Evidence-Based Management Canvas (EBMc)

The Evidence-Based Management Canvas (EBMc) is a tool that helps organize the decision-making process in an organization systematically. It is based on analyzing reliable data and evidence from various sources, such as scientific research, organizational data, expert opinions, and the values or expectations of stakeholders. It enables managers to make effective, thoughtful, and justified decisions that enhance the efficiency and accuracy of actions within the organization.

Evidence-Based Management Canvas (EBMc)

^{It enables managers to make effective, thoughtful, and justified decisions.}

1. Problem Question Identifying the key management issue or challenge. This stage involves: Thorough understanding of the organizational context and the situation in which the problem arises. Formulating the question clearly and precisely to enable targeted evidence searching. Determining the objectives to be achieved and the criteria that will indicate success in solving the problem. Ensuring the question is relevant to stakeholders and aligns with the organization's strategic goals.		2. Data and Evidence Gathering evidence from six sources: Scientific Research: Review of scientific literature, such as peer-reviewed articles, meta-analyses, and research reports. It is important to consider studies on organizational behavior and the specificities of local and global markets. Gray Literature: Government reports, white papers, conference materials, and industry organization studies that often provide the latest practical data. Organizational Data: Internal company data, including operational reports, financial results, KPI analyses, or employee and customer satisfaction data, helping identify current challenges and trends. Expert Opinions: Recommendations from practitioners and industry specialists who can provide in-depth insights based on professional experience. Critical thinking is essential to avoid bias. Stakeholder Values and Expectations: Understanding the needs and priorities of individuals involved in the decision-making process, both internally and externally. Including their perspective builds engagement and acceptance of implemented solutions. Cultural Aspects: Analysis of norms, values, beliefs, and practices characteristic of the organization, industry, and broader environment in which the company operates.
3. Data Analysis Analyzing collected evidence using quantitative and qualitative methods.		4. Conclusions and Recommendations Developing and prioritizing data-driven recommendations.
5. Implementation Implementing the recommendations in practice and monitoring outcomes.

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Evidence-Based Management Canvas (EBMc) is a tool that helps organize the decision-making process in an organization systematically.

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Analysis of Max Ringelmann's experiment

Scientific research is the foundation of progress in science, but the question of whether it should be conducted individually or in teams remains relevant. The same applies to social sciences. The word social here plays an object role.

Max Ringelmann's 1913 experiment on tug-of-war can serve as a starting point for analyzing the impact of a group on the effectiveness of research work. This study reveals an interesting phenomenon related to the diffusion of responsibility, which can be crucial in the context of teams (including research teams). It is also worth considering what psychological mechanisms might influence research outcomes in a group, including the application of theories related to motivation and group dynamics.

Max Ringelmann’s Experiment

Max Ringelmann conducted an experiment comparing the effectiveness of individual and group tug-of-war. The results showed that participants who pulled the rope in a group exerted less force than those who participated in individual competitions. This phenomenon, called the Ringelmann Effect, indicates a decrease in effort in group situations, which stems from the "diffusion of responsibility." When people work together, they often feel that their individual contribution is not crucial to the final result. This can lead to reduced engagement and, consequently, lower group effectiveness.

Image by Ron Lach: pexels.com

Other Psychological Models

When analyzing the impact of teamwork on scientific research, it is useful to consider two other psychological models that can explain why working in a group may lead to less engagement:

1. Diffusion of Responsibility Theory (Latané, Williams, & Harkins, 1979)

   According to the diffusion of responsibility theory, when people work in a group, they tend to reduce their effort because they feel their individual contribution will not significantly affect the outcome. This effect is particularly pronounced when group members do not have clearly assigned roles or responsibilities. In scientific research, where each team member contributes their knowledge and skills, the lack of individual responsibility for the whole project can lead to decreased motivation and lower engagement in the task.

