Quality Thinking: Essential skills for the 21st century (or, how to make friends with the “Big Brain”)
As technological progress makes our lives easier, we, paradoxically, need to work harder. Not harder in terms of effort and hours committed to work, but a greater effort towards something quite difficult and elusive: the ability to adapt and change in ways that improve the quality of our thinking.
The Coming Wave of AI/LLMs
The next wave of AI technologies, like ChatGPT, will profoundly affect those engaged in knowledge work. In the not-too-distant future, machines will be responsible for a significant share of the value embedded in any product or service. This includes knowledge worker tasks such as copywriting and coding that are already seeing substantial productivity improvements in the short time these new AI-powered solutions have been in the market.
Looking at Github’s Copilot solution, two interesting and early trends have emerged: 1. Developer productivity has jumped significantly, and 2. Non-technical users will be able to create software code on their own. So, in the first use case, a user increases productivity using an existing skill set; the other enables a user to learn new skills that were previously the domain of folks with technical competency (software development).
Impact on the Future of Knowledge Work
Let’s assume that because AI removes significant technical barriers to the software development process, a glut of AI-powered software applications may emerge, not only from freelance developers but also within companies with a substantial number of business analysts and developers. Also, with solutions like ChatGPT, barriers to information (dare we say “knowledge”) will continue to fall away as vast repositories of unstructured information transform into usable knowledge with minimal to no human intervention.
But the question remains, “usable” in what ways? How can we apply these capabilities to solve real problems and determine the right use cases to pursue? Uncovering and applying these use cases will require individuals, specifically those operating in larger organizations where the effects could be immediate and profound, to exercise better discernment or judgment. To effectively use the new “big brain” that is AI, people need to think differently, or more to the point, improve the quality of their thinking.
New Skills are Needed: The Rise of Quality Thinking
We need to tap into our higher cognitive abilities to create new things, build our critical thinking skills and unleash our creative potential. But, doing so requires a disciplined process and mindset dedicated to experimentation, testing, and learning. It’s about augmenting our thinking, not outsourcing it to the Big Brain.
Therefore, we need to adapt and change how we think and work, which requires developing the mindsets, skillsets, and habits of creative, critical thinkers. These new mindsets and skills apply to everyone in the organization, not just leaders, as AI will create greater autonomy when greater knowledge and more powerful tools are accessible to everyone in the organization.
We can unlock unimaginable human potential, but the limiting factor is not technology but us, our thinking abilities, and our capacity for change.
What is Quality Thinking?
Quality Thinking (QT) applies critical thinking concepts in an organizational context comprised primarily of knowledge workers exercising better judgment to improve decision-making. It’s taking an idea or process like critical thinking and applying it in the context of a business process, decision process, job function, or job role. It’s using a new way of thinking and working.
Let’s break out Quality Thinking and define the two terms separately. The “Thinking” aspect refers to the critical thinking methods and practices that are learned, refined, and applied in the workplace. It’s the process.
“Quality” refers to outcomes, where you can point to this thinking process producing better results. For example, new products launched, increased revenue, improved customer retention, better sales win rates, lower product defects, etc.
So, if improving the quality of our thinking is the end objective, how do we accomplish it? There are three core elements:
Preparing for Change: Overcoming Fear and Resistance
Before we go any deeper into this, I should clarify that the target audience for this discussion is primarily knowledge workers and their leaders. Of course, the impact of AI will be widespread, but the gatekeepers, if you will, will be those in technology and data science roles responsible for selecting, deploying, and managing the new technology. And they face a daunting task as resistance to the adoption of AI among the general employee population will be unlike anything they have seen in the past, as workers' fear of being replaced grows.
So, how does improving Quality Thinking (QT) help solve this problem? In two ways: 1. QT helps leaders exercise better judgment when selecting AI technologies and determining the use cases that will create the greatest value, and 2. QT helps create mindsets among employees that are receptive to change and open to new ways of solving problems, along with the skillsets for effectively working with the big brain. The combination of leaders being able to make a compelling case for adoption and employees more receptive to change creates a flywheel effect, accelerating adoption.
