone Africa are working together to develop a framework and guidance on responsible data management for MERL in the Anglophone African context. As part of this effort, we held three virtual events in early June during CLEAR’s gLOCAL Evaluation Week.

At our June 2 event, Korstiaan Wapenaar, Genesis Analytics, Jerusha Govender, Data Innovator, and Teki Akkueteh, Africa Digital Rights Hub, shared tips on how to be more responsible with data.

Data is a necessary and critical part of COVID-19 prevention and response efforts to understand where the virus might appear next, who is most at risk, and where resources should be directed for prevention and response. However we need to be sure that we are not putting people at risk of privacy violations or misuse of personal data and to ensure that we are managing that data responsibly so that we don’t unnecessarily create fear or panic.

Watch the video below:

Listen to the audio from the session here:

Session summary:

  • MERL Practitioners have clear responsibilities when sharing, presenting, consuming and interpreting data. Individuals and institutions may use data to gain prestige, and this can allow bias to creep in or to justify government decisions. Data quality is critical for informing decisions, and information gaps create the risk of misinformation and flawed understanding. We need to embrace uncertainty and the limitations of the science, provide context and definitions so that our sources are clear, and ensure transparency around the numbers and the assumptions that are underpin our work.
  • MERL Practitioners should provide contextual information and guidance on how to interpret the data so that people can make sense of it in the right way. We should avoid cherry picking data to prove a point, and we should be aware that data visualization carries power to sway opinions and decisions. It can also influence behavior change in individuals, so we need to take responsibility for that. We also need to find ways to visualize data for lay people and non-technical sectors.
  • Critical data is needed, yet it might be used in negative or harmful ways, for example, COVID-related stigmatization that can affect human dignity. We must not override ethical and legal principles in our rush to collect data. Transparency around data collection processes and use are also needed, as well as data minimization. Some might be taking advantage of the situation to amass large amounts of data for alternative purposes, which is unethical. Large amounts of data also bring increased risk of data breaches. When people are scared, such as in COVID times, they will be willing to hand over data. We need to ensure that we are providing oversight and keeping watch over government entities, health facilities, and third-party data processors to ensure data is protected and not misused.
  • MERL Practitioners are seeking more guidance and support on: aspects of consent and confidentiality; bias and interference in data collection by governments and community leaders; overcollection of data leading to fatigue; misuse of sensitive data such as location data; potential for re-identification of individuals; data integrity issues; lack of encryption; and some capacity issues.
  • Good practices and recommendations include ethical clearance of data and data assurance structures; rigorous methods to reduce bias; third party audits of data and data protection processes; localization and contextualization of data processes and interpretation; and “do no harm” framing.

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Read about the other gLOCAL Evaluation 2020 events from CLEAR-AA and MERL Tech:

Research Opportunity: Harm and the M&E Cycle

We are looking for a researcher to undertake desk-based research into how harm has been defined and integrated into monitoring and evaluation cycles. Please see the Terms of Reference and submit your short proposal by July 5, 2020, or read more about this initiative below.

Monitoring and evaluation practitioners are in a privileged position where they have the opportunity to listen and hear the voices and stories of the people that aid and development agencies work with. These professionals often determine what gets counted and what counts. Yet, practical guidance for commissioners, managers, and evaluators on managing harm is limited. The above graphic shows just some of the areas where the monitoring and evaluation process could contribute to harm.

Our privileged position as M&E practitioners brings with it the responsibility to do no harm. We need to be aware of how we might create or exacerbate harm and also how we might overlook harm due to our positions of power.  Evaluators need to play a strong role in identifying areas where M&E can cause harm and develop mitigation strategies to prevent or reduce that potential harm. There has been patchy recognition about the variety of potential harms that can arise from both action and inaction of an evaluator and others involved in monitoring and evaluation processes. There is also a wider discussion to be had around evaluation as a whole and its inherent power dynamics that can lead to, enable, or obfuscate different types of harm and which play a role in determining what is considered to be harmful.

Over the past two years, a group of senior M&E practitioners* has been reflecting on harm in M&E. In the course of this work we’ve organized conversations and collective reflection workshops, think pieces, reports on priority areas and presentations at M&E conferences. The group now looks to build these actions into a practitioner-orientated publication. The research being commissioned aims to further map harms that arise within monitoring and evaluation practice.

