Home > Articles

  • Print
  • + Share This
This chapter is from the book

1.2 Developing Analytical Thinking

Developing analytical thinking is the first step of business analytics, because it will determine which data should be gathered, where these data should be acquired, how these data should be analyzed to extract meaningful information, and how such information can be exploited to address ongoing business issues. Analytical thinking, however, should not be confused with critical thinking. Table 1.1 summarizes the subtle differences between analytical and critical thinking.

Table 1.1 Analytical and Critical Thinking

Analytical Thinking

Critical Thinking


Seek answers/solutions for ongoing issues

Determine what is right or wrong

The Use of Facts

To support your conclusions

To form your own opinions and beliefs

Style of Thinking

Streamlined problem-solving approach by the step-by-step breakdown of the cause-and-effect relationships of events/datasets

Opinion-based approach with constant reasoning and questioning


Organized system of thoughts


Interpretation of Information

Information is useful for understanding certain events and explaining patterns/trends; thus, it helps gain insights into problems to be solved.

No information is considered valid, true, applicable, and accurate automatically without clear evidence.

Key Tools

Mind-maps, flow diagrams, mathematical tools

Brainstorming sessions, open forums for arguments

Given the importance of analytical thinking to the successful application of business analytics, the development of analytical thinking (or nurturing analytical thinking skills) should precede the adoption of business analytics. The following summarizes ways to develop analytical thinking in a systematic manner:

  1. Fact-finding and checking through thought experiments: Thought experiments involve hypothesizing “what-if” scenarios in the imaginary world and allow us to see the outcome (what will happen) if we select a certain decision. If the repeated experiments result in the same outcome, the pattern emerging from those experiments can be a basis for facts. Also, we can map out the individual outcome resulting from each choice of the decision.
  2. Raising the correct line of reasoning for what you read, learned, and wrote in the past: Unless we verify the validity of information sources (e.g., books, published articles, digital media), we can be sold on logical fallacies and may end up making wrong decisions. To obviate such mistakes, we should be aware of common logical fallacies based on the faulty reasoning. For example, a premise based on the inverse reasoning stating “If you do not reduce product price, it will not affect product value and thus will not hurt the potential sales of that product” can lead to no business action when the product at the current price is not selling well in the market. Instead, we should have developed the proper reasoning stating “If you reduce product price, it will improve product value for potential customers and thus increase its sales.” Other potential sources of logical fallacies may include the hasty generalization of one-time instance or limited anecdotal incidents, the unconditional belief in the high authority’s opinions, and the false association (e.g., a turtle brings good luck to the individual who owns it as a pet, although it is more likely to contain deadly salmonella bacteria than other pets).
  3. Building a habit of thinking without preconceived notions or biases: To avoid bias traps, one should bring various perspectives (viewpoints) in a broad spectrum and figure out what we are taking for granted. The thought process originating from many different angles will lower the chance of getting trapped in one flat point of view reflecting one’s bias or partial facts.
  4. Structural thinking: Analytical thinking should guide us to develop meaningful inferences out of gathered data. However, it would be hard for us to make meaningful inferences and draw conclusions without structured, step-by-step thought processes. These processes may include the following steps:

    1. Setting purposes of solving the given problems emanating from particular events, practices, and behaviors.
    2. Raising questions about the nature of the given problems.
    3. Gathering data and facts associated with the observed problems.
    4. Utilizing well-established concepts, theories, axioms, laws, principles, and models to dissect data and extract meaningful information.
    5. Making inferences and drawing conclusions under proper assumptions.
    6. Understanding and generating implications of new problem solutions found from inferences and conclusions.
  • + Share This
  • 🔖 Save To Your Account