Thinking Independently, Acting Collectively
For large organizations, pushing through any change can be a significant challenge if leaders don't manage the change effort in a more deliberate, adaptive way that is responsive to our complex world.
Part of the complexity lies in the inherent tension in organizations that encourage independent thought leading to innovations and clear-eyed decision-making and collective action required to make things happen. Too often, the latter, in the spirit of just getting things done, leads to a culture of conformity laden with bureaucracy. By raising the level of QT across the organization, you become better equipped to manage the tension between independent thought and collective action.
Leaders and staff can operate more like networked teams rather than separate organizational units. The emphasis here is more on changing individual behaviors than organizational structures, as good information flow is critical to faster, better decision-making. And siloed org structures and turf battles restrict this flow.
Two pre-conditions are required for this to work: the mindsets that encourage independent thinking and the skillsets (communications, analysis) to act collectively. Like any networked system, the throughput and quality of information determine the system's effectiveness. To do this, you need to increase the number of Quality Thinkers in the organization. It's bottom-up, requiring a deliberate process of personal and professional development where small, individual, incremental improvements compound across the organization to produce non-linear results.
The Path to Quality Thinking
So, what's the journey look like for someone looking to improve the quality of their thinking? It includes both foundational and transformational elements.
Self-Awareness and Situational Awareness
These foundational mindsets, self, and situational awareness provide the baseline skills that enable everything that follows. Self-awareness is the ability to see, without blinders or bias, how you think and react to situations. Situational awareness involves understanding the external conditions in which you operate. In theory, you could lump the two together under self-awareness, but the distinction is important in this context as both these skills are cultivated and applied in an organizational environment. One way to think about this is self-awareness involves “zooming in,” focusing on self-improvement, while situational awareness means “zooming out,” understanding how the organizational systems and structures impact individual and corporate performance. In any organization, you will find the two (self and situational) intersect inside a decision process.
For example, let's say you missed your quarterly sales forecast and need to explain to your boss or colleagues why it happened and what you plan to do to fix the situation. The first issue, missing your forecast, requires you to zoom in and conduct an honest self-assessment that may reveal a consistent overconfidence that causes you to ignore clear warning signs. The second issue, your plan to fix it, requires zooming out and evaluating those warning signals that you perhaps deliberately overlooked or misunderstood how, or to what extent, they impact your forecast. Furthermore, are they even good leading indicators? Any plan to address the issues of inaccurate forecasts must first begin with an honest self-assessment and a clear situational understanding of the input metrics that inform your decisions.
There are two mindset and behavioral changes required: 1. the humility to say, “It’s on me; I was overconfident. I’m not 100% sure why I missed it,” and 2. the curiosity to find out how to fix the problem, seek out possible explanations that will improve your forecasting in the future.
Humility and Curiosity
A mindset that encourages humility and curiosity creates the conditions for clear-headed thinking as it combines two essential ingredients: recognizing what you don't know with the active pursuit of knowledge.
In their book, Humility is the New Smart, researchers Edward Hess and Katherine Ludwig talk about how our instincts for fight, flight, or freeze can inhibit our personal growth. They found in scientific research that two big inhibitors of learning and emotionally engaging with others are our ego and our fears. They further claim, "To mitigate ego and fear and excel at the highest levels of human thinking and emotional engagement requires a new mindset that embraces humility." Humility doesn't mean being weak or subservient but more open to new ideas, technologies, and ways of working.
While humility creates a mindset open to learning, curiosity is the catalyst for action. Curious people are motivated to learn more, and a learning culture provides fertile soil for personal growth. In addition, people that approach problems with a curious mindset tend to be less judgmental. As they try to understand and unpack a problem, they replace the tendency toward criticism with curiosity. Finding who's at fault is easier than understanding the complexity inherent in systems like large organizations operating in a highly dynamic market. Adopting Quality Thinking allows you to move from ego and blame, which damages trust and communication (and information flows across the organization), to better understanding and problem-solving.