As part of this publication, we are looking for a researcher to take a deeper look at how harm has been defined and if and how “do no harm” approaches have been integrated into M&E cycles.

Potential questions for this research include:

  1.  What definition, association, or conception (or definitions, associations, or conceptions) of harm emerge from M&E literature and practice?
  2. Who are the key social actors who interact in M&E cycles?
  3. What strategies for addressing, preventing or reducing these harms have emerged and how successful have these been?

Please see the full Terms of Reference and instructions for submitting your application if you are interested in conducting this research. The deadline for submissions is Sunday July 5th. 

*The group of M&E practitioners who are working together on this topic includes: Stephen Porter, Evaluation Strategy Advisor – Independent Evaluation Group, World Bank; Veronica Olazabal, Senior Adviser and Director, Measurement, Evaluation and Organizational Performance – The Rockefeller Foundation; Prof. Rodney Hopson, Department of Educational Psychology – University of Illinois; Linda Raftree, Convener of MERL Tech; Adj. Prof Dugan Fraser, Director of the Centre for Learning on Evaluation and Results Anglophone Africa – University of the Witwatersrand.

Open Call for MERL Center Working Group Members!

By Mala Kumar, GitHub Social Impact, Open Source for Good

I lead a program on the GitHub Social Impact team called Open Source for Good — detailed in a previous MERL Tech post and (back when mass gatherings in large rooms were routine) at a lightning talk at the MERL Tech DC conference last year.

Before joining GitHub, I spent a decade wandering around the world designing, managing, implementing, and deploying tech for international development (ICT4D) software products. In my career, I found open source in ICT4D tends to be a polarizing topic, and often devoid of specific arguments. To advance conversations on the challenges, barriers, and opportunities of open source for social good, my program at GitHub led a year-long research project and produced a culminating report, which you can download here.

One of the hypotheses I posed at the MERL Tech conference last year, and that our research subsequently confirmed, is that IT departments and ICT4D practitioners in the social sector* have relatively less budgetary decision-making power than their counterparts at corporate IT companies. This makes it hard for IT and ICT4D staff to justify the use of open source in their work.

In the past year, Open Source for Good has solidified its strategy around helping the social sector more effectively engage with open source. To that aim, we started the MERL Center, which brings together open source experts and MERL practitioners to create resources to help medium and large social sector organizations understand if, how, and when to use open source in their MERL solutions.**

With the world heading into unprecedented economic and social change and uncertainty, we’re more committed than ever at GitHub Social Impact to helping the social sector effectively use open source and to build on a digital ecosystem that already exists.

Thanks to our wonderful working group members, the MERL Center has identified its target audiences, fleshed out the goals of the Center, set up a basic content production process, and is working on a few initial contributions to its two working groups: Case Studies and Beginner’s Guides. I’ll announce more details in the coming months, but I am also excited to announce that we’re committing funds to get a MERL Center public-facing website live to properly showcase the materials the MERL Center produces and how open source can support technology-enabled MERL activities and approaches.

As we ramp up, we’re now inviting more people to join the MERL Center working groups! If you are a MERL practitioner with an interest in or knowledge of open source, or you’re an open source expert with an interest in and knowledge of MERL, we’d love to have you! Please feel free to reach out me with a brief introduction to you and your work, and I’ll help you get on-boarded. We’re excited to have you work with us! 

*We define the “social sector” as any organization or company that primarily focuses on social good causes.

**Here’s our working definition of MERL.

 

8 Ways to Adapt Your M&E During the COVID-19 Pandemic

Guest post from Janna Rous. Original published here.

So, all of a sudden you’re stuck at home because of the new coronavirus.  You’re looking at your M&E commitments and your program commitments.  Do you put them all on hold and postpone them until the coronavirus threat has passed and everything goes back to normal?  Or is there a way to still get things done”!?  This article reviews 8 ways you can adapt your M&E during the pandemic.

