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Research methods--quantitative, qualitative, and more: overview.

• Quantitative Research
• Qualitative Research
• Data Science Methods (Machine Learning, AI, Big Data)
• Text Mining and Computational Text Analysis
• Evidence Synthesis/Systematic Reviews
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About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley. 

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more.  This guide is an introduction, but if you don't see what you need here, always contact your subject librarian, and/or take a look to see if there's a library research guide that will answer your question. 

Suggestions for changes and additions to this guide are welcome! 

START HERE: SAGE Research Methods

Without question, the most comprehensive resource available from the library is SAGE Research Methods.  HERE IS THE ONLINE GUIDE  to this one-stop shopping collection, and some helpful links are below:

• SAGE Research Methods
• Little Green Books  (Quantitative Methods)
• Little Blue Books  (Qualitative Methods)
• Dictionaries and Encyclopedias  
• Case studies of real research projects
• Sample datasets for hands-on practice
• Streaming video--see methods come to life
• Methodspace- -a community for researchers
• SAGE Research Methods Course Mapping

Library Data Services at UC Berkeley

Library Data Services Program and Digital Scholarship Services

The LDSP offers a variety of services and tools !  From this link, check out pages for each of the following topics:  discovering data, managing data, collecting data, GIS data, text data mining, publishing data, digital scholarship, open science, and the Research Data Management Program.

Be sure also to check out the visual guide to where to seek assistance on campus with any research question you may have!

Library GIS Services

Other Data Services at Berkeley

D-Lab Supports Berkeley faculty, staff, and graduate students with research in data intensive social science, including a wide range of training and workshop offerings Dryad Dryad is a simple self-service tool for researchers to use in publishing their datasets. It provides tools for the effective publication of and access to research data. Geospatial Innovation Facility (GIF) Provides leadership and training across a broad array of integrated mapping technologies on campu Research Data Management A UC Berkeley guide and consulting service for research data management issues

General Research Methods Resources

Here are some general resources for assistance:

• Assistance from ICPSR (must create an account to access): Getting Help with Data , and Resources for Students
• Wiley Stats Ref for background information on statistics topics
• Survey Documentation and Analysis (SDA) .  Program for easy web-based analysis of survey data.

Consultants

• D-Lab/Data Science Discovery Consultants Request help with your research project from peer consultants.
• Research data (RDM) consulting Meet with RDM consultants before designing the data security, storage, and sharing aspects of your qualitative project.
• Statistics Department Consulting Services A service in which advanced graduate students, under faculty supervision, are available to consult during specified hours in the Fall and Spring semesters.

Related Resourcex

• IRB / CPHS Qualitative research projects with human subjects often require that you go through an ethics review.
• OURS (Office of Undergraduate Research and Scholarships) OURS supports undergraduates who want to embark on research projects and assistantships. In particular, check out their "Getting Started in Research" workshops
• Sponsored Projects Sponsored projects works with researchers applying for major external grants.
• Next: Quantitative Research >>
• Last Updated: Apr 25, 2024 11:09 AM
• URL: https://guides.lib.berkeley.edu/researchmethods

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“Evidence-Based” vs. “Research-Based”: Understanding the Differences

Often, when reviewing resources, programs, or assessments, we might come across terms like “evidence-based” or “research-based.” These terms each tell us something about the resources that they describe and the evidence supporting them. Understanding each term’s meaning can help us make informed decisions when selecting and implementing resources.

So what do these terms mean, exactly?

Typically, the terms  Evidence-Based   Practices  or  Evidence-Based   Programs  refer to individual practices (for example, single lessons or in-class activities) or programs (for example, year-long curricula) that are considered effective based on scientific evidence. To deem a program or practice “evidence-based,” researchers will typically study the impact of the resource(s) in a controlled setting – for example, they may study differences in skill growth between students whose educators used the resources and students whose educators did not. If sufficient research suggests that the program or practice is effective, it may be deemed “evidence-based.”

Evidence-Informed  (or  Research-Based )  Practices  are practices that were developed based on the best research available in the field. This means that users can feel confident that the strategies and activities included in the program or practice have a strong scientific basis for their use. Unlike Evidence-Based Practices or Programs, Research-Based Practices have not been researched in a controlled setting.

What about assessment?

Terms like “evidence-based” and “research-based” are often used to describe  intervention activities,  like strategies or curricula designed to build skills in specific areas. But the process of measuring skills with assessment tools can be evidence-based as well. An assessment process can be considered  Evidence-Based Assessment  if:

• The choice of skills to be measured by the assessment was informed by research;
• The assessment method and measurement tools used are informed by scientific research and theory and meet the relevant standards for their intended uses; and
• The way that the assessment is implemented and interpreted is backed by research.

Using evidence-based assessment to guide or evaluate an intervention gives us confidence that the process is well-suited for our purpose, is grounded in scientific theory, and will be effective for our students.

What Standards Exist for Educational Assessments?

The process of Evidence-Based Assessment involves the use of a measurement tool that “meets the relevant standards for their intended uses.” What are the relevant standards, and how can we know if a tool meets them?

Some foundational standards for educational assessments, as compiled by experts in the educational, psychological, and assessment fields, include:

• Validity for an Intended Use:  the tool should have been researched to determine that it is valid, or appropriate, for the decisions we may make based on its results. Just like we wouldn’t use a math quiz to inform whether a student needs additional practice with reading comprehension, we shouldn’t use an assessment for purposes outside of those that research has deemed “valid.”
• Reliability:  the tool should have been researched to ensure that it meets expectations for reliability, or consistency. For example, researchers might explore whether the tool produces similar results if it is completed twice in a short period of time. Reliability can be explored via a variety of methods, depending on the measurement tool.
• Fairness:  the tool should have been researched to explore how fair, or unbiased, it is among different subgroups of students, such as subgroups based on race, ethnicity, or cultural background. Using a biased measurement tool can lead to biased decision-making and threaten our ability to provide equitable services.

Specific standards within each of these domains, and others, are compiled in the handbook, “Standards for Educational and Psychological Testing” (2014), written by the American Educational Research Association, the American Psychological Association, and the National Council on Measurement in Education. This handbook can be a useful companion when reviewing the specific evidence behind measurement tools.

In Conclusion

Terms like “evidence-based” or “research-based” are useful indicators of the type of evidence behind programs, practices, or assessments – however, they can only tell us so much about the specific research behind each tool. For situations where more information on a resource’s evidence base would be beneficial, it may be helpful to request research summaries or articles from the resource’s publisher for further review.

