Linda Raftree supports strategy, program design, research, and technology in international development initiatives. She co-founded MERLTech in 2014 and Kurante in 2013. Linda advises Girl Effect on digital safety, security and privacy and supports the organization with research and strategy. She is involved in developing responsible data policies for both Catholic Relief Services and USAID. Since 2011, she has been advising The Rockefeller Foundation’s Evaluation Office on the use of ICTs in monitoring and evaluation. Prior to becoming an independent consultant, Linda worked for 16 years with Plan International. Linda runs Technology Salons in New York City and advocates for ethical approaches for using ICTs and digital data in the humanitarian and development space. She is the co-author of several publications on technology and development, including Emerging Opportunities: Monitoring and Evaluation in a Tech-Enabled World with Michael Bamberger. Linda blogs at Wait… What? and tweets as @meowtree. See Linda’s full bio on LInkedIn.
View all posts by Linda Raftree →
Guest post, Lauren Weiss, European Evaluation Society
As you may be aware, the European Evaluation Society’s biennial conference has been postponed to September 2021, due to the COVID-19 pandemic.
In the meantime, EES is continuing to work for you, and we are excited to announce the launch of two new initiatives.
First, our new podcast series, EvalEdge, is now available! It focuses on the role of evaluation in shaping how new and emerging technologies can be adapted in international development and in larger society. It explores the latest technological developments, from dig data and geospatial analysis, to blockchain and Internet of Things (IoTs).
Our first episode features MERL Tech’s co-founder Linda Raftree, who discusses innovative examples of using big data, the ethical considerations to be aware of, and much more! Check it out here!
Building on this momentum, EES is also launching a webinar series titled “Emerging Data Landscapes in M&E.” In partnership with Dev CAFÉ, MERL Tech, and the World Bank IEG, this series is devoted to discussing the use of innovative technologies in the world of evaluation.
This interactive and free webinar will provide concrete examples of using geospatial and location data to improve our M&E practices. It will also discuss the barriers to using such technologies and brainstorm on ways to overcome them, by inviting feedback and questions from the online audience.
It will include speakers from the World Bank IEG, the European Commission’s DEVCO/ESS, and the Global Environment Facility. You can find more information on our website.
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:
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
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.
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?
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.
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:
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.
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:
What definition, association, or conception (or definitions, associations, or conceptions) of harm emerge from M&E literature and practice?
Who are the key social actors who interact in M&E cycles?
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.
by Linda Raftree, Independent Consultant and MERL Tech organizer
Back in 2014, the humanitarian and development sectors were in the heyday of excitement over innovation and Information and Communication Technologies for Development (ICT4D). The role of ICTs specifically for monitoring, evaluation, research and learning (aka “MERL Tech“) had not been systematized (as far as I know), and it was unclear whether there actually was “a field.” I had the privilege of writing a discussion paper with Michael Bamberger to explore how and why new technologies were being tested and used in the different steps of a traditional planning, monitoring and evaluation cycle. (See graphic 1 below, from our paper).
The approaches highlighted in 2014 focused on mobile phones, for example: text messages (SMS), mobile data gathering, use of mobiles for photos and recording, mapping with specific handheld global positioning systems (GPS) devices or GPS installed in mobile phones. Promising technologies included tablets, which were only beginning to be used for M&E; “the cloud,” which enabled easier updating of software and applications; remote sensing and satellite imagery, dashboards, and online software that helped evaluators do their work more easily. Social media was also really taking off in 2014. It was seen as a potential way to monitor discussions among program participants, gather feedback from program participants, and considered an underutilized tool for greater dissemination of evaluation results and learning. Real-time data and big data and feedback loops were emerging as ways that program monitoring could be improved, and quicker adaptation could happen.
In our paper, we outlined five main challenges for the use of ICTs for M&E: selectivity bias; technology- or tool-driven M&E processes; over-reliance on digital data and remotely collected data; low institutional capacity and resistance to change; and privacy and protection. We also suggested key areas to consider when integrating ICTs into M&E: quality M&E planning, design validity; value-add (or not) of ICTs; using the right combination of tools; adapting and testing new processes before roll-out; technology access and inclusion; motivation to use ICTs, privacy and protection; unintended consequences; local capacity; measuring what matters (not just what the tech allows you to measure); and effectively using and sharing M&E information and learning.
We concluded that:
The field of ICTs in M&E is emerging and activity is happening at multiple levels and with a wide range of tools and approaches and actors.
The field needs more documentation on the utility and impact of ICTs for M&E.
Pressure to show impact may open up space for testing new M&E approaches.
A number of pitfalls need to be avoided when designing an evaluation plan that involves ICTs.