Here are a few ideas that you and your team might consider doing to make sure you can stay on track (and maybe even IMPROVE your MEAL practices) even if you might currently be in the middle of a lockdown, or if you think you might be going into a lockdown soon:

1. Phone Call Interviews instead of In-Person Interviews

Do you have any household assessments or baseline surveys or post-distribution monitoring that you had planned in the next 1 to 3 months? Is there a way that you can carry out these interviews by phone or WhatsApp calls?  This is the easiest and most direct way to carry on with your current M&E plan.  Instead of doing these interviews face-to-face, just get them on a call.  I’ve created a checklist to help you prepare for doing phone call interviews – click here to get the “Humanitarian’s Phone Call Interview Checklist”.  Here are a few things you need to think through to transition to a phone-call methodology:

  • You need phone numbers and names of people that need to be surveyed. Do you have these?  Or is there a community leader who might be able to help you get these?
  • You also need to expect that a LOT of people may not answer their phone. So instead of “sampling” people for a survey, you might want to just plan on calling almost everyone on that list.
  • Just like for a face-to-face interview, you need to know what you’re going to say. So you need to have a script ready for how you introduce yourself and ask for consent to do a phone questionnaire.  It’s best to have a structured interview questionnaire that you follow for every phone call, just like you would in a face-to-face assessment.
  • You also need to have a way to enter data as you ask the questions. This usually depends on what you’re most comfortable with – but I recommend preparing an ODK or KoboToolbox questionnaire, just like you would for an in-person survey, and filling it out as you do the interview over the phone.  I find it easiest to enter the data into KoboToolbox “Webform” instead of the mobile app, because I can type information faster into my laptop rather than thumb-type it into a mobile device.  But use what you have!
  • If you’re not comfortable in KoboToolbox, you could also prepare an Excel sheet for directly entering answers – but this will probably require a lot more data cleaning later on.
  • When you’re interviewing, it’s usually faster to type down the answers in the language you’re interviewing in. If you need your final data collection to be in English, go back and do the translation after you’ve hung up the phone.
  • If you want a record of the interview, ask if you can record the phone call. When the person says yes, then just record it so you can go back and double check an answer if you need to.
  • Very practically – if you’re doing lots of phone calls in a day, it is easier on your arm and your neck if you use a headset instead of holding your phone to your ear all day!

2. Collect Videos & Photos Directly from Households and Communities

When you’re doing any in-person MEAL activities, you’re always able to observe evidence. You can look around and SEE impact, you don’t just hear it through an interview or group discussion.  But when you’re doing M&E remotely, you can’t double-check to see what impact really looks like.  So I recommend:

  • Connect with as many beneficiaries and team members as possible through WhatsApp or another communication app and collect photos and videos of evidence directly from them.
  • Video – Maybe someone has a story of impact they can share with you through video. Or if you’re overseeing a Primary Health Care clinic, perhaps you can have a staff member walk you through the clinic with a video so you can do a remote assessment.
  • Pictures – Maybe you can ask everyone to send you a picture of (for example) their “hand washing station with soap and water” (if you’re monitoring a WASH program). Or perhaps you want evidence that the local water point is functioning.

3. Programme Final Evaluation

It’s a good practice to do a final evaluation review when you reach the end of a program.  If you have a program finishing in the next 1-3 months, and you want to do a final review to assess lessons learned overall, then you can also do this remotely!

  • Make a list of all the stakeholders that would be great to talk to: staff members, a few beneficiaries, government authorities (local and/or national), other NGOs, coordination groups, partner organizations, local community leaders.
  • Then go in search of either their phone numbers, their email addresses, their Skype accounts, or their WhatsApp numbers and get in touch.
  • It’s best if you can get on a video chat with as many of them as possible – because it’s much more personal and easy to communicate if you can see one another’s faces! But if you can just talk with audio – that’s okay too.
  • Prepare a semi-structured interview, a list of questions you want to talk through about the impact, what went well, what could have gone better. And if there’s anything interesting that comes up, don’t worry about coming up with some new questions on the spot or skipping questions that don’t make sense in the context.
  • You can also gather together any monitoring reports/analysis that was done on the project throughout its implementation period, plus pictures of the interventions.
  • Use all this information to create a final “lessons learned” evaluation document. This is a fantastic way to continually improve the way you do humanitarian programming.