Further Reading

• Hunsley, J., & Mash, E. J. (2007). Evidence-based assessment. Rev. Clin. Psychol., 3, 29-51 .
• Joint Committee on the Standards for Educational and Psychological Testing of the American Educational Research Association, the American Psychological Association, and the National Council on Measurement in Education (2014). Standards for Educational and Psychological Testing. The American Educational Research Association, the American Psychological Association, and the National Council on Measurement in Education .
• S. Department of Education (2016). Using Evidence to Strengthen Education Investments .

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Evidence-Based Research Series-Paper 1: What Evidence-Based Research is and why is it important?

Affiliations.

• 1 Johns Hopkins Evidence-based Practice Center, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA.
• 2 Digital Content Services, Operations, Elsevier Ltd., 125 London Wall, London, EC2Y 5AS, UK.
• 3 School of Nursing, McMaster University, Health Sciences Centre, Room 2J20, 1280 Main Street West, Hamilton, Ontario, Canada, L8S 4K1; Section for Evidence-Based Practice, Western Norway University of Applied Sciences, Inndalsveien 28, Bergen, P.O.Box 7030 N-5020 Bergen, Norway.
• 4 Department of Sport Science and Clinical Biomechanics, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark; Department of Physiotherapy and Occupational Therapy, University Hospital of Copenhagen, Herlev & Gentofte, Kildegaardsvej 28, 2900, Hellerup, Denmark.
• 5 Musculoskeletal Statistics Unit, the Parker Institute, Bispebjerg and Frederiksberg Hospital, Copenhagen, Nordre Fasanvej 57, 2000, Copenhagen F, Denmark; Department of Clinical Research, Research Unit of Rheumatology, University of Southern Denmark, Odense University Hospital, Denmark.
• 6 Section for Evidence-Based Practice, Western Norway University of Applied Sciences, Inndalsveien 28, Bergen, P.O.Box 7030 N-5020 Bergen, Norway. Electronic address: [email protected].
• PMID: 32979491
• DOI: 10.1016/j.jclinepi.2020.07.020

Objectives: There is considerable actual and potential waste in research. Evidence-based research ensures worthwhile and valuable research. The aim of this series, which this article introduces, is to describe the evidence-based research approach.

Study design and setting: In this first article of a three-article series, we introduce the evidence-based research approach. Evidence-based research is the use of prior research in a systematic and transparent way to inform a new study so that it is answering questions that matter in a valid, efficient, and accessible manner.

Results: We describe evidence-based research and provide an overview of the approach of systematically and transparently using previous research before starting a new study to justify and design the new study (article #2 in series) and-on study completion-place its results in the context with what is already known (article #3 in series).

Conclusion: This series introduces evidence-based research as an approach to minimize unnecessary and irrelevant clinical health research that is unscientific, wasteful, and unethical.

Keywords: Clinical health research; Clinical trials; Evidence synthesis; Evidence-based research; Medical ethics; Research ethics; Systematic review.

Copyright © 2020 Elsevier Inc. All rights reserved.

Publication types

• Research Support, Non-U.S. Gov't
• Biomedical Research* / methods
• Biomedical Research* / organization & administration
• Clinical Trials as Topic / ethics
• Clinical Trials as Topic / methods
• Clinical Trials as Topic / organization & administration
• Ethics, Research
• Evidence-Based Medicine / methods*
• Needs Assessment
• Reproducibility of Results
• Research Design* / standards
• Research Design* / trends
• Systematic Reviews as Topic
• Treatment Outcome

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Evidence-Based? Research-Based? What does it all Mean?

Have you ever felt puzzled by trying to discern the difference between the terms, evidence-based and research-based ? Or have you ever found yourself feeling intimidated when someone asked you, “But is that program/practice evidence-based?” I know I have. To help me clarify my understanding, I reached out to my colleagues here at the Center and my old friend, Google. I’ve come to the following understandings and a bit of friendly advice – stay curious! Please keep reading if you’re feeling as perplexed as I am.

Clarifying the Difference between Research-Based and Evidence-Based

My current working definition of research-based instruction has come to mean those practices/programs that are based on well-supported and documented theories of learning. The instructional approach is based on research that supports the principles it incorporates, but there may not be specific research or its own evidence to directly demonstrate its effectiveness.

Defining evidence-based practice has been more headache-inducing as the term is frequently and widely used to mean a myriad of things. Currently, I have come to understand that evidence-based practices are those that have been researched with either experimental studies (think randomly assigned control groups), quasi-experimental studies (comparison groups that are not randomized), or studies that were well-designed and well-implemented correlational studies with statistical controls for selection bias. In brief, a specific study (or studies) has been done to test its effectiveness.

By no means are these definitions ready for Merriam-Webster, but they are helping me to make sense of the terms.

So what do you say or ask when “research” is thrown your way?

Recently, I met with a group of literacy coaches and we discussed how to respond when a fellow educator approaches them with “research” either supporting or refuting an instructional practice or program. My best advice to them probably sounded like a Viking River Cruise commercial – “Be curious!” Below are some examples of ways to respond to demonstrate that you are open to learning more.

• Thank you for bringing that information to my attention. Can you share your source of information or the article so I can read it too and we can talk about it together?
• Please talk more about what you have learned (or read or heard). I’m curious to learn more about: a. Whether the research was published in a peer-reviewed journal or if the research was sponsored by a publisher or other interested party. b. The sample size or the number of schools/students involved in the study. c. The demographics of the subjects involved in the study. d. The type of research conducted.

3. I’m wondering how many studies have been conducted that replicate those results. 4. That research sounds important. Can you share the source with me? Perhaps it will be helpful for our grade level team to read it and discuss the findings together.

As educators, we are always looking for the most effective ways to support our students. Stay open to new findings and be sure to slow the process down so you probe deeper to learn if there truly is current research to back what people are claiming. Then be sure to evaluate the credibility of the source of information, the methods or processes used to critique or research, and don’t forget to rely upon trusted sources like What Works Clearinghouse . You might also appreciate a lecture presented by Maren Aukerman that discusses comprehensive, research-informed literacy instruction . The more you dig, the more you may find that many practices and programs touted as evidence-based are either based on personal anecdotes and stories or the research base is flimsy at best.

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Phone: 617.349.8424

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Iowa Reading Research Center

Evidence-based vs. research-based interventions—update.

Have you ever wondered about the terms  evidence-based  and  research-based  interventions? Educators and schools often wrestle with these terms as they consider programs or intervention to implement.

Evidence-Based vs. Research-Based: What is the Difference?

Many publishers tout their programs as being research-based or evidence-based, and oftentimes people use those terms interchangeably.   Have you ever wondered if there was a difference between  evidence-based  and  research-based  and, if so, what that difference might be?

Dr. Sally Shaywitz, Co-Director of the Yale Center for Dyslexia and Creativity, provides a simple explanation in a brief  video clip  about the difference between the two terms and how they relate to reading programs. She discusses how research-based means there are theories behind it, but that they aren’t always proven true. She tells how evidence-based means there is efficacy to back it up.

