Critical Thinking and “What-If” Analyses

Critical Thinking and “What-If” Analyses in Management Decisions

Title: Critical Thinking and “What-If” Analyses in Management Decisions

“No problem can be solved by the same consciousness that created it.”

          – Albert Einstein

“We are approaching a new age of synthesis. Knowledge cannot be merely a degree or skill . . . it demands a broader vision, capabilities in critical thinking and logical deduction without which we cannot have constructive progress.”

   – Li Ka Shing

“To every complex question there is a simple answer and it is wrong.”

          – H. L. Mencken

In its simplest interpretation, we all apply critical thinking in our daily lives, often without even giving a nod to the process we use to arrive at routine decisions. The common characteristics of basic decision making that we all use are so elementary: Gathering information and keeping informed about areas of interest and the particulars to be considered before arriving at a decision; asking questions to ensure we clearly understand pertinent factors; brainstorming; weighing the evidence we have gathered, utilizing a “tried and true” method we have adopted or usually rely on, and – in so doing – determining what is actually relevant to the problem or decision at hand; taking historical elements into account, but assessing facts within their current context; seeking to discern the truth of any claims or assertions, and determining if bias exists that would affect facts or outcomes.

This pattern is repeated for all decisions, from the smallest – for instance, what apparel to wear, in light of planned physical activities or appropriateness for an event – to the most important of decisions, such as whether or not to propose or accept an offer of marriage, or what university to attend.

From a more sophisticated perspective, the simple steps commonly used to arrive at a decision can be deconstructed as

  • Systematic questioning
  • Structured problem solving
  • Risk assessment and management
  • Progressive decision-making
  • Management of thought process
  • Arrival at a solution and implementation

Brainstorming can help determine the appropriate framework of inquiry necessary to gather the most pertinent information, which depends, of course, upon the answers being sought. Methodology used in the problem solving process provides the structure, and there are several methods and systems that can be utilized depending on the nature and scope of the factors to be evaluated, and their relationship, if any. The broader the criteria and more interrelated the particular set of decision problems and apparent alternatives, and the more variable in number and threat level the kinds of risks to be considered, the more complicated the methodology must be in order to assimilate all pertinent information and accommodate as many options and outcomes as is possible. Once again, brainstorming is required to envision all potential perils or disruptive forces that might impinge upon the success of an entity or endeavor.

Critical Thinking and “What-If” Analyses in Management Decision Making
Critical Thinking and “What-If” Analyses in Management Decision Making

A simple outranking of one outcome above the next is a concept that provides a variety of alternatives responses and outcomes to unintended events, pairing alternatives to determine the better performing of each pair. Upon determining which alternative is more effective, or outranks the other, these assessments of problem-solving or responsive value can be aggregated into a ranking or partial-ranking scheme which, although it may not deliver a definitive answer, offers a reduced “shortlist” of acceptable alternatives.

Progressive decision-making tackles one element at a time, in order of importance, placing decisions in a sequence that comprises a plan of avoidance, attack or defense in the face of envisioned obstacles or other developments. Management of the thought process provides a discipline that enables a rational approach to even the most upsetting of possibilities, removing emotion to thereby clarify thought and enable focus. Arrival at a solution and implementation, perforce, requires that the number of likely risks and feasible alternatives be winnowed and refined, to arrive at those scenarios that are most credible, so that they may be addressed in some detail.

Decision Making Criteria

When facing single criterion or limited-criteria problems and decisions a number of relatively simple methods are available to determine the alternative offering the best value or outcome. Elementary decision tools include decision trees that sequentially branch one decision into the next in a basic “this, therefore that” progression; decision tables of alternatives, pro-con analytical comparisons maximax/maximin strategies, cost-benefit analyses. contingency planning, what-if analysis.

All are elementary pencil-to-paper analyses, simple enough to calculate manually, with no need of sophisticated mathematical skill or computational resources.

Multi-attribute optimization problems such as those that are often addressed by planning departments and larger businesses and organizations often reflect a finite number of criteria but an infinite number of alternatives that are feasible.

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Approaches for Research Dissertations

Qualitative or Quantitative?

Approaches for all research, whether qualitative or quantitative, requires interpretation and contextualization by the researcher. Narrative statements or a series of figures will not give the answer to the research question or statement (hypothesis) by themselves.

Therefore it is important to choose a research approach (or approaches) that will give the correct ‘type’ of data to answer your research question.

A number of approaches are available when gathering data, but these don’t have to be used in isolation. For instance a focus group can elicit viewpoints which may need exploring further will a larger research cohort using a closed question survey. For this reason, it is important to plan your approach thoroughly before you start, to ensure your research question can be answered and to let your respondees know what is expected of them.

Don’t forget that whichever research method is chosen, it needs to have a robust ethics form that has been approved before contacting participants and starting to gather data.

Approaches that can be used:

Focus groups

This is where a group of people discuss a particular problem, facilitated by the researcher. The group interaction and the sharing of ideas not only means that rich and meaningful data can be pulled out from the focus group but also during the course of the focus groups, ideas can be co-constructed between participants which can be used to further the depth of research.

Structured interviews

When using structured interviews, the questions are written beforehand and are strictly adhered to regardless of the answer.

Semi-structured interviews

Whilst pre written questions are also used in semi structured interviews, this approach allows for the researcher to spontaneously build on answers given, allowing the base question to be answered but also elaborating on any areas which may impact on the research answer.


