Mindware: 33 Mental Models for The Modern Agribusiness Leader

Essential frameworks for agribusiness leaders working in crop inputs, ag retail and precision agriculture.

Introduction

Agribusiness professionals operate in a world full of volatility, complexity, and constant change.

Commodity price swings, regulatory shifts, changing customer demands, and technological evolution create a landscape where uncertainty is the norm, not the exception.

Since joining the industry, one thing has become clear to me: whether I have interacted with a senior executives, a marketing manager, or an elite agronomist, what separates the best from the rest in navigating these challenges is how they think.

Just like a carpenter has a tool belt with a hammer and drill, or a golfer has fourteen clubs to use depending on shot demands; high-performing agribusiness professionals need a collection of mental tools ready to be deployed for any situation they encounter.

I think of that toolset as Mindware.

Note: The full contents of this article are being published as a digital guidebook and will be available in July 2025.

Mindware

The term Mindware was popularized by psychologist Richard Nisbett to describe a combination of mental models, reasoning strategies, and frameworks that help people think clearly and make better decisions.

It's effectively cognitive software— the internal code we run to solve problems, analyze trade-offs, and interpret the world.

Mental models are at the heart of mindware. They are simplified representations of how the world works— patterns, principles, and frameworks that help you see clearly in complex environments. They’re the shortcuts to insight and the differentiator in demanding situations and important decisions.

As Charlie Munger, the godfather of mental models, put it:

“Developing the habit of mastering the multiple models which underlie reality is the best thing you can do.” 

The more useful models and frameworks you hold, the better your judgment.

Mental models come in many forms, but for me they broadly fall into three core categories.

Each plays a different role in improving how we think, reason, and act:

1. Descriptive Models

These models help us understand systems, processes, and relationships in the world. They’re rooted in disciplines like physics, biology, economics, and systems thinking. In agribusiness, these are especially useful for simulating dynamics, forecasting outcomes, and understanding interdependencies. Examples include the law of diminishing returns, entropy, creative destruction, inertia and many more.

2. Cognitive Models

These come from psychology and behavioral economics. They explain how our brains shortcut decisions, fall into traps, or misjudge information. As agribusiness becomes more data-rich and decision-heavy, avoiding cognitive bias becomes a major differentiator. Some of these are covered in 25 Concepts for Improved Career Outcomes in Agribusiness. Examples include things like inversion, incentives, Occams Razor, Loss Aversion, and many more.

3. Strategic Models

Arguably, these models could fall into #1. They help guide strategic decision-making, resource allocation, and competitive positioning. They’re used in business, and often come from game theory, or military strategy. But they are crucial for thinking strategically about business, products or careers.

When our mental models and frameworks align with reality, they help us make better decisions. But when they’re misaligned — when we operate based on faulty assumptions or cognitive bias — they cause problems of their own.

For agribusiness professionals, whether in crop inputs, equipment, ag retail, or startups, having strong mindware is a force multiplier. It enables faster learning, sharper thinking, and more confident action — even when conditions are challenging.

This guide curates a set of mental models and frameworks that I’ve found particularly useful from all three categories above, with a heavy emphasis on strategic models.

Some are borrowed from strategy leaders, some from biology and some I created when applying concepts from the industry.

These models are adapted to the unique dynamics of agriculture and aren’t abstract strategy concepts.

They’re practical lenses designed to help you lead, decide, and operate more effectively in one of the most complex industries in the world.

Each of the 33 frameworks includes:

  1. A Corresponding Illustration (where applicable)

  2. Overview of the Framework

  3. Application to Agribusiness

  4. Key Takeaway for Agribusiness Professionals

Index

  1. The Red Queen Effect

  2. Roger Martin’s Playing to Win Framework

  3. Hierarchy of Agronomic Needs

  4. Innovation Adoption Framework

  5. Ecosystem Disruption and Disruption Through Complements

  6. Commoditize Your Complement

  7. Control Points in Software

  8. Influence Erosion

  9. Closed Loops and Precision Ag

  10. Friction Reduction and Schlep Blindness

  11. Strategy Tax

  12. Contrarian Decisions: Uncertainty is Where There is Upside

  13. The Lump of Labor and The Job Bundle: Considerations for Artificial Intelligence

  14. Jobs to Be Done

  15. The Sauce Paradox and the Funnel of Specificity

  16. 7 Powers by Hamilton Helmer

  17. Porter’s Five Forces

  18. Innovation Theatre

  19. Thinking from First Principles

  20. The Apps → Infrastructure Cycle

  21. Carlotta Perez’s Five-Phase Framework of Technological Revolutions

  22. Trapped Value

  23. Weak Link vs. Strong Link Problems

  24. Eroom’s Law 

  25. Rugged Landscapes

  26. Value Chain Mapping & Modularity

  27. Integrated Insights

  28. Unknown Unknowns Framework

  29. Ergodicity

  30. One-Way vs. Two-Way Door Decisions

  31. The Barbell Effect

  32. Control: Influencing the Market vs. Letting the Market Influence You

  33. Jevons Paradox

  34. Bringing It All Together: Why Mental Models Matter in Agribusiness

  35. Other Useful Resources

The Red Queen Effect

Overview

The Red Queen Effect is a concept from evolutionary biology that explains how species must constantly adapt and evolve— not just for progress, but to simply maintain their current position in a changing environment.