We can help explain what Dr. Shaywitz meant by “efficacy” in several ways. First, it requires that the program was studied by researchers who were not involved in creating the program. In addition, the researchers cannot stand to profit from the outcomes. Finally, the study the researchers conducted should have the following characteristics:

• The program was compared to another type of program or a different kind of instruction.
• Improvements in students’ reading abilities were measured with valid and reliable instruments.
• There was a thorough description of how the program was implemented so that others could follow those same procedures and include the same elements.
• The effect sizes were reported, and those revealed an improvement that was significantly greater than any improvement in the comparison condition.

Understanding what creates an evidence base is helpful when thinking about intervention programs, particularly for those students with serious reading difficulties. As Dr. Shaywitz commented, “Our children’s reading is too important to be left to theoretical, but unproven, practices and methods. We must replace anecdotal and common, but not evidence-based practices with those that are proven; that is, they are evidence-based.”

Reviews of Intervention Programs

The  Iowa Department of Education  has commissioned a review of the evidence base for literacy interventions commonly used in the state. Studies that examined the effectiveness of these programs were evaluated against rigorous criteria such as those used by the  National Center on Intensive Interventions  (NCII) and the What Works Clearinghouse (WWC). The NCII maintains an  Academic Intervention Tools Chart  to summarize their reviews of individual studies on programs.

The  What Works Clearinghouse  (WWC), part of the Institute of Education Science, is another source for determining which programs and practices have  evidence of effectiveness . The WWC reviews research designed to answer the question, “What works in education?” You can visit the WWC and use the filters to locate reviews specific to reading skills.

• evidence-based practice
• interventions
• research-based practice

6 Spring Break Literacy Activities for Families

Research-Based Teacher Education

• Living reference work entry
• First Online: 13 July 2019
• Cite this living reference work entry

• Elaine Munthe 2  

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Introduction

Conceptions of what teacher education is and should prepare for have changed along with growing social complexity, a stronger focus on accountability, and deepening understanding of how people learn and what teachers need to know (Cochran-Smith et al. 2016 ). Teachers face an increasingly wide range of student learning differences in their classrooms, they are expected to develop new ways of teaching and learning, and technology is being introduced at a rapid pace, often with little support. In many countries, this has led to a call for teacher education programs that help teachers to become innovators and researchers in education, laying a foundation for continuous learning and change in the workplace (Brouwer and Korthagen 2005 ).

Research-based teacher education is one key to this development, but how research-based teacher education is understood can vary, and there can be varying degrees of strength in a research-based teacher education program. In the following,...

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British Educational Research Association/BERA. (2014). Research and the teaching profession, final report of the BERA-RSA inquiry into the role of research in teacher education, BERA. Downloaded from: https://www.bera.ac.uk/project/research-and-teacher-education

Brouwer, N., & Korthagen, F. A. (2005). Can teacher education make a difference? American Educational Research Journal, 42 (1), 153–224.

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Niemi, H. (2016). Academic and practical: Research-based teacher education in Finland. In B. Moon (Ed.), Do universities have a role in the education and training of teachers? An international analysis of policy and practice (pp. 19–34). Cambridge, UK: Cambridge University Press.

Toom, A., Kynäslahti, H., Krokfors, L., Jyrhämä, R., Byman, R., Stenberg, K., et al. (2010). Experiences of a research based approach to teacher education: Suggestions for future policies. European Journal of Education, 45 (2), Part II, 331–Part II, 344.

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Elaine Munthe

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Munthe, E. (2019). Research-Based Teacher Education. In: Peters, M. (eds) Encyclopedia of Teacher Education. Springer, Singapore. https://doi.org/10.1007/978-981-13-1179-6_53-1

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11 Knights Earn NSF Graduate Research Fellowship Recognitions for 2024

The U.S. National Science Foundation Fellowship helps students continue research-based master’s and doctoral degrees at accredited U.S. institutions.

By Ryan Randall | May 23, 2024

Five Knights have earned the most prestigious STEM research fellowship in the United States. Another six have earned honorable mentions for the award.

Five UCF alums have received U.S. National Science Foundation (NSF) Graduate Research Fellowships (GRF), which supports outstanding graduate students in STEM disciplines who are pursuing research-based master’s and doctoral degrees at accredited U.S. institutions. The five-year fellowship includes three years of financial support with an annual stipend of $37,000 and a cost of education allowance of $16,000 to the institution. Each award is valued up to $159,000.

“This is a campuswide achievement that could not be possible without the support of faculty like [Associate Professor of Writing and Rhetoric] Laurie Pinkert, and other academic support offices such as Honors Research and Academic Advancement Programs,” says Morgan Bauer, director of the Office of Prestigious Awards in UCF’s Burnett Honors College.

The Knights who are named fellows are:

Laurie Agosto ’19 Applied sciences alum with a biology minor College of Undergraduate Studies College of Sciences

Saoulkie Bertin ’23 Interdisciplinary studies alum with a medical anthropology minor and anthropology of global health certificate Burnett Honors College College of Undergraduate Studies College of Sciences

Stephen Staklinski ’20 Biomedical sciences alum Burnett Honors College College of Medicine

Andres Torres ’08 Aerospace engineering alum College of Engineering and Computer Science

Stephanie Washburn ’24 Psychology alum with a statistics minor Burnett Honors College College of Sciences

Those who received honorable mentions are:

Rachel Cooper Psychology doctoral student College of Sciences

Michael Kwara ’22 Mechanical engin eering alum; mechanical engineering master’s student Burnett Honors College College of Engineering and Computer Science

Andrea Mullin Psychology student Burnett Honors College College of Sciences

Fahad Nabid ’23 Aerospace engineering alum Burnett Honors College College of Engineering and Computer Science

Sachin Shah ’22 Computer science alum Burnett Honors College College of Engineering and Computer Science

Nyle Siddiqui Computer science doctoral student College of Engineering and Computer Science

For some graduates, such as Bertin and Washburn, the journey to the fellowship was assisted through their involvement with the Ronald E. McNair Scholars Program, a U.S. Department of Education program that aims to increase the attainment of doctoral degrees by students from underrepresented segments of society.

Through the McNair Scholars Program, Bertin conducted summer research at John Hopkins University and participated in a global health internship in Puerto Rico while she earned a degree in interdisciplinary studies at UCF.

In 2021, Bertin led a point-of-sale task force in promoting a healthier and tobacco-free county through a collaboration between UCF and the Florida Department of Health (FDOH) in Orange County. For her work, she received the FDOH Health Equity Hero Award, which recognizes public health individuals in the community. The work also led to a thesis in 2023 examining the culture of local activist groups in Central Florida and their influence nicotine-related policy change, using data collected through participant observation and semi-structured interviews with activist group members, key actors, and nicotine users in Volusia County and Orange counties.