4. Adapt Your Focus Group Discussion Plan

If everyone is at home because your country has imposed a lockdown, it will be very difficult to do a focus group discussion because….you can’t be in groups!  So, with your team decide if it might be better to switch your monitoring activity from collecting qualitative data in group discussions to actually just having one-on-one interviews on the phone with several people to collect the same information.

  • There are some dynamics that you will miss in one-to-one interviews, information that may only come out during group discussions. (Especially where you’re collecting sensitive or “taboo” data.) Identify what that type of information might be – and either skip those types of questions for now, or brainstorm how else you could collect the information through phone-calls.

5. Adapt Your Key Informant Interviews

If you normally carry out Key Informant Interviews, it would be a great idea to think what “extra” questions you need to ask this month in the midst of the coronavirus pandemic.

  • If you normally ask questions around your program sector areas, think about just collecting a few extra data points about feelings, needs, fears, and challenges that are a reality in light of Covid-19. Are people facing any additional pressures due to the epidemic? Or are there any new humanitarian needs right now? Are there any upcoming needs that people are anticipating?
  • It goes without saying that if your Key Informant Interviews are normally in person, you’ll want to carry these out by phone for the foreseeable future!

6. What To Do About Third Party Monitoring

Some programs and donors use Third Party Monitors to assess their program results independently.  If you normally hire third party monitors, and you’ve got some third party monitoring planned for the next 1-3 months, you need to get on the phone with this team and make a new plan. Here are a few things you might want to think through with your third party monitors:

  • Can the third party carry out their monitoring by phone, in the same ways I’ve outlined above?
  • But also think through – is it worth it to get a third party monitor to assess results remotely? Is it better to postpone their monitoring?  Or is it worth it to carry on regardless?
  • What is the budget implication? If cars won’t be used, is there any cost-savings?  Is there any additional budget they’ll need for air-time costs for their phones?
  • Make sure there is a plan to gather as much photo and video evidence as possible (see point 2 above!)
  • If they’re carrying out phone call interviews it would also be a good recommendation to record phone calls if possible and with consent, so you have the records if needed.

7. Manage Expectations – The Coronavirus Pandemic May Impact Your Program Results.

You probably didn’t predict that a global pandemic would occur in the middle of your project cycle and throw your entire plan off.  Go easy on yourself and your team!  It is most likely that the results you’d planned for might not end up being achieved this year.  Your donors know this (because they’re probably also on lockdown).  You can’t control the pandemic, but you can control your response.  So proactively manage your own expectations, your manager’s expectations and your donor’s expectations.

  • Get on a Skype or Zoom call with the project managers and review each indicator of your M&E plan. In light of the pandemic, what indicator targets will most likely change?
  • Look through the baseline numbers in your M&E plan – is it possible that the results at the END of your project might be worse than even your baseline numbers? For example, if you have a livelihoods project, it is possible that income and livelihoods will be drastically reduced by a country-wide lockdown.  Or are you running an education program?  If schools have been closed, then will a comparison to the baseline be possible?
  • Once you’ve done a review of your M&E plan, create a very simple revised plan that can be talked through with your program donor.

8. Talk To Your Donors About What You Can Do Remotely

When you’re on the phone with your donors, don’t only talk about revised program indicators.

  • Also talk about a revised timeframe – is there any flexibility on the program timeframe, or deadlines for interim reporting on indicators? What are their expectations?
  • Also talk about what you CAN do remotely. Discuss with them the plan you have for carrying on everything possible that can be done remotely.
  • And don’t forget to discuss financial implications of changes to timeframe.

 

Three Problems — and a Solution — for Data Viz in MERL and ICT4D

Guest post by Amanda Makulec, MPH, Data Visualization Society Operations Director

Just about everyone I know in the ICT4D and MERL communities has interacted with, presented, or created a chart, dashboard, infographic, or other data visualization. We’ve also all seen charts that mislead, confuse, or otherwise fall short of making information more accessible. 

The goal of the Data Visualization Society is to collect and establish best practices in data viz, fostering a community that supports members as they grow and develop data visualization skills. With more than 11.5K members from 123 countries on our first birthday, the society has grown faster than any of the founders imagined.

There are three reasons you should join the Data Visualization Society to improve your data visualizations in international development.