Investment in the development, application and evaluation of new M&E methods could help evaluators and organizations adapt their approaches throughout the entire program cycle, making them more flexible and adjusted to the complex environments in which development initiatives and M&E take place.
Where are we now: MERL Tech in 2019
Much has happened globally over the past five years in the wider field of technology, communications, infrastructure, and society, and these changes have influenced the MERL Tech space. Our 2014 focus on basic mobile phones, SMS, mobile surveys, mapping, and crowdsourcing might now appear quaint, considering that worldwide access to smartphones and the Internet has expanded beyond the expectations of many. We know that access is not evenly distributed, but the fact that more and more people are getting online cannot be disputed. Some MERL practitioners are using advanced artificial intelligence, machine learning, biometrics, and sentiment analysis in their work. And as smartphone and Internet use continue to grow, more data will be produced by people around the world. The way that MERL practitioners access and use data will likely continue to shift, and the composition of MERL teams and their required skillsets will also change.
The excitement over innovation and new technologies seen in 2014 could also be seen as naive, however, considering some of the negative consequences that have emerged, for example social media inspired violence (such as that in Myanmar), election and political interference through the Internet, misinformation and disinformation, and the race to the bottom through the online “gig economy.”
In this changing context, a team of MERL Tech practitioners (both enthusiasts and skeptics) embarked on a second round of research in order to try to provide an updated “State of the Field” for MERL Tech that looks at changes in the space between 2014 and 2019.
Based on MERL Tech conferences and wider conversations in the MERL Tech space, we identified three general waves of technology emergence in MERL:
First wave: Tech for Traditional MERL: Use of technology (including mobile phones, satellites, and increasingly sophisticated data bases) to do ‘what we’ve always done,’ with a focus on digital data collection and management. For these uses of “MERL Tech” there is a growing evidence base.
Second wave: Big Data. Exploration of big data and data science for MERL purposes. While plenty has been written about big data for other sectors, the literature on the use of big data and data science for MERL is somewhat limited, and it is more focused on potential than actual use.
Third wave: Emerging approaches. Technologies and approaches that generate new sources and forms of data; offer different modalities of data collection; provide ways to store and organize data, and provide new techniques for data processing and analysis. The potential of these has been explored, but there seems to be little evidence base to be found on their actual use for MERL.
We’ll be doing a few sessions at the American Evaluation Association conference this week to share what we’ve been finding in our research. Please join us if you’ll be attending the conference!
People are accessing the Internet, smartphones, and social media like never before, and the social and behavior change communication community is exploring the use of digital tools and social media for influencing behavior. The MERL Tech session, “Engaging for responsible change in a connected world: Good practices for measuring SBCC impact” was put together by Linda Raftree, Khwezi Magwaza, and Yvonne MacPherson, and it set out to help dive into Digital Social and Behavior Change Communication (SBCC).
Linda is the MERL Tech Organizer, but she also works as an independent consultant. She has worked as an Advisor for Girl Effect on research and digital safeguarding in digital behavior change programs with adolescent girls. She also recently wrote a landscaping paper for iMedia on Digital SBCC. Linda opened the session by sharing lessons from the paper, complemented by learning drawn from research and practice at Girl Effect.
Digital SBCC is expanding due to smartphone access. In the work with Girl Effect, it was clear that even when girls in lower income communities did not own smartphones they often borrowed them. Project leaders should consider several relevant theories on influencing human behavior, such as social cognitive theory, behavioral economics, and social norm theory. Additionally, an ethical issue in SBCC projects is whether there is transparency about the behavior change efforts an organization is carrying out, and whether people even want their behaviors to be challenged or changed.
When it comes to creating a SBCC project, Linda shared a few tips:
Users are largely unaware of data risks when sharing personal information online
We need to understand peoples’ habits. Being in tune with local context is important, as is design for habits, preferences, and interests.
Avoid being fooled by vanity metrics. For example, even if something had a lot of clicks, how do you know an action was taken afterwards?
Data can be sensitive to deal with. For some, just looking at information online, such as facts on contraception, can put them at risk. Be sure to be careful of this when developing content.
The session’s second presenter was Khwezi Magwaza who has worked as a writer and radio, digital, and television producer. She worked as a content editor for Praekelt.org and also served as the Content Lead at Girl Effect. Khwezi is currently providing advisory to an International Rescue Committee platform in Tanzania that aims to support improved gender integration in refugee settings. Lessons from Khwezi from working in digital SBCC included:
Sex education can be taboo, and community healthcare workers are often people’s first touch point.
There is a difference between social behavior change and, more precisely, individual behavior change.