As an incoming global and sociocultural sciences doctoral student at with Florida International University, she will further her research interests at the intersection of climate change and the intricate interplay of government and industry policies concerning food, tobacco/nicotine, and their health implications.

“I like community-engaged research, so [I] definitely [have done] a lot of volunteering in the community [and] I know that can help inform my research in the long term,” Bertin says.

While at UCF, Washburn, a psychology major with a specialization in neuroscience, mainly investigated identity research, which examines how one’s characteristics can ultimately shape resiliency and adaptation in the face of trauma. In particular, her work explored identity’s impact on executive functions, which are dominated by the prefrontal cortex and consist of planning and time organization.

Her research led her to studying at MIT, as well as a TEDx talk, titled The Kaleideoscope of You . As part of the GRF, she has been accepted to the University of Florida, where she’ll be a doctoral candidate in psychology and will focus on furthering her research on Alzheimer’s disease.

“As populations get older, we’re striving for keeping them independent and we don’t really know how. That drove me more toward the aging side of things,” Washburn says. “My grandmother also passed away with Alzheimer’s disease, so there’s a personal motivation as well, in addition to the fascination with neuroscience.”

The McNair Scholars Program not only provided students like Bertin and Washburn with research opportunities, but also support and guidance to apply for the NSF fellowship, ultimately taking their studies even further.

“For me, I needed something outside to push me and empower me to apply, and that was my mentor, [Associate Professor of Anthropology] Shana Harris,” Bertin says. “She and the director of the McNair program, [Michael Aldarondo-Jeffries], told me ‘I think you’d be a good fit.’ Now, if there’s an opportunity and I don’t think I fit, I shrug it off and apply because the worst thing they can say is ‘no.’ Not applying is an automatic no.”

Those interested in the NSF Graduate Research Fellowship program and other opportunities, please reach out to the Office of Prestigious Awards at [email protected] .

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Everything counts!

Research finds step-count and time are equally valid in reducing health risks

Kira Sampson

BWH Communications

A new study suggests that both step-count and time-based exercise goals are equally effective in reducing risks of heart disease and early death.

Researchers from Harvard-affiliated Brigham and Women’s Hospital reviewed data on healthy women age 62+, who used wearable devices to record their physical activity, and then tracked their health outcomes. After a median follow-up of nine years, the researchers found higher levels of physical activity, whether in time of exercise or step counts, were associated with large risk reductions in mortality and cardiovascular disease. The most active quarter of women in the study had a 30 to 40 percent reduced risk compared to the least active quarter.

Results of the study are published in JAMA Internal Medicine . 

“We recognized that existing physical activity guidelines focus primarily on activity duration and intensity but lack step-based recommendations,” said lead author Rikuta Hamaya, a researcher in the  Division of Preventive Medicine  at BWH. “With more people using smartwatches to measure their steps and overall health, we saw the importance of ascertaining how step-based measurements compare to time-based targets in their association with health outcomes — is one better than the other?” 

“Movement looks different for everyone, and nearly all forms of movement are beneficial to our health.”  Rikuta Hamaya

The current  U.S. guidelines , last updated in 2018, recommend that adults engage in at least 150 minutes of moderate to vigorous physical activity (e.g., brisk walking) or 75 minutes of vigorous activity (e.g., jogging) per week. At that time, most of the existing evidence on health benefits came from studies where participants self-reported their physical activity. Few data points existed on the relationship between steps and health. Fast-forward to the present — with wearables being ubiquitous, step counts are now a popular metric among many fitness-tracking platforms. How do time-based goals stack up against step-based ones? Investigators sought to answer this question. 

For this study, investigators collected data from 14,399 women who participated in the Women’s Health Study, and were healthy (free from cardiovascular disease and cancer). Between 2011 and 2015, participants aged 62 years and older were asked to wear research-grade wearables for seven consecutive days to record their physical activity levels, only removing the devices for sleep or water-related activities. Throughout the study period, annual questionnaires were administered to ascertain health outcomes of interest, in particular, death from any cause and cardiovascular disease. Investigators followed up with participants through the end of 2022. 

At the time of device wear, researchers found that participants engaged in a median of 62 minutes of moderate-to-vigorous intensity physical activity per week and accumulated a median of 5,183 steps per day. During a median follow-up of nine years, approximately 9 percent of participants had passed and roughly 4 percent developed cardiovascular disease.

Higher levels of physical activity (whether assessed as step counts or time in moderate to vigorous activity) were associated with large risk reductions in death or cardiovascular disease — the most active quarter of women reduced their risk by 30-40 percent compared with the least-active quarter. Individuals in the top three quartiles of physical activity outlived those in the bottom quartile by an average of 2.22 and 2.36 months respectively, based on time and step-based measurements, at nine years of follow-up. This survival advantage persisted regardless of differences in body mass index (BMI). 

While both metrics are useful in portraying health status, Hamaya explained that each has its advantages and downsides. For one, step counts may not account for differences in fitness levels. For example, if a 20-year-old and 80-year-old both walk for 30 minutes at moderate intensity, their step counts may differ significantly. Conversely, steps are straightforward to measure and less subject to interpretation compared to exercise intensity. Additionally, steps capture even sporadic movements of everyday life, not just exercise, and these kinds of daily life activities likely are those carried out by older individuals. 

“For some, especially for younger individuals, exercise may involve activities like tennis, soccer, walking, or jogging, all of which can be easily tracked with steps. However, for others, it may consist of bike rides or swimming, where monitoring the duration of exercise is simpler,” said Hamaya. “That’s why it’s important for physical-activity guidelines to offer multiple ways to reach goals. Movement looks different for everyone, and nearly all forms of movement are beneficial to our health.” 

The authors note that this study incorporates only a single assessment of time and step-based physical activity metrics. Further, most women included in the study were white and of higher socioeconomic status. Finally, this study was observational, and thus causal relations cannot be proven. In the future, Hamaya aims to collect more data via a randomized controlled trial to better understand the relationship between time and step-based exercise metrics and health. 

“The next federal physical activity guidelines are planned for 2028,” said senior author I-Min Lee, an epidemiologist in the Division of Preventive Medicine at BWH. “Our findings further establish the importance of adding step-based targets, in order to accommodate flexibility of goals that work for individuals with differing preferences, abilities and lifestyles.”  

Disclosures : Hamaya reported receiving consulting fees from DeSC Healthcare, Inc., outside of the submitted work. Co-authors Christopher Moore, Julie Buring, Kelly Evenson, and Lee reported receiving institutional support from the National Institutes of Health during the conduct of the study.