Self-service data visualization tools are everywhere, but that doesn’t mean we’re always building usable charts and graphs.

We’ve seen the proliferation of dashboards and enthusiasm for data viz as a tool to promote data driven decisionmaking.

Just about anyone can make a chart if they have a table of data, thanks to the wide range of tools out there (Flourish, RAWgraphs, Datawrapper, Tableau, PowerBI…to name a few). Without a knowledge of data viz fundamentals though, it’s easy to use these tools to create confusing and misleading graphs.

A recent study on user-designed dashboards in DHIS2 (a commonly used data management and analysis platform in global health) found that “while the technical flexibility of [DHIS2] has been taken advantage of by providing platform customization training…the quality of the dashboards created face numerous challenges.” (Aprisa & Sebo, 2020).  

The researchers used a framework from Stephen Few to evaluate the frequency of five different kinds of ‘dashboard problems’ on 80 user-designed sample dashboards. The five problem ‘types’ included: context, dashboard layout, visualization technique, logical, and data quality. 

Of the 80 dashboards evaluated, 69 (83.1%) had at least one visualization technique problem (Aprisa & Sebo, 2020). Many of the examples shared in the paper could be easily addressed, like transforming the pie chart made of slices representing points in time into a line graph.

With so many tools at our fingerprints, how can we use them to develop meaningful, impactful charts and interactive dashboards?  Learning fundamentals of data visualization is an excellent place to start, and DVS offers a free-to-join professional home to learn those fundamentals.

Many of the communities that exist around data visualization are focused on specific tools, which may not be relevant or accessible for your organization.

In ICT4D, we often have to be scrappy and flexible. That means learning how to work with open source tools, hack charts in Excel, and often make decisions about what tool to use driven as much by resource availability as functionality. 

There are many great tool specific communities out there: TUGs, PUGs, RLadies, Stack Overflow, and more. DVS emerged out of a need to connect people looking to share best practices across the many disciplines doing data viz: journalists, evaluators, developers, graphic designers, and more. That means not being limited to one tool or platform, so we can look for what fits a given project or audience.

After joining DVS, you’ll receive an invite to the Society’s’ Slack, a community “workspace” with channels on different topics and for connecting different groups of people within the community.  You can ask questions about any data viz tool on the #topic-tools channel, and explore emerging and established platforms with honest feedback on how other members have used them in their work.

Data visualization training often means one-off workshops. Attendees leave enthusiastic, but then don’t have colleagues to rely on when they run into new questions or get stuck.

Data visualization isn’t consistently taught as a foundation skill for public health or development professionals.

In university, there may be a few modules within a statistics or evaluation class, but seldom are there dedicated, semester long classes on visualization; those are reserved for computer science and analytics programs (though this seems to be slowing changing!).  Continuing education in data viz is usually short workshops, not long-term mentoring relationships. 

So what happens when people are asked to “figure it out” on the job? Or attend a two day workshop and come away as a resident data viz expert?  

Within DVS, our leadership and our members step up to answer questions and be that coach for people at all stages of learning data visualization. We even have a dedicated feedback space within Slack to share examples of data viz work in progress and get feedback.

DVS also enables informal connections on questions on a wide range of topics. Go to #share-critique, for posting work-in-progress visualizations and seeking feedback from the community. We also host quarterly challenges where you can do hands-on practice with provided data sets to develop your data viz skills and have plans for a formal mentorship program to launch in 2020.

Join DVS today to get its benefits – members from Africa, Asia, and other underrepresented areas are especially encouraged to join us now!

Have any questions? Or ideas on ways DVS can support our global membership base? Find me on Twitter – my DMs are open.

A Toolkit to Measure the Performance and Labour Conditions in Small and Medium Enterprises

Guest post from ILO The Lab

Performance measurement is critical not only to see whether enterprise development projects are making a difference, but so that small and medium enterprises (SME) themselves can continuously improve. As the saying goes: “If you can’t measure something, you can’t understand it. If you can’t understand it, you can’t control it. If you can’t control it, you can’t improve it.” In other words, the measurement of performance is the first step towards the management of performance.