People and organizations working in SBCC need to think outside the box and learn how to measure it in non-traditional ways.
Just because something is free doesn’t mean people will like it. We need to aim for high quality, modern, engaging content when creating SBCC programs.
It’s also critical to hire the right staff. Khwezi suggested building up engineering capacity in house rather than relying entirely on external developers. Having a digital company hand something over to you that you’re stuck with is like inheriting a dinosaur. Organizations need to have a real working relationship with their tech supplier and to make sure the tech can grow and adapt as the program does.
The third panelist from the session was Yvonne MacPherson, the U.S. Director of BBC Media Action, which is the BBC’s international NGO that was made to use communication and media to further development. Yvonne noted that:
Donors often want an app, but it’s important to push back on solely digital platforms.
Face-to-face contact and personal connections are vital in programs, and social media should not be the only form of communication within SBCC programs.
There is a need to look at social media outreach experiences from various sectors to learn, but that the contexts that INGOs and national NGOs are working in is different from the environments where most people with digital engagement skills have worked, so we need more research and it’s critical to understand local context and behaviors of the populations we want to engage.
Challenges are being seen with so-called “dark channels,” (WhatsApp, Facebook Messenger) where many people are moving and where it becomes difficult to track behaviors. Ethical issues with dark channels have also emerged, as there are rich content options on them, but researchers have yet to figure out how to obtain consent to use these channels for research without interrupting the dynamic within channels.
I asked Yvonne if, in her experience and research, she thought Instagram or Facebook influencers (like celebrities) influenced young girls more than local community members could. She said there’s really no one answer for that one. There actually needs to be a detailed ethnographic research or study to understand the local context before making any decisions on design of an SBCC campaign. It’s critical to understand the target group — what ages they are, where do they come from, and other similar questions.
Resources for the Reader
To learn more about digital SBCC check out these resources, or get in touch with each of the speakers on Twitter:
MERL and development practitioners have long wrestled with complex ethical, regulatory, and technical aspects of adopting new data approaches and technologies. The topic of responsible data has gained traction over the past 5 years or so, and a handful of early adopters have developed and begun to operationalize institutional RD policies. Translating policy into practical action, however, can feel daunting to organizations. Constrained budgets, complex internal bureaucracies, and ever-evolving technology and regulatory landscapes make it hard to even know where to start.
We don’t think organizations should do that anyway, given that each organization’s context and operating approach is different, and policy means nothing if it’s not rolled out through actual practice and behavior change!
In September, we hosted a MERL Tech pre-workshop on Operationalizing Responsible Data to discuss and share different ways of turning responsible data policy into practice. Below we’ve summarized some tips shared at the workshop. RD champions in organizations of any size can consider these when developing and implementing RD policy.
1. Understand Your Context & Extend Empathy
Before developing policy, conduct a non-punitive assessment (a.k.a. a landscape assessment, self-assessment or staff research process) on existing data practices, norms, and decision-making structures . This should engage everyone who will using or affected by the new policies and practices. Help everyone relax and feel comfortable sharing how they’ve been managing data up to now so that the organization can then improve. (Hint: avoid the term ‘audit’ which makes everyone nervous.)
Create ‘safe space’ to share and learn through the assessment process:
Allow staff to speak anonymously about their challenges and concerns whenever possible
Highlight and reinforce promising existing practices
Involve people in a ‘self-assessment’
Use participatory workshops (e.g. work with a team to map a project’s data flows or conduct a Privacy Impact Assessment or a Risk-Benefits Assessment) – this allows everyone who participates to gain RD awareness while also learning new practical tools along with highlighting any areas that need attention. The workshop lead or “RD champion” can also then get a better sense of the wider organizations knowledge, attitudes and practices as related to RD
Acknowledge (and encourages institutional leaders to affirm) that most staff don’t have “RD expert” written into their JDs; reinforce that staff will not be ‘graded’ or evaluated on skills they weren’t hired for.
Identify organizational stakeholders likely to shape, implement, or own aspects of RD policy and tailor your engagement strategies to their perspectives, motivations, and concerns. Some may feel motivated financially (avoiding fines or the cost of a data breach); others may be motivated by human rights or ethics; whereas some others might be most concerned with RD with respect to reputation, trust, funding and PR.
Map organizational policies, major processes (like procurement, due diligence, grants management), and decision making structures to assess how RD policy can be integrated into these existing activities.
2. Consider Alternative Models to Develop RD Policy
There is no ‘one size fits all’ approach to developing RD policy. As the (still small, but promising) number of organizations adopting policy grows, different approaches are emerging. Here are some that we’ve seen:
Top-down: An institutional-level policy is developed, normally at the request of someone on the leadership team/senior management. It is then adapted and applied across projects, offices, etc.