This research was supported in part by the National Institutes of Health (CA154647, CA047988, CA182913, HL043851, HL080467, and HL09935), the National Cancer Institute (5R01CA227122), Office of the Director, Office of Disease Prevention, and Office of Behavioral and Social Sciences Research; and by the extramural research program at the National Heart, Lung, and Blood Institute. 

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Community violence generally happens outside the home in public spaces. Most community violence involves a relatively small number of people as victims or perpetrators. Still, its effects impact entire communities, eroding public health, causing economic disruption, and contributing to lasting individual and community traumas. Mitigation efforts typically focus on high-risk individuals, gun violence, specific violent crime problems, as well as the historical and structural challenges that often result in community violence.

Community violence intervention (CVI) is an approach that uses evidence-informed strategies to reduce violence through tailored community-centered initiatives. These multidisciplinary strategies engage individuals and groups to prevent and disrupt cycles of violence and retaliation, and establish relationships between individuals and community assets to deliver services that save lives, address trauma, provide opportunity, and improve the physical, social, and economic conditions that drive violence.

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Study explains why the brain can robustly recognize images, even without color

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Even though the human visual system has sophisticated machinery for processing color, the brain has no problem recognizing objects in black-and-white images. A new study from MIT offers a possible explanation for how the brain comes to be so adept at identifying both color and color-degraded images.

Using experimental data and computational modeling, the researchers found evidence suggesting the roots of this ability may lie in development. Early in life, when newborns receive strongly limited color information, the brain is forced to learn to distinguish objects based on their luminance, or intensity of light they emit, rather than their color. Later in life, when the retina and cortex are better equipped to process colors, the brain incorporates color information as well but also maintains its previously acquired ability to recognize images without critical reliance on color cues.

The findings are consistent with previous work showing that initially degraded visual and auditory input can actually be beneficial to the early development of perceptual systems.

“This general idea, that there is something important about the initial limitations that we have in our perceptual system, transcends color vision and visual acuity. Some of the work that our lab has done in the context of audition also suggests that there’s something important about placing limits on the richness of information that the neonatal system is initially exposed to,” says Pawan Sinha, a professor of brain and cognitive sciences at MIT and the senior author of the study.

The findings also help to explain why children who are born blind but have their vision restored later in life, through the removal of congenital cataracts, have much more difficulty identifying objects presented in black and white. Those children, who receive rich color input as soon as their sight is restored, may develop an overreliance on color that makes them much less resilient to changes or removal of color information.

MIT postdocs Marin Vogelsang and Lukas Vogelsang, and Project Prakash research scientist Priti Gupta, are the lead authors of the study, which appears today in Science . Sidney Diamond, a retired neurologist who is now an MIT research affiliate, and additional members of the Project Prakash team are also authors of the paper.

Seeing in black and white

The researchers’ exploration of how early experience with color affects later object recognition grew out of a simple observation from a study of children who had their sight restored after being born with congenital cataracts. In 2005, Sinha launched Project Prakash (the Sanskrit word for “light”), an effort in India to identify and treat children with reversible forms of vision loss.

Many of those children suffer from blindness due to dense bilateral cataracts. This condition often goes untreated in India, which has the world’s largest population of blind children, estimated between 200,000 and 700,000.

Children who receive treatment through Project Prakash may also participate in studies of their visual development, many of which have helped scientists learn more about how the brain's organization changes following restoration of sight, how the brain estimates brightness, and other phenomena related to vision.

In this study, Sinha and his colleagues gave children a simple test of object recognition, presenting both color and black-and-white images. For children born with normal sight, converting color images to grayscale had no effect at all on their ability to recognize the depicted object. However, when children who underwent cataract removal were presented with black-and-white images, their performance dropped significantly.

This led the researchers to hypothesize that the nature of visual inputs children are exposed to early in life may play a crucial role in shaping resilience to color changes and the ability to identify objects presented in black-and-white images. In normally sighted newborns, retinal cone cells are not well-developed at birth, resulting in babies having poor visual acuity and poor color vision. Over the first years of life, their vision improves markedly as the cone system develops.

Because the immature visual system receives significantly reduced color information, the researchers hypothesized that during this time, the baby brain is forced to gain proficiency at recognizing images with reduced color cues. Additionally, they proposed, children who are born with cataracts and have them removed later may learn to rely too much on color cues when identifying objects, because, as they experimentally demonstrated in the paper, with mature retinas, they commence their post-operative journeys with good color vision.

To rigorously test that hypothesis, the researchers used a standard convolutional neural network, AlexNet, as a computational model of vision. They trained the network to recognize objects, giving it different types of input during training. As part of one training regimen, they initially showed the model grayscale images only, then introduced color images later on. This roughly mimics the developmental progression of chromatic enrichment as babies’ eyesight matures over the first years of life.

Another training regimen comprised only color images. This approximates the experience of the Project Prakash children, because they can process full color information as soon as their cataracts are removed.

The researchers found that the developmentally inspired model could accurately recognize objects in either type of image and was also resilient to other color manipulations. However, the Prakash-proxy model trained only on color images did not show good generalization to grayscale or hue-manipulated images.

“What happens is that this Prakash-like model is very good with colored images, but it’s very poor with anything else. When not starting out with initially color-degraded training, these models just don’t generalize, perhaps because of their over-reliance on specific color cues,” Lukas Vogelsang says.

The robust generalization of the developmentally inspired model is not merely a consequence of it having been trained on both color and grayscale images; the temporal ordering of these images makes a big difference. Another object-recognition model that was trained on color images first, followed by grayscale images, did not do as well at identifying black-and-white objects.

“It’s not just the steps of the developmental choreography that are important, but also the order in which they are played out,” Sinha says.

The advantages of limited sensory input

By analyzing the internal organization of the models, the researchers found that those that begin with grayscale inputs learn to rely on luminance to identify objects. Once they begin receiving color input, they don’t change their approach very much, since they’ve already learned a strategy that works well. Models that began with color images did shift their approach once grayscale images were introduced, but could not shift enough to make them as accurate as the models that were given grayscale images first.

A similar phenomenon may occur in the human brain, which has more plasticity early in life, and can easily learn to identify objects based on their luminance alone. Early in life, the paucity of color information may in fact be beneficial to the developing brain, as it learns to identify objects based on sparse information.

“As a newborn, the normally sighted child is deprived, in a certain sense, of color vision. And that turns out to be an advantage,” Diamond says.

Researchers in Sinha’s lab have observed that limitations in early sensory input can also benefit other aspects of vision, as well as the auditory system. In 2022, they used computational models to show that early exposure to only low-frequency sounds, similar to those that babies hear in the womb, improves performance on auditory tasks that require analyzing sounds over a longer period of time, such as recognizing emotions. They now plan to explore whether this phenomenon extends to other aspects of development, such as language acquisition.

