research help us solve our problems

Research to Solve Problems

The 2023 SSRC Centennial Lectures showcased a shared focus on not only describing problems, but also finding solutions to those problems. SSRC President Anna Harvey reflects on what it means to pursue research designed to solve problems, and how the SSRC can most effectively support problem-solving research.

During 2023, the Centennial year for the Social Science Research Council, we hosted ten Centennial lectures showcasing recent social and behavioral science on ten social problems central to the Council’s 100-year history of work: immigration , social insurance , racial discrimination , economic development , the green revolution , education , persistent poverty , climate change , democracy , and pandemic response (the recorded lectures are all available here ). A striking feature of these lectures was a shared focus on not only describing problems, but also finding solutions to those problems.

What does it mean to solve problems using social and behavioral science? In the first instance, the researchers who gave our Centennial lectures had all identified patterns of human decision making on questions such as migration, health, or employment that presented problems, in the sense that there plausibly existed decisions that could produce better outcomes for more people: e.g., higher incomes, less disease, less conflict. Further, these problems of decision making were all potentially responsive to the resources generally available to large organizations: e.g., money, information, attention, status. Alternative allocations of these resources could potentially shift decision making in ways that produced more societally beneficial outcomes. The researchers who gave our Centennial lectures were all looking for interventions that, by leveraging alternative allocations of available resources, could induce more societally beneficial decisions and actions.

But our Centennial lecturers weren’t seeking just any interventions that would work in this way. They were looking for effective interventions with a decent chance of being implemented into policy and practice at scale. From the very beginning of their research projects, they had looked down the path from identifying a problem of decision making, to developing a potential solution, to evaluating that solution, to implementation at scale by large-footprint organizations–governments, firms, large NGOs–and had designed their projects so as to maximize their chances of success at the end of that path. 

The interventions that were likely to be both effective and adopted at scale shared similar features, features that have also been identified in the implementation science literature: they were likely to be low cost, and not increasing in cost as they were scaled to larger populations ( Kremer et al 2021 , List 2022 ). They were likely to have been developed by or in partnership with a client organization, and designed to be integrated into the organization’s existing workflow ( Kremer et al 2021 , DellaVigna et al 2022 , Bonargent 2023 ). Their effectiveness was likely to have been evaluated using rigorous methods, including in some cases multiple small-scale evaluations, to guard against single-trial false positives at the pilot stage ( Kremer et al 2021 , List 2022 ).

Designing problem-solving research with implementation in mind at inception has clear benefits in a world of scarce research funds for social and behavioral science . Spending valuable research funds on evaluating potential solutions that have little chance of being implemented at scale, even if effective in small samples (e.g., because of increasing marginal costs), is not an efficient use of the research community’s limited resources. Building feasible implementation into research designs at inception is a potentially more cost-effective way to spend our scarce funding resources.

As we enter the Social Science Research Council’s second century of work, we have been reflecting on how the Council can best support social and behavioral science aimed at solving important problems. We have been reading the research on the research-to-policy pipeline, and have found much there that can guide our work. Our new website features the research undergirding our programs to support problem-solving social and behavioral science:

• we support fellowships giving researchers the time and freedom to pursue novel ideas, because unrestricted research funds are more likely to result in innovative policy solutions;
• we administer research grants underwriting the evaluation of new policy solutions, because rigorous evaluation increases the likelihood that effective solutions will be implemented at scale; 
• we host in-person convenings to share research-backed policy solutions with stakeholders and to incubate new research agendas, because such events lead to increased evidence uptake and to more productive collaborations; 
• we produce curated and accessible online knowledge platforms and technical reports , because these communication strategies increase the likelihood that research-based policy solutions will be widely adopted; 
• we offer mentoring programs to researchers underrepresented in their disciplines, because mentoring is a proven strategy to broaden problem-solving research opportunities.

As we launch the Council’s second century, we also look forward to engaging with new research on problem solving. This year’s College and University Fund Lecture Series will showcase new research illuminating practices increasing the likelihood that research-backed solutions will be implemented at scale; we look forward to sharing more information about this lecture series.

And finally, in 2024 we will be exploring new strategies to deploy the SSRC’s Agenda Fund to provide opportunities for researchers to use social and behavioral science to innovate new solutions to our most pressing social problems. Stay tuned for announcements of these upcoming opportunities.

Best wishes for a happy, healthy, and productive New Year!

Privacy Overview

• About the LSE Impact Blog
• Comments Policy
• Popular Posts
• Recent Posts
• Subscribe to the Impact Blog
• Write for us
• LSE comment

Ulviyya Khalilova

February 20th, 2024, understanding humans: how social science can help solve our problems – review.

0 comments | 7 shares

Estimated reading time: 10 minutes

In   Understanding Humans: How Social Science Can Help Solve Our Problems ,  David Edmonds   curates a selection of interviews with social science researchers covering the breadth of human life and society, from morality, bias and identity to kinship, inequality and justice. Accessible and engaging, the research discussed in the book illuminates the crucial role of social sciences in addressing contemporary societal challenges, writes  Ulviyya   Khalilova .

This blogpost originally appeared on  LSE Review of Books . If you would like to contribute to the series, please contact the managing editor at  [email protected] .

Understanding Humans: How Social Science Can Help Solve Our Problems . David Edmonds. SAGE. 2023.

In the  Social Science Bites  podcast series, David Edmonds, a Consultant Researcher and Senior Research Associate at the Oxford Uehiro Centre for Practical Ethics, collaborated with Nigel Warburton to explore the dynamics of modern society, interviewing eminent social and behavioural scientists on different topics. The engaging discussions that resulted led Edmonds to curate a selection of the episodes in a written format to bring the research to new audiences. The resulting book,  Understanding Humans: How Social Science Can Solve Our Problems , offers valuable insights into various aspects of human life and society, covering subjects from morality, bias and identity to kinship, inequality and justice.

Understanding Humans  […] offers valuable insights into various aspects of human life and society, covering subjects from morality, bias and identity to kinship, inequality and justice.

In his foreword to the book, Edmonds highlights that the selection of interviews, which translate into different chapters, reflect his own interests, though the criteria for their inclusion remains undisclosed. The book consists of eighteen chapters split between five thematic sections titled, respectively: Identity, How We Think and Learn, Human Behaviour, Making Social Change, and Explaining the Present, and Unexpected. Some topics introduced in one section can also fit into others, leading to overlaps between certain sections.

In the section on Identity, Sam Friedman discusses the insufficiency of education to eliminate the influence of class privilege, while Janet Carsten talks about the interconnectedness of kinship with politics, work, and gender. In his discussion of class, Friedman states that despite educational attainments, class privilege still significantly impacts career progression. The level of autonomy in the workplace, alongside one’s position and salary, could indicate whether career success correlates with social class. Friedman suggests that societal beliefs in meritocracy often overlook the inherent class-related barriers that hinder individuals’ opportunities for career development.

In the next section, Daniel Kahneman, Mahzarin Banaji, Gurminder K. Bhambra, Jonathan Haidt, Jo Boaler, and Sasika Sassen discuss various aspects of human thinking and learning. In his chapter on bias, Kahneman sheds light on biases in human thinking, discussing the dual processes of thinking: fast, associative thinking (System 1) and slower, effortful control (System 2). System 2 assists us in providing reasoning or explanations for our conclusions, essentially aiding in articulating our feelings and emotions. Education enhances System 2 and develops rational thinking, although achieving absolute rationality remains an elusive goal.

Boaler challenges the myth of innate mathematical ability, highlighting the crucial role of active engagement in developing mathematical skills.

In her chapter on the “Fear of Mathematics,” Boaler challenges the myth of innate mathematical ability, highlighting the crucial role of active engagement in developing mathematical skills. Deep thinking is crucial for developing maths skills, but it is a slow process that requires time. There is also a need for reforms in maths education, particularly addressing the issue of timed assessments that impede the brain’s capacity to develop mathematical skills effectively. Boaler states that the purpose of mathematics shouldn’t glorify speed, considering that many proficient mathematicians acknowledge working at a slower pace.

In the chapter “Before Method,” Sassen discusses how prior experiences shape research approaches, introducing the concept of “before method”, referring to both the desire for conducting research in a particular way and the actual execution of a research study. The rationale behind selecting a specific research method and topic is connected with the pre-existing experience preceding the method itself. Sassen challenges established categories by questioning whether it is possible to perceive things without initially considering categories, potentially influencing the direction of the study. She acknowledges that her awareness of prior research studies, established categories, and personal life experiences significantly shape her perception of the world as a researcher.

Following this, Stephen Reicher, Robert Shiller, David Halpern, and Valerie Curtis talk about various facets of human behaviour. Reicher discusses group dynamics, elucidating how physical proximity and psychological commonality foster different groups. Reicher also posits that group boundaries are loose and attributes this to the social changes, which, according to his explanation, result from a we-they dichotomy. Understanding intergroup interactions is crucial, particularly when individuals might not wish to be associated with confrontational aspects. However, belonging to a specific group often leads to labelling individuals, linking all their actions with that group, despite the distinctive nature of their involvement.

Halpern in his chapter on nudging explains that humans are not solely rational beings; their behaviour is influenced by various factors including impulses and emotions.

Halpern in his chapter on nudging explains that humans are not solely rational beings; their behaviour is influenced by various factors including impulses and emotions. He elaborates on how nudging proves beneficial for jobseekers, where incorporating specific human-related elements in emails encourages them to attend interviews. Halpern also posits that our inherent ‘groupish’ tendencies are intricately linked to human psychology. Various factors influence our proximity or distance from others, ultimately affecting societal progress, including economic development. Trust, for instance, varies significantly among different social classes. An individual from an impoverished social class facing financial challenges tends to have lower social trust. Conversely, someone from an affluent background might experience the opposite due to their social circle being influenced by their wealth.

Chenoweth’s research highlights the efficacy of nonviolent political action when contrasted with violent approaches, emphasising its higher success rates and potential to facilitate democratic transitions.

In the section on “Making Social Change” Jennifer Richeson, Erica Chenoweth, and Alison Liebling discuss how employing various approaches and research methods can drive social changes. Chenoweth’s research highlights the efficacy of nonviolent political action when contrasted with violent approaches, emphasising its higher success rates and potential to facilitate democratic transitions. Within the political sphere, an emerging trend is the digital revolution, distinct in some aspects from other revolutions. Erica Chenoweth also states that the digital revolution might foster a misleading impression by mobilising thousands to march in the streets.

In the section “Explaining the Present and the Unexpected,” Hetan Shah discusses the impacts of the Covid-19 pandemic on social and economic spheres, while Bruce Hood talks about supernatural attitudes or beliefs. Shah elucidates how the pandemic has shifted societal norms and behaviour. He also draws attention to the impact of these norms on human behaviour and the potential for fostering a fair society. Examining the pandemic from multiple angles – medical, social, and economic – deepens our understanding of human behaviour Shah emphasises that social sciences play a crucial role in unveiling how biases shape our thoughts and actions, addressing the social problems.

[Understanding Humans] provides readers with a compelling overview of exceptional research studies on how we think and act as individuals, and the social, economic, educational and political structures that we operate within.

Overall, the eclectic chapters in ‘Understanding Humans: How Social Science Can Solve Our Problems’ illuminate the profound role of social sciences in exploring and addressing social issues. This book serves as a valuable resource for a broad audience, being accessible and engaging for readers without prior knowledge or expertise in the fields drawn upon by the researchers. It provides readers with a compelling overview of exceptional research studies on how we think and act as individuals, and the social, economic, educational and political structures that we operate within.

The content generated on this blog is for information purposes only. This Article gives the views and opinions of the authors and does not reflect the views and opinions of the Impact of Social Science blog (the blog), nor of the London School of Economics and Political Science.  Please review our  comments policy  if you have any concerns on posting a comment below.

Image Credit:  tadamichi  on  Shutterstock .

About the author

Ulviyya Khalilova is a PhD student at University of Birmingham, UK. Her research focuses on cultural changes, values, identity, and social class within the contexts of Westernisation, modernisation, globalisation, and technological diffusion.

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Notify me of follow-up comments by email.

Related Posts

Art, Science and the Politics of Knowledge – review

January 26th, 2024.

By prioritising STEM over SHAPE in schools we poorly prepare students for a complex future

February 5th, 2024.

What new data can tell us about the essential role of social science to innovation

January 25th, 2024.

Excluding the social sciences, arts and humanities from reporting downplays their importance to research, development and innovation

August 3rd, 2023.

Visit our sister blog LSE Review of Books

Root out friction in every digital experience, super-charge conversion rates, and optimize digital self-service

Uncover insights from any interaction, deliver AI-powered agent coaching, and reduce cost to serve

Increase revenue and loyalty with real-time insights and recommendations delivered to teams on the ground

Know how your people feel and empower managers to improve employee engagement, productivity, and retention

Take action in the moments that matter most along the employee journey and drive bottom line growth

Whatever they’re are saying, wherever they’re saying it, know exactly what’s going on with your people

Get faster, richer insights with qual and quant tools that make powerful market research available to everyone

Run concept tests, pricing studies, prototyping + more with fast, powerful studies designed by UX research experts

Track your brand performance 24/7 and act quickly to respond to opportunities and challenges in your market

Explore the platform powering Experience Management

• Free Account
• Product Demos
• For Digital
• For Customer Care
• For Human Resources
• For Researchers
• Financial Services
• All Industries

Popular Use Cases

• Customer Experience
• Employee Experience
• Net Promoter Score
• Voice of Customer
• Customer Success Hub
• Product Documentation
• Training & Certification
• XM Institute
• Popular Resources
• Customer Stories
• Artificial Intelligence
• Market Research
• Partnerships
• Marketplace

The annual gathering of the experience leaders at the world’s iconic brands building breakthrough business results, live in Salt Lake City.

• English/AU & NZ
• Español/Europa
• Español/América Latina
• Português Brasileiro
• REQUEST DEMO

Academic Experience

How to identify and resolve research problems

Updated August 23, 2024

In this article, we’re going to take you through one of the most pertinent parts of conducting research: a research problem (also known as a research problem statement).

When trying to formulate a good research statement, and understand how to solve it for complex projects, it can be difficult to know where to start.

Not only are there multiple perspectives (from stakeholders to project marketers who want answers), you have to consider the particular context of the research topic: is it timely, is it relevant and most importantly of all, is it valuable?

In other words: are you looking at a research worthy problem?

The fact is, a well-defined, precise, and goal-centric research problem will keep your researchers, stakeholders, and business-focused and your results actionable.

And when it works well, it's a powerful tool to identify practical solutions that can drive change and secure buy-in from your workforce.

Free eBook: The ultimate guide to market research

What is a research problem?

In social research methodology and behavioral sciences , a research problem establishes the direction of research, often relating to a specific topic or opportunity for discussion.

For example: climate change and sustainability, analyzing moral dilemmas or wage disparity amongst classes could all be areas that the research problem focuses on.

As well as outlining the topic and/or opportunity, a research problem will explain:

• why the area/issue needs to be addressed,
• why the area/issue is of importance,
• the parameters of the research study
• the research objective
• the reporting framework for the results and
• what the overall benefit of doing so will provide (whether to society as a whole or other researchers and projects).

Having identified the main topic or opportunity for discussion, you can then narrow it down into one or several specific questions that can be scrutinized and answered through the research process.

What are research questions?

Generating research questions underpinning your study usually starts with problems that require further research and understanding while fulfilling the objectives of the study.

A good problem statement begins by asking deeper questions to gain insights about a specific topic.

For example, using the problems above, our questions could be:

"How will climate change policies influence sustainability standards across specific geographies?"

"What measures can be taken to address wage disparity without increasing inflation?"

Developing a research worthy problem is the first step - and one of the most important - in any kind of research.

It’s also a task that will come up again and again because any business research process is cyclical. New questions arise as you iterate and progress through discovering, refining, and improving your products and processes. A research question can also be referred to as a "problem statement".

Note: good research supports multiple perspectives through empirical data. It’s focused on key concepts rather than a broad area, providing readily actionable insight and areas for further research.

Research question or research problem?

As we've highlighted, the terms “research question” and “research problem” are often used interchangeably, becoming a vague or broad proposition for many.

The term "problem statement" is far more representative, but finds little use among academics.

Instead, some researchers think in terms of a single research problem and several research questions that arise from it.

As mentioned above, the questions are lines of inquiry to explore in trying to solve the overarching research problem.

Ultimately, this provides a more meaningful understanding of a topic area.

It may be useful to think of questions and problems as coming out of your business data – that’s the O-data (otherwise known as operational data) like sales figures and website metrics.

What's an example of a research problem?

Your overall research problem could be: "How do we improve sales across EMEA and reduce lost deals?"

This research problem then has a subset of questions, such as:

"Why do sales peak at certain times of the day?"

"Why are customers abandoning their online carts at the point of sale?"

As well as helping you to solve business problems, research problems (and associated questions) help you to think critically about topics and/or issues (business or otherwise). You can also use your old research to aid future research -- a good example is laying the foundation for comparative trend reports or a complex research project.

(Also, if you want to see the bigger picture when it comes to research problems, why not check out our ultimate guide to market research? In it you'll find out: what effective market research looks like, the use cases for market research, carrying out a research study, and how to examine and action research findings).

The research process: why are research problems important?

A research problem has two essential roles in setting your research project on a course for success.