Mental Models and Decision Processes
The simplest definition of mental models is that they describe the way the world works. They also influence how we think, understand, and form beliefs. Mental models can be employed to reveal flaws in our thinking as corrective measures against sloppy or biased thinking. Examples of commonly used mental models include first principles thinking, leading vs. lagging indicators, and probabilistic thinking (a more comprehensive discussion can be found here and here). These methods help expose assumptions underlying your thinking and challenge what you think you know about a problem. They also help you anticipate problems, intervene before it’s too late to fix them, and help maintain your outside view by constantly adding new information to your existing data to get closer to the truth. Finally, mental models provide the bridge from thinking about a problem by reframing or organizing your thoughts to making a decision, all of which happens inside a defined decision process.
So, what is a decision process, and how does it differ from a business process? A decision process is a set of discrete steps individuals or teams use to evaluate and analyze information to create insights that inform decisions. At a high level, it involves locating and evaluating evidence, structuring it for analysis, and making decisions based on this analysis (you can find a deeper dive into decision process improvement here).
Decision processes usually are embedded in a broader business process, with the distinction that the output of a decision process is an agreement to take some action. The output of a business process, however, is typically a tangible thing (e.g., a product or service) resulting from many cumulative decisions. The fact is that most decision processes are not well understood, documented, or objectively evaluated. Building Quality Thinking skills enables leaders and staff to apply the right mindsets and skillsets to improve decision processes and, ultimately, organizational performance. It requires a commitment to continuous improvement with people operating inside a process that closely examines decision processes, determines where there are deficiencies, makes adjustments, and measures results.
What should we be looking for in evaluating decision processes? There are three priorities or objectives, 1. Exposing gaps in decision processes related to throughput, quality, and cost, 2. Documenting behavioral changes within the process necessary for improvement, and 3. capturing potential use cases for the application of new technology to support decisions, in particular, looking at AI/LLMs to determine how to incorporate advances like ChatGPT into existing decision processes.
As noted earlier, we can unlock unimaginable human potential to creatively solve our hardest problems. Still, the limiting factor is not technology but us, our thinking abilities, and our capacity for change.
Quality Thinking provides a framework for individuals to focus their personal and professional development in ways that prepare them for what’s next. And what’s next is hard to predict. Hence the central idea with QT is that “preparing” means honing the skills of observing, adjusting, and adapting, which means open-mindedness combined with disciplined practice.
A critical takeaway is this: discipline and creativity are not incompatible but complementary and self-reinforcing. Throughout history, we’ve seen this pattern across domains that include art, literature, architecture, science, philosophy, and technological innovation, where creativity combined with disciplined effort produced “genius” breakthroughs in scientific discovery or timeless art.
Below are quotes from people across disciplines (and time periods) to drive home the point. The first from Chopra speaks to a mindset of openness, be it to new ideas or information, that is essential to improving the quality of your thinking. The rest of the quotes reinforce the universality of rigor, discipline, and creative output.
"Be comfortable with and embrace paradox, contradiction, and ambiguity. It is the womb of creativity.”
Deepak Chopra, physician and best-selling author on alternative medicine.
"I was always conscious of the constructed aspect of the writing process, and that art appears natural and elegant only as a result of constant practice and awareness of its formal structures."
Toni Morrison, award winning novelist
"What made Leonardo [Da Vinci] a genius, what set him apart from people who are merely extraordinarily smart, was creativity, the ability to apply imagination to intellect."
Walter Isaacson, professor, journalist, and best-selling author
"Imitation and mastery of form or skills must come before major creativity."
Oliver Sacks, neurologist, naturalist, historian of science
"The really rare skill is the ability to marry discipline to creativity in such a way that the discipline amplifies your creativity rather than destroying it."
Jim Collins, researcher, author, speaker and consultant
So, what’s next? What should we be working on every day? The answer is ourselves. We must work systematically to improve the quality of our thinking. And the future is coming at us fast—time to get started.
Image credit: engineered by Eddie Hinton using Dall-e