The research was funded by the National Eye Institute of NIH and the Intelligence Advanced Research Projects Activity.

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Acing Value-Based Sales

To get the best returns on innovative products, collaborate with customers to define and share the commercial opportunity.

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Imagine that burst of enthusiasm when a senior executive unveils a plan that promises a significant and lasting impact on the organization’s financial performance. “Our new product creates more value for our customers than anything else on the market, and we should get paid accordingly,” they proudly declare. “If we measure and communicate that value precisely, then we can finally get the return we deserve.”

The sales team buys into the logic. Now armed with a superior product, a sophisticated value calculator, and a host of new selling arguments, they quickly turn the senior executive into a prophet. Price, margin, and profit all improve significantly in the first quarter of implementation, with a smaller but still important increase the next.

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A year later, however, few traces of the highly touted program remain. The selling arguments have gone stale. The state-of-the-art value calculator is dismissed as theoretical and complex. The early financial gains have evaporated as the sales team, under constant pressure from fierce buyers, returns to aggressive discounts to win the volume and customers lost at the outset.

Such sagas are an open secret in B2B markets around the world. Many companies embrace value-based selling programs, but few succeed in a significant, sustainable way. They invest heavily in product development, but frustration spreads when customers don’t understand the points of differentiation, never mind wanting to pay for them. The dream outcome of selling on value rather than cutting good deals never materializes, leaving a trail of demotivated salespeople and missed opportunities. Worst of all, lacking a clear return, companies postpone or cut back on investments — which reassures competitors that they can get away with mediocre offerings.

In our experience, value-based selling initiatives often start with the wrong premise. Senior executives assume that their company’s differentiated offerings deserve a higher price. In turn, this sense of entitlement lulls them into thinking that the only challenge is to quantify and communicate every advantage. Faced with hard numbers, they reason, any customer in their right mind would happily pay a premium.

However, in most commercial relationships, value is not at the sole discretion of the seller but cocreated with customers who play an active role in realizing desired outcomes. It follows that successful value-based sellers not only prove the added value of their products and services but also gain commitment from customers and foster a shared understanding of the opportunity.

Our framework, developed over years of helping companies achieve long-term returns from product development, grounds a five-part process for successful value-based sales in three key principles essential to such initiatives: commitment, understanding, and proof. (See “Engaging Customers in Value-Based Selling.”) Establishing commitment is required at the start to motivate customers to work with the sales team, and again at the end to reward customers appropriately. The drive to reach mutual understanding shapes the second step, where salespeople educate customers about the range of benefits offered by their solutions, as well as the fourth step, where they translate expected customer savings and gains into a compelling business case. At the center of our framework and the sales process is proof — because, ultimately, companies attract and retain customers only when they can quantify the value that their solutions add.

Best-in-class value-based selling realizes that “showing customers the money” is not enough. In this article, we will expand on each of these steps and explain how to tackle them in your business.

Motivate: Set the Context for Value Cocreation

The potential of a commercial opportunity may be clear, but it will fail to materialize if your company or the customer lacks the motivation to collaborate in creating and sharing value. The two key dimensions to motivation, the first step in our framework, are the balance of power between sides and the customer’s financial wherewithal.

Conventional wisdom calls for the party with the greater bargaining power to shape the deal in its favor. This results in higher prices and more stringent conditions when the seller has the advantage, and lower prices and more generous conditions when the buyer does. In this view, any codependence between the two parties relies more on force or acquiescence than on actual need or mutual choice.

But this perspective is myopic. The overconfidence that comes from having leverage tempts the dominant side to appropriate as much value as it can in the short term, meanwhile neglecting the opportunity to create greater value in the long run by working with the other side. When your company has the advantage, you should exercise self-restraint and pass up short-term gains for longer-term value creation. An excessively short-term focus fosters an arm’s-length relationship that keeps high prices top of mind for customers and encourages them to look for alternative suppliers. If the customer switches suppliers, you lose not only a revenue opportunity with a partner but also insights into product performance and customer benefits that can accrue only from long-term, repeated engagements. When the customer has the advantage, look to reduce its leverage by developing other customer relationships. You can also look for ways to influence the customer’s own customers to demand the value that you provide, such as via a stronger branding effort. The “Intel Inside” tag on personal computers is an example of how to drive awareness and end-user demand.

Buyers and sellers, then, have the best basis for joint value creation when the balance of power between them is relatively even. Yet, even with a level playing field, value creation will not happen unless customers have the money, time, and talent to purchase and properly implement a demonstrably better solution. Innovative offerings, especially those whose value accrues over time, are irrelevant if customers cannot afford them or cannot get them to perform to their potential.

Affordability was a barrier for global tire manufacturer Michelin when it introduced new products to its industrial customers. Its solution was to change the price metric such that, instead of selling customers the tires they needed for their fleets of trucks, Michelin retained ownership of the tires and invoiced on a per-mile-driven basis. The company not only improved access to better tires by spreading the burden of payment across time but also improved relationships: Low-consumption customers assumed less commercial risk (since they paid only when trucks were on the road) and could rely on Michelin’s expertise in the selection, repair, replacement, and recycling of tires to ensure that their fleets always had optimal equipment at hand. Michelin and its customers improved productivity and profitability because the common metric became a way to align their interests and not merely a clever way to pay for tires.

Motivating customers to participate in joint value creation is important, but it isn’t the only element of context-setting that your company needs to attend to. It’s also essential that customers understand the full extent of benefits that your products or services can bring.

Educate: Raise Awareness of Customer Benefits

A commercial opportunity relies on how well your company and your customers understand the benefits that drive value creation. The assistance of marketing and communications teams is critical at this point, in particular because benefits often accrue not only when a product is used but also at acquisition and disposal. At this step, the goal is simply to make customers question the wisdom of pushing on price.

Scot Forge, a 130-year-old metals forging company, succeeds with its value-based selling efforts because its teams think about value and price separately. They achieve this hard separation by focusing on a prospective customer’s biggest needs and challenges. In a joint process of discovery and exploration, Scot Forge and its customers create a standard vocabulary to define benefits and how the two parties will then quantify them.

A commercial opportunity relies on how well your company and your customers understand the benefits that drive value creation.

They aren’t starting this process with a blank slate: Scot Forge maintains a long list of potential benefits for its products and services that is based on how the benefits are initially defined and measured. This standardization facilitates the discussions with buyers by providing a starting point. Many customers can intuitively judge whether the initial estimate of a benefit is too high or too low, but if asked directly, they would struggle to provide an accurate estimate of their own.