1. They set the scope

The research problem defines what problem or opportunity you’re looking at and what your research goals are. It stops you from getting side-tracked or allowing the scope of research to creep off-course .

Without a strong research problem or problem statement, your team could end up spending resources unnecessarily, or coming up with results that aren’t actionable - or worse, harmful to your business - because the field of study is too broad.

2. They tie your work to business goals and actions

To formulate a research problem in terms of business decisions means you always have clarity on what’s needed to make those decisions. You can show the effects of what you’ve studied using real outcomes.

Then, by focusing your research problem statement on a series of questions tied to business objectives, you can reduce the risk of the research being unactionable or inaccurate.

It's also worth examining research or other scholarly literature (you’ll find plenty of similar, pertinent research online) to see how others have explored specific topics and noting implications that could have for your research.

Four steps to defining your research problem

Image credit: http://myfreeschooltanzania.blogspot.com/2014/11/defining-research-problem.html

1. Observe and identify

Businesses today have so much data that it can be difficult to know which problems to address first. Researchers also have business stakeholders who come to them with problems they would like to have explored. A researcher’s job is to sift through these inputs and discover exactly what higher-level trends and key concepts are worth investing in.

This often means asking questions and doing some initial investigation to decide which avenues to pursue. This could mean gathering interdisciplinary perspectives identifying additional expertise and contextual information.

Sometimes, a small-scale preliminary study might be worth doing to help get a more comprehensive understanding of the business context and needs, and to make sure your research problem addresses the most critical questions.

This could take the form of qualitative research using a few in-depth interviews , an environmental scan, or reviewing relevant literature.

The sales manager of a sportswear company has a problem: sales of trail running shoes are down year-on-year and she isn’t sure why. She approaches the company’s research team for input and they begin asking questions within the company and reviewing their knowledge of the wider market.

2. Review the key factors involved

As a marketing researcher, you must work closely with your team of researchers to define and test the influencing factors and the wider context involved in your study. These might include demographic and economic trends or the business environment affecting the question at hand. This is referred to as a relational research problem.

To do this, you have to identify the factors that will affect the research and begin formulating different methods to control them.

You also need to consider the relationships between factors and the degree of control you have over them. For example, you may be able to control the loading speed of your website but you can’t control the fluctuations of the stock market.

Doing this will help you determine whether the findings of your project will produce enough information to be worth the cost.

You need to determine:

• which factors affect the solution to the research proposal.
• which ones can be controlled and used for the purposes of the company, and to what extent.
• the functional relationships between the factors.
• which ones are critical to the solution of the research study.

The research team at the running shoe company is hard at work. They explore the factors involved and the context of why YoY sales are down for trail shoes, including things like what the company’s competitors are doing, what the weather has been like – affecting outdoor exercise – and the relative spend on marketing for the brand from year to year.

The final factor is within the company’s control, although the first two are not. They check the figures and determine marketing spend has a significant impact on the company.

3. Prioritize

Once you and your research team have a few observations, prioritize them based on their business impact and importance. It may be that you can answer more than one question with a single study, but don’t do it at the risk of losing focus on your overarching research problem.

Questions to ask:

• Who? Who are the people with the problem? Are they end-users, stakeholders, teams within your business? Have you validated the information to see what the scale of the problem is?
• What? What is its nature and what is the supporting evidence?
• Why? What is the business case for solving the problem? How will it help?
• Where? How does the problem manifest and where is it observed?

To help you understand all dimensions, you might want to consider focus groups or preliminary interviews with external (including consumers and existing customers) and internal (salespeople, managers, and other stakeholders) parties to provide what is sometimes much-needed insight into a particular set of questions or problems.

After observing and investigating, the running shoe researchers come up with a few candidate questions, including:

• What is the relationship between US average temperatures and sales of our products year on year?
• At present, how does our customer base rank Competitor X and Competitor Y’s trail running shoe compared to our brand?
• What is the relationship between marketing spend and trail shoe product sales over the last 12 months?

They opt for the final question, because the variables involved are fully within the company’s control, and based on their initial research and stakeholder input, seem the most likely cause of the dive in sales. The research question is specific enough to keep the work on course towards an actionable result, but it allows for a few different avenues to be explored, such as the different budget allocations of offline and online marketing and the kinds of messaging used.

Get feedback from the key teams within your business to make sure everyone is aligned and has the same understanding of the research problem and questions, and the actions you hope to take based on the results. Now is also a good time to demonstrate the ROI of your research and lay out its potential benefits to your stakeholders.

Different groups may have different goals and perspectives on the issue. This step is vital for getting the necessary buy-in and pushing the project forward.

The running shoe company researchers now have everything they need to begin. They call a meeting with the sales manager and consult with the product team, marketing team, and C-suite to make sure everyone is aligned and has bought into the direction of the research topic. They identify and agree that the likely course of action will be a rethink of how marketing resources are allocated, and potentially testing out some new channels and messaging strategies .

Can you explore a broad area and is it practical to do so?

A broader research problem or report can be a great way to bring attention to prevalent issues, societal or otherwise, but are often undertaken by those with the resources to do so.

Take a typical government cybersecurity breach survey, for example. Most of these reports raise awareness of cybercrime, from the day-to-day threats businesses face to what security measures some organizations are taking. What these reports don't do, however, is provide actionable advice - mostly because every organization is different.

The point here is that while some researchers will explore a very complex issue in detail, others will provide only a snapshot to maintain interest and encourage further investigation. The "value" of the data is wholly determined by the recipients of it - and what information you choose to include.

To summarize, it can be practical to undertake a broader research problem, certainly, but it may not be possible to cover everything or provide the detail your audience needs. Likewise, a more systematic investigation of an issue or topic will be more valuable, but you may also find that you cover far less ground.

It's important to think about your research objectives and expected findings before going ahead.

Ensuring your research project is a success

A complex research project can be made significantly easier with clear research objectives, a descriptive research problem, and a central focus. All of which we've outlined in this article.

If you have previous research, even better. Use it as a benchmark

Remember: what separates a good research paper from an average one is actually very simple: valuable, empirical data that explores a prevalent societal or business issue and provides actionable insights.

And we can help.

Sophisticated research made simple with Qualtrics

Trusted by the world's best brands, our platform enables researchers from academic to corporate to tackle the hardest challenges and deliver the results that matter.

Our CoreXM platform supports the methods that define superior research and delivers insights in real-time. It's easy to use (thanks to drag-and-drop functionality) and requires no coding, meaning you'll be capturing data and gleaning insights in no time.

It also excels in flexibility; you can track consumer behavior across segments , benchmark your company versus competitors , carry out complex academic research, and do much more, all from one system.

It's one platform with endless applications, so no matter your research problem, we've got the tools to help you solve it. And if you don't have a team of research experts in-house, our market research team has the practical knowledge and tools to help design the surveys and find the respondents you need.

Of course, you may want to know where to begin with your own market research . If you're struggling, make sure to download our ultimate guide using the link below.

It's got everything you need and there’s always information in our research methods knowledge base.

Scott Smith

Scott Smith, Ph.D. is a contributor to the Qualtrics blog.

Related Articles

April 1, 2023

How to write great survey questions (with examples)

February 8, 2023

Smoothing the transition from school to work with work-based learning

December 6, 2022

How customer experience helps bring Open Universities Australia’s brand promise to life

August 9, 2022

3 things that will improve your teachers’ school experience

August 2, 2022

Why a sense of belonging at school matters for K-12 students

July 14, 2022

Improve the student experience with simplified course evaluations

March 17, 2022

Understanding what’s important to college students

February 18, 2022

Malala: ‘Education transforms lives, communities, and countries’

Stay up to date with the latest xm thought leadership, tips and news., request demo.

Ready to learn more about Qualtrics?

Educational resources and simple solutions for your research journey

What is a Research Problem? Characteristics, Types, and Examples

A research problem is a gap in existing knowledge, a contradiction in an established theory, or a real-world challenge that a researcher aims to address in their research. It is at the heart of any scientific inquiry, directing the trajectory of an investigation. The statement of a problem orients the reader to the importance of the topic, sets the problem into a particular context, and defines the relevant parameters, providing the framework for reporting the findings. Therein lies the importance of research problem s.  

The formulation of well-defined research questions is central to addressing a research problem . A research question is a statement made in a question form to provide focus, clarity, and structure to the research endeavor. This helps the researcher design methodologies, collect data, and analyze results in a systematic and coherent manner. A study may have one or more research questions depending on the nature of the study.   

Identifying and addressing a research problem is very important. By starting with a pertinent problem , a scholar can contribute to the accumulation of evidence-based insights, solutions, and scientific progress, thereby advancing the frontier of research. Moreover, the process of formulating research problems and posing pertinent research questions cultivates critical thinking and hones problem-solving skills.   

Table of Contents

What is a Research Problem ?  

Before you conceive of your project, you need to ask yourself “ What is a research problem ?” A research problem definition can be broadly put forward as the primary statement of a knowledge gap or a fundamental challenge in a field, which forms the foundation for research. Conversely, the findings from a research investigation provide solutions to the problem .  

A research problem guides the selection of approaches and methodologies, data collection, and interpretation of results to find answers or solutions. A well-defined problem determines the generation of valuable insights and contributions to the broader intellectual discourse.  

Characteristics of a Research Problem  

Knowing the characteristics of a research problem is instrumental in formulating a research inquiry; take a look at the five key characteristics below:  

Novel : An ideal research problem introduces a fresh perspective, offering something new to the existing body of knowledge. It should contribute original insights and address unresolved matters or essential knowledge.   

Significant : A problem should hold significance in terms of its potential impact on theory, practice, policy, or the understanding of a particular phenomenon. It should be relevant to the field of study, addressing a gap in knowledge, a practical concern, or a theoretical dilemma that holds significance.  

Feasible: A practical research problem allows for the formulation of hypotheses and the design of research methodologies. A feasible research problem is one that can realistically be investigated given the available resources, time, and expertise. It should not be too broad or too narrow to explore effectively, and should be measurable in terms of its variables and outcomes. It should be amenable to investigation through empirical research methods, such as data collection and analysis, to arrive at meaningful conclusions A practical research problem considers budgetary and time constraints, as well as limitations of the problem . These limitations may arise due to constraints in methodology, resources, or the complexity of the problem.  

Clear and specific : A well-defined research problem is clear and specific, leaving no room for ambiguity; it should be easily understandable and precisely articulated. Ensuring specificity in the problem ensures that it is focused, addresses a distinct aspect of the broader topic and is not vague.  

Rooted in evidence: A good research problem leans on trustworthy evidence and data, while dismissing unverifiable information. It must also consider ethical guidelines, ensuring the well-being and rights of any individuals or groups involved in the study.

Types of Research Problems  

Across fields and disciplines, there are different types of research problems . We can broadly categorize them into three types.  

• Theoretical research problems

Theoretical research problems deal with conceptual and intellectual inquiries that may not involve empirical data collection but instead seek to advance our understanding of complex concepts, theories, and phenomena within their respective disciplines. For example, in the social sciences, research problem s may be casuist (relating to the determination of right and wrong in questions of conduct or conscience), difference (comparing or contrasting two or more phenomena), descriptive (aims to describe a situation or state), or relational (investigating characteristics that are related in some way).  

Here are some theoretical research problem examples :   

• Ethical frameworks that can provide coherent justifications for artificial intelligence and machine learning algorithms, especially in contexts involving autonomous decision-making and moral agency.  
• Determining how mathematical models can elucidate the gradual development of complex traits, such as intricate anatomical structures or elaborate behaviors, through successive generations.  
• Applied research problems

Applied or practical research problems focus on addressing real-world challenges and generating practical solutions to improve various aspects of society, technology, health, and the environment.  

Here are some applied research problem examples :   

• Studying the use of precision agriculture techniques to optimize crop yield and minimize resource waste.  
• Designing a more energy-efficient and sustainable transportation system for a city to reduce carbon emissions.  
• Action research problems

Action research problems aim to create positive change within specific contexts by involving stakeholders, implementing interventions, and evaluating outcomes in a collaborative manner.  

Here are some action research problem examples :   

• Partnering with healthcare professionals to identify barriers to patient adherence to medication regimens and devising interventions to address them.  
• Collaborating with a nonprofit organization to evaluate the effectiveness of their programs aimed at providing job training for underserved populations.  

These different types of research problems may give you some ideas when you plan on developing your own.  

How to Define a Research Problem  

You might now ask “ How to define a research problem ?” These are the general steps to follow:   

• Look for a broad problem area: Identify under-explored aspects or areas of concern, or a controversy in your topic of interest. Evaluate the significance of addressing the problem in terms of its potential contribution to the field, practical applications, or theoretical insights.
• Learn more about the problem: Read the literature, starting from historical aspects to the current status and latest updates. Rely on reputable evidence and data. Be sure to consult researchers who work in the relevant field, mentors, and peers. Do not ignore the gray literature on the subject.
• Identify the relevant variables and how they are related: Consider which variables are most important to the study and will help answer the research question. Once this is done, you will need to determine the relationships between these variables and how these relationships affect the research problem . 
• Think of practical aspects : Deliberate on ways that your study can be practical and feasible in terms of time and resources. Discuss practical aspects with researchers in the field and be open to revising the problem based on feedback. Refine the scope of the research problem to make it manageable and specific; consider the resources available, time constraints, and feasibility.
• Formulate the problem statement: Craft a concise problem statement that outlines the specific issue, its relevance, and why it needs further investigation.
• Stick to plans, but be flexible: When defining the problem , plan ahead but adhere to your budget and timeline. At the same time, consider all possibilities and ensure that the problem and question can be modified if needed.

Key Takeaways  

• A research problem concerns an area of interest, a situation necessitating improvement, an obstacle requiring eradication, or a challenge in theory or practical applications.   
• The importance of research problem is that it guides the research and helps advance human understanding and the development of practical solutions.  
• Research problem definition begins with identifying a broad problem area, followed by learning more about the problem, identifying the variables and how they are related, considering practical aspects, and finally developing the problem statement.  
• Different types of research problems include theoretical, applied, and action research problems , and these depend on the discipline and nature of the study.  
• An ideal problem is original, important, feasible, specific, and based on evidence.  

Frequently Asked Questions  

Why is it important to define a research problem?  

Identifying potential issues and gaps as research problems is important for choosing a relevant topic and for determining a well-defined course of one’s research. Pinpointing a problem and formulating research questions can help researchers build their critical thinking, curiosity, and problem-solving abilities.   

How do I identify a research problem?  

Identifying a research problem involves recognizing gaps in existing knowledge, exploring areas of uncertainty, and assessing the significance of addressing these gaps within a specific field of study. This process often involves thorough literature review, discussions with experts, and considering practical implications.  

Can a research problem change during the research process?  

Yes, a research problem can change during the research process. During the course of an investigation a researcher might discover new perspectives, complexities, or insights that prompt a reevaluation of the initial problem. The scope of the problem, unforeseen or unexpected issues, or other limitations might prompt some tweaks. You should be able to adjust the problem to ensure that the study remains relevant and aligned with the evolving understanding of the subject matter.

How does a research problem relate to research questions or hypotheses?  

A research problem sets the stage for the study. Next, research questions refine the direction of investigation by breaking down the broader research problem into manageable components. Research questions are formulated based on the problem , guiding the investigation’s scope and objectives. The hypothesis provides a testable statement to validate or refute within the research process. All three elements are interconnected and work together to guide the research.  

R Discovery is a literature search and research reading platform that accelerates your research discovery journey by keeping you updated on the latest, most relevant scholarly content. With 250M+ research articles sourced from trusted aggregators like CrossRef, Unpaywall, PubMed, PubMed Central, Open Alex and top publishing houses like Springer Nature, JAMA, IOP, Taylor & Francis, NEJM, BMJ, Karger, SAGE, Emerald Publishing and more, R Discovery puts a world of research at your fingertips.  

Try R Discovery Prime FREE for 1 week or upgrade at just US$72 a year to access premium features that let you listen to research on the go, read in your language, collaborate with peers, auto sync with reference managers, and much more. Choose a simpler, smarter way to find and read research – Download the app and start your free 7-day trial today !  

Related Posts

What is Research Impact: Types and Tips for Academics

Research in Shorts: R Discovery’s New Feature Helps Academics Assess Relevant Papers in 2mins 

• Work & Careers
• Life & Arts

Using research to solve real world problems

• Using research to solve real world problems on x (opens in a new window)
• Using research to solve real world problems on facebook (opens in a new window)
• Using research to solve real world problems on linkedin (opens in a new window)
• Using research to solve real world problems on whatsapp (opens in a new window)

By Rebecca Knight

Roula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.

In India, a country with a population of 1.2bn, fewer than 30 per cent of citizens have a passport, driver’s licence or other form of identification.

It may seem a minor point, except that the absence of these documents makes it difficult to apply for a bank account, obtain a mobile phone or even receive the government subsidies for education and food that individuals are entitled to.

But according to a new survey led by Arun Sundararajan, an associate professor of information, operations and management sciences at New York University’s Stern School of Business and a group of his students, that is changing. A government-sponsored project that began towards the end of 2010 to give every person in India a unique 12-digit ID number is showing signs of success. If enrolment continues according to projections, Prof Sundararajan reckons that about 300m citizens who previously did not have a portable ID will have one by the end of the year.

“It’s a moon-shot project,” says Prof Sundararajan. “It’s having a transformative impact on the lives of hundreds of millions of people.”