Works best when there is strong leadership buy-in for RD policy and a focal point (e.g. an ‘Executive Sponsor’) coordinating policy formation and navigating stakeholders
Bottom-up: A group of staff are concerned about RD but do not have support or interest from senior leadership, so they ‘self-start’ the learning process and begin shaping their own practices, joining together, meeting, and communicating regularly until they have wider buy-in and can approach leadership with a use case and budget request for an organization-wide approach.
Good option if there is little buy-in at the top and you need to build a case for why RD matters.
Project- or Team-Generated: Development and application of RD policies are piloted within a targeted project or projects or on one team. Based on this smaller slice of the organization, the project or team documents its challenges, process, and lessons learned to build momentum for and inform the development of future organization-wide policy.
Promising option when organizational awareness and buy-in for RD is still nascent and/or resources to support RD policy formation and adoption (staff, financial, etc.) are limited.
Hybrid approach: Organizational policy/policies are developed through pilot testing across a reasonably-representative sample of projects or contexts. For example, an organization with diverse programmatic and geographical scope develops and pilots policies in a select set of country offices that can offer different learning and experiences; e.g., a humanitarian-focused setting, a development-focused setting, and a mixed setting; a small office, medium sized office and large office; 3-4 offices in different regions; offices that are funded in various ways; etc.
Promising option when an organization is highly decentralized and works across a diverse country contexts and settings. Supports the development of approaches that are relevant and responsive to diverse capacities and data contexts.
3. Couple Policy with Practical Tools, and Pilot Tools Early and Often
In order to translate policy into action, couple it with practical tools that support existing organizational practices.
Make sure tools and processes empower staff to make decisions and relate clearly to policy standards or components; for example:
If the RD policy includes a high-level standard such as, “We ensure that our partnerships with technology companies align with our RD values,” give staff tools and guidance to assess that alignment.
When developing tools and processes, involve target users early and iteratively. Don’t worry if draft tools aren’t perfectly formatted. Design with users to ensure tools are actually useful before you sink time into tools that will sit on a shelf at best, and confuse or overburden staff at worst.
4. Integrate and “Right-Size” Solutions
As RD champions, it can be tempting to approach RD policy in a silo, forgetting it is one of many organizational priorities. Be careful to integrate RD into existing processes, align RD with decision-making structures and internal culture, and do not place unrealistic burdens on staff.
When building tools and processes, work with stakeholders to develop responsibility assignment charts (e.g. RACI, MOCHA) and determine decision makers.
When developing responsibility matrices, estimate the hours each stakeholder (including partners, vendors, and grantees) will dedicate to a particular tool or process. Work with anticipated end users to ensure that processes:
Can realistically be carried out within a normal workload
Will not excessively burden staff and partners
Are realistically proportionate to the size, complexity, and risk involved in a particular investment or project
5. Bridge Policy and Behavior Change through Accompaniment & Capacity Building
Integrating RD policy and practices requires behavior change and can feel technically intimidating to staff. Remember to reassure staff that no one (not even the best resourced technology firms!), has responsible data mastered, and that perfection is not the goal.
In order to feel confident using new tools and approaches to make decisions, staff need knowledge to analyze information. Skills and knowledge required will be different according to role, so training should be adapted accordingly. While IT staff may need to know the ins and outs of network security, general program officers certainly do not.
Accompany staff as they integrate RD processes into their work. Walk alongside them, answering questions along the way, but more importantly, helping staff build confidence to develop their own internal RD compass. That way the pool of RD champions will grow!
What approaches have you seen work in your organization?
The MERL Tech Conference explores the intersection of Monitoring, Evaluation, Research and Learning (MERL) and technology. The main goals of the conference and related community are to:
Improve development, tech, data & MERL literacy
Help people find and use evidence & good practices
Promote ethical and appropriate use of technology
Build and strengthen a “MERL Tech community”
Spot trends and future-scope for the sector
Transform and modernize MERL in an intentionally responsible and inclusive way
Our sixth MERL Tech DC conference took place on September 5-6, 2019, and we held four pre-workshops on September 4. Some 350 people from 194 organizations joined us for the 2-days, and another 100 people attended the pre-workshops. About 56% of participants attended for the first time, whereas 44% were returnees.
Attendees came from a wide range of organization types and professions.
The theme for this year’s conference was “Taking Stock” and we had 4 sub-themes:
As always, MERL Tech conference sessions were related to: technology for MERL, MERL on ICT4D and Digital Development programs, MERL of MERL Tech, data for decision-making, ethical and responsible data approaches and cross-disciplinary community building. (See the full agenda here):
We checked in with participants on the last day to see how the field had shifted since 2015, when our keynote speaker (Ben Ramalingam) gave some suggestions on how tech could improve MERL.