2. Social Proof Theory (Cialdini, 1984)

   According to this theory, people in a group often follow the behavior of other members, especially in situations where they are unsure of how to behave. In the context of scientific research, this can lead to a situation where group members conform to the expectations and standards of other researchers, which can reduce creativity and originality in their work. Rather than actively engaging in searching for new solutions, researchers may rely on behaviors and methods already used by others, diminishing their individual contribution.

Individual Work vs. Team Collaboration

Based on the Ringelmann Effect and the aforementioned psychological theories, conclusions can be drawn about the advantages and disadvantages of individual and team-based work in scientific research:

1. Benefits of Individual Work:

   Working individually allows for complete control over the research process. The researcher independently makes decisions regarding methodology, data analysis, and the direction of research. Additionally, it may lead to a deeper understanding of the subject, as the researcher has more freedom to explore specific issues. Moreover, the lack of external expectations fosters greater creativity and independence.

2. Benefits of Team Collaboration:

   On the other hand, collaboration in a research team allows for the exchange of ideas, integration of different specialized skills and experiences, which can lead to more comprehensive and accurate research. However, as shown by the Ringelmann Effect, it is crucial for the team to be well-organized, with clear responsibility for results, to avoid diffusion of responsibility and decreased engagement.

The Two Pizza Rule

In the context of organizing effective research teams, it is also worth mentioning the so-called Two Pizza Rule, proposed by Jeff Bezos, the founder of Amazon. This rule states that teams should have as many members as can be fed with two pizzas. This means the team should consist of 4 to 6 members to be small enough to enable effective communication and collaboration but also large enough to have a diverse set of skills and perspectives. In scientific research, this rule emphasizes the importance of maintaining small, agile groups that can quickly make decisions and focus on specific tasks, minimizing the risk of reduced engagement and diffusion of responsibility.

“Together, with full responsibility – every strength matters.”

Summary

Max Ringelmann's experiment and psychological models such as the diffusion of responsibility theory and social proof theory show that scientific research conducted in groups may encounter challenges related to motivation and engagement among team members. In individual work, the researcher has full control over the project, which leads to greater engagement. However, in the case of complex research, teamwork can yield better results, provided that each team member is responsible for their contribution and engagement. Ultimately, the key to success lies in the proper organization of team work and clear division of responsibilities.

Sources:

1. https://agilehunters.com/prozniactwo-spoleczne/ [2024-12-25]
2. Elizabeth Mieczkowski, Cameron Turner, Natalia Vélez, Thomas L. Griffiths, *Many Hands Don’t Always Make Light Work: Explaining Social Loafing via Multiprocessing Efficiency*, “Proceedings of the Annual Meeting of the Cognitive Science Society” (2024), pp. 5958–6005, Link.

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Merton's norms and Mitroff's counter-norms and real science

The reality of management science is based on solid methodological foundations that ensure the reliability, objectivity, and effectiveness of research and scientific processes. Merton's norms, developed by Robert Merton, introduced principles that form the foundation for a scientific approach to research in various fields. However, in the context of management science, there is also a need to consider the counter-norms proposed by Ian Mitroff, which address practical challenges that may arise in organizational reality. This article discusses the application of Merton's norms and Mitroff's counter-norms in the context of management Science, highlighting their significance in ensuring the effectiveness of organizational processes.

Merton's Norms

Robert Merton introduced four key principles (here presented as five, in a later variation) that are fundamental to science and research, and their application in the field of management science can serve as the foundation for an effective approach to innovation, development, and process improvement. In the context of management, these principles help ensure the reliability and transparency of decision-making and maintain high standards in the management science.

1. Universality

The principle of universality assumes that the results and decisions regarding quality management and organizational processes should be evaluated based on uniform, objective criteria, regardless of the identity of the person making the decision. In practice, this means that methods for assessing quality and management effectiveness must be universal, so they can be applied in different contexts and organizations.

2. Objectivity

The principle of objectivity means that decisions based on measurement results and analysis should be made independently of personal preferences, interests, or external pressures. Objectivity guarantees that the evaluation and improvement processes will be conducted based on actual data, not subjective opinions.