It is also, he hopes, a project that will have a transformative impact on the careers of the dozen MBA students who are working with him on the survey. The survey, which is analysing the impact of India’s Unique Identity project, is part of the Stern Consulting Corps programme.

International trips provide hands-on experience

To try to better prepare students to operate in the global economy, a number of leading business schools have introduced courses for MBAs to embark on international consulting projects.

The courses are designed to give students an applied learning experience that is very different from the one they receive on campus.

Harvard Business School , for instance, recently launched a year-long required course for its first-year students called “Field Immersion Experiences for Leadership Development”, or Field for short. The capstone of the course is a week-long trip to a developing country where student teams work closely with a company to develop an idea for a product or service.

Last year, projects were based in cities including Cape Town, Mumbai, Shanghai, Warsaw and Buenos Aires.

“Our aspiration is that it becomes so self-evident about how valuable this is that other schools do it too,” says Youngme Moon, who chairs HBS’s MBA programme.

Massachusetts Institute of Technology’s Sloan School , meanwhile, has expanded its G-Lab course in which students work with the management of overseas start-ups. Student teams work remotely from MIT for three months and full-time at their host companies for at least three weeks. Last year students worked on projects in Kenya, Colombia, Indonesia and other countries.

While some schools may view courses with an international consulting component as a way to “teach students how to be [a] consultant, it’s very much meant to be an interesting learning challenge,” says Michellana Jester, director of Sloan’s action learning programme.

According to her, business schools are using these courses to strike the right balance between academic rigour and relevance. “Scholarship is important and research is important, but how do you make it relevant for students in business schools today?

“It’s a transition for business schools right now in terms of how we navigate this,” she says.

SCC, an elective course now in its 10th year, began as a programme that placed students with local non-profits on 10-week project engagements. This year, for the first time, students worked on projects in emerging markets linked to faculty research. This new element provides students with vivid illustrations of how academic research can be used to solve real world problems.

“What [students] are gaining from this is an understanding of the potential of business to be an agent of social change,” says Prof Sundararajan. “It’s one thing to be exposed to examples of this in a textbook, it’s another to witness it first hand.”

As top schools strive to infuse their curricula with more hands-on learning experiences by adding overseas exchange programmes and class consulting projects in far-flung corners of the world, SCC stands out for its emphasis on research.

The new focus of the SCC programme reflects the increasing interest from MBA students in using their degrees to work on social policy issues. The programme is popular on campus: more than 100 students participated in the programme this past academic year and applications to the SCC rose 117 per cent this spring compared with last year.

Academic research is often accused of being ponderous, narrow and detached from the real world. But there is a new wave of research coming out of schools today that concerns how government and business can work together to solve big social problems, according to Professor Peter Henry, Stern’s dean.

There is also a growing recognition on the part of management faculty that the type of research they conduct about corporations has potentially broad applications for other kinds of organisations.

“There is a false dichotomy between research and the real world,” says Prof Henry. “Research can have a real impact.”

One group of students, for instance, worked on a business plan for a city that is being developed in Honduras. Because the city is a new concept, the business plan will have a direct effect on policy decisions in the country.

The students, under the supervision of Professor Paul Romer who heads the Urbanization Project, a research centre at Stern that focuses on urban growth and governance in the developing world, spent the semester devising potential scenarios for the city, such as population growth models and potential financial rules and regulations, as well as working up infrastructure estimates and writing policy briefs. Some of their findings were presented in a meeting Prof Romer had with Octavio Sánchez, chief of staff to the Honduran president.

“We’re getting students into the world through the lens of research,” says Prof Henry. “We’re giving students the chance to say, ‘I didn’t just take a set of classes. I built something’.”

Throughout the projects, students work closely with a faculty member and often develop the type of mentoring relationship that has typically been the province of PhD programmes. Teams also work with an outside mentor from a top-tier consulting company.

Students hone their analytical skills, but are also able to practise their professional responsibilities such as meeting a timeline and soliciting feedback from a client.

“The learning experience for the students was better than I expected,” says Prof Romer. “What they learnt was not just how to think abstractly about governance and fiscal policy – the kind of things you have to think about when you’re creating a new city – but also how will you work in teams, how will you divide tasks, what will you do when one sub-team gets stuck.”

The fact that students were working on a project with real world implications “lent more urgency to the group effort”, he says. “People are taking real decisions on [the students’ work]. A term paper doesn’t really matter. This goes out of the realm of a pretend exercise and makes it real.”

For students, the risk of working on such an engrossing project is that it can make other business school assignments seem dull or unworthy by comparison.

But Benjamin Wise, a student who worked on the Honduras project, says that it forced him to think about how to apply concepts learnt in the classroom.

“I’d be sitting in my corporate finance class on the edge of my seat because we were learning about a financial model that I couldn’t wait to plug in to [one of the models in] my project,” he says.

Prof Sundararajan says that spending a week in India was an eye-opening experience for his students.

“I could see them immersed in the context. They gained a clearer understanding of the breadth of vision and they could see what the problem was.

“This is the kind of immersive experiential learning that alters the worldview of students.”

Promoted Content

Follow the topics in this article.

• Business education Add to myFT
• Work & Careers Add to myFT
• MBA Add to myFT
• New York University Add to myFT
• Service correctionnel du Canada Add to myFT

Indigenous science can help solve some of the great problems of our time. Here’s how

Professor & Pro Vice-Chancellor (Indigenous), Monash University

Acting Pro Vice-Chancellor Research, Monash University

Disclosure statement

The authors do not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.

Monash University provides funding as a founding partner of The Conversation AU.

View all partners

Australia has committed to elevating Aboriginal and Torres Strait Islander knowledge as one of five national priorities in science and research.

This comes as part of the National Science Statement released on Monday by the Minister for Industry and Science, Ed Husic. The statement signals the national priorities that will shape investment and policy across research and development over the next decade.

Australian research already punches above its weight. The statement notes we produce 3.4% of the world’s research with just 0.33% of the world’s population. So how can we accelerate our impact?

Indigenous knowledge systems are a national strength. The history of science on this continent is extraordinary, yet we often fail to recognise the sophisticated knowledges held by our First Nations peoples. Indigenous voices must be at the table.

The first peoples, the first scientists

Aboriginal and Torres Strait Islander peoples were the first astronomers , physicists, biologists and pharmacists on this continent. From as far back as 65,000 years Indigenous people have been integrating knowledge systems with and for people and Country.

There are many examples of Indigenous knowledge contributing to contemporary problems. Traditional Aboriginal burning takes into account local weather conditions, plants, environments and animals. It is showing how plants react to fire , how to reduce the risk of major fire events, and support regeneration and biodiversity .

Indigenous-led approaches to urban water are pointing towards more sustainable water management practices that also regenerate ecological and cultural environments.

Beyond this, Indigenous approaches to research can challenge Western science models in important ways that can bring about new leaps of innovation.

The stakes are high

The new national statement comes at a time when we face existential threats in climate change, artificial intelligence, new pandemics, social unrest and beyond. Research remains crucial to finding solutions for our survival.

But we must approach the task of elevating these knowledge systems in the right way and be mindful of the ongoing legacies of colonisation.

Eminent Māori scholar Linda Tuhiwai Smith has noted: Indigenous people are considered the most researched in the world, and yet have seen the least amount of benefit. The legacy of these past practices continues to foster uncertainty and distrust of research (and researchers) by many in Indigenous communities.

This observation, based on engagement and conversations with communities, highlights an imbalance in research benefit between those who are studied and those who do the research. It is tied to centuries of colonisation.

Science has long adhered to the principle of “do no harm”. However, Western science has sometimes done harm. This was recently highlighted in Melbourne University’s book Dhoombak Goobgoowana , or truth-telling in the Woi Wurrung language, which described some of the terrible outcomes of colonial biases in science.

At the same time Western institutions and industries have extracted an extraordinary amount of knowledge from Indigenous peoples. According to the World Health Organization

around 40% of pharmaceutical products today draw from nature and traditional knowledge, including landmark drugs: aspirin, artemisinin [an ancient Chinese herbal malaria treatment], and childhood cancer treatments.

This has benefited humanity, and fattened the profits of many pharmaceutical companies. Yet Indigenous people have seen very little financial benefit – or even credit.

This is one of the many reasons we need to foster Indigenous-led research and engage communities in research.

A seat at the table – and more

Bringing more people to the table – both in research and at universities in general – will help us ask better questions. It will ensure people, especially Indigenous peoples, can lead or guide the research, see benefit and help build capacity in communities.

The Australian Institute of Aboriginal and Torres Strait Islander Studies code of ethics points the way forward. It centres Indigenous self-determination, Indigenous leadership, sustainability and accountability, and demonstrating impact and value. It all starts with listening, and ensuring that research addresses priorities determined and supported by Aboriginal and Torres Strait Islander people.

The National Science Statement calls for teamwork. It calls for research collaborations between universities, civil society, governments and international partners to solve some of our biggest societal, geopolitical, economic and environmental challenges.

This task also demands new approaches to what responsibility means in research. To create futures in which people can thrive, responsible research must go beyond compliance to formal rules of ethics and integrity.

It must ask much bigger questions about the place of research within local communities and much larger geopolitical environments. And it must reconsider how we partner well with the governments, industries and the communities with which we are embedded.

This takes us right back to the question of why we do research. Is it to publish more papers, or find a drug that makes a lot of money? Or are we here to make the world a better place?

It’s a question the National Statement on Science is asking. It is up to us to put it into practice.

• Aboriginal knowledge
• Indigenous knowledge
• Indigenous science
• First Nations
• Cultural burning
• Caring for Country
• Indigenous knowledges

Quantitative Analyst

Director of STEM

Community member - Training Delivery and Development Committee (Volunteer part-time)

Chief Executive Officer

Head of Evidence to Action

Can science and technology really help solve global problems? A UN forum debates vital question

Facebook Twitter Print Email

Science and technology offer part of the solution to climate change, inequality and other global issues, a United Nations official said on Tuesday, spotlighting the enormous potential these fields hold for achieving humanity’s common goal, of a poverty and hunger-free world by 2030.

“New advances in science and technology hold immense promises for achieving the 2030 Agenda for Sustainable Development ,” said UN Under-Secretary-General for Economic and Social Affairs, Liu Zhenmin, in his opening remarks to a session of the intergovernmental body overseeing the UN’s development work.

The 2018 Integration Segment of the Economic and Social Council (ECOSOC), being held from Tuesday to Thursday at UN Headquarters, brings together key stakeholders to review policies that support an integrated approach to achieving sustainable development and poverty eradication - with a focus this year on increasing resilience.

“To truly leverage the benefits of science and technology for sustainable development, we need to prioritize solutions that are pro-poor and equitable,” Mr. Liu said. “Only in this way can we ensure that no one is left behind.”

He stated that a rapidly warming planet was one of the greatest threats today, but a wide array of technological measures for climate change adaptation and mitigation can help the transition from carbon-intensive growth, towards more sustainable and resilient development.

Technologies can also help provide jobs to disadvantaged groups in society, and can help make cities smarter and more sustainable, by facilitating new transport systems and improving the management of natural resources.

To truly leverage the benefits of science and technology for sustainable development, we need to prioritize solutions that are pro-poor and equitable –  Liu Zhenmin, head of DESA

Threatened by unsustainable consumption and production patterns, the ocean is also suffering, he added. Numerous technologies have been shown to help mitigate and address these effects, such as innovations in sustainable fishing; enhanced surveillance of ocean acidification, and environmentally-sensitive forms of pollution prevention and clean-up, he added. 

To make new technology and innovation work in support of communities, any efforts must be driven on a local level, and be inclusive. 

Taking integrated approaches and working to break down barriers is of utmost urgency, too, as crises and shocks are increasingly complex and span the economic, social and environmental spheres. 

“And, finally, we need to build capacities and institutions for anticipating risk, and for planning and strategic foresight to effectively leverage technologies,” Mr. Liu said.

Also addressing the opening segment was Marc Pecsteen, Vice-President of the Economic and Social Council, who said that technology and innovation have been identified as “two key enablers, whose appropriate, efficient, equitable and sustainable use can support our efforts to build and maintain resilient societies.”

How can science solve all of our problems?

Category: Society      Published: September 25, 2013

By: Christopher S. Baird, author of The Top 50 Science Questions with Surprising Answers and Associate Professor of Physics at West Texas A&M University

Science can not solve all of our problems. While scientific understanding can help battle things like disease, hunger, and poverty when applied properly, it does not do so completely and automatically. Furthermore, there are many areas of life where science can have little impact. Let us look at some of the reasons why this is so.

First of all, there is a huge difference between knowing something and acting on it. Science is concerned with accumulating and understanding observations of the physical world. That understanding alone solves no problems. Individual people have to act on that understanding for it to help solve problems. For instance, science has found that regular exercise can lower your risk of heart disease . Knowing this fact is interesting, but it will do nothing for your personal heath unless you act on it and actually exercise. And that's the hard part. Reading an article about exercise is easy. Getting into an actual routine of regular exercise is harder. In this sense, science really solves no problems at all. Problems are only solved when people take the knowledge (or tool, or pill, or whatever) provided by science and use it. In fact, many of humanity's biggest problems are caused by lack of action, and not lack of knowledge.

Take world hunger, for example. There is currently enough food produced on the earth every year to comfortably feed every single person. The world produces about 700 trillion grams of rice each year. With seven billion people on the planet, 365 days in the year, and about 40 grams per typical serving of rice, there is enough rice on the planet to feed every single last person seven servings of rice every day. And this is just rice. Similar numbers hold up for wheat, corn, meat, etc. Science has done an amazing job in the last 50 years of making farms productive. And yet, millions of people in the world still suffer starvation. Why? Because of actions. If all it took was science to solve problems, no one would go hungry anymore because there is enough food. We could fill books with the analysis of human actions that cause world hunger if we wanted to, but let's just focus on a few factors to illustrate the point. A large portion of the world's food is simply wasted by lazy humans. People in affluent countries buy more food than they need, so that much of their food goes rotten and must be tossed before it is eaten. Or they pile more food on their plate than they could possibly eat and much of the food ends up in the trash. Another major factor is corrupt or incompetent governments who hoard food among a select few, poorly distribute food, or refuse to adopt modern agricultural methods. Tyrants sometimes even use forced hunger as a way to subdue the masses or punish opponents. Science can make an acre of farmland amazingly productive, but it can't force a dictator to give back the food he has stolen from his people.

Secondly, science can only tell us what exists and not what we should want as humans. Science can answer questions such as "is the average global temperature increasing?" but can never answer questions such as "what should humans do about global warming?" Such a question really depends on what humans want. Some humans want to be free to enjoy gas-guzzling trucks regardless of what long-term impacts this may have on the environment, while others want to force everyone to give up such freedoms in order to protect the environment. Settling who is "right" in such a debate is largely a matter of ethics, morality, and opinion; not science. If I am personally on the environmental side of the debate and am frustrated that countries can't pass more stringent environmental laws, my real problem is that too many people want something different (freedom) from what I want (environmental controls). Science can build cars that emit less pollution, but it cannot force people to drive those cars. It takes laws to force people to drive environmentally friendly cars, and laws are just the written wishes of the majority of the people (or of dictators).

Many of the "problems" that are discussed in the political sphere are not really problems at all in the scientific sense. They are simply a clash of human wants: one large faction wants one thing and the other faction wants something else. No one is really "right" in the scientific sense in such cases (although, fervent partisans are usually convinced they are always right and their opponents are always wrong). For instance, is it better to let the free market run a nation's healthcare system or should the government take over? The answer to this question really depends on how you define "better", which depends entirely on what you personally want. To people that want freedom above all else, "better" will mean letting the free market provide healthcare. To humans that want a uniform system that won't let people fall through the cracks, "better" may mean centralized medicine. The point is that neither side of the debate is "better" in a scientific sense, so science can never solve this problem. Science can save more lives through medical breakthroughs, and can even streamline the healthcare bureaucracy, but it can't find out if government-run or market-run healthcare is better, because "better" is so subjective. The same situation exists for many "problems" debated in the political sphere. For this reason, scientists do not make good political leaders. The role of political leaders is to ascertain and carry out the wants of the people, which science is fundamentally not equipped to do.

Lastly, many areas of life are simply too non-physical to be satisfactorily addressed by science. Love, hate, relationships, poetry, art, music, literature, and spirituality are all outside the realm of science. Any problems that arise in these areas cannot be completely solved by science.

Topics: healthcare , politics , science in politics , world hunger

• Need to solve an intractable problem? Collaboration is hard but worth it.

In This Section

• After an attempted assassination, how to turn back a rising tide of political threats and violence 
• The populism of self-destruction: How better policy can blunt the anti-clean energy backlash that threatens humanity’s future
• Public policy, values, and politics: Why so much depends on getting them right
• The Ghost Budget: How U.S. war spending went rogue, wasted billions, and how to fix it
• The Great Creep Backward: Policy responses to China’s slowing economy
• Two peoples. Two states. Why U.S. diplomacy in Israel and Palestine needs vision, partners, and a backbone
• We can productively discuss even the toughest topics—here’s how
• Legacy of privilege: David Deming and Raj Chetty on how elite college admissions policies affect who gains power and prestige

Complex problems facing cities like homelessness and climate change can only be solved by multiple organizations collaborating across boundaries, say Harvard Kennedy School faculty member Jorrit de Jong and Harvard Business School Professor Amy Edmondson. 