This process narrows down the list of benefits to what matters to each customer. Agreement on how to quantify the benefits is about more than mathematical formulas. The parties also agree on how accurate measurements should be. In reality, “close enough” is acceptably accurate for many measurements.

Such a process allows salespeople to set aside their assumptions regarding “this is what our solution does” to reach consensus on “this is how our solution helps you.” Salespeople in companies with a strong engineering culture may know, for example, that their new equipment has a smaller footprint and half the moving parts compared with a similar product offered by their main competitor. But outperforming competitors on one or more attributes does not guarantee that every customer will benefit from it.

Salespeople may also know that their solution has helped other companies reduce labor costs. But that benefit may not matter as much to a customer whose shops employ union labor or a customer that relies on offshore manufacturing to keep labor costs competitive. In another case, a company’s solution may yield a step change down in energy costs only after a certain volume threshold is reached. Salespeople need to know whether a prospective customer can at least meet that threshold, which would make the benefit worth prioritizing.

The number of benefits, and the mix between tangible and intangible benefits, is specific to an individual customer or, at most, to a segment of similar customers. Benefits such as less downtime, lower per-unit labor costs, or reduced energy consumption are easier to understand and quantify than potential increases in demand or higher brand awareness.

The business and technology consulting firm West Monroe succeeds with an approach similar to Scot Forge’s. The firm delivers value by advising organizations and implementing new technologies and ways of working, but those benefits are achieved only by changing people’s mindsets and behaviors. It’s about helping clients understand how new and different ways of working can deliver value across stakeholders.

Indeed, West Monroe saw an opportunity across the consulting industry. “Approximately half of our competitors’ clients didn’t feel that their consulting firm’s value delivered was greater than the fees charged,” said Casey Foss, West Monroe’s chief commercial officer. “That’s a big opportunity, but competing on financial results required us to be better at creating, optimizing, and communicating our value to clients.” The firm now tracks value-creation scores that rate the value received compared to fees paid. Those scores can be 32% higher among clients with whom it jointly quantifies value, because both parties are focused on the initiatives expected to have the greatest impact.

We’ve found very few companies engaging with customers the way Scot Forge and West Monroe do. We often encounter salespeople who lack the basic training to engage buyers in discussions about value and acknowledge the right trade-offs. Professional buyers are quick to point out that there are cheaper solutions available in the market; of course, there are always going to be competitors offering better deals. The issue is whether salespeople can help customers see — and quantify — the results they will be sacrificing to enjoy a better price.

Quantify: Solve the ABC Problem

Proof sits at the center of our framework because it is the fundamental part of any business transaction. Every commercial opportunity must be expressed in the medium customers use to gauge value. In most business markets, this medium is money. Your company’s task, then, is figuring out how your solution yields savings and gains — a challenge that we call the “ABC problem” because the path leads from product or service attributes to customer benefits to shared cash .

Solving the ABC problem is a numerical exercise that feeds on data and creativity. The data element is clear: Your company cannot substantiate claims without evidence of how an attribute or feature generates a benefit and how that benefit impacts the customer’s finances. This evidence, however, often arises when a solution is used, which implies that the customer must be enticed to share information. These enticements can include exclusive access to future innovations, consulting or other insights, temporary discounts, or other rewards.

But sellers should not underestimate the role of creativity and discovery. It is not always clear how the technical specifications of a given attribute can be expressed numerically as a benefit. One common misconception is that tangible benefits such as higher productivity or reduced energy consumption are relatively easy to convert into dollars and cents. Sometimes the tangible benefits are indirect. When a manufacturer introduced a new generation of machines that had a significantly lower operating temperature than its predecessors, its sales and marketing teams struggled at first to express the advantage in monetary terms. It turned out that the lower temperature meant the equipment required less lubrication, which translated into measurable savings for customers in terms of materials, labor, and waste disposal.

Another misconception is that intangible benefits such as brand equity or ease of use are nearly impossible to articulate in monetary terms. While there is some truth to this, blanket assumptions are dangerous if they lead companies to give up on quantifying intangible benefits too soon and use them as add-ons to sweeten the deal rather than as inputs to a better price. In many cases, intangible benefits represent a large part of the added value of an innovative product. If your company undersells or underestimates them, then it effectively renounces a good part of the margin it stands to make from the sale.

In our view, the impact of a benefit depends on the extent to which it fulfills the following criteria.

• Relevant: A customer needs to understand how it can capitalize on a given benefit. Superior towing capacity and cold-weather performance are wonderful innovations, but they mean nothing to a company that does little towing and never operates in cold weather. If your sales team doesn’t understand which benefits are relevant for a prospective customer, they risk dumping features into the offer indiscriminately or making every offer “all you can eat” for simplicity’s sake.
• Quantifiable: Is the relevant benefit observable and countable? Ideally, the customer can easily perceive a direct relationship between cause and effect. A heavy vehicle manufacturer may, for example, document that it has twice the towing capacity of its competitors and has superior cold-weather performance. But finding a concept and an equation to quantify a benefit is not sufficient. Quantification is possible only with a reliable flow of credible data. Does your company and the customer have the means in place to monitor performance and collect data? Do you have a central collection point that can serve as a single source of truth? The better the data, the better the company can estimate the value of the benefit.
• Verifiable: The customer still needs to realize the estimated benefits. This depends on cooperation between the buyer and seller to share data and agree on the calculations. Following up regularly after the sale gives your team a chance to observe how successfully the customer has implemented the solution and verify that the estimated benefits exist. You can work on corrective actions if the implementation or the benefits are falling short of expectations. Follow-up visits also provide additional data you can use to adjust claimed benefits for future sales. One way to support verification is to make the outcomes visible through a tool such as a value calculator tailored to the customer’s business.

These three criteria should be considered sequentially when deciding where to focus the sales effort. First, your company must identify the benefits that are relevant to the customer in question. From these relevant benefits, priority goes to the ones that are quantifiable. Then, among the quantifiable relevant benefits, the emphasis should be on the verifiable ones.

These criteria also determine the nature of the sales effort. The more a benefit satisfies all three criteria, the greater the underlying certainty that it is achievable. Your sales team can then focus on making direct comparisons to alternative and presumably inferior solutions. Indirect comparisons and general statements such as “a 1% improvement in this benefit yields $X million in savings” may not be meaningful to most customers, given that estimated and actual results often deviate significantly from an average. One buyer told us that if his company were to achieve all the savings that potential sellers have promised him in those “1%” claims, its savings would be greater than its actual costs. Such cynicism has prompted some buyers to insist on guarantees or other forms of risk sharing that compel sellers to take a more active role in ensuring that they achieve the estimated benefits.