3. Skepticism

Scientific skepticism means that all solutions and processes must be regularly evaluated and verified, even if they have been considered effective in the past. The principle of skepticism allows organizations to avoid stagnation and adapt to changing market, technological, or social conditions.

4. Organization

The principle of organization refers to collaboration within the scientific community, but in the context of management and quality, it also has an organizational dimension. This means that quality management and innovation processes must be carried out collaboratively, with the exchange of information and a common effort toward excellence.

5. Public Accessibility
Scientific knowledge should be available to everyone. Research results must be published and shared with the broader scientific community so that they can be further analyzed, criticized, and developed.

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Mitroff's Counter-Norms

While Merton's norms represent a theoretical ideal, real scientific processes often encounter challenges that lead to the application of counter-norms proposed by Ian Mitroff. Mitroff pointed out that in practice, these norms are not always adhered to, which may lead to the introduction of new rules that better reflect the complexity of modern organizations.

1. Relativism

Mitroff highlights relativism, which arises in organizational practice when research results or quality decisions are evaluated through the lens of the interests of the organization. Instead of universal criteria for evaluation, decisions may be based on local, political, or economic conditions.

2. Subjectivism

In management, subjectivism may occur when decisions regarding quality assessment are based on the preferences and personal beliefs of those responsible for the processes. Instead of using objective assessment tools, processes may be shaped by the subjective opinions of managers or project leaders.

3. Dogmatism

Dogmatism in management means relying on previously accepted solutions without verifying their effectiveness in new conditions. In organizations that adopt a dogmatic approach, there is a strong tendency to maintain old methods despite emerging new challenges.

4. Isolationism

Isolationism in management may occur when different departments within an organization do not collaborate on quality improvement, leading to discrepancies in approach and a lack of consistency in processes.

5. Public availability

The public availability of research results may be limited in cases where sensitive data, intellectual property or commercial interests prevent their full publication.

Conclusion

Merton's norms and Mitroff's counter-norms provide valuable insights into how any science, including management science, should be conducted. While Merton's principles represent an ideal model for striving for objectivity, universality, and transparency, Mitroff's counter-norms remind us of the realities in which organizations must adjust their approach to changing market, technological, and political conditions. Understanding these two perspectives allows for better management, providing a balance between the ideal scientific approach and the demands of business practice.

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Pseudoscience vs. Parascience and Protoscience vs. Evidence-Based Management: How to Distinguish and Apply Sound Management Approaches

The modern world of management faces a vast amount of data and theories that aim to support decision-making. However, not all approaches are based on solid scientific foundations. Often, theories appear credible but, upon closer examination, prove to be pseudoscientific, parascientific, or protonscientific. Distinguishing these approaches and understanding how to use evidence-based management (EBM) in management is crucial for making effective decisions. To better understand these differences, let’s examine controversial theories such as wandering RNA and the structure of water, and their relevance to management practice.

We believe that in an era of easy access to information and frequent encounters with pseudoscientific theories, our role as responsible professionals is to clearly distinguish science from pseudoscience, parascience, and protonscience.

Pseudoscience, Parascience, and Protonscience

Pseudoscience

Pseudoscience refers to a set of theories or claims that present themselves as scientific but lack solid evidence and fail to meet basic methodological standards. Pseudoscience often lacks the verifiability of results, and the hypotheses are untestable or disproven by experimental evidence.

Example in management: The idea that an organization can achieve success solely through a so-called "secret formula" based on unverified thoughts or popular but unconfirmed ideas (e.g., manipulation of "organizational energy").

Parascience

Parascience is a field that is not fully recognized by mainstream science but still remains within the scientific interest. It often lacks the standards required to be considered full science but may be helpful in certain research or experimental cases.

Example in management: Theories based on popular but unconfirmed research suggesting that certain motivational techniques (such as affirmations or "sound therapy") can be effective in management, despite lacking full confirmation in studies on management effectiveness.