Featuring jorrit de jong and amy edmondson, november 9, 2023 42 minutes and 21 seconds.

Harvard Kennedy School faculty member Jorrit de Jong and Harvard Business School Professor Amy Edmondson say the big, intractable challenges facing city leaders today are too complex to be addressed by any one agency or government department. Complex challenges like the shortage of economic opportunity and affordable housing, homelessness, the effects of the climate crisis, and crime, can only be solved by multiple organizations working together. But that’s easier said than done. Bringing together government agencies, nonprofits, private businesses, academia, and the public into successful collaborations can be a huge challenge. Different people bring different agendas and goals. They don’t necessarily trust each other. Sometimes they can’t even agree on what the problem actually is, and they fail before even getting started. In a recent study, de Jong and Edmondson found that the most successful problem-solving collaborations have a number of things in common, including building a culture of safety and trust and being empowered to try, fail, and learn from mistakes. Sometimes, they say, the key can be just finding a place to start. 

Episode Notes:

Martínez Orbegozo, E. F., de Jong, J., Bowles, H. R., Edmondson, A., Nahhal, A., & Cox, L. (2022).  Entry Points: Gaining Momentum in Early-Stage Cross-Boundary Collaborations . The Journal of Applied Behavioral Science, 58(4), 595-645.  https://doi.org/10.1177/00218863221118418

Jorrit de Jong is the Emma Bloomberg Senior Lecturer in Public Policy and Management at Harvard Kennedy School. He is director of the Bloomberg Center for Cities at Harvard University. His research and teaching focus on the challenges of making the public sector more effective, efficient, equitable, and responsive to social needs. A specialist in experiential learning, he has taught strategic management and public problem-solving in degree and executive education programs at HKS and around the world. He is also faculty co-chair of the Bloomberg Harvard City Leadership Initiative, a joint program of Harvard Business School and Harvard Kennedy School, the world’s most comprehensive effort to advance effective problem-solving and innovation through executive education, research, curriculum development, and fieldwork in cities. 

He is also Academic Director of the Innovations in Government Program at the Kennedy School’s Ash Center for Democratic Governance and Innovation. In that capacity, he launched the  Innovation Field Lab , an experiential learning, executive education, and action-oriented research project working with 15 cities in Massachusetts and New York to help them leverage data, community engagement and innovation to revitalize distressed and underinvested neighborhoods. He holds a PhD in Public Policy and Management from Vrije Universiteit Amsterdam, as well as a master's in philosophy and a master's in public administration from Leiden University. He has written extensively, including the books “The State of Access: Success and Failure of Democracies to Create Equal Opportunities;” “Agents of Change: Strategy and Tactics for Social Innovation;” and “Dealing with Dysfunction: Innovative Problem Solving in the Public Sector.”  

Amy C. Edmondson is the Novartis Professor of Leadership and Management at the Harvard Business School, a chair established to support the study of human interactions that lead to the creation of successful enterprises that contribute to the betterment of society. Edmondson has been recognized by the biannual Thinkers50 global ranking of management thinkers since 2011, and most recently was ranked No. 1 in 2021. She also received that organization’s Breakthrough Idea Award in 2019, and Talent Award in 2017.   

She studies teaming, psychological safety, and organizational learning, and her articles have been published in numerous academic and management outlets. Her 2019 book, “The Fearless Organization: Creating Psychological Safety in the Workplace for Learning, Innovation and Growth,” has been translated into 15 languages. Her prior books: “Teaming: How organizations learn, innovate and compete in the knowledge economy;” “Teaming to Innovate;” and “Extreme Teaming” explore teamwork in dynamic organizational environments.  Edmondson’s latest book, “Right Kind of Wrong,” builds on her prior work on psychological safety and teaming to provide a framework for thinking about, discussing, and practicing the science of failing well. Edmondson received her PhD in organizational behavior, AM in psychology, and AB in engineering and design from Harvard University.  

Ralph Ranalli of the HKS Office of  Communications and Public Affairs is the host, producer, and editor of HKS PolicyCast. A former journalist, public television producer, and entrepreneur, he holds an AB in Political Science from UCLA and an MS in Journalism from Columbia University. 

The co-producer of PolicyCast is Susan Hughes . Design and graphics support is provided by Lydia Rosenberg , Delane Meadows , and the OCPA Design Team. Social media promotion and support is provided by Natalie Montaner and the OCPA Digital Team.  

For more information please visit our webpage or contact us at [email protected] .

This episode is available on Apple Podcasts, Spotify, and wherever you get your podcasts.

Preroll: (Ralph Ranalli): PolicyCast explores evidence-based policy solutions to the big problems we’re facing in our society and our world. This podcast is a production of the Kennedy School of Government at Harvard University. 

Jorrit de Jong (Intro): Let me give you one example, homelessness. You can think of that as one big problem, but if you break it down into smaller subsets of problems, you see that some people experiencing homelessness are dealing with mental illness and others are the victims of domestic violence, and yet others are experiencing substance abuse issues and others may have lost their house and are living below the poverty line. When you disaggregate a problem, you see a variety of different causes and consequences, but also it becomes very clear that, for some parts of the problem, you need the social services department, for another part of the problem, you need affordable housing, and for another part of the problem, you may need law enforcement or addiction help.  

Amy Edmondson (Intro): The problems can be roughly referred to as wicked problems, which are the kinds of problems that have incomplete, contradictory, and shifting requirements. They do not have easy answers and they impact different groups in different ways. They're just by their very nature hard to solve, and so you need the different perspectives both for the innovation and the creative problem solving that that allows, but also for the acceptability of the solution. If people aren't participating, then they're unlikely to appreciate and effectively use or implement solutions that just came in from outside and, "Here, we think this is going to fix your problem for you." 

Ralph Ranalli (Intro): Cities, like our world, are complex and interconnected places. So it’s hardly a surprise that our most intractable problems—lack of economic opportunity and affordable housing, homelessness, the effects of the climate crisis, crime—are that way too, complicated and seemingly hopelessly tangled, like that box of extensions cords you’re too afraid to bring up from the basement. Harvard Kennedy School faculty member Jorrit de Jong and Harvard Business School Professor Amy Edmondson say the big challenges facing city leaders today have another thing in common: they’re too tough to be addressed by any one agency or government department and can only be solved by multiple organizations working together. But that’s easier said than done. Bringing together city departments, nonprofits, private business, academia, and the public into successful collaborations can be a huge challenge. Different people bring different agendas and goals. They don’t necessarily trust each other. Sometimes they can’t even agree on what the problem actually is and they fail before even getting started. In a recent study, de Jong and Edmondson found that the most successful problem-solving collaborations have a number of things in common, including building a culture of safety and trust and being willing to try, fail, and learn from mistakes. Sometimes it's even just finding a place to start. Jorrit de Jong is the director of the Bloomberg Center for Cities at Harvard University and academic director of the Innovations in Government Program at the Ash Center for Democratic Governance and Innovation at HKS. Edmondson is the Novartis Professor of Leadership and Management at the Harvard Business School, whose books and writings on teamwork in successful organizations have been translated into 15 languages. They’re here with me today. 

Ralph Ranalli: Amy, Jorrit, welcome to PolicyCast. 

Jorrit de Jong: Thanks for having us. 

Amy Edmondson: Great to be here. 

Ralph Ranalli: We're talking today about cross-boundary collaboration, which I think is a term that a lot of people aren’t familiar with. Well maybe they're more familiar with the general concept, but can we start with a little bit about its origins in the context of solving intractable problems in cities and why it's important? Jorrit do you want to start us off? 

Jorrit de Jong: Sure. Well, the main thing about cross-boundary collaboration is that it is something that is necessary because the problems that we face in society today are multifaceted, they're complex, they're volatile and no single organization, unfortunately, is able to tackle them. When we talk about homelessness or climate change or poverty or crime, we need multiple organizations to work together to come up with a good diagnosis of what the problem is and then to generate ideas for action and then to implement those ideas. 

Ralph Ranalli: Amy? 

Amy Edmondson: Let me just even say something more basic, which is what's a boundary? I mean, a boundary is a line between groups. The kinds of groups that Jorrit and I studied include expertise groups, different sectors, different employers, different organizations, even different levels on a hierarchy. Having people come across those boundaries to do something together is what we studied. 

Ralph Ranalli: Right. The stakeholders are usually government, nonprofits and NGOs, the business community, and academia. Is there anything else on that list? 

Amy Edmondson: Well, I think, occasionally, citizens, community. 

Ralph Ranalli: Amy, you've written four books on the subject of teamwork including one where you said: "The work done in the modern organization is less and less about looking inward and creating strong teams inside a company and more about teaming across boundaries that are often in flux. What’s causing that shift to companies and organizations needing to look outwards? 

Amy Edmondson: Organizations are more and more dependent on the cooperation of and the contributions of people from other organizations. That can be as simple as suppliers and customer organizations where the degree to which you can collaborate effectively across those boundaries matters for the effective delivery of services and goods in supply chains of all kinds. That's just one ordinary way of doing business that involves that. Beyond that, there's a real interest for companies and government organizations and others to be working together to solve some of the more thorny problems that society faces. These are the kinds of problems that cannot be solved by one organization alone or even one sector working alone, so there's just more need for that kind of reaching out, reaching across, and collaborating. 

Ralph Ranalli: Jorrit, you're a leading scholar on collective governance to address multi-stakeholder problems. What are some examples of the problems that either can only be solved by or addressed or best addressed with cross-boundary collaboration? 

Jorrit de Jong: Yeah. I would say that there's almost no significant problem facing cities today that can be solved by a single organization. Local government obviously offers a variety of basic services and is responsible for law enforcement in a variety of different areas, but most of the problems— whether it's crime or economic development or homelessness—require multiple types of expertise, multiple skill sets, resources that cannot be offered by one organization alone and, therefore, if you really want to make progress on these issues, you can't go it alone. 

It makes sense that we have silos within government agencies. Division of labor is, of course, a very basic principle of organizational design. You can't do everything all at once, and therefore we've created departments, a department for buildings, a department for parks and recreation, a department of police, fire department and so forth, human services, but those departments are focused on the types of activities, types of services that they're responsible for. What we increasingly find is that the way problems manifest themselves in the real world requires interventions, actions and resources from multiple departments. Even within governments, you need cross-boundary collaboration where the boundaries are the departmental boundaries. 

Let me give you one example, homelessness. You can think of that as one big problem, but if you break it down into smaller subsets of problems, you see that some people experiencing homelessness are dealing with mental illness and others are the victims of domestic violence, and yet others are experiencing substance abuse issues and others may have lost their house and are living below the poverty line. When you disaggregate a problem, you see a variety of different causes and consequences, but also it becomes very clear that, for some parts of the problem, you need the social services department, for another part of the problem, you need affordable housing, and for another part of the problem, you may need law enforcement or addiction help.  

The way problems manifest themselves in cities, it's very varied. It varies from city to city. It varies from time to time. And it definitely depends on how you look at it. The way you look at it can inform the way you try to solve it. What we're claiming in this study is that the nature of these problems requires a more comprehensive, a broader, more holistic look and, therefore, it requires multiple organizations to look at it together and then to solve it together. 

Amy Edmondson: Right, and I'll just double down on that idea, the nature of the problems. I mean, the nature of the problems can be roughly referred to as wicked problems, which are the kinds of problems that have incomplete, contradictory, and shifting requirements. They do not have easy answers and they impact different groups in different ways. They're just by their very nature hard to solve, and so you need the different perspectives both for the innovation and the creative problem solving that that allows, but also for the acceptability of the solution. If people aren't participating, then they're unlikely to appreciate and effectively use or implement solutions that just came in from outside and, "Here, we think this is going to fix your problem for you." 

Ralph Ranalli: Right. I think we all have this lovely ideal of what collaboration looks like, right? But one of the things that struck me when I was reading your study is how difficult it is and how significant the barriers are that need to be broken down. On the one hand, we have a nice picture in your mind of people holding hands and singing kumbaya and everyone bringing their own expertise to bear on a problem in this lovely holistic way, but on the other you identified the process of just getting started as something that's difficult to the point where you used the term "disorientation" to talk about early phase of trying different groups together. Can you talk a bit about that notion of disorientation and why it's so difficult to get traction with cross-boundary collaborations? 

Jorrit de Jong: Absolutely. You may know the expression, "If you have a hammer, everything looks like a nail." If you are the Department of, let's say, Parks and Recreation, you look at a problem from that perspective and you think, "Oh, the problem to solve is to get this park clean and safe, and you may look at the people experiencing homelessness in that park as people that need to be removed, but if you are from the Department of Social Services, you look at the people in the park and you think, "Hey, we need to help these individuals," get them into housing, stabilize their condition and so forth, and you don't care as much about the park. Both are very legitimate perspectives, but very often—and this is what we found in a number of different studies that we conducted over the past 10 years—is that there are, in almost every cross-boundary collaboration phases, three major barriers.  

The very first one is how to define the problem. How do we define the problem in a way that generates sufficient consensus, not full consensus, but sufficient consensus to actually start working on it, because, if you don't see yourself in that problem definition, you're like, "What am I doing here?" It needs to be sufficiently inclusive to get the right parties on board and to get started. The second barrier is actually team building. Amy is, of course, an expert on this. It requires a certain kind of psychological safety—and maybe Amy you can say a little bit more about that—to actually engage in work where you don't know the problem yet and where you don't know the solution yet and where you don't maybe trust each other or understand each other enough yet to work together. 

The final barrier that we always find is multiple accountability challenges. You're committed to solving the problem and to working together, yet you're also on the payroll of your organization and, at the end of the day, your boss or your constituents will hold you accountable for the siloed organizational task and not the work that you did with other parties, and so there's this natural tension that occurs. 

Amy Edmondson: Yes. I mean, I'll build on that by saying, you mentioned psychological safety, and that's something that research, including my own, has shown is a really important factor in teamwork in general. And it's because it's not easy to be candid, it's not easy to speak up with a wild idea that people might laugh at, and it's not easy to ask for help if you don't understand something. Nobody likes to admit their ignorance or advertise their incompetence. I use those terms almost tongue in cheek, but we can naturally think, "Oh, someone will think I'm an idiot because I don't know something." It's much easier to hold back, wait and see. And so there's that challenge of speaking up. 

Roughly speaking, there's psychological, I mean, there's many psychological barriers, and you alluded to several, but just, "I don't maybe trust you because you come from a different department or a different background. I don't feel safe speaking up, honestly, candidly." There are so many things that get in the way of the innovation we're talking about, so it's much, much easier to fail than to succeed in this domain, and then layered on top of that are what I would call technological or logistical hurdles related to the jargon, different expertise areas, and different sectors have different jargon. The alphabet soup is a really big deal in the public sector and private sector, and so you can have people talking right by each other and really just struggling to have the effortless collaboration that you envision in this kumbaya moment that you recalled. You can't underestimate both the logistical, technological challenges and the psychological, sociological challenges. 

Ralph Ranalli: Sure. If you just think about the groups that you're talking about who are trying to collaborate with each other. One example is you've got nonprofits who are probably distrustful of for-profits. A lot of the time, that's a common nonprofit worldview. Then you've got for-profit businesses who are often distrustful of government, and … 

Amy Edmondson: ... and vice versa. 

Ralph Ranalli: Exactly, and vice versa. You talked about in the study about finding an entry point. Can you talk about that, Amy, maybe starting out with what is an entry point and how does one help you break through those initial difficulties and get a collaborative process moving? 

Amy Edmondson: Yeah. I guess what I will have to admit is that this is more descriptive, and I think it makes good sense theoretically and practically, but I'll tell you what we found. What we found was, as I alluded to earlier, that most, all the teams struggle, but the ones that end up making traction in their wicked problems and their challenging problems are the ones, now this will sound almost tautological, but they're the ones who found an entry point. There's a point at which, if you find an entry point, you get enough momentum to keep going through the hard work of teaming up across boundaries and making progress in new territory, and it's easy not to find one. 

What is an entry point? It took different forms in different projects, but we created this acronym, M-A-A-P. It means they found some way to get started that was meaningful. People could agree that this was connected to our broader goal even though it isn't a solution to our broader goal. It was meaningful. It was acceptable, meaning, different constituents would find it an okay thing to be working on. It was actionable, right? Again, not a magic wand or big solution to everything, but it was something you could go try, and it was provisional. I mean, it was almost deliberately seen by all as a starting point that, as we learn more together, we will get more clear, we will get better at making progress. 

Ralph Ranalli: At this point, I'd really like to if we can get into some concrete examples. In your study, you used the example of Manchester, New Hampshire. There were 10 other groups that were a big part of your study. Can you talk about how the group in Manchester, New Hampshire, found its entry point and what problem they were tackling? 

Jorrit de Jong: Absolutely. It's a great story, and I have to say it's not a story that is finished. It's a work in progress. I think it's fair to say that most of these problems are not solved. You can make progress. You can mitigate the problem, but there's only one way, as Amy suggested, to get started, which is to get started, but then you have to figure out and agree with this whole group, "Where do we start and how do we start?" There's often a theme that we see around the ideal is the enemy of good, right? We think we know enough about the problem to say that any tiny step in the right direction is not sufficient, because it will not solve the problem or it will not make progress fast enough, but what we've found in this study is that, if you start and focus on something small but meaningful, and if you make sure that you learn from that first step, you will see the next step and the next step and the next step. 

