The Unavoidable Research Bias

One of the most complex aspects of qualitative research is the ontological idea that researchers must adapt to the multiple realities of those being researched as well as those who consume the research. As we know, especially in research, there is really not a "one size fits all" approach that works.

Bias is part of human life whether we choose to acknowledge it or not.  Bias contributes to our interpretation of the world, of others and of research.  As a researcher, identifying this bias is crucial in helping us to define and better understand ourselves when presenting our research to others.

While collecting the Pinterest items, I found that my team came across some incredibly powerful tools in the areas of positive results bias, egocentric bias, projection bias, and confirmation bias.  In reviewing these items, the bias suggests a sort of hybrid ignorance-selfishness that exists within all of us and a tendency to hide behind this "flaw"or perhaps this "reality."  Now, some argue that humans are naturally selfish, but others claim that this is a social norm which could be a learned behavior.

Bias has also led to some bad research results which has led to negative publicity in the press.  Bad press on research bias can then further entrench our individual bias which affects the validity and applicability of the results.  Known examples of this include extremely well-known and large pharmaceutical companies paying large sums of money to researchers to cover up unfavorable data to find significant data correlation even when the data should be more inconclusive.  This now becomes an issue of ethics, morality and requires us, as researchers, to honestly reflect our values and biases in order to be most effective.

When selecting the best research approach, we must consider the bias that exists within us and within our research subjects.  As a researcher, I continue to wonder if it is possible to generate universally accepted findings or if my results will always be subjectively interpreted?  What tools exist to develop a bias inventory?

P= 40 to 70

Producing effective and useful research that can be used in a practical sense seems comparable to landing a small fighter jet on an aircraft carrier amid high winds and turbulent seas. It can be done, but only after significant training, practice, and understanding. Effective research requires incredible focus, a well-defined problem amid a sea of possibilities, and a strong understanding of the environment while giving rise to the amount of time it takes to market. As the sort of "novice pilot" in this particular research course, I am ill-prepared to successfully make an attempt at landing a study that may be useful for practitioners in the field. While this is not the likely goal of the course, it remains a longer-term personal goal of mine that I hope to use in my go-forward career life.

My choice in the title of P= 40 to 70 derives from one of Colin Powell's well-known leadership quotes. Harari (2002) quotes Powell's leadership rule # 15 as “Use the formula P=40 to 70, in which P stands for the probability of success and the numbers indicate the percentage of information acquired. Once the information is in the 40 to 70 range, go with your gut.” While the actual percentage of information may not be easily measured, the idea is that if you have less than 40%, you don't have enough information to make an informed decision. If you have more than 70%, then you maybe have waited too long and someone else may have already made the decision for you.

As scholar-practitioners in the increasingly important field of Organization Development, I believe our usefulness and ultimate effectiveness will rely on our ability to arm our leaders and stakeholders with enough information to make critical decisions, but also being sensitive to the time and cost which fits Powell's leadership principle. Powell's leadership rule #3 worth noting is "“Don’t be buffaloed by experts and elites. Experts often possess more data than judgment. Elites can become so inbred that they produce hemophiliacs who bleed to death as soon as they are nicked by the real world.” Navigating the board rooms with elites and relying on opinions of the experts in an organization is potentially a dangerous move if we are conducting organizational research.

While the common theme in my blog here has to do with a sort of military mindset, the challenges and unpredictabilities in the context of organizations and generating useful "intel" is really a solid analogy in my mind.  To combat this, I hope to learn more about the following questions in this course:

 1. How do you know when you have enough information to help leaders make sound decisions in an OD intervention? How much is needed to be effective?  When is too much information ineffective? 

2. Why is there such a disconnect between producing effective research in an academic sense and producing research that is seen as effective and valued in the practical sense?  

3. How do you handle an OD intervention when the client is focused on implementing a solution while the OD consultant believes that more research is needed before moving forward?

4. When would a researcher use a combination of research methods as opposed to maintaining focus on one?

5. If you are conducting research in more than one country where multiple languages are written and spoken, how do you ensure consistency in data collection within various qualitative methods?


I am particularly drawn to the Case Study research approach given its seemingly more practical application. The case study approach allows for both quantitative and qualitative research methods which I find to be more valuable as a consumer of information.  As Creswell points out, the case study approach requires substantial thought in scoping the case and setting the boundaries which does add time and effort to the front end.

Reference List:

Harari, O. (2002). The Leadership Secrets of Colin Powell. New York: McGraw-Hill.