Protonscience

Protonscience refers to an area that lies on the border between science and pseudoscience but has the potential for further development and could lead to real science. Protonscience does not yet meet all scientific requirements but research in this area may provide new tools to understand phenomena.

Example in management: Research on organizational psychology that begins to study subjective factors influencing employee performance but is not yet fully confirmed, such as studying the impact of "employee feelings" on their results, which needs further validation in different organizational contexts.

Image by Abby Chung: https://www.pexels.com

Wandering RNA and the Structure of Water

Wandering RNA is an example of pseudoscience because this theory lacks experimental confirmation and does not meet the methodological standards of science. Claims that RNA can wander freely between cells in a way unrelated to existing biological mechanisms are an example of speculation that lacks solid scientific support. From the EBM perspective, such theories would have no place in decision-making processes because they are not based on reliable evidence.

Application in management: Using theories that lack solid scientific evidence can lead to wrong decisions by management. For example, implementing unconfirmed motivational or developmental methods that may turn out to be ineffective, instead of using proven management practices based on evidence.

Theories about the structure of water, which suggest that water has "memory" and can store information (e.g., in homeopathy), are classic examples of parascience. While research on water and its properties is fascinating, there is still little evidence to support this theory. Water may have some structures that are an interesting area of research, but claims that it can store information are speculative and lack solid evidence.

Application in management: Just like with pseudoscience, the use of theories that are not confirmed by evidence can lead to ineffective solutions in organizations. In management, using unproven theories (e.g., related to organizational psychology or motivation) can result in poor decisions that do not deliver the expected outcomes.

Evidence-Based Management (EBM)

Evidence-Based Management (EBM) is an approach that relies on solid scientific evidence when making managerial decisions. EBM requires organizations to use available research, data, and experiences to make informed decisions. This approach is the opposite of using pseudoscientific, parascientific, or protonscientific theories, which can lead to erroneous conclusions.

EBM example: Instead of relying on unverified ideas, organizations using EBM base their decisions on data regarding employee performance, organizational outcomes, and scientific research to implement practices that have been proven to be effective.

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Training called Effective Bibliography Management

An essential element of every research process, occurring at almost every stage of a researcher's work, is the review and analysis of the subject literature. The aim of the training is to draw attention to how to organize literature using databases in combination with modern technological tools, such as bibliography managers (RMS, Reference Management Software). Such activities, which will soon become a permanent element of scientific research methodology, should be of particular importance in the discipline of management and quality sciences, the main goal of which is to search for newer and newer solutions that affect better organization and greater efficiency of performed tasks and works.

Framework Program

1. Citavi: program installation and cooperation with plugins for Adobe and WORD,
2. Citavi: automation of creating a copy of the project,
3. Citavi: adding and describing sources of offline publications,
4. Citavi: adding and describing sources by DOI number, ISBN,
5. Citavi: adding and describing sources from a pdf file,
6. Citavi: searching in databases or directories,
7. Citavi: importing and exporting sources between Citavi, ORCID and Google Schoolar,
8. Chrome browser: adding publications using Citavi Picker,
9. WORD: embedding citations from sources in the style of the Oxford Referencing System, Harvard Referencing System: converting in-text citations to citations in footnotes and vice versa.

I order once
Group
A short guide

Price: by agreement or barter
Training language: Polish

Certificate based on § 23 ust. 4 Rozporządzenia Ministra Edukacji i Nauki z dnia 6 października 2023 r. w sprawie kształcenia ustawicznego w formach pozaszkolnych (Dz. U. z 2023 r., poz. 2175).

Trainer: Piotr Janulek, PhD. Entrepreneur since 1997, building bridges between education and business. Runs the akademia-nauki.eu platform, focusing on accounting, communication and personal development. Interested in social media, accounting, innovative business models and evidence-based management.

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Types of scientific evidence

Scientific evidence is the foundation for reasoning and decision-making in various fields, such as medicine, psychology, and education. To understand how to assess the reliability and credibility of evidence, it is worth looking at the evidence hierarchy, which divides evidence into five levels, depending on the methodology and nature of the studies. Below is a detailed description of each level.

