Four steps to improve critical thinking
Key steps to improving critical thinking include analyze, interpret, present, and evaluate
As an engineer, your technical skills are likely already finely honed. Yet, it may be that colleagues with weaker technical skills are getting ahead.
What’s going on? The truth is, even in the world of engineering, technical skills are only part of the answer. As important are professional skills: the ability to identify and overcome business challenges, with the same acumen used to solve technical ones.
In other words: to increase your impact and grow your career, develop critical thinking skills. We all have heard about critical thinking, vaguely remember covering it in college, and often downplay it as simply common sense. However, there is much more to it.
What is critical thinking?
The world is awash in data. There’s too much to analyze, too little time to accomplish goals, and too many pressing problems that need immediate attention.
Critical thinking is a process by which anyone can consistently and accurately solve problems, by seeing the world more clearly than others and envisioning solutions others do not. Of course, critical thinking isn’t limited to technical problems.
The most successful professionals tend to be the people with the best critical thinking skills, who look beyond the rote facts and figures of their discipline. In a world where infinite data is instantly available, critical thinking and the ability to learn quickly are the long-term competitive differentiators.
How to improve critical thinking
To improve critical thinking, follow the same four-step process many of the world’s top consultants follow: analyze the most relevant data, interpret that data to create actionable solutions, present the findings in a compelling manner, and thoughtfully evaluate the success of the solutions involved.
1. Analysis: When faced with an actual problem to solve, too many professionals fall victim to analysis paralysis. With all the data available today, information gathering can go on forever, extending to cranking through formulas and formatting reports and dashboards. How many times have you heard, "Wait, we haven’t analyzed all the data yet…?"
Instead, as a professional, the initial task is to identify and frame the real problem. Scan available data, develop an initial hypothesis, then use that to guide a narrower, deeper collection of relevant data. Prioritize what’s needed through the lens of that initial hypothesis and test it for validity. If it holds, double down on that path of reasoning. If not, revector and try again.
2. Interpretation: Once the relevant data is identified and collected, the goal is to make connections between ideas and convert them to actionable insights.
Frameworks and mental models are great tools to evaluate abstract ideas and translate them to the real world. Since most business problems are complicated and too complex to be comprehended in their entirety, a model contains only those features that are of primary importance to the purpose at hand. Think of frameworks as mental scaffolding to guide thinking while allowing flexibility to solve problems based on actual data; not a rote formula that may not apply to the situation at hand.
3. Presentation: Once the data is analyzed and interpreted, it’s time to present the findings. But the work of critical thinking isn’t done yet. Time is the most precious commodity for executives, so present the results so that they anticipate and answer the reader’s most likely questions, in a sequence that supports a natural storyline. This means straddling the world of summary and detail, giving readers the answer up front and supporting with the detail needed. Remember, think deductively (in sequence), but communicate inductively (answer first, then support with details).
A great approach to structuring an individual output is the Pyramid Principle. It starts with situational context, describes complicating factors, and then formulates overarching questions and sub-questions to set up the analysis. Those questions are then addressed as a mutually exclusive, collectively exhaustive set of answers, with supporting detail.
4. Evaluation: Critical thinking culminates in measuring the results. Determine the correct metrics, accurately measure what worked and what did not. See the results with intellectual integrity, as they really are, not as hoped or feared. Identify personal bias and then filter for it. The closer the individual is to the problem, and the more expert, the greater the danger. Strive to see with a beginner’s mindset.
Critical thinking is not a linear, one-time activity. The beauty of critical thinking and a well-crafted message is that even if initially wrong, recommendations can be explained and then refined. This naturally follows an agile, iterative approach that loops back upon itself until a sufficiently accurate answer can be reached, and other interested parties can understand and accept the result.
Why is critical thinking important?
Every industry is being disrupted, and the very nature of work is changing. Research indicates that up to 40% of human work will be automated within 10 years. If a process and policy can be documented, it can be automated. This is true for engineering as well.
Yet, there is at least one kind of work that isn’t going anywhere soon: the human ability to solve problems through critical thinking. By developing the skills that can’t be automated, a career is future proofed, no matter what the robots have in store. Invest time to develop this foundational skill.
Jeff Kavanaugh is a senior partner at Infosys, the consulting and technology firm. He is also an adjunct professor at the University of Texas at Dallas. His book Consulting Essentials was published in April. It is available in Kindle, paperback, and hardcover formats.
This article appears in the IIoT for Engineers supplement for Control Engineering and Plant Engineering.
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