Diversity and Inclusion
We have been making an effort to improve diversity and inclusion at the conference and in the MERL Tech space. An unofficial estimate on speaker racial and gender diversity is below. As compared to 2018 when we first began tracking, the number of women of color speakers increased by 5% and women of color by 2%. The number of white female speakers decreased by 6% and the number of white male speakers went down by 1%. Our gender balance remained fairly consistent.
Where we are failing on diversity and inclusion is at having speakers and participants from outside of North America and Europe – that likely has to do with cost and visas which affect who can attend. It also has to do with who organizations select to represent them at MERL Tech. We’re continuing to try to find ways to collaborate with groups working on MERL Tech in different regions. We believe that new and/or historically marginalized voices should be more involved in shaping the future of the sector and the future of MERL Tech. (If you would like to support us on this or get involved, please contact Linda!)
Post Conference Feedback
Some 25% of participants filled in the post-conference survey and 85% rated their experience “good” or “awesome” (up from 70% in 2018). Answers did not significantly differ based on whether a participant had attended previously or not. Another 8.5% rated sessions via the “Sched” conference agenda app, with an average session satisfaction rating of 9.1 out of 10.
The top rated session was on “Decolonizing Data and Technology in MERL.” As one participant said, “It shook me out of my complacency. It is very easy to think of the tech side of the work we do as ‘value free’, but this is not the case. Being a development practitioner it is important for me to think about inequality in tech and data further than just through the implementation of the projects we run.” Another noted that “As a white, gay male who has a background in international and intercultural education, it was great to see other fields bringing to light the decolonizing mindset in an interactive way. The session was enlightening and brought up conversation that is typically talked about in small groups, but now it was highlighted in front of the entire audience.”
Sign up for MERL Tech News if you’d like to read more about this and other sessions. We’re posting a series of posts and session summaries.
Key suggestions for improving next time were similar to those we hear every year: less showcasing and pitching, ensure that titles match what is actually delivered at the session, ensuring that presenters are well-prepared, and making sessions relevant, practical and applicable.
Additionally, several people commented that the venue had some issues with noise from conversations in the common area spilling into breakout rooms and making it hard to focus. Participants also complained that there was a large amount of trash and waste produced, and suggested more eco-friendly catering for next time.
As noted, we are interested in finding a model for MERL Tech that allows for more diversity of voices and experiences, so we asked participants how often and where they thought we should do MERL Tech in the future. The majority (44.3%) felt we should run MERL Tech in DC every 2 years and somewhere else in the year in between. Some 23% said to keep it in DC every year, and around 15% suggested multiple MERL Tech conferences each year in DC and elsewhere. (We were pleased that no one selected the option of “stop doing MERL Tech altogether, it’s unnecessary.”)
Given this response, we will continue exploring options for partners who would like to support financially and logistically to enable MERL Tech to happen outside of DC. Please contact Linda if you’d like to be involved or have ideas on how to make this happen.
New ways to get involved!
Last year, the idea of having a GitHub repository was raised, and this year we were excited to have GitHub join us. They had come up with the idea of creating a MERL Tech Center on GitHub as well, so it was a perfect match! More info here.
We also had a request to create a MERL Tech Slack channel (which we have done). Please get in touch with Linda by email or via Slack if you’d like to join us there for ongoing conversations on data collection, open source, technology (or other channels you request!)
On September 6, we wrapped up three days of learning, reflecting, debating and sharing at MERL Tech DC. The conference kicked off with four pre-workshops on September 4: Big Data and Evaluation; Text Analytics; Spatial Statistics and Responsible Data. Then, on September 5-6, we had our regular two-day conference, including opening talks from Tariq Khokhar, The Rockefeller Foundation; and Yvonne MacPherson, BBC Media Action; one-hour sessions, two-hour sessions, lightning talks, a dashboard contest, a plenary session and two happy hour events.
This year’s theme was “The State of the Field” of MERL Tech and we aimed to explore what we as a field know about our work and what gaps remain in the evidence base. Conference strands included: Tech and Traditional MERL; Data, Data, Data; Emerging Approaches; and The Future of MERL.
In addition to learning and sharing, one of our main goals at MERL Tech is to create community. “I didn’t know there were other people working on the same thing as I am!” and “This MERL Tech conference is like therapy!” were some of the things we heard on Friday night as we closed down.
Stay tuned for blog posts about sessions and overall impressions, as well as our conference report once feedback surveys are in!