Level I: Experimental randomized controlled trials (RCTs)

The highest level contains evidence from experimental studies, such as randomized controlled trials (RCTs) and their systematic reviews with or without meta-analysis. These studies are characterized by the highest methodological quality, because random selection of participants and control of variables minimize the risk of systematic errors. Additionally, meta-analyses allow the results of multiple studies to be combined, which increases statistical power and precision of conclusions.

Level II: Quasi-experimental studies

The second level includes quasi-experimental studies, systematic reviews combining the results of RCTs and quasi-experimental studies, and quasi-experimental studies alone, with or without meta-analysis. Although the lack of random assignment of groups may introduce the risk of bias, such studies still provide valuable information, especially in situations where RCTs are not feasible.

Level III: Non-experimental studies and systematic reviews

The third level includes non-experimental studies, such as observational studies, systematic reviews of RCTs, quasi-experimental studies, and qualitative studies with or without meta-synthesis. The inclusion of qualitative methods allows for a deeper understanding of social and behavioral phenomena, but the lack of control over variables may limit the generalizability of the results.

Level IV: Opinions of recognized authorities

The fourth level refers to the opinions of respected authorities, reports of expert committees or consensus panels based on scientific evidence. Although this type of evidence does not come directly from empirical research, it is important for decision-making, especially in areas where solid empirical data are lacking.

Level V: Literature Reviews and Expert Experience

At the lowest level are literature reviews, program evaluation reports, financial analyses, case studies, and expert opinion based on experience. Although this evidence is of limited strength, it is often a starting point for more rigorous research.

The Importance of the Evidence Hierarchy

Understanding the different levels of evidence allows us to critically evaluate the credibility of information and make decisions based on scientific evidence. In practice, this hierarchy helps researchers, practitioners, and policymakers choose the best available evidence to address specific problems.

This approach helps us build a solid foundation for science, education, and public policy while promoting transparency and effectiveness in our actions.

Sources:

1. https://academicguides.waldenu.edu/library/healthevidence/types [2024-12-24]
2. Janulek, P., Dowody naukowe, https://badania-naukowe.blogspot.com/2024/09/dowody-naukowe.html [2024-12-24]

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Evidence-based management in managerial decision-making process

Evidence-based management has not yet been considered in the context of practical managerial decision-making systems that leverage modern information technologies and big data. While management and quality sciences have always focused on application solutions, modern technologies have significantly broadened the scope of utilizing scientific research results in managerial decision-making. 

Save to bibliography manager: RIS

Our aim is to demonstrate the rationale for developing a new theory of business decision-making systems based on large datasets of scientific research results. New management concepts, ideas, and messages should be created, developed, and refined through a systematic and interdisciplinary approach to evaluating solutions described in carefully selected scientific publications.

Link to summary:  https://przegladorganizacji.pl/artykul/2024/10.33141po.2024.01.05 

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Why scientific research makes sense in a world of subjective beliefs

The modern world is characterized by a multitude of views and beliefs. In societies that value freedom of speech and individualism, there is a tendency to treat truth as something subjective, determined on the basis of personal experiences, beliefs, or emotions. If everyone has the right to their own truth, is there any point in scientific research? Does research that allows us to discover new facts and solve puzzles have any justification in such a world? The answer is yes, because the pursuit of truth is based on the assumption that there are better answers than others, and truth is not just the effect of a subjective view of reality.

Objective vs. subjective truth

In a situation where all views are treated as equal and equally valuable, a fundamental question arises: why undertake any scientific research? If there is no single objective truth, then why analyze the histories of the past, investigate the causes of contemporary conflicts, or search for new methods of treatment? In such reasoning, all answers may seem equally important, and each form of knowledge equally valid. However, what distinguishes science from relativism is the assumption that there are objective, measurable criteria for evaluating different views, discoveries, and theories.