Enterprise development projects need to measure changes in SME performance, not only to report results to project funders, but also to help SMEs continuously improve. But measuring the performance of SMEs in the context of a developing economy brings special considerations, including:

  • Pressing capacity challenges in record keeping, data collection, and access to modern management techniques – along with the technology that drives it. Most SMEs have some kind of performance measurement system, however, these tend to be very basic.
  • Intensely competitive environments where there is little market differentiation – meaning most SMEs have to tussle just to survive, reducing the incentive to collect and use data. Some countries have 5-year survival rates as low as 10%.
  • Flatter management structures, less bureaucracy and – in theory at least – can be more agile and adaptive to use performance information to improve.
  • SME’s dependence on productivity gains to maximise long-term competitiveness and profitability. In the absence of intellectual property or technology as a source of comparative advantage, labour productivity is often critical to sustaining SME performance.

Moreover, enterprise development projects are facing increasing pressure to demonstrate that their work is leading to qualitative improvements in people’s terms and conditions of employment. As researchers have noted, it is “not only the number, but also the quality of jobs matters to poverty alleviation and economic development”.

For many SMEs in the global south, workers are a critical determinant of business success. Since SMEs often undertake labour-intensive activates, they rely on a supply of labour – with varying skills requirements – to produce their goods and services. Labour and employment issues are frequently included in non-financial performance measurement systems, but they often only focus on the most easily quantifiable elements such as the number of accidents. However, labour conditions refer to the working environment and all circumstances affecting the workplace, including job hours, physical aspects, and the rights and responsibilities of SMEs towards their workers. Many aspects of this work environment are covered by national labour laws, which in turn are shaped by the eight fundamental ILO conventions.

By improving labour conditions, SMEs can improve their business outcomes. Better health and safety practices can boost productivity and employee retention. Companies have shown growth in sales per employee workforce hour following targeted training programmes. As recent research has demonstrated, jobs with decent wages, predictable hours, sufficient training, and opportunities for advancement can be a source of competitive advantage. For many businesses, thinking about employee working conditions has shifted from a way to minimize risk to a competitive advantage.

Conversely, bad conditions can be bad for business: Poor health and safety practices can result in fines and slow task completion. Industrial action and absenteeism can lead to prolonged disruption to operations. An SME owner says, “You have to have an environment where people are happy working, where they cooperate well, interact well. If you have problems in the way people work, it could terribly affect the performance”.

Against this complex framework and challenges, the International labour Organization has launched the ILO SME Measurement Toolkit

This Toolkit is a practical resource for practitioners and and projects to support SMEs decide what aspects of SME performance (productivity, working conditions, etc.) to measure, as well as how to measure them.

  • +250 indicators including a set of actionable metrics drawn from existing sustainability standards, company codes of conduct and international development monitoring and evaluation frameworks
  • Methods outlining different tools and data collection techniques
  • Real-life examples of SME measurement in a developing country context

We’d love to hear your comments, questions and suggestions about the Toolkit. Drop us an email at thelab@ilo.org!

More ILO The Lab’s resources on results measurement:

Open Call for ideas: 2020 GeOnG forum

Guest post by Nina Eissen from CartONG, organizers of the GeOnG Forum.

The 7th edition of the GeOnG Forum on Humanitarian and Development Data will take place from November 2nd to 4th, 2020 in Chambéry (France). CartONG is launching an Open Call for Suggestions.

Organized by CartONG every two years since 2008, the GeOnG forum gathers humanitarian and development actors and professionals specialized in information management. The GeOnG is dedicated to addressing issues related to data in the humanitarian and development sectors, including topics related to mapping, GIS, data collection & information management. To this end, the forum is designed to allow participants to debate current and future stakes, introduce relevant and innovative solutions and share experience and best practices. The GeOnG is one of the biggest independent fora on the topic in Europe, with an average of 180 participants from 90 organizations in the last three editions.

The main theme of the 2020 edition will be: “People at the heart of Information Management: promoting responsible and inclusive practices”. More information about the choice of this main theme is available here.

We also invite you to discover the 2020 GeOnG teaser here: 

To submit your ideas, please use this online form. The Open Call for Suggestions will remain open until the end of May 2020.