In Manchester, New Hampshire, they were facing multiple crises, homelessness on one the hand and opioid abuse on the other. There was overlap, but the city did not have data on how exactly these problems were intertwined, who was experiencing what problem or what condition and how to intervene as a city. Now, the parties in Manchester included social service providers, caregiving organizations, the police, fire departments, the Department of Public Works, but also the business community, especially downtown where business owners were complaining about people sleeping on the streets and panhandling. 

The mayor, Joyce Craig, really was worried about the situation and did not have necessarily enough resources for affordable housing or for the help, but she did know that just banning panhandling wasn't going to solve the problem. It's like fighting a symptom and not addressing the underlying problems. However, the business community was primarily interested in addressing that part of the problem because it mattered most to them and to their customers. What they agreed to do is to say, "Okay, we are going to think of panhandling as an entry point, but under one condition, that if we discourage panhandling, then we will make sure that the individuals that are being removed from the downtown area will be directed to treatment, to shelter, to social workers and so forth, and we will learn from what they're experiencing, what their needs are, and then we will use that to generate new funding and additional services so that we can make progress on the larger issue and the underlying problems."

Even though it looks like fighting a symptom to some and solving a problem to others, it allowed the group to start to work together, to look at the problem together, to learn from what works and what doesn't work together. And because they formed a coalition as such, they had a much better case to make to the state and to other funders. A few years later, they changed the structure in their governments. They have much more cross-silo collaboration in their government because they did find out that about 50% of the people who were homeless also were struggling with addiction problems. They changed their approach to helping the individuals, but they also helped create better conditions in downtown at the same time. 

Now, has it been solved? Absolutely not, but is the city in a better place to tackle the problem? Absolutely, and that is basically what we're seeing in all of those teams that are making progress. How they're getting traction is they start somewhere that is imperfect, but they learn, and as they learn they get to a better place. 

Amy Edmondson: One thing to just underline strongly here is that we've talked about, in a sense, to get started, you have to get started. And that might sound at first glance like a willpower problem where we just have to take the first step. I don't want to underplay how creative the first step was. 

This isn't a matter of: "It's obvious what the first step is. Let's just do it." This is truly a matter of: "We don't have a clue what the first step is because it's a wicked problem with multi-dimensional, multifaceted challenges." It's actually a team creative project to figure out an entry point, something that we can do that's meaningfully connected to our broader, ambitious goal that again is acceptable and something fundamentally we can learn from together. 

Jorrit de Jong: One other example that I really love, and not just because it's from my home country, the Netherlands, is the problem that they had in the City of Breda with illegal grow houses. They were growing marijuana. 

The idea was, or the suspicion was, that organized crime was exploiting or coercing low-income residents to use their attics and basements for this illegal activity. The police and the prosecutor's office had been trying the traditional law enforcement approach, but the community wouldn't want to work with them because they were afraid or didn't trust law enforcement.  

Then they started working within a utility company that had been experiencing electricity theft because grow houses take a lot of electricity. They also worked with the City of Breda, which was interested in community engagement, and they worked with a tax office who was interested in money laundering related to organized crime. They came up with a very different approach, and they found their entry points were focused on fire safety, because everybody cares about fire safety because your family needs to be safe, and so- 

Amy Edmondson: Neighbor could be- 

Jorrit de Jong: Your neighbors could be having a grow house and create that risk for you because they're using the electricity and the wiring catches fire because of the overuse, the overload. They started knocking on doors and said , "Hey, here's what you need to know about fire safety. If you smell this smell," and they had a sample with them, "then you might be at risk, and so you need to report that." That was a way to build trust with the community. Well, did it solve organized crime? Did it end illegal grow houses? No, but at least they found a way, literally, into the houses, an entry point, but also into the problem and, from there, they learned and adjusted their approach. I think that's another example of not giving up on the goal, the ultimate goal, but just structuring the process of learning. 

Ralph Ranalli: It's wonderful when these things succeed, but they don't all succeed. What have you found about when they fail, why they fail? 

Amy Edmondson: In a way, I mean, this is a bit tautological, but they fail because they fail to overcome the very real hurdles. These challenges are both creative challenges, they're political, they're effortful. There's lots and lots of pushback and barriers. They're overwhelming, so it's almost the assumed outcome that they will struggle anyway. 

Ralph Ranalli: You talk in the study about inherent paradoxes. Can you expound on that a little bit? 

Jorrit de Jong: Sure. There's a chicken-and-egg issue which is interesting to think about. For busy people and organizations with limited resources to commit to a collaboration, they need to know what's in it for them or why it would be important for them to participate. But you don't know that until you actually start looking at the problem together.  

For example, the growing house case did not include the fire department at first. It did include the tax office. Now, when you would have asked the fire department, "Hey, do you want to go chase organized crime in this neighborhood?" They're like, "Why would we do that?" They're like, "We got fires to put out. Organized crime is not in our job description," but because they learned more about the problem, and one part of it was the fire risk, then it became more relevant for the fire to be included. 

Here's the other thing. The tax office was less relevant, and you can imagine this poor tax inspector who would go to you about like, "What have you been doing lately, John?" and then, "Well, I've been finding illegal grow houses and detecting fire risk." Well, that's not your job description either, so you can see that, because all these problems were multifaceted, that a case has to be made for involvement and inclusion and participation. The inherent paradox there is that you need to have a broader group to work and look at the problem, but in order to get that group to look at the problem, you need to have a sufficient idea of what you're doing. That cannot be resolved one way or the other, other than just getting started and trying something out. 

Amy Edmondson: Yeah, and people who are willing to just be operating slightly outside their normal job description and willing to be creative and not worry so much about: "Is this my boss' number one priority right now?" because they glimpse an opportunity to make a real difference in something that speaks to them and matters to the community. 

Ralph Ranalli: Right, and you go back to the trust issue, too. You need to trust enough to have collaboration, but you also build trust through collaboration, so we're back to chickens and eggs. 

Amy Edmondson: It's chickens and eggs for sure. I'm not sure it's paradoxes. To me, the word paradox is overused. I shouldn't maybe say that, but it technically means two things that can't both be true at the same time, versus I think what we're talking about is a little bit more interesting and subtle, which is it's hard to get started and it's hard to know which comes first, the chicken or the egg. 

Ralph Ranalli: I love that you quoted the philosopher John Dewey and his saying that: “A problem well put is a problem half solved.” But that's not necessarily easy either. What happens when you can't even agree on the problem? I live in a suburb of Boston and our local political dividing line basically breaks down along the issue of affordable housing. One group identifies the lack of affordable housing as the problem, where the other basically views the impulse to build more affordable housing as the problem. What happens when you can’t agree on  whether a problem actually exists?  

Amy Edmondson: In a way, it's everything. It's the frame. With that frame, if you get stuck and stay in that frame, you will get nowhere. That is a guarantee because neither side is going to willingly change their view of the problem. What's needed is something that both sides care about, the future, the children and the future, or things along those lines, access to our schools, what have you.  

I won't try to solve that particular problem in your particular area, but the only way to break out and go forward is by finding an overarching shared goal or value that we both care about and then we get to start to take baby, creative steps toward what might this look like to help us resolve some of that very real tension. 

Jorrit de Jong: I would also say that a lot of this work was informed by Bloomberg Harvard City leadership program that Amy and I both teach in. It's a program for mayors and their senior teams. Mayors are often the ones nominating a problem for action. They run on a campaign platform, and they want to do something about inclusive growth or climate resilience or crime, and then, when they create a task force or try to build a coalition around that problem, it is important for them to know that, yes, they need to say, "This is the problem that I care about."  

But they also, as authorizers of this work, need to keep an open mind and be flexible because, if they're not flexible, the group will be reluctant to zoom in on one particular entry point that doesn't immediately make sense. Knowing what the nature is of this work—going back to Amy's notion earlier about the wicked problem—acknowledging and being explicit that you expect the group to learn rather than to deliver on the specific thing you're asking them to do.  What we've seen is that the role of authorizers is often understudied. One of the things that we see in the groups is those groups that felt like they had agency—they had the license to innovate and the permission to learn and develop as they went along—those groups were more successful in making progress. In our executive education program for mayors, both Amy and I spent a lot of time like, "How can leaders create the conditions for these diverse teams to do their work and to make meaningful progress?" 

Ralph Ranalli: I was interested in the personal aspect of when these collaborations start achieving success. What have you seen in terms of transformations in people's attitudes and outlooks when all of a sudden things start clicking and positive things start happening? What have you seen in terms of changes in the participants once this cross-boundary collaboration starts working? 

Amy Edmondson: I'll just say more abstractly, and then maybe Jorrit can give more concrete observations, but more abstractly, they start to feel like a "we" rather than, "I'm here. I'm from tax," or, "I'm from fire," or, "I'm from city hall.” They start to be part of the homelessness task force. They start to feel like each other as a mighty resource and that they start to care about each other, they start to care about their work together. 

Jorrit de Jong: Yeah. A colleague of ours, Ronnie Heifetz, uses the metaphor of a vegetable soup where you can throw different types of vegetables in a pan and add cold water, and then these vegetables will remain the same thing and there's no blending. You can also turn up the heat and cook them to pieces, and it's like one ratatouille, but the idea is to raise the temperature enough so that the individual vegetables still keep their taste and their shape, but they also start to form like a vegetable soup. Very often, we think of these processes of cross-boundary collaboration as pressure cookers. Without heat, there will be no dinner, but with too much heat, there will also be no dinner or it won't taste very well. Getting the temperature right, raising the pressure, creating a holding environment if you like around a group, which is what we do in our Executive Education programs, we bring people together and support them as they engage with the work and with each other and regulate the temperature so that they get to a level of productivity and trust that is required to make progress. 

Ralph Ranalli: You also teach this in the Executive Education program. Why is it important to connect with that audience? 

Amy Edmondson: I mean, I think, in professional schools, certainly in the Kennedy School and the Business School at Harvard, our goal is knowledge for action. Our research is always in the back of our minds. Sometimes, in the very front of our minds is how would this work? What can we learn about how to help people in tough jobs, tough leadership roles? How can we help them do a better job in achieving their results? 

One of the ways that we both share, but also develop our insights is in the executive classroom. We are teaching there, but we are also learning from them, from their feedback, from their examples, from their stories. We use the case method quite deliberately so that we have some principles that we're trying to convey and make them memorable and sticky through the stories, but we also want to hear their stories and how they've seen this work in practice, so that allows us to learn, that allows them to learn. 

Jorrit de Jong: Yeah, I would say I fully agree with that. A lot of the research questions come from practice and come from our interactions with mayors and their senior leaders and others. The work that we do at Harvard is  only good if it's both rigorous and relevant. If it's only rigorous and not relevant, we wouldn't want to do it because why? 

Amy Edmondson: If it's only relevant and not rigorous, then we don't feel so good either. 

Jorrit de Jong: Exactly, because you don't want to be sharing just ideas that are not rooted in research, right? That's why Amy and I and the whole group of authors, when we learned early on that mayors were struggling with cross-boundary collaboration and forming coalitions and task forces, we said like, "That's a really interesting research question." Amy had done research for many years on teaming and increasingly on wicked problem solving. I had been doing a lot of work on collaborative governance, but mostly at national or even international levels. We felt like, if we could combine our expertise and bring in some other colleagues, Hannah Riley Bowles, Eva Flavia Martinez Orbegozo, Jan Rivkin, and Mark Moore, then we could actually fill that gap. 

The studies that we've recently published are the first fruits of that labor, and we immediately bring it back to the classroom. When we teach now, we refer to these studies and we say, "Well, we don't have the definitive answer to the question how to do this, but we have some ideas that may help you guide the work as you go along." 

Amy Edmondson: We see if it resonates. Does it resonate? 

Ralph Ranalli: We've been talking about using this approach at the city level, but a lot of the problems that cities are facing are national and international in scope: climate readiness, the green energy transition, migration. Does the cross-boundary collaboration approach scale up? 

Jorrit de Jong: Well, we haven't done that research yet, but I think what we are seeing in the cross-sector collaborations in cities, those themes are not necessarily only happening in cities. It's much more about different professions, disciplines, organizational realities trying to work together than that it is about city-specific issues. Obviously, at the national level and at the international level, you have many more wicked problems, and some are the same, climate change, poverty, drugs, crime. Anywhere where people try to make progress on wicked problems, you will see the same types of mechanisms, barriers and patterns. Therefore, our hypothesis is that this applies to other contexts as well, but we haven't done that research yet. 

Amy Edmondson: We haven't done that research, but I think, if you look to any effective body that has trudged, made a dent in something, maybe child labor or human trafficking at a more global scale versus a local city scale, you will always find the requirement of different areas of expertise more often than not coming from multiple organizations, the NGOs, governments, business, large business players. Obviously, not all of these efforts are successful, but if they're serious, they will nearly always involve cross-boundary collaboration. 

Ralph Ranalli: We've reached the point in the podcast where we put the policy in PolicyCast, which is where I'm going to ask you for some specific recommendations, and in this case I think policy recommendations. Do you have any  policies that would encourage or make it easier to create successful cross-boundary collaborations or to help them along the road to success? What policies could turbocharge this process, which has shown that it can make a dent in big and intractable problems? 

Amy Edmondson: This is where I'm not a policy person, so I could just have a free ride here, but I will say one thing. I mean, one policy thing that occurs to me is making funding available. I think, oftentimes, funding is only available for things that are really clear cut and proven and have been done before. Making seed funding available for this kind of exploratory work is something that I think could be a policy issue. 

Jorrit de Jong: I don't think it is a policy question. I think it's a leadership question and a management question. What is helpful for creating and sustaining cross-boundary collaboration is for authorizers to be supportive of the process of, as Amy calls it, execution as learning, so try something out, come back and hold teams accountable for learning.  

What I always tell authorizers is that, if you say, "Well, have you fixed the problem?" then everybody is going to be very fixed on delivering exactly what they think the authorizer expects. And that may not be the best thing for solving the problem. What you have to do as an authorizer is to say, "Well, I expect you to do something" and whether it works or not … 

Amy Edmondson:  … learn from it … 

Jorrit de Jong:  ... it doesn't matter, but you have to come back and tell me, "This is what I've done. This is what worked. This is what didn't work. This is what I've learned or what we have learned, and this is the next step that we're thinking of taking, and we want authorization for that next iteration."  

I think that is a very different way of providing guidance and support and sponsorship than many authorizers are used to. I would say, if that's something, if you're a mayor or if you're a secretary, the national government or if you're a CEO even, then that's the difference in how you create the conditions for this type of work to be successful. 

Ralph Ranalli: Great. Well, I would just like to thank you both. This was a really interesting conversation that I enjoyed very much. Thanks for your time. 

Amy Edmondson: Thanks for having us. 

Ralph Ranalli (Outro) : Thanks for listening. Please join us for our next episode, when Harvard Kennedy School Professor David Deming and Harvard University Economics Professor Raj Chetty will discuss their research on how legacy preference affects college admissions.  

And please subscribe to PolicyCast on your favorite podcasting app so you don’t miss any of our great upcoming episodes. If you have a comment or a suggestion for the team here at PolicyCast, please drop us an email at [email protected]—we’d love to hear from you. And until next time, remember to speak bravely, and listen generously. 

More from PolicyCast

Suggestions or feedback?

MIT News | Massachusetts Institute of Technology

• Machine learning
• Sustainability
• Black holes
• Classes and programs

Departments

• Aeronautics and Astronautics
• Brain and Cognitive Sciences
• Architecture
• Political Science
• Mechanical Engineering

Centers, Labs, & Programs

• Abdul Latif Jameel Poverty Action Lab (J-PAL)
• Picower Institute for Learning and Memory
• Lincoln Laboratory
• School of Architecture + Planning
• School of Engineering
• School of Humanities, Arts, and Social Sciences
• Sloan School of Management
• School of Science
• MIT Schwarzman College of Computing
• 3 Questions: How history helps us solve today's issues

3 Questions: How history helps us solve today's issues

Press contact :.

Previous image Next image

Science and technology are essential tools for innovation, and to reap their full potential, we also need to articulate and solve the many aspects of today’s global issues that are rooted in the political, cultural, and economic realities of the human world. With that mission in mind, MIT's School of Humanities, Arts, and Social Sciences has launched The Human Factor — an ongoing series of stories and interviews that highlight research on the human dimensions of global challenges. Contributors to this series also share ideas for cultivating the multidisciplinary collaborations needed to solve the major civilizational issues of our time.

Malick Ghachem is an attorney and a professor of history at MIT who explores questions of slavery and abolition, criminal law, and constitutional history. He is the author of  "The Old Regime and the Haitian Revolution" (Cambridge University Press, 2012), a history of the law of slavery in Saint-Domingue (Haiti) between 1685 and 1804. He teaches courses on the Age of Revolution, slavery and abolition, American criminal justice, and other topics. MIT SHASS Communications recently asked him to share his thoughts on how history can help people craft more effective public policies for today's world.  Q: Your new research focuses on economic globalization and political protest in Haiti, a country with a complex social, political, and economic history. What lessons can we learn from Haiti's history that can inform more effective public policies? A: I think the most important lesson for public policy may be that we cannot ignore the distant past — and in the case of Haiti, by "distant past" I mean only so far back as the 18th century. (With apologies to colleagues who study the yet more distant centuries of ancient and medieval history!) Public policy has a short-term memory, however, and this is especially true of economic policy, which tends to look back only so far as the early 20th century to understand, for example, how a financial crisis comes about and what it entails.