Scientific research only makes sense when verifiable answers are more accurate than others, when there is something behind the truth that is independent of our subjective preferences. 

Also in the case of archaeological excavations, medicine, or research on the Universe, the goal is to discover objective facts that, regardless of who examines them, will be an invariable part of our knowledge of the world.

Science as the pursuit of better answers

One example that perfectly illustrates the meaning of research is medicine. The search for a cure for cancer is an issue in which research can really change the lives of millions of people. If all views on cancer treatment were treated equally, we would not make an effort to develop effective therapies. Medical knowledge develops on the basis of scientific evidence that indicates the effectiveness of specific treatments and rejects others that turn out to be ineffective or harmful.

We are dealing with a similar logic in the case of analyzing the causes of tensions in the Middle East. To understand why conflicts occur, we need to go beyond subjective interpretations and learn about the objective factors – historical, political, social – that influence them. It is this research that allows for effective diplomatic and aid actions.

Discovering the truth about the Universe

The same is true for space exploration. Man has always been curious about what lies beyond our planet. When we begin to explore the Galaxy, we ask about its structure, origins, and the mechanisms that govern its functioning. There is no point in seeking answers to these questions if we do not believe that there is an objective truth that can be discovered. Understanding the Universe is not about subjective interpretations, but about discovering the laws of physics that govern reality, regardless of whether someone believes in them or not.

Seeking truth as the fundamental goal of human action

Every field of science aims to discover the truth – not only to expand our knowledge, but above all to improve the quality of life, increase understanding of the world, and facilitate solving global problems. If we assumed that every truth was equally good, we would not make any effort to find out which answer is more accurate, more evidence-based, and more useful in practice.

Truth, while difficult to grasp, is not a product of subjective beliefs. It is an independent, objective reality that can be discovered through research, experimentation, and analysis. When we allow everyone to determine their own truth, we give up the pursuit of knowing reality in a way that is independent of personal preferences. The effort that scientists, researchers, and doctors make to discover what is objectively true only makes sense if we believe that there are better answers than others, and that truth is something to strive for.

Foto: Luis Quintero: https://www.pexels.com/pl-pl/zdjecie/czlowiek-dotyka-ksiazki-2258252/

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Using Boolean operators in scientific research vs. quick fact checking: How can our tool help?

In today's information-driven world, skillful management of search processes is key. Different goals require tailored methods—especially in scientific research and quick information verification.

1. Research-Based Searching: In-Depth Information Exploration

Research-based searching is a complex process involving precise planning, the use of Boolean operators (AND, OR, NOT), analyzing diverse sources, and critical evaluation. The main objectives of this approach include:

• Gathering comprehensive literature: For instance, searching for literature on “AI AND ethical implications” might involve exploring databases such as Google Scholar or Semantic Scholar to find the latest scientific publications.
• Contextualizing data: Analyzing collected materials in the context of existing studies.
• Ensuring reliability: Verifying the credibility and accuracy of sources.

2. Quick Information Verification: Instant Source Checking

Not every situation requires a complex research process. Sometimes the goal is to quickly confirm whether a specific paper, article, or piece of information exists. This is where our tool—Rapid Query Formulation—comes into play, designed to reduce the time needed for verification.

• Minimal effort: Just type the title into the form, and one click will take you to the appropriate search engine.
• User-friendly: Intuitive operation makes it suitable for both professionals and beginners.
• Access to diverse databases: A set of icons directs users to platforms like Semantic Scholar, Google Scholar, or dblp, offering wide-ranging search capabilities.

Choose a Tool Tailored to Your Needs

In a world dominated by information, search strategy is crucial. Our form will not replace advanced research-based searching but serves as indispensable support for quick source checks. Combine simplicity with efficiency—use our tool as the first step toward reliable and trustworthy information.

Foto: Ron Lach : https://www.pexels.com/pl-pl/zdjecie/mezczyzna-las-polaczenie-kontakt-10374364/

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