A few topics we hope to see covered during the 2020 GeOnG Forum:

  • How to better integrate vulnerable populations into the data life cycle, with a focus on ensuring that the data collected is particularly representative of populations at risk of discrimination.
  • How to implement the Do No Harm approach in relation to data: simple security & protection measures, streamlining of data privacy rights in programming, algorithmization of data processing, etc.
  • What is the role of the often considered ‘less direct stakeholders’ of humanitarian and development data (such as civil society actors, governments, etc.) so as to identify clearer pathways to share the data that should be shared for the common good and protect the data that should clearly not be shared.
  • How to promote data literacy beyond NGO information management and M&E staff to facilitate data-driven decision making.
  • How to ensure that tools and solutions used and promoted by humanitarian and development organizations are also sufficiently user-friendly and inclusive (for instance by limiting in-built biases and promoting human-centric design).
  • Beyond the main theme of the conference, don’t hesitate to send us any idea that you think might be relevant for the next GeOnG edition (about tools, methodologies, lessons learned, feedback from the field, etc.)!

Registration for the conference will open in the Spring of 2020.

 

 

Measuring Local Ownership in International Development Projects

by Rachel Dickinson, Technical Officer for Research and Learning, Root Change

“Localization”, measuring local ownership, USAID’s Journey to Self-Reliance… We’re all talking about these ideas and policies, and trying to figure out how to incorporate them in our global development projects, but how do we know if we are making progress on these goals? What do we need to measure?

Root Change and Keystone Accountability, under a recent USAID Local Works research grant, created the Pando Localization Learning System (LLS) as both a tool and a methodology for measuring and tracking local ownership within projects in real time. Pando LLS is an online platform that uses network maps and feedback surveys to assess system health, power dynamics, and collaboration within a local development system. It gives development practitioners simple, easy-to-use visuals and indicators, which can be shared with stakeholders and used to identify opportunities for strengthening local development systems.

We launched the Pando platform at MERL Tech DC in 2018, and this year we wanted to share (and get reactions to) a new set of localization measures and a reflective approach we have embedded in the tool. 

Analysis of local ownership on Pando LLS is organized around four key measures. Under each we have determined a series of indicators pulling from both social network analysis (SNA) and feedback survey questions. For those interested in geeking out on the indicators themselves, visit our White Paper on the Pando Localization Learning System (LLS), but the four measures are: 

1) Leadership measures whether local actors can voice concerns, set priorities and define success in our projects. It measures whether we, as outsiders, are soliciting input from local actors. In other words, it looks at whether project design and implementation is bottom-up.

2) Mutuality measures whether strong reciprocal, or two-way, relationships exist. It measures whether we, as external actors, respond to and act on feedback from local actors. It’s the respect and trust required for success in any interaction. 

3) Connectivity measures whether the local system motivates and incentivizes local actors to work together to solve problems. It measures whether we, as program implementers, promote collaboration and connection between local actors. It asks whether the local system is actually improving, and if we are playing the right roles. 

4) Financing measures whether dependency on external financial resources is decreasing, and local financial opportunities are becoming stronger. It measures whether we, as outsiders, are preparing local organizations to be more resilient and adaptive. It explores the timeless question of money and resources. 

Did you notice how each of these measures assesses not only local actors and their system, but also our role as outsiders? This takes us to the reflective approach.

The Pando LLS approach emphasizes dialogue with system actors and self-reflection by development practitioners. It pushes us to question our assumptions about the systems where we work and tasks us with developing project activities and M&E plans that involve local actors. The theories behind the approach can also be found in our White Paper, but here are the basic steps: 

  • Listen to local actors by inviting them to map their relationships, share feedback, and engage in dialogue about the results;
  • Co-create solutions and learn through short-term experiments that aim to improve relationships and strengthen the local system;
  • Incorporate what’s working back into development projects and celebrate failures as progress; and 
  • Repeat the listen, reflect, and adapt cycles 3-4 times a year to ensure each one is small and manageable.

What do you think of this method for measuring and promoting local ownership? Do we have the measures right? How are you measuring local ownership in your work? Would you be interested in testing the Pando LLS approach together? We’d love to hear from you! Email me at rdickinson@rootchange.org to share your feedback, questions, or ideas!