Haiti showcases the decisive present-day impact and legacies of a history that goes back more than 300 years, to the rise of the slave plantation system. My current work tells the story of a planter rebellion in the 1720s against the French Indies Company, an event that ended the era of slave-trading monopolies in Saint-Domingue (as Haiti was known under French rule) and left large-scale sugar planters in effective control of the colony.

Some of the key political and social cleavages that have characterized Haitian life ever since date back to this period. A history of Haiti that begins with the revolutionary years leading up to Haitian independence in 1804, or any period thereafter, will necessarily lack a handle on just how deeply rooted are Haiti’s current circumstances.

We can see this on any number of levels. Colonial history continues to hamper prospects for broad-based education in Haiti, as my colleague Michel DeGraff’s work on the linguistic politics of French vs. Haitian Kreyòl powerfully demonstrates. The environment is another example. Part of the resistance to accepting the reality of climate change (whether in Haiti or elsewhere) is a reluctance to acknowledge that history in this deep sense matters. Yet it is clear that deforestation in Haiti begins no later than the 17th century, when French settlers began using trees for purposes of lumber and fuel. By the time of Haiti’s independence, the lack of forest cover had already left many parts of the country vulnerable to flooding.

That historical perspective, in turn, suggests one of the difficulties that besets even the most well-intentioned relief work in Haiti today. Such work tends to focus on repairing the immediate damage caused by the latest “natural” catastrophe, whether an earthquake, a hurricane-induced flood, or an outbreak of contagious disease. These tragedies rightly call upon the generous aid of first-responders, but after the sense of emergency passes, the eyes of the world often turn elsewhere.

An understanding of how these tragedies draw on the full weight of Haitian history encourages and even demands a longer-term commitment to the problems at hand. And it suggests that effective responses to what seem like essentially medical, environmental, or legal problems must cut across conventional categories of policy analysis and understandings of responsibility. Take the case of United Nations liability for the cholera outbreak in Haiti after the 2010 earthquake.

The natural impulse of human rights lawyers in that context was to file suit against the U.N., which then spent several years digging in its heels and denying its role in the outbreak. But the U.N.’s position in Haiti is a legacy of the much deeper impact that individual nations/states — most notably, France and the United States — have had on Haitian affairs over the course of three centuries. Framing responsibility in narrowly legal or chronological terms runs head-on into this reality and limits rather than expands our sense of the potential remedies.

Q: What connections do you see between economic conditions (including globalization and monetary policy) and the ability of a people or a culture to make innovations in science, technology, and public policy?

A: Waking up hungry each morning does not leave one with great deal of energy for scientific (or any other kind of) work during the day. The resources that make possible scientific and technological innovation are the same ones that sustain the relatively high standard of daily living many of us enjoy in the United States.

Haiti’s economy has long existed in a state of colonial dependency upon one or another foreign power; today it is the United States. The country’s economy is also beset by many woes, among them an ongoing currency crisis that makes the Haitian gourde an increasingly ineffective form of money. This fact places a premium on access to U.S. dollars, which elites and companies enjoy at the expense of workers paid in the local currency.

This is a crisis of sovereignty that takes the form of a monetary crisis. The earliest such currency crisis dates back (again) to the 1720s, and it’s one dimension of my current research. One of the two key triggers of the revolt against the Indies Company was a suspicion that the Company intended to eliminate the use of local Spanish silver coins, on which most colonists depended for their livelihood. The lack of a reliable and stable currency remained a problem throughout the colonial period and continues to severely constrict the economic horizons of many Haitians today.

Q: As MIT President Reif has said, solving the great challenges of our time will require multidisciplinary problem-solving — bringing together expertise and ideas from the sciences, technology, the social sciences, arts, and humanities. Can you share why you believe it is critical for any effort to address the well-being of human populations, and the planet itself, to incorporate tools and perspectives from the field of history? Also, what challenges do you see to multi-disciplinary collaborations — and how can we overcome them?

A: President Reif’s observation is correct and important. We also need to appreciate that, even within the world of the social sciences and the humanities, there are deep and abiding differences about how best to understand and implement public policy.

Let’s take the case of development economics. There is a growing literature, associated mostly with political economy and the new institutional economics, that seeks to explain the disparities in wealth and income between more and less “developed” nations. These works tend to suggest that there is a unifying model, theory, or historical pattern that accounts for the disparities: political corruption, institutional competence, the rule of law, protection of private property, etc. These phenomena are all important, but the particular forms they take can really only be understood on a case-by-case basis.

It’s important to do the unglamorous, nitty-gritty, heavily historical work of understanding the local and the particular — which requires much more patience that even those social scientists who speak of “path dependence” tend to exhibit. I believe that this kind of sustained patience for understanding the local in historical contexts is itself a tool of public policy, a way of seeing and talking about the world, and (if wielded correctly) an instrument of power and justice.

One of the principal ways historians can contribute to problem-solving work at MIT and elsewhere is by helping to identify what the real problem is in the first place. When we can understand and articulate the roots and sources of a problem, we have a much better chance of solving it.

Interview prepared by MIT SHASS Communications Editorial team: Kathryn O'Neill, Emily Hiestand (series editor)

Share this news article on:, related links.

• Malick Ghachem
• MIT History
• Online course: (21H.319) Race, Crime, and Citizenship in American Law
• Book: "The Old Regime and the Haitian Revolution"
• Article: "Election Insights: Malick Ghachem on Criminal Justice Reform"
• Article: "Black Histories Matter"

Related Topics

• International development
• Education, teaching, academics

Related Articles

Analyzing the 2016 election: Insights from 12 MIT scholars

SHASS welcomes six new faculty members

Previous item Next item

More MIT News

No detail too small

Read full story →

Study assesses seizure risk from stimulating the thalamus

Atoms on the edge

New filtration material could remove long-lasting chemicals from water

Keeping the cosmos clean

Sam Madden named faculty head of computer science in EECS

• More news on MIT News homepage →

Massachusetts Institute of Technology 77 Massachusetts Avenue, Cambridge, MA, USA

• Map (opens in new window)
• Events (opens in new window)
• People (opens in new window)
• Careers (opens in new window)
• Accessibility
• Social Media Hub
• MIT on Facebook
• MIT on YouTube
• MIT on Instagram

Can Quantitative Research Solve Social Problems? Pragmatism and the Ethics of Social Research

• Open access
• Published: 13 June 2019
• Volume 167 , pages 41–48, ( 2020 )

Cite this article

You have full access to this open access article

• Thomas C. Powell 1  

26k Accesses

9 Citations

3 Altmetric

Explore all metrics

Journal of Business Ethics recently published a critique of ethical practices in quantitative research by Zyphur and Pierides (J Bus Ethics 143:1–16, 2017). The authors argued that quantitative research prevents researchers from addressing urgent problems facing humanity today, such as poverty, racial inequality, and climate change. I offer comments and observations on the authors’ critique. I agree with the authors in many areas of philosophy, ethics, and social research, while making suggestions for clarification and development. Interpreting the paper through the pragmatism of William James, I suggest that the authors’ arguments are unlikely to change attitudes in traditional quantitative research, though they may point the way to a new worldview, or Jamesian “sub-world,” in social research.

Explore related subjects

• Artificial Intelligence

Avoid common mistakes on your manuscript.

Introduction

I was invited by the editors of this journal to comment on an article called “Is Quantitative Research Ethical? Tools for Ethically Practicing, Evaluating, and Using Quantitative Research” (Zyphur and Pierides 2017 ). The topic of the article is important and of great intrinsic interest to me, so I am pleased to offer this commentary. As will become clear, I agree with much of what the authors wrote, and with their overall philosophical orientation. The authors presented a compelling critique of traditional approaches to quantitative research (QR) in the social sciences, offering an ethical orientation for organizational research and providing helpful examples of ethical approaches to QR in management studies.

Of course, agreement makes uninteresting commentary and it is pointless to repeat the authors’ arguments and agree with them. What I have done instead is to play the devil’s advocate, selecting a few key points from the paper and evaluating them from the perspective of a traditional QR practitioner. For example, the authors argued that traditional approaches to QR are not objective but value-laden. I agree with this (see Powell 2001a ), but I evaluate whether the authors’ proposals alleviate this problem or make it worse. The authors argued that quantitative researchers should do their part to solve human problems. I agree with this (see Powell 2014a ), but I consider whether the problems they discussed were caused by quantitative methods, and whether it is reasonable to expect any research method to solve them. The authors endorsed a pragmatist epistemology as against foundationalist or “correspondence” epistemologies. I agree with this (see Powell 2001b , 2002 , 2003 , 2014b ), but I review the origins of pragmatist philosophy and consider whether pragmatism can legitimately be used to justify the social agendas of academic researchers.

My overall theme is that we should be careful what we wish for. If all social research is value-laden, then we should be wary of privileging the values of a particular community, including the community of socially minded elites working in universities, or of academic journal editors who aspire to make social impacts in the world. Many of us want to solve human problems but we should also examine ourselves, asking if we are the right people for the job, working in the right places, carrying the right tools. The authors’ pragmatic philosophy can help explain the nature of research practices, but it may not be the best platform for choosing between the competing values of academic researchers.

In the next section, I briefly summarize the argument in Zyphur and Pierides ( 2017 ) and provide overall comments. After that, I explore a few of the authors’ arguments in detail, considering their wider implications for social research. I conclude with a discussion of pragmatism in social research, examining the pragmatism of William James and its consequences for ethics in social research.

Overview of Zyphur and Pierides ( 2017 )

Zyphur and Pierides ( 2017 ) offered an ethical critique of traditional quantitative research (QR) in the social sciences. The authors challenged the philosophical foundations of traditional QR, such as its rationalist-materialist ontology and presumed scientific “objectivity.” They also challenged specific methods and practices in social research, including “best practices” in research design, sampling, measurement, hypothesis testing and data analysis.

The authors’ core message was that traditional QR practices are not objective but value-laden. Implicitly or otherwise, traditional QR takes an ethical position that impedes research that might address the real problems facing humankind today, such as racial inequality, poverty, corruption, and climate change. The authors did not reject QR as an enterprise, but criticized the assumption that standard QR “best practices” are objective and value-free. The authors called for a new “built for purpose” approach, in which researchers make their ethical purposes clear at the start, adapting research designs and analytical methods to those purposes.

The authors criticized traditional assumptions of “representation,” “correspondence,” and “probabilistic inference.” In traditional QR, researchers begin by defining theoretical constructs or variables that purportedly represent tangible or intangible objects in the real world. QR practitioners assume that these labels correspond to things in the external world with a degree of one-to-one accuracy; and they propose correlational or causal relations, which presumably correspond with how these objects relate in the real world. These relations are then tested by drawing samples which presumably correspond to larger populations. To establish the correspondence of sample results to populations, researchers use probabilistic inference, which they represent by statistical artefacts such as regression coefficients, confidence intervals and p -values.

The authors argued that the assumptions of traditional QR—that labels correspond to things; that hypothesized relations correspond to actual relations; that samples correspond to populations; that probabilistic inference allows valid inductions—are open to philosophical and methodological objections across the board, some of which the authors discussed in the paper. More to the point, however, traditional QR methods smuggle hidden values into the research process, dictating which research questions can be asked, how constructs can be measured, and how data can be gathered and analysed. According to the authors, these values, operating under a cover of scientific respectability, impede social researchers who would use QR to improve the human condition.

As an alternative to traditional QR, the authors proposed a “built for purpose” approach, in which researchers do not mimic traditional QR, but develop QR practices capable of addressing real human problems in the world. Instead of starting with representations and correspondences, researchers should start with a clear ethical purpose—for example, to combat corporate corruption or to eliminate racial discrimination. Instead of focusing on concept validity, construct validity, and other correspondences, researchers should maximize “relational validity”—that is, the “mutual fitness” of research designs, analytical methods, and ethical purposes. According to the authors, “relational validity offers a novel response to the centuries old problem of induction.” (p. 12).

The authors argued that a “built for purpose” approach requires new perspectives and research practices, which they called “orientations” and “ways of doing.” The new “orientations” require researchers to begin by asking, “Who is the research for?” “What is it trying to achieve?” and “How will it improve the human condition?” The new “ways of doing” require researchers to adapt research methods—measurement, sampling, data analysis, and causal inferences—to ethical purposes. In proposing this approach, the authors aimed to dispel traditional QR’s fixation on scientific objectivity by “putting QR to work for other purposes that are of greater concern—inequality, global warming, or corruption.” (p. 2).

Comments on Zyphur and Pierides ( 2017 )

To evaluate the paper on its own terms, I want to say what I think the authors were trying to do, and not trying to do. In particular, I do not think the authors were making an exhaustive technical critique of quantitative methods in social research. The authors criticized certain tendencies in QR practice—such as data-mining for low p -values (“ p -hacking”), and focusing on averages in regression analysis—but seemed less concerned with statistical technique than with the broader goal of “disrupting the universality” of scientific method. Their main recommendations—that researchers should focus on human problems, “built for purpose” research designs, and the “mutual fitness” of methods and purposes—could be applied equally to quantitative or qualitative research. If the authors had intended the paper as a technical deconstruction of QR in the social sciences, much more could have been said, and indeed has been said by other authors (e.g. Gelman 2015 ; Schwab et al. 2011 ; Simmons et al. 2011 ; Vul et al. 2009 ).

But the authors focused on a different point; namely, that traditional QR practices impede research on social problems even when these practices are used as they were intended. Researchers should avoid obvious errors in statistical inference, such as inferring causation from correlation. But if the real problem in QR is unthinking obedience to the orthodoxies of scientific method, the issues are behavioural rather than statistical. For example, replicability and generalizability are sound QR principles, but they incentivize research on repeatable problems while neglecting specific or non-replicable contexts; and representative sampling improves probabilistic inference, but many human problems involve minorities facing unique hardships. Hence the authors focused less on QR technique than on the need for new “orientations” and “ways of doing” in the choice and implementation of QR methods.

This approach places the authors in a tradition reminiscent of C. Wright Mills in The Sociological Imagination ( 1959 ). Mills criticized the “abstracted empiricism” of quantitative sociology in mid-20th century North America; that is, the trend of importing assumptions from the natural sciences, defining social constructs as if they were physical objects, and using statistical methods to define problems rather than the other way around. Like Zyphur and Pierides, Mills argued that social researchers should put the scientific method in the service of research problems: “Controversy over different views of ‘methodology’ and ‘theory’ is properly carried on in close and continuous relation with substantive problems.” (Mills 1959 , p. 83) Mills was concerned less with statistical methods than with the philosophies lurking beneath the supposed “objectivity” of quantitative social research:

As a matter of practice, abstracted empiricists often seem more concerned with the… Scientific Method. Methodology, in short, seems to determine the problems. And this, after all, is only to be expected. The Scientific Method that is projected here did not grow out of, and is not a generalization of, what are generally and correctly taken to be the classic lines of social science work. It has been largely drawn, with expedient modifications, from one philosophy of natural science. (Mills 1959 , pp. 39, 40)

The authors share not only Mills’ scepticism of scientific method but also his philosophical pragmatism. It is important to recognize the authors’ pragmatism and not to conflate it with ontologies aligned with nominalism, subjectivism, social constructionism, and postmodern social theory. The authors sympathize with these views, but to classify their position as “subjectivism” or “social constructionism” would be to misunderstand what they are saying. When the authors use a term like “correspondence,” they are not making a vague reference to similarity, but invoking the terminology of the pragmatist philosophy of science. Pragmatism anticipated many of the philosophical moves that would later characterize postmodern social theory, but the two approaches have different origins, and different consequences for social research.

Although the authors explained their pragmatism in an earlier paper (Zyphur et al. 2016 ), they might have done more in the current paper to guide readers through their philosophical position, linking pragmatism with their critique of traditional QR and recommendations for future QR practice. As it stands, the paper seems to blend non-pragmatist and pragmatist ideas together in a kind of free-floating subjectivist relativism that may strike some readers as confusing or unhelpful. For example, in explaining their approach, the authors used abstract language that is hard to place in any philosophical tradition:

To begin, we put forth two infinitely long and intersecting dimensions of QR practice that we call orientations and ways of doing, which connect purposes to QR practice. Instead of being ‘foundations’ or somehow fundamental in a representation correspondence sense, each category and its contents are akin to idioms or axiomatic lists that tend toward infinity because they can be populated indefinitely, limited only by the creativity of those who adopt them. They may also be orthogonal, indicating that each orientation can, at least in theory, be combined with any way of doing QR in order to achieve a given purpose. In what follows, we describe these dimensions, beginning to populate the lists that may constitute each dimension while illustrating the fruitfulness of combinations that emerge. However, there are two caveats to mentioned upfront which, if ignored, undermine our broader recommendations. (p. 4)

Due in part to the paper’s lack of clarity, both in language and narrative structure, a skeptical reader might argue that the authors have left their recommendations open to ethical misinterpretation, even by those who want to put them into practice. For example, a reader might interpret the authors’ “built for purpose” method roughly as follows: (1) Identify a serious social problem (poverty, racial inequality, climate change, etc.); (2) Choose a desired outcome (elimination of poverty, racial equality, climate stabilization, etc.); (3) Design a quantitative study that demonstrates the severity of the problem; (4) Use the quantitative results to campaign for social change that solves the problem.