The term comes from Lewis Carroll’s Through the Looking-Glass, where the Red Queen tells Alice, “It takes all the running you can do, to keep in the same place.” In nature, this means organisms must continually evolve to survive against ever-evolving competitors, predators, and parasites.

The Red Queen Effect is often used to describe competitive dynamics— especially in fast-moving industries. Companies must continually innovate just to retain their market position because competitors, technology, and customer expectations are always advancing.

Applied to Agriculture

Example: An ag retail company introduces a premium crop scouting service that uses drones, imagery, and digital reporting tools to deliver faster, more accurate insights to farmers. It quickly becomes a differentiator— farmers see value, yields improve, and the retailer gains market share and manages margin erosion.

But within two seasons, competitors begin offering similar services. And some take it a step further and partner with companies like Solinftec and bundle scouting, product and the application service to deliver an entirely new experience to the farmer.

Suddenly, what was once a competitive edge is now expected, and in some cases, has been surpassed.

To maintain relevance, the original retailer must continue evolving— integrating new tools and system, layering in See & Spray prescriptions, and hiring entirely new teams to compete and differentiate.

Takeaway

Ongoing innovation isn’t about getting ahead one time— it’s about having the mindset, or the company culture, to continually find ways to do so.

Roger Martin’s Playing to Win Framework

Overview

Roger Martin’s Playing to Win framework defines strategy as a set of integrated choices that position a business to win. It revolves around five core questions:

1. What is our winning aspiration? Defines the end goal— what success looks like.

2. Where will we play? Identifies the specific markets, customers, and segments to focus on.

3. How will we win? Articulates the unique value proposition and competitive advantage.

4. What capabilities must be in place? Specifies the activities, competencies, and assets required to execute.

5. What management systems are required? Ensures alignment of processes, incentives, KPIs, and organizational structures.

The strength of the framework is in forcing clarity and alignment between ambition, focus, differentiation, execution, and measurement.

Application to Agriculture

Agribusinesses often drift into reactive mode— serving everyone with everything. The Playing to Win framework challenges this by demanding focused choices:

An independent retailer might define its aspiration as becoming the most trusted advisor to progressive row crop farmers in the Midwest.

- Its “where to play” choice could focus on 1,000–5,000 acre farms in a five-county region growing corn and soybeans.

- Its “how to win” could be through proprietary agronomic programs and integrated service offerings— not price or scale.

- The capabilities might include top-tier agronomists, a detailed training approach for their team, a new approach to service, and a uniquely thought out supply chain.

- Management systems would align incentive structures, data tracking, and service models to reinforce the strategy.

This clarity helps avoid generic strategies like "grow market share" or "become more innovative" without knowing who you're serving, how you're different, and what you need to be excellent at.

Takeaway

Strategy is not a vision or a plan— it's about making hard, integrated choices that define where to focus and how to win.

In agriculture, with rising complexity and margin pressure, companies that clearly articulate their strategic choices and align their teams and systems around them, will be far more likely to create loyal customers and enduring value.

Hierarchy of Agronomic Needs

Overview


Adapted from Maslow’s hierarchy, this framework structures what a grower needs to succeed based on foundational needs up to more “elevated” outcomes.

The Hierarchy of Agronomic Needs is a framework that helps illustrate how farmers prioritize different crop inputs based on necessity, particularly through avrying economic conditions.

Applied to Agriculture

At the base of the pyramid are Foundational and Functional products— things like land, seed, fertilizer, and basic crop protection. These are used every year regardless of price or weather outlook. These are essential.

Then we move to Functional Needs— herbicides, insecticides and macronutrients like N and P. These are not required to grow a crop, but the average farmer wants access to these tools and products every year.

Moving up the pyramid, we reach Optimization Options (like micronutrients or variable-rate tools), products that a farmer can go without, but are beneficial.

Finally we get to Elevated Outcomes— products like biostimulants, which tend to be used only when prices are strong, yield potential is high and farm income has been positive.

Farmers are more likely to cut back on products higher in the pyramid during tough years.

But with strong positioning, education, and integration into essential use cases, companies can move products down the pyramid— making them feel more like “must-haves” instead of “nice-to-haves.”

Takeaway

Input manufacturers, agtech companies and ag retailers should focus on actions that move their products down the pyramid— closer to default use and foundational or functional. That means deeply understanding where and why they work, tightly positioning inputs to specific agronomic problems, clearly communicating economic return, and tying usage to familiar systems or foundational practices. The closer a product gets to being seen as essential, the more resilient its demand becomes regardless of the weather, prices or overall commodity cycle.

Innovation Adoption Framework

Overview

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