Surveys are an excellent way to reach a large number of people. This approach works if there is a clear idea of the questions that will elicit research to support the hypothesis. A mix of qualitative (open text fields) or quantitative (set questions and answers) can be used.

Case study

This approach is valuable when more in depth research is required and allows the researcher to investigate the issues in the place or time that they occur. The researcher will observe the participant and often will have follow up meetings to clarify or build on the information gained.

Narrative enquiry

This method works on the ideology that it is less important what is said, then how it is said. The story a participant will tell may not be entirely factual but it will be their perception of what happened which gives greater in sight. This approach is linked to discourse analysis methodology.

Appreciative enquiry (AI)

AI shifts the traditional focus of looking for the negative impacts of an issue and instead approaches the issue from a positive perspective.


Ethnographical methodology requires the researcher to embed themselves in the participatory groups own setting, for a sustained time in order to observe, talk and learn from participants.

There are a number of branches from the ethnographic methodology:

Auto ethnographic

More than just an autobiographical account, an auto-ethnographic researcher should reflect on events and use these to uncover meanings and feelings that a purely narrative account may miss.

Visual ethnographic

Using video, photos and artefacts as the main source of research data rather than supplementing it.


Researchers using this methodology are involved and participants or ‘lurkers’ in virtual groups and communities. Ethical issues need to be carefully considered with this approach.

Soft Systems Methodology (SSM)

Instead of studying isolated issues, SSM is a holistic way of looking at and solving problems. These are often presented in mind map formats, making this a good research methodology for visual learners.

Questions to ask before choosing a research approach:

  1. Will we learn more about this topic using quantitative or qualitative approaches?
  2. Which approach will produce more useful knowledge?
  3. Which will do more good?


Taken from:  Cousin. Glynis, (2009) Researching Learning in Higher Education. Routledge. UK.

Research Approaches Dissertations
Research Approaches Dissertations

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Mixed Method Research Design

The Mixed Method in Research Design

The mixed method approach to evaluating research data may be applicable to studies that are designed to gather both qualitative and quantitative information. This technique is often used in disciplines such as psychology, sociology or certain types of medicine. The continued development of these fields may depend on data that is derived from standardized scales or rating systems in addition to that gleaned from interviews, ‘focus group’ sessions and other similar tools. Therefore, the mixed method may be appropriate in a new project on a complex issue or situation that generates complex and highly individualized answers to research questions. Examples of these may include the societal impact of homelessness or the treatment of a lost or diminished sense. The data here may need to cover detailed and varied feedback (or ‘self-reports’) on the effect(s) of these target variables, as well as scores from formal quantitative tools typically used within the research community in question. One data type does not give a complete ‘picture’ of the outcome(s) without the other. Therefore, a methodology that incorporates both to analyse the data set as a whole is necessary.

The mixed method may combine and synthesize this data through a process called triangulation. This may involve the conversion of qualitative data into quantitative data. Such a form of triangulation is most applicable to data resulting from the administration of structured interviews or surveys, provided that data is sufficiently standard or homogeneous across respondents to be coded or scored effectively (i.e. without bias or other forms or statistical inadequacy). In this way, it may be converted to quantitative data, and compared or analysed in accordance with the requirements of the study design (e.g. subjected to a form of analysis such as a paired t-test). On the other hand, the qualitative data may be too individualized and/or complex to be coded. In this case, a thematic analytical technique may be used, incorporating findings such as significant differences among the quantitative data points as a theme or concept.

Mixed Method Research Design
Mixed Method Research Design

The aim of triangulation is the full integration of both data types to generate contiguous concepts or conclusions. This leads to another advantage of the mixed method: i.e. that it can address research aims that do not stem from standard null hypotheses. Questions, in other words, along the lines of ‘Does this novel treatment result in an improvement in the life quality of patients with hearing loss?’ rather than statements such as ‘This treatment improves hearing loss [in comparison to an existing alternative]’ to be confirmed or denied.

The mixed method is not, however, without disadvantages or detractors. Critics of this methodology often cite the risk of the ‘incompatibility paradox’; the probability that one data type will be inadequately analysed compared to the other. A prominent example of this risk is known as ‘pragmatism’, or the perception that researchers who use the mixed method value ‘experiential data’ (i.e. self-reports recorded from respondents) at the expense of quantitative data. The use of the mixed method may also be subject to preconceptions, judgement or other forms of observer bias that a researcher may impose on qualitative data in the course of its collection. These risks can be ameliorated, mainly through the skill and training of the individual researcher. Under these conditions, the mixed-method technique can be applied to generating full, comprehensive conclusions for non-standard research questions.

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Brown RA, Kennedy DP, Tucker JS, Golinelli D, Wenzel SL. Monogamy on the Street: A Mixed Methods Study of Homeless Men. Journal of Mixed Methods Research. 2013;7(4):328-346

Windsor LC. Using Concept Mapping in Community-Based Participatory Research A Mixed Methods Approach. Journal of mixed methods research. 2013;7(3):274-293

Robson C. Real World Research. 2 ed. Oxford: Blackwell; 2002

Mertens DM, Hesse-Biber S. Triangulation and Mixed Methods Research: Provocative Positions. Journal of Mixed Methods Research. 2012;6(2):75-79

Lieber E, Weisner TS. Meeting the practical challenges of mixed methods research. SAGE handbook of mixed methods in social and behavioral research. 2010;2:559-579

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