A Model of Business Expertise
Business expertise comes from better ways of structuring or organizing knowledge.
A Model of Business Expertise
Better business expertise does not come from greater analysis or greater information, but better ways of structuring or organizing knowledge.
Business expertise is distributed cognition.
Business expertise is domain-specific mental models of the business and cognitive agility (the ability to update mental models in light of new information).
Business expertise means a deep understanding of:
- Factors involved in effective operations
- Forces influencing the market
- Forces driving business finance and economic climates
One way of describing it is ‘supply/demand/capital’. Another is ‘leadership/strategy/finance’.
- Supply, or leadership: factors involved in effective operations. Have good mental models of the org and its people, and the ability to push through plans given internal politics.
- Demand, or strategy: forces influencing the market. Includes everything from market shape, competitive analysis, positioning, changing consumer demand, and the ‘path to power’ (from 7 Powers)
- Capital, or finance: factors driving business finance and economic climates. Financial concepts like cash flow lockup, return on invested capital, margins, and their relationship with the other two categories.
The key property of business expertise is in understanding how a change in one leg of the triad affects the other two legs, at least within the context of one’s specific industry.
Want to get really good at business? Then systematically acquire skills in each of the three categories, specific to your particular business, and then — more importantly — cultivate an understanding of the relationships between the three categories.
Internalize the relationships.
Every business is a system, and developing intuition for a system requires you to watch that system in action.
To maintain cognitive agility, one must resist being impervious to new data, not hold rigid frameworks or paradigms tightly otherwise risking to filter out new information and create blind spots. Cognitively agile individuals learn from their inaccurate predictions or judgments and improve as they go along. In the face of dynamic feedback, mental models must be rapidly revised.
A committee can function as an expert only if they know where the different elements of their expertise reside.
For learning to happen people, need to have their old mental models destroyed through visceral failure, to make way for new models.
They need to fail hard enough for the game to stop so they examine their patterns of decision making, reconstruct what happened, and compare their results to the ideal results. Only then are people ready to be facilitated to play the game with different results.
People must begin to reflect on their default strategies and examine how a different approach might have accomplished their goals. Only then can people become aware of the assumptions guiding their decisions under pressure and the attendant results. They must ‘deconstruct’ their decisions before they can ‘reorganize’.
Cognitive Transformation Theory
Learning consists of the elaboration and replacement of mental models. Mental models are limited and include knowledge shields. Knowledge shields lead to wrong diagnoses and enable the discounting of evidence. Therefore learning must also involve unlearning.
Additional Propositions in the Theory
- Mental models are reductive and fragmented; therefore incomplete and flawed.
- Learning is the refinement of mental models. Mental models provide causal explanations.
- Experts have more detailed and more sophisticated mental models than novices. Experts have more accurate causal mental models.
- Flawed mental models are barriers to learning (knowledge shields).
- Learning is by sense-making (discovery, reflection) as well as by teaching.
- Refinement of mental models entails at least some un-learning (accommodation; restructuring, changes to core concepts).
- Refinement of mental models can take the form of increased sophistication of a flawed model, making it easier for the learner to explain away inconsistencies or anomalous data.
- Learning is discontinuous. (Learning advances when flawed mental models are replaced, and is stable when a model is refined and gets harder to disconfirm.)
- People have a variety of fragmented mental models. “Central” mental models are causal stories.
Cognitive Transformation Theory tells us that people learn when they replace flawed mental models with better ones, as a result of trial and error cycles.
What makes one person more effective at trial and error when compared to another? Well, Cognitive Transformation Theory tells us that their effectiveness is limited by their ability to unlearn previous mental models in the pursuit of better, more effective new ones.
Sensemaking is to deliberately discover what is wrong with one’s mental models and to abandon and replace them.
As expertise increases, the work needed to replace flawed mental models goes up.
A training program to accelerate expertise should be optimized to break knowledge shields, and quickly. Teams must fail in a very rapid, public manner, within a simulation that feels like the real company they work in. Visceral failure enables the ‘deconstruction’ phase, allowing ‘reorganization’ of the company’s mental models.
Most people must be violently shown that their models are deficient before they are willing to learn new ones.
- Supply, or leadership: factors involved in effective operations. (Management, org design, incentives, ops…)
- Demand, or strategy: forces influencing the market. (Competition, government, Power, market cycles…)
- Capital, or finance: factors driving business finance and economic climates. (Understanding financial metrics, access to and cost of capital…)
Or, remapped even simpler, the shape of business expertise is
- Expertise in making (understanding operations)
- Expertise in selling (understanding markets)
- Expertise in capital (understanding financing)
A simple evaluation of your skill might go something like this:
- What are the operational factors involved in running a business in this industry, and what are you lacking?
- What are the factors influencing the market for the market you’ve chosen to play in? What do your competitors understand that you do not?
- What are the financial metrics and capital climate for this particular business? What do your competitors or peers in adjacent markets get that you do not?
- Can you predict how changes in each leg affect the other two, at least for your specific industry?
It’s the living dynamic between the triad that matters. E.g., demand goes down, it instantly changes the opportunities and constraints in the other two.
Given an idea, look for a history of application. Look for an application of how this can be useful.
Cognitive Flexibility Theory
Cognitive Flexibility Theory (CFT) is a theory of expertise in ill-structured domains.
Concepts in computer programming (e.g., variables, loops) always show up in the exact same way—computer programming is a well structured domain. Well-structured domains are domains where concepts show up in the exact same way.
Concepts in software design often vary with the details of the problem—software design is an ill-structured domain. Ill-structured domains are domains where concept instantiations are highly variable.
Expertise in a well-structured domain is suited towards understanding principles.
Expertise in an ill-structured domain is suited towards having examples of concept instantiations. You need to know examples of principles in action. Principles or frameworks are not enough, as the concept are highly variable. Experts in ill-structured domains can reason by combining examples of concept instantiations.
In ill-structured domains, universal principles apply themselves in so many different ways that knowing the ways and contexts they show up is more important than knowing the principles. No framework perfectly captures the novelty of real-world situations.
You have to compare cases—what’s similar? Does it remind you of a particular case—if no, what’s different?
The most important lessons from history are the takeaways that are so broad they can apply to other fields, other eras, and other people. That’s where lessons have leverage and are most likely to apply to your own life. — Morgan Housel
- Venkatesh Rao: Thinking in OODA Loops
- Cedric Chin: Much Ado About The OODA Loop
- Cedric Chin: Ability to See Expertise is a Milestone Worth Aiming For
- Mapping the Unknown – The Ten Steps to Map Any Industry
Pursuit of knowledge
- Commoncog series on Becoming Data Driven in Business
- Can simpler technology produce better learning outcomes?
- Stumbling Towards Rightness
- Embrace Complexity; Tighten Your Feedback Loops
- (1984) Eliyahu M. Goldratt - The Goal: A Process of Ongoing Improvement
- (1989) Dietrich Dörner - The Logic of Failure: Recognizing and Avoiding Error in Complex Situations
- (1993) Donald J. Wheeler - Understanding Variation: The Key to Managing Chaos
- (2016) Hamilton Helmer - 7 Powers
- (2020) Bob Moesta - Demand Side Sales 101
- (2012) Will Thorndike - The Outsiders
- (2015) Marathon Asset Management - Capital Returns: Investing Through the Capital Cycle