For benefits that are relevant and quantifiable but not verifiable, your company owns the burden of proof. You can use mechanisms such as benchmarking, pilot tests, or samples to offset perceived risk by the customer. Finally, for benefits that are relevant but neither quantifiable nor verifiable, look to market research for support. When introducing data that comes from customer surveys, though, it is important to make sure respondents have sufficient prior experience with the product to validate their judgments, and an incentive to answer truthfully. You want credible and accurate data at hand as you move toward building a strong case in the next step.

Translate: Turn Impact Into a Compelling Business Case

Specialty chemicals company Borealis conducts value workshops with its potential customers to help them connect the prioritized list of quantified benefits to their day-to-day operations. “We build a customized model, and we present it step by step, validating our assumptions during the conversation,” said Paolo De Angeli, head of customer value management. This not only gets buy-in from customers but also enables Borealis and the customer to reach a common understanding of the differential value that the company creates. It also allows both parties “to identify opportunities for further value creation by working together as partners,” De Angeli added. The common metrics keep conversations focused on quantified value delivered.

We talk about translating impact because numbers seldom speak for themselves. Calculating the monetary gains from adopting a particular product is a must, but wrapping dry figures in language, visuals, and interfaces that resonate with customers is also critical. The more familiar the story feels, the more agency the customer will feel it has. Your company can use that as a call to action to cocreate value.

Calculating the monetary gains from adopting a particular product is a must, but wrapping dry figures in language, visuals, and interfaces that resonate with customers is critical.

The most powerful business cases are stories that travel well, meaning that they retain meaning beyond the people directly involved with negotiating a deal — such as the senior executive who has final control over budget approval, the local manager who is responsible for implementing the company’s innovative product, and so on. This extended audience usually has limited time, a limited understanding of the context, and its own vernacular. Therefore, successful business cases feature the following.

• A small number of key messages: Benefits are not necessarily additive; less may be more. The choice of what benefits to communicate, in which order, can affect a buyer’s value perception. For example, juxtaposing a strong or resonating benefit with a less impactful one can diminish the perception of the more valuable benefit.
• The right amount of detail: It is better to share just enough detail to enable a decision and keep the information specific and relevant to the customer. When discussing the business case directly, your company can share more information if the listener indicates a need for it or asks a question. To help the business case travel better, you could include a brief Q&A in an appendix that anticipates and answers additional questions. Refraining from telling the whole story may be difficult for sellers who know their product back to front, because they may struggle to put themselves in the position of someone looking at the product for the first time. Salespeople need to resist the temptation to smother the customer with extraneous details.
• Clear next steps: The business case should include an operational framework that specifies the KPIs and the tools and data to measure and validate them. Creating a joint agreement for documentation and validation keeps your company involved after the sale closes and draws the attention of senior management beyond the buying team that negotiated the deal.

Reward: Align Interests With Smart Incentives

Any value-based selling effort must be coupled with strong incentives for the company and customers to create and allocate value over an extended period. With respect to the customer, incentives operate at two levels: the price metric and the price points.

Michelin and its customers in the mining sector agreed on a price metric — cost per mile driven — that aligned with the way the parties create value together. The more material the mine can transport more frequently over longer distances, the more productive the mine will be. Contrast this approach with setting a price per product and offering discounts ex post to adjust for observed outcomes. The money paid and received may be the same, but the latter process is far less collegial.

Early-stage motivation and late-stage incentives both belong in the commitment layer of our recommended process because the price points — the split of the value pie — need to reflect and maintain the stable balance of power established at the outset of the process. The split should reflect the proof behind benefits and the time frame of the agreement. A split that favors one party too strongly will eventually give the other party a disincentive to create additional value.

After moving through the first four steps of our framework, salespeople should be well prepared to counter requests for lower prices or larger scopes by making the appropriate price-value trade-offs. But they also need incentives to negotiate those trade-offs in a way that secures the best price for your company, which is usually neither the highest possible price nor a low price that cedes too much value to the customer. Specific incentives can include rewards for negotiating a price within a target range or for growing the value pie, or rewards that are inversely proportional to discount levels. This marks a significant shift for companies that have trained and rewarded their salespeople to meet revenue or volume goals rather than goals related to profit or prices.

Closing the deal doesn’t mark the end of the transaction but rather the initiation of a new phase of the relationship.

How the buyer pays also makes a difference, and these payment methods and terms must be codified in advance. Let’s say a seller creates $10 million in mutually validated value for a customer over a two-year period. No matter how appreciative buyers are, few of them will have the willingness or even the authority to write a lump-sum check based on that value. Sellers can overcome these issues with financing options or with price metrics based on consumption, outcomes, or other parameters.

Closing the deal doesn’t mark the end of the transaction but rather the initiation of a new phase of the relationship. Tracking actual performance versus projected value allows your company to identify and resolve problems early and build a robust database for benchmarks. To ensure that it has a natural role in ongoing validation, for example, Michelin builds its models together with its customers, based on a common vision and goals.

In our experience, companies that implement our process for value-based selling start with two initiatives in parallel. First, they improve their ability to provide proof. Rigorous quantification is the core task for a reason. If your company does nothing else, this change will improve your sales efforts. Thinking through what is relevant, quantifiable, and verifiable ensures that business cases have a robust basis.

Second, they need to appoint a full-time value leader who is independent of sales and marketing. Marketing professionals tend to overshoot “soft” benefits such as brand and expertise. Apart from being wrong, this loses the trust of salespeople and complicates collaboration: Marketers blame sales for not being able to sell value; salespeople blame marketing for sending them into battle unprepared. If there is collective ownership of value throughout the organization, no function feels accountable for it, and each applies its own definitions and tools.

Appointing an independent value manager, then, marks the first move toward establishing commitment and understanding, the two outer layers of the framework. Marketing and communications support the process in promoting understanding, while finance and strategy have influence over commitment. The value leader also provides a powerful cross-check or counterweight by representing the customer’s interests as your company develops its plans for each step of the process.

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Perhaps the most important task of the value leader, though, is to align the organization on a shared and respected definition of value: how to define it, measure it, and adapt it for an individual customer. This is the ultimate prerequisite for successful value selling because the term value can mean everything and nothing at the same time. Continuous attention to the ABC problem makes value a habit and enables salespeople to adapt the definition to an individual customer’s needs.

Companies that make our framework the basis for their value selling can also expand their target markets. We refer to this as key account management at scale. A standard definition of value, supported by the right tools and mindset, enables your company to define and quantify value for any customer — even small ones — and decide the best way to share that value.

About the Authors

Marco Bertini is a professor of marketing and the director of open executive programs at Esade, in Barcelona, and a senior adviser to Globalpraxis. Oded Koenigsberg is executive dean, Dubai; professor of marketing; and chair, marketing faculty, at London Business School. Todd Snelgrove is the founder of consultancy Experts in Value and a fractional VP of sales at Sales Xceleration.

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