This is an oversimplification of the authors’ advice, but a traditional QR practitioner might argue that the method ignores the crucial distinction between ethical outcomes and ethical processes . The received scientific method has many faults, but it recognizes, in principle, that scientists should not choose their desired outcomes or contrive their research processes to achieve those outcomes. Admittedly, scientists have abused scientific method in exactly this way, but the whole point of scientific method is to neutralize researchers’ preferences. Without a relatively objective process, researchers will choose the outcomes they want and manipulate research processes to achieve them. These manipulations may produce social changes, and some of the changes may be socially desirable—but this is not an ethical process unless we believe that “the ends justify the means” (consequentialist ethics) or that “bad people achieve their goals this way, so good people must do it too” (compensatory ethics). Either way, achieving social purposes comes at a high ethical price.

Similarly, a critic might stand behind the Rawlsian “veil of ignorance” (Rawls 1971 ) and ask: If we wanted accurate and reliable research on a social problem, would we prefer a team of researchers bound to a fixed research process they believe is ethical, or a team of researchers bound to a fixed social outcome they believe is ethical? Either team might have false beliefs, so the research process might actually be unethical, or the social outcome might be unethical. The problem is that a research team bound to a fixed outcome will reach the same conclusions whether the outcome is ethical or not, whereas a team that follows a fixed process has a chance of reaching new conclusions; and, if its process is ethical, of reaching conclusions independent of its own preferences. A reasonable person behind the Rawlsian veil might prefer a process capable of producing new or unbiased results, even if the process was imperfectly implemented.

Traditional quantitative researchers might also challenge the authors’ assumption that researchers who practice their methods are the ones who should define the world’s problems and decide which ideas get published. How do we know their values are trustworthy? If an ethical problem exists with scientific method, should we relocate our trust from the scientific community to a sub-community of socially minded university professors, journal editors and government funding agencies? Does this sub-community have a shared and coherent view of social ethics and human purposes—and if not, by what process will they define and prioritize social outcomes? What would stop an ambitious social researcher with political connections and a social media profile from hijacking the method to perpetrate mass social harm?

The authors rightly point out that traditional QR is not value-free, nor is scientific method in general. Scientists often allow quantitative methods to dictate research problems, and they have perverse incentives to find publishable results in their data. When QR is driven by methods indifferent to human purposes, it crowds out research that might address large-scale human problems. All of this is true. On the other hand, the authors’ claim that traditional QR is “ethics-laden” relies on the charge that it “produces an orientation toward ‘facts’ rather than ‘values.’” (p. 3). Therefore, the authors need to show how a commitment to facts undermines the solving of human problems, and how a commitment to values removes the ethical biases of traditional methods. Unfortunately the paper does not provide the needed clarity:

By separating facts from values, facts appear to be unrelated to ethics; and with a focus on facts, ethics appear irrelevant for QR validity… New understandings of validity are needed to address the ways that QR is an ethical act and ethically consequential. This ethicality may be unrelated to representation or correspondence, such as if QR is meant to produce images of society that change the way people think and act – an enactment of a reality that did not yet exist to be merely ‘represented’… (p. 7)

Many researchers, qualitative and quantitative alike, may disagree with the authors on the fundamental nature and purpose of social research. For example, the authors implicated traditional QR in the global financial crisis (p. 10), but many traditional researchers would reject any suggestion that the financial crisis can be laid at the doorstep of a research method—why not qualitative methods?—or that a research method can solve the world’s problems. Traditional QR practitioners would acknowledge that “Determine the nature and extent of human poverty” is a QR problem; but they would not acknowledge that “Eliminate human poverty” is a QR problem. In their worldview, it is a human problem, a social problem, an economic problem, a political problem, a gender problem, a racial problem, and many other kinds of problem. QR can help us understand what is going on in the domain of human poverty, and QR analysis provides input to policy-makers. But this does not prove that researchers should stop using “best practices,” but merely begs the question of whether traditional QR or “built for purpose” QR is the better method for understanding what is going on.

QR practitioners might also question the authors’ logical consistency in rejecting assumptions like “representation” and “correspondence.” Presumably, when the authors made statements about traditional QR—for example, that QR includes hypothesis testing and regression analysis—they were affirming that their sentences represented something, and that their ideas corresponded to something beyond words on a page. When the authors wrote “QR is often done in terms of representation and correspondence (Zyphur et al. 2016 )” (p. 2), they affirmed that this proposition, and the term “Zyphur et al. ( 2016 ),” corresponded to things and persons that possessed a reality independent of the words, even if that reality was a social construction rather than an objective material object. In other words, the authors seemed to be using representation and correspondence to critique representation and correspondence.

I think QR researchers will be especially interested in the illustrations of exemplary QR provided by the authors. Without critiquing the papers individually, the examples show that the search for better QR methods is fraught with pitfalls. Regardless of QR methods, social research is a human process concerned with human subjects. It is not obvious that researchers who follow the QR method of Zyphur and Pierides are behaving more ethically than researchers who follow traditional QR, even when they are researching worthy causes. The choice is not between ethical and unethical QR, but among a range of imperfect quantitative methods, each inviting its own forms of human error. Along with the authors, I hope that QR can make contributions to solving human problems; but I also believe that if we did not have something like traditional QR, we would have to invent it. Whatever its flaws, the question is not whether scientific method eliminates human error, but whether, among the imperfect alternatives available to us, it gives us the best explanations for what is going on in the world.

This is why we must be careful what we wish for. Humanity is confronted with many problems, and social researchers need to find a way to do their part. Whatever objections can be raised against the paper, I endorse what the authors are trying to achieve. But removing or reforming traditional QR will not solve the problems of the human condition because these problems are not caused by a research method. The problems of the human condition are caused by people, and shifting responsibility from one group of researchers to another will not improve the human condition. We should use QR to address human problems, while bearing in mind that the authors’ method confers power to solve the world’s problems on fallible people and institutions—academic elites, journal editors, and the governments, corporations and philanthropic agencies that fund social research—which have vested interests of their own, and are, to a significant degree, responsible for the problems we are trying to solve.

William James and Ethics in Management Research

I have written elsewhere about pragmatism and its relevance for organizational research Powell 2001a , 2002 , 2014a ). In this section, I want to show how pragmatism, or a version of it, relates to the ethical issues raised by Zyphur and Pierides. In particular, I want to examine the pragmatism of William James and its consequences for ethics in management research.

In doing this I am prompted by statements in Zyphur and Pierides ( 2017 ) and its predecessor (Zyphur et al. 2016 ), such as:

‘Best practices’… may be useful for the purpose of standardizing QR, but this… distracts from the task of putting QR to work for other purposes. (Zyphur and Pierides 2017 , p. 14) Inductive inference means actively working to enact research purposes, making research ‘true’ by helping it to shape the world. (Zyphur and Pierides 2017 , p. 13) Many pragmatists propose that organizing practical action is the point of thinking and speaking… (Zyphur et al. 2016 , p. 478) Instead of having to gather large samples to avoid statistical errors of inference, researchers would be better off trying to guard against actions that have unhelpful consequences. (Zyphur et al. 2016 , p. 478)

I agree with the authors’ turn to pragmatism and their rejection of conventional philosophical foundations. As a philosophy of science, pragmatism is concerned with human purposes, and the authors are right to cite pragmatism in supporting ethics in social research. However I hope that readers will not misconstrue pragmatism as a literal invitation to reject QR “best practices” while “putting QR to work for other purposes.” Philosophical pragmatism argues that most statements about truth and being (epistemology and ontology) can be resolved into statements about things people actually do, or might do. They do not resolve, however, into statements about what people should do. To explain why pragmatists make this distinction, and to show its consequences for the method proposed by Zyphur and Pierides, requires a brief digression on the origins of William James’s pragmatism.

William James developed his pragmatist philosophy over many years, exploring its consequences for psychology, epistemology, ontology and philosophy of science (e.g., James 1890a , 1902 , 1907 ). In the two-volume Principles of Psychology ( 1890b ), James linked psychology with philosophy through the concept of belief . He asked: What happens in the consciousness of a subjectively experiencing human being when confronted with a statement of fact, or proposition? What feelings are evoked? How does a person translate the words of a proposition into the state of consciousness we call “belief”?

James argued that belief occurs when a proposition evokes marked feelings of subjective rightness, like a puzzle piece fitting into place. Instead of discomfort or agitation, a proposition evokes a sense of cognitive and emotional harmony, producing a warm psychological glow of mental assent. In Jamesian psychology, belief is the warm psychological glow of mental assent. People justify their beliefs using underlying reasons or causes, such as sense data, logic, intuition, authority, persuasion, or common sense. But belief is a feeling, not a fact; and the belief that a belief is a fact and not a feeling, is also a feeling. In Jamesian psychology, a justification only counts as belief when it evokes the feeling, or psychological “yes” signal, that provides the glow of subjective rightness.

James’s theory of belief formed the psychological foundation for his pragmatism. An object becomes real for people when they believe in its existence; and a proposition becomes true for people when they believe in its truth. Scientific propositions become true for scientists when scientists believe in their truth. This does not mean that scientific propositions are arbitrary, or do not correspond with sense observations shared with other people. In Jamesian ontology, people have no direct access to metaphysical “truths” or “realities,” so their beliefs rely on sense data, logic, intuition, and other forms of justification. Indeed, other peoples’ beliefs are themselves unobservable, so we infer them from what people say and do. When we affirm that something is “true” for other people, what we mean is that we have observed people saying and doing things that make us believe that they believe that the thing is true. Human behaviour—what people say and do, including ourselves—comprises the whole of the evidence.

Despite his interest in the experiencing person, James did not see pragmatism as justifying a relativist or subjectivist social science, any more than it justified a positivist or objectivist one. James began as a physiologist, building his psychological theories on experimental physiology and the functional anatomy of the human brain; and his pragmatism did not deny the existence of the external world, the laws of propositional logic, or the validity of scientific method. James observed reality through the medium of human consciousness, which he held to speak for itself and not for things outside itself. James did not deny the existence of an external world, but saw the external world as becoming manifest through the meanings conferred on it in the perceptions and interpretations of human beings.

In Jamesian pragmatism, people adopt beliefs in order to solve problems in human consciousness, and these problems are infinitely varied. James did not propose pragmatism as a form of prescriptive advice to scientists, urging them to focus on final purposes instead of processes, or to “be practical” instead of thinking abstractly. The problems of poets and metaphysicians are not “practical” compared to the problems of engineers and airline pilots, but pragmatism does not urge poets to become more practical. Pragmatism is a descriptive theory of human ontology and epistemology which holds that people derive their ideas of truth and reality not from comparisons between propositions and realities, but by solving problems that arise in human consciousness. The theory makes no claims about the degree of “practicality” of interests or problems people may or should have.

Beyond affirming the centrality of human experience for psychology and philosophy of science, James argued that any phenomenon in the domain of human consciousness can become a legitimate object of human inquiry. Whatever has meaning for an experiencing human being has ontological reality, and there are no greater or lesser realities. The beliefs we call “scientific,” derived from theory and empirical observation, do not have higher ontological status, or “more reality,” than other propositions in human consciousness, and hence no superior claim on truth. Everything that enters human consciousness has the same eligibility for inquiry, examination and analysis, whether derived from sense experience, reasoning, dreams, delusions, hallucinations, mythology, or religious faith.

James saw the natural sciences as domains of human inquiry concerned with aspects of human consciousness associated with the natural world. While recognizing the widespread human impacts of science, James regarded the scientific community as one of many “sub-worlds” of human inquiry (see James 1890b , p. 291). A Jamesian sub-world, like a Wittgensteinian “language game,” denotes a community of inquiry with its own conventions, beliefs and vocabularies (on Wittgenstein’s reliance on James’s pragmatism, see Goodman 2002 ). By the conventions of the scientific sub-world, scientists follow a method of inquiry grounded in theory, quantification, measurement and experiment, while rejecting propositions grounded in private opinion or groundless speculation. James acknowledged the efficacy and significance of science, since its problems very often affect non-scientists, and solving them makes life better (or worse) for many people. At the same time, James affirmed that scientific problem-solving conventions do not give scientists superior access to extra-experiential realities, but function in human consciousness like other conventions.

James’s philosophy allowed for great pluralism among the sub-worlds of human inquiry; for example, there are sub-worlds of myth, literature, art and religion, each with its own conventions, beliefs, and vocabularies. James argued that these sub-worlds produced beliefs that were no less real or true, within their own conventions, than the beliefs of natural scientists—and that it was futile to judge the beliefs of one sub-world by the conventions of another: to the poet, a scientific discovery may seem misguided; or to a scientist, a religious inspiration may seem superstitious. Participants negotiate conventions within their own sub-worlds, but pragmatism does not make value judgments about the comparative legitimacy of sub-worlds. As in James’s The Varieties of Religious Experience ( 1902 ), any phenomenon that appears in human consciousness is fruitful subject matter for human inquiry.

And this is where ethics comes in. Pragmatists do not hold that truth is relative or a matter of preference. Each sub-world of inquiry follows its own problem-solving conventions, and these conventions become relatively hardened, even as they continue to evolve. Within the sub-world of science, truth is not groundless but evidence-based, and to pretend otherwise is not merely to get it wrong, but to behave unethically . Scientists can debate the kinds of evidence that bear on a particular question, but they cannot debate whether evidence bears on scientific questions. Theologians can debate whether God is known by faith, revelation, or church tradition, but they cannot debate whether God is relevant to theology. Outside claimants who deny the conventions of a sub-world, unlike insiders disputing how those conventions are applied, are perceived not merely as mistaken, but as immoral, ignorant or both. Disputes within a sub-world of practice can solve problems for participants, but disputes across sub-worlds tend to devolve into name-calling and ethical recrimination.

From a Jamesian pragmatist perspective, the debate initiated by Zyphur and Pierides is a dispute across sub-worlds rather than a conversation that can be progressed within the sub-world of QR practice. Quantitative social research is a legitimate sub-world of practice, and like the proposals by C. Wright Mills a half-century earlier, the authors’ proposals are unlikely to alter or deter that sub-world. From the perspective of the traditional QR sub-world, the debate initiated by the authors—dropping QR best practices and using QR to achieve researchers’ social aspirations—is not so much a challenge to QR practice as a kind of category mistake. The authors’ paper is not written in the language of quantitative researchers, it does not acknowledge their legitimacy, it does not anticipate or address their potential responses, and it proposes to overthrow the standards of their community without discussing the consequences of abandoning those standards. The authors seem to inhabit a different sub-world altogether, and the two sub-worlds do not have very much to say to each other.

I believe this is a good thing. If traditional QR is a legitimate sub-world of practice, so is the sub-world proposed by the authors. I can imagine a sub-world in which people put QR in the service of solving human problems, with its own conventions, beliefs and vocabularies. This sub-world cannot replace traditional QR or operate within it, but requires an independent code of practice and community of participants. To build this community within the conventions of traditional QR would constrain and diminish both traditional QR and what the authors are trying to accomplish. The authors have started the conversation by articulating a set of principles for purpose-driven QR. Perhaps now they can define the social and intellectual agenda for this community, and build the human and institutional infrastructure required for its growth and development. I support what they are trying to do and I hope they succeed.

Gelman, A. (2015). The connection between varying treatment effects and the crisis of unreplicable research: A Bayesian perspective. Journal of Management, 41 (2), 632–643.

Article   Google Scholar  

Goodman, R. B. (2002). Wittgenstein and William James . Cambridge UK: Cambridge University Press.

Book   Google Scholar  

James, W. (1890a). The principles of psychology (Vol. I). New York: Henry Holt and Company.

Google Scholar  

James, W. (1890b). The principles of psychology (Vol. II). New York: Henry Holt and Company.

James, W. (1902). The varieties of religious experience: A study in human nature . London: Longmans, Green and Co.

James, W. (1907). Pragmatism: A new word for some old ways of thinking . London: Longmans, Green and Co.

Mills, C. Wright. (1959). The sociological imagination . New York: Oxford University Press.

Powell, T. C. (2001a). Competitive advantage: Logical and philosophical considerations. Strategic Management Journal, 22 (9), 875–888.

Powell, T. C. (2001b). Fallibilism and organizational research: The third epistemology. Journal of Management Research, 4, 201–219.

Powell, T. C. (2002). The philosophy of strategy. Strategic Management Journal, 23 (9), 873–880.

Powell, T. C. (2003). Strategy without ontology. Strategic Management Journal, 24 (3), 285–291.

Powell, T. C. (2014a). Strategic management and the person. Strategic Organization, 12 (3), 200–207.

Powell, T. C. (2014b). William James. In Jenny Helin, Tor Hernes, Daniel Hjorth, & Robin Holt (Eds.), The Oxford handbook of process philosophy and organization studies (pp. 166–184). Oxford: Oxford University Press.

Rawls, J. (1971). A theory of justice . Cambridge MA: Belknap.

Schwab, A., Abrahamson, E., Starbuck, W. H., & Fidler, F. (2011). Researchers should make thoughtful assessments instead of null-hypothesis significance tests. Organization Science, 22, 1105–1120.

Simmons, J., Nelson, L., & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allow presenting anything as significant. Psychological Science, 22, 1359–1366.

