By David Kreutter, Senior Lecturer and Associate Academic Director, Master of Science in Applied Analytics
Columbia University’s M.S. in Applied Analytics program is unique in its focus on both the technical and leadership skills—i.e., “soft skills”—required to be a successful analyst in an organizational setting. I have taught the courses Applied Analytics in the Organizational Context, Analytics and Leading Change, Health Care Analytics, and Strategy and Analytics. In all of these courses, I’ve focused on helping our students develop their leadership skills, which require an integration of critical and analytical thinking. My views are shaped by scholarly research and my experience leading decision and business analysis groups in the biopharmaceutical industry.
Analytical reasoning involves using logic and critical thinking to understand a situation, identify patterns, and find solutions to problems. Critical thinking involves evaluating information, arguments, and assumptions to form a judgment or decision. Albert Einstein is quoted as saying, “If I were given one hour to save the planet, I would spend 59 minutes defining the problem and one minute resolving it,” which illustrates the integration of critical and analytical thinking skills. In the context of a business, developing an elegant solution to the wrong problem creates no value for the business.
We live in an age where ChatGPT can do in seconds what Einstein dedicated 59 minutes to accomplish, raising an intriguing question about the necessity of thinking skills given the advancements in generative AI. A critical thinker identifies opportunities and problems that are relevant to a business’s context and formulates distinct, precise, and essential questions. Anybody who has used ChatGPT has experienced the importance of this skill. The response that is generated is dependent upon the wording of the prompt and the clarity of the context the user provides. This leads naturally to another critical thinking behavior, which is gathering and assessing relevant information and using abstract ideas to interpret it effectively. The technical underpinning of deep learning makes transparency challenging at best, and therefore, assessing the output of a generative AI model requires careful evaluation by the user.
Another important critical thinking skill for analysts in an organizational setting is to consider contextual factors such as the actionability of their results. A very precise solution to an optimization problem that requires a complete redesign of an organization’s workflow is not practical as a near-term opportunity. Actionability is also bounded by ethical, regulatory, and legal considerations. In an organizational setting, the goal of analysis should be to develop a solution space, not a specific answer such as the output of a generative AI model. Judging the balance between the precision and actionability of the results requires an understanding of the company’s operations, stakeholders, and culture, and that is not a machine task; it requires human critical thinking skills.
The ultimate goal of critical thinking is to reach well-reasoned conclusions and solutions, testing them against relevant criteria and standards. It is too easy to be lulled into believing the output of a generative AI model because it is stated so definitively and authoritatively, regardless of the quality of the information supporting it. There is no question about the importance of critical thinking in the age of AI—it is more crucial than ever, and it is a uniquely human skill.
About the Program
Columbia University’s Master of Science in Applied Analytics prepares students with the practical data and leadership skills to succeed. The program combines in-depth knowledge of data analytics with the leadership, management, and communication principles and tactics necessary to impact decision-making at all levels within organizations.
The fall 2025 application priority deadline for the M.S. in Applied Analytics program is February 15. The final deadline is June 1. Learn more about the program here.