Vul, E., Harris, C., Winkielman, P., & Pashler, H. (2009). Puzzlingly high correlations in fMRI studies of emotion, personality, and social cognition. Perspectives on Psychological Science, 4 (3), 274–290.

Zyphur, M. J., & Pierides, D. C. (2017). Is quantitative research ethical? Tools for ethically practicing, evaluating, and using quantitative research. Journal of Business Ethics, 143, 1–16.

Zyphur, M. J., Pierides, D. C., & Roffe, J. (2016). Measurement and statistics in ‘organization science’: Philosophical, sociological, and historical perspectives. In R. Mir, H. Willmott, & M. Greenwood (Eds.), The Routledge companion to philosophy in organization studies (pp. 474–482). Abingdon: Routledge.

Download references

The author received no funding to support this research.

Author information

Authors and affiliations.

Said Business School, University of Oxford, Park End Street, Oxford, OX1 1HP, UK

Thomas C. Powell

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Thomas C. Powell .

Ethics declarations

Conflict of interest.

The author declares having no conflict of interest in this research.

Research Involving in Human and Animal Rights

The author declares that this article does not contain any studies with human participants or animals performed by the author.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

Powell, T.C. Can Quantitative Research Solve Social Problems? Pragmatism and the Ethics of Social Research. J Bus Ethics 167 , 41–48 (2020). https://doi.org/10.1007/s10551-019-04196-7

Download citation

Received : 21 December 2017

Accepted : 23 May 2019

Published : 13 June 2019

Issue Date : November 2020

DOI : https://doi.org/10.1007/s10551-019-04196-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Quantitative research

Advertisement

• Find a journal
• Publish with us
• Track your research

How to Solve Problems

To bring the best ideas forward, teams must build psychological safety. by Laura Amico

Teams today aren’t just asked to execute tasks: They’re called upon to solve problems. You’d think that many brains working together would mean better solutions, but the reality is that too often problem-solving teams fall victim to inefficiency, conflict, and cautious conclusions. The two charts below will help your team think about how to collaborate better and come up with the best solutions for the thorniest challenges.

Partner Center

Suggested Searches

• Climate Change
• Expedition 64
• Mars perseverance
• SpaceX Crew-2
• International Space Station
• View All Topics A-Z

Humans in Space

Earth & climate, the solar system, the universe, aeronautics, learning resources, news & events.

Hubble Examines a Busy Galactic Center

NASA Earth Scientists Take Flight, Set Sail to Verify PACE Satellite Data

What’s Up: September 2024 Skywatching Tips from NASA

• Search All NASA Missions
• A to Z List of Missions
• Upcoming Launches and Landings
• Spaceships and Rockets
• Communicating with Missions
• James Webb Space Telescope
• Hubble Space Telescope
• Why Go to Space
• Commercial Space
• Destinations
• Living in Space
• Explore Earth Science
• Earth, Our Planet
• Earth Science in Action
• Earth Multimedia
• Earth Science Researchers
• Pluto & Dwarf Planets
• Asteroids, Comets & Meteors
• The Kuiper Belt
• The Oort Cloud
• Skywatching
• The Search for Life in the Universe
• Black Holes
• The Big Bang
• Dark Energy & Dark Matter
• Earth Science
• Planetary Science
• Astrophysics & Space Science
• The Sun & Heliophysics
• Biological & Physical Sciences
• Lunar Science
• Citizen Science
• Astromaterials
• Aeronautics Research
• Human Space Travel Research
• Science in the Air
• NASA Aircraft
• Flight Innovation
• Supersonic Flight
• Air Traffic Solutions
• Green Aviation Tech
• Drones & You
• Technology Transfer & Spinoffs
• Space Travel Technology
• Technology Living in Space
• Manufacturing and Materials
• Science Instruments
• For Kids and Students
• For Educators
• For Colleges and Universities
• For Professionals
• Science for Everyone
• Requests for Exhibits, Artifacts, or Speakers
• STEM Engagement at NASA
• NASA's Impacts
• Centers and Facilities
• Directorates
• Organizations
• People of NASA
• Internships
• Our History
• Doing Business with NASA
• Get Involved

NASA en Español

• Aeronáutica
• Ciencias Terrestres
• Sistema Solar
• All NASA News
• Video Series on NASA+
• Newsletters
• Social Media
• Media Resources
• Upcoming Launches & Landings
• Virtual Guest Program
• Image of the Day
• Sounds and Ringtones
• Interactives
• STEM Multimedia

NASA Invites Social Creators to Experience Launch of Europa Clipper Mission

Persevering Through the Storm

NASA’s Hubble, MAVEN Help Solve the Mystery of Mars’ Escaping Water

NASA Astronaut Don Pettit’s Science of Opportunity on Space Station

NASA, Boeing Optimizing Vehicle Assembly Building High Bay for Future SLS Stage Production

NASA Seeks Input for Astrobee Free-flying Space Robots

NASA Summer Camp Inspires Future Climate Leaders

NASA Mission Gets Its First Snapshot of Polar Heat Emissions

Artemis IV: Gateway Gadget Fuels Deep Space Dining

NASA’s Webb Reveals Distorted Galaxy Forming Cosmic Question Mark

NASA’s Mini BurstCube Mission Detects Mega Blast

NASA Tunnel Generates Decades of Icy Aircraft Safety Data

Research Plane Dons New Colors for NASA Hybrid Electric Flight Tests 

NASA G-IV Plane Will Carry Next-Generation Science Instrument

OSAM-1 Partnership Opportunity: Request for Information 

NASA to Support DARPA Robotic Satellite Servicing Program

NASA JPL Developing Underwater Robots to Venture Deep Below Polar Ice

Learn Math with NASA Science

Eclipses Create Atmospheric Gravity Waves, NASA Student Teams Confirm

La NASA invita a los medios al lanzamiento de Europa Clipper

El X-59 de la NASA avanza en las pruebas de preparación para volar

La NASA invita a creadores de las redes sociales al lanzamiento de la misión Europa Clipper

12 min read

15 Ways the International Space Station Benefits Humanity Back on Earth

Space station research integration office, 1. producing the next generation of medical scanning technology, 2. creating new drugs for disorders like duchenne muscular dystrophy, 3. forming the components for producing artificial blood for animals, 4. robotic arm technology applications in an automotive factory, 5. student research in space, 6. lowering heat in cities and tracking water, 7. ultrasound procedures on earth, 8. apply station air filtration technology to fighting covid and preserving food in grocery stores, 9. colloids and everyday household products, 10. creating artificial retinas in space, 11. making cancer treatments simpler for patients, 12. dna sequencing microorganisms around the solar system, 13. monitoring heat safety on earth, 14. better understanding the fundamental science of our world, 15. talking with station and inspiring the next generation, additional resources.

The first decade of the International Space Station was the decade of construction. The second decade moved from initial studies to fully using the orbiting lab. We have now entered the decade of results.

With more than 20 years of experiments now conducted on the station, more breakthroughs are materializing than ever before.

Explore 15 of the ways the space station is benefiting humanity.

In their quest to study neutron stars, the team behind the NICER telescope created and patented an X-ray source that could be turned on and off very quickly. This also happened to be what a neuroradiologist at Massachusetts General Hospital needed for his quest to improve CT scans.

Traditional CT machines are large, heavy, and consume a lot of power. This makes them hard to deploy in environments with few resources. Rather than spinning the large X-ray machine around to capture a CT scan, the Massachusetts General Hospital and NICER teams worked together to create a stationary ring of these small new modulated X-ray sources that can be mounted around the patient, firing when needed. This technique can decrease the amount of radiation the patient is exposed to and enable a better image quality even at the lower radiation level.

Limiting radiation exposure is helpful for patients on Earth now and potentially for future astronauts on their way to Mars. The device has been patented, and additional work is now underway to take it from a prototype to a testable device.

An International Space Station study of the crystal structure of a protein associated with Duchenne Muscular Dystrophy (DMD), an incurable genetic disorder, provided hints for compounds that might inhibit it. A professor at the University of Tsukuba in Tsukuba, Japan used those hints to design several promising compounds, including TAS-205. A 2015 study verified the safety of TAS-205 for use in humans, and a small clinical trial in human patients was published in 2017. A Phase 3 trial to examine the effectiveness of TAS-205 in situations similar to actual clinical use began in Dec. 2020 and will continue until 2027. 

The research team estimates the drug may slow the progression of DMD by half, potentially doubling the lifespan of many patients.

In addition to showing promise in drug development, the Japan Aerospace Exploration Agency’s (JAXA’s) other work on crystallizing proteins in microgravity inspired development of an artificial animal albumin. Albumin is the most abundant protein in blood but is difficult to crystallize on Earth. Researchers used the space station to crystalize albumin from cats and dogs to better understand the structures of these proteins and how they are formed. Veterinarians in animal hospitals have trouble providing blood transfusion treatments since there aren’t large stores of donated animal blood, an issue that could be positively impacted through potential application of this work to veterinary medicine.

The creation of space station robot Robonaut led to the development of an industrial strength robotic glove. NASA and General Motors (GM) developed a Robonaut prototype and tested it on the station, where it successfully performed simple tasks alongside astronauts. The team then reconfigured the hand-like portion of Robonaut into a wearable device to help both astronauts and auto workers avoid hand fatigue and injury. Initially called Robo-Glove, the device now is commercially available as Ironhand, produced by Bioservo Technologies of Sweden. 

People born after November 2000 have always known life with humans in space: they grew up in a world with an International Space Station orbiting overhead. Call them Generation Station, those for whom space has always seemed accessible, a place where scientists from around the globe conduct research. Numerous students from around the globe have even sent their own research or code to station. They have helped conduct DNA sequencing experiments as a part of the Genes in Space program, or controlled robots using their code as a part of the Kibo Robot Programming Challenge. Many have designed and deployed small satellites from the space station, sending their work into low-Earth orbit.

Data from NASA’s ECOSTRESS payload has already had many applications. ECOSTRESS measures subtle changes in temperature to identify plant stress. Those same measurements can be used to identify extreme heat, such as that produced by fires or lava flows, and to study movement of warm water currents and heatwaves in cities.

ECOSTRESS data has been employed in efforts to reduce heat absorbed by city surfaces, better allocate water, reduce fire risk in forests, measure plant stress, search for geothermal energy sources, track mosquitos, and help farmers efficiently water their fields. For example, Cool Streets LA researchers studying different materials that could reduce urban heat used data from ECOSTRESS to see how the surface heat of neighborhoods changed as they applied coatings. They found a thin gray coating can make an asphalt roadway reflect the sun like a concrete roadway, reducing surrounding heat about 2 degrees F.

For people who live in major cities with fully equipped hospitals, having access to quick and accurate medical imaging technology is not usually a problem. However, when medical facilities are not within easy reach, accessing this technology can mean the difference between life and death.

To care for astronauts aboard the International Space Station, crew members were trained to use a small ultrasound unit to examine fellow crew members through the Advanced Diagnostic Ultrasound in Microgravity (ADUM) study.

In partnership with the World Interactive Network Focused on Critical Ultrasound (WINFOCUS), the ADUM team took techniques developed for station astronauts and adapted them for use in remote areas on Earth by developing protocols for rapidly performing complex procedures with remote expert guidance and training. Using the ADUM methods, WINFOCUS has trained more than 45,000 physicians and physician extenders in over 60 countries. As local healthcare providers are empowered, more patients can access quality and timely diagnostic care, making the healthcare system more efficient by allowing for earlier diagnosis and treatment.

Using NASA’s Advanced Astroculture (ADVASC) system, station crews successfully grew two generations of Arabidopsis plants, a model organism that is well understood and often used in fundamental biology experiments. The system provided precise control of environmental parameters for plant growth, including temperature, relative humidity, light, fluid nutrient delivery, and carbon dioxide and ethylene concentrations.

Scientists adapted the ADVASC system for use in air purification on Earth. Initially used to prolong the shelf life of fruits and vegetables in grocery stores, the technology drew the attention of winemakers, who used it in their cellars to enhance storage conditions. Multiple companies also now use this technology in air purifiers that were shown to be effective in eliminating the SARS-CoV-2 virus. The companies have produced and distributed numerous purifiers during the pandemic. A separate technology tested for detecting contaminants on the space station went on to be included in an air sensor used on Earth to generate a “virus propagation risk index” in shared spaces, letting people know to reduce crowding or take other steps to limit risk. 

The latest formulation of Procter & Gamble (P&G)’s Febreze Unstopables TOUCH Fabric Spray with touch-activated scent release technology is the company’s first to incorporate materials based on its colloid research conducted on station.

Colloids are mixtures of tiny particles suspended in a liquid. They include natural mixtures such as milk and muddy water as well as manufactured products from shampoo to medicine. Studying colloids is complicated by the fact that gravity causes some particles to rise and others to sink. Microgravity removes that complication and makes possible research like the Advanced Colloid Experiments ( ACE ) conducted by NASA, the ISS National Laboratory, and P&G.

P&G says that the work on the station helped them envision and understand the formulation, allowing them to create a fluid that looks and feels like water. As of 2022, station research has contributed to three new patents for the company. 

Artificial retinas could restore meaningful vision for the millions of people on Earth who suffer from retinal degenerative diseases. U.S.-based company LambdaVision has now flown experiments to the space station five times working toward their goal of manufacturing artificial retinas in microgravity. LambdaVision is evaluating a manufacturing process to develop artificial human retinas using a light-activated protein called bacteriorhodopsin, which could replace the function of damaged light-sensing cells in the eye. The process creates implants by applying layer after layer of a thin film. Microgravity may improve the quality and stability of the films by limiting the aggregation and sedimentation of particles that occur on Earth. The experiment that launched in Dec. 2021 demonstrated the manufacture of a 200-layer film for the first time in microgravity. This is a crucial step towards using the microgravity environment for life-changing medical manufacturing.

The ISS National Lab sponsored PCG-5 study is focused on improving how drugs are delivered to patients. The study worked to grow a more uniform crystalline form of the monoclonal antibody Keytruda®, which is used to treat several types of cancers, including melanoma and lung cancer. Monoclonal antibodies do not dissolve easily in liquid. That makes it difficult to create a drug that can be given via an injection in a doctor’s office rather than intravenously, requiring patients to spend hours in a clinic setting to receive the drug.

The PCG-5, a Merck Research Laboratories study, produced high-quality crystalline suspensions that could make Keytruda® deliverable by injection, making treatment more convenient for patients and caregivers while significantly reducing cost. This work is ongoing, as is research on other potential therapeutics, according to Merck Research Laboratories. 

Scientists use the International Space Station as a testing ground to study how to keep astronauts safe and healthy on long-duration missions. In 2016, NASA astronaut Kate Rubins successfully conducted the first DNA sequencing in space, opening the door to molecular biology research in spaceflight conditions. The team used a MinION (pronounced “min ion”) sequencing platform, a device no bigger than a cell phone, to read the nucleic acid bases in samples sent to the station for study.

This technology can enable scientists to quickly identify pathogens on the space station or on future exploration missions, and even potentially identify life on other planets in the solar system if it shares a common biochemistry with life as we know it on Earth. The use of the device in space can also help provide information to researchers using the device in remote locations on Earth.

NASA astronaut Kate Rubins prepares for a run of the Biomolecule Sequencer experiment. It demonstrated, for the first time, that DNA sequencing is feasible in an orbiting spacecraft. A space-based DNA sequencer could identify microbes, diagnose diseases, help researchers understand crew member health, and potentially help detect DNA-based life elsewhere in the solar system. Credits: NASA

Core body temperature rises faster during exercise on the space station than it does on Earth. ESA’s (European Space Agency’s) ThermoLab experiment has investigated body temperature regulation and cardiovascular adaptations in crew members since 2009. 

Technology that measures body temperature developed for the study by German company Dräge has begun to make a difference on Earth. The devices are deployed in many clinics to monitor infant incubators and patients during surgery and have been used to study how extreme heat affects farmers in Kenya and Burkina Faso. Other applications of the device include monitoring for signs of fatigue in people working in extreme conditions, including firefighters and fighter pilots.

Many experiments on station are uncovering new information and providing clues to long-standing scientific mysteries. This information helps researchers to further humanity’s understanding of things like combustion or fluid physics, which can lead to improvements in everything from fuel efficiency to electronics cooling.

When researchers on NASA’s FLEX study analyzed fire suppressants by studying burning fuel droplets, they made a surprising discovery: continued, low temperature “burning” after apparent flame extinction. Now known as cool flames, this combustion process is distinct from the flames that keep us warm by the campfire. Typical flames produce soot, carbon dioxide, and water. Cool flames produce carbon monoxide and formaldehyde. Learning more about the behavior of these chemically different flames could lead to the development of more-efficient, less-polluting vehicles.

Conversations with astronauts, story times recorded by crew members, and educational science video recorded aboard station bring all of humanity along on its exploration of the cosmos. Amateur Radio on the International Space Station (ARISS) provides students from around the world the chance to ask questions directly to an astronaut in orbit while learning the technical basics of ham radio operations. The program has now connected more than 250,000 participants with the space station and over 100 crew members. Hundreds of thousands of additional students have connected to astronauts through educational downlink as well, helping inspire the next generation of scientists and engineers. 

Lee esta historia en español aquí .

Discover More Topics

Station Benefits for Humanity

Latest News from Space Station Research

Space Station Research and Technology

Space Station Research Results