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The Value Creators Podcast Episode #3. Jason LaBaw: Culture And Technology Amidst High-Speed Change

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You need two types of knowledge to succeed in the business world: specialized technical knowledge and deep customer knowledge. This will allow you to create uniquely valued experiences tailored to your customers and thus build a thriving business.

Jason LaBaw, as the founder and CEO of Bonsai Media Group and a pioneer in web development, AdWords, Google Analytics, and Umbraco development, has accumulated over 18 years of industry experience, client service, and strategic leadership in the digital world and has become an expert in combining technical and customer knowledge to scale.

In this episode, Jason touches on how he believes the future will look and what principles he is certain will be invaluable to thrive in a futuristic economy, such as empathy, planning, and budgeting.

Show Notes:

0:00 | Intro to Entrepreneurial Management

1:56 | Introducing Jason Labaw

3:10 | Businesses Coping with Technology

7:11 | Ways to Engineer Technology

8:32 | How to Work & Run a Business These Days

10:31 | End-user Experience

11:52 | User testing

12:35 | Secrets of Empathy

14:49 | Getting into Depth with Bonsai Media Group

21:01 | Trends: Augmented Reality 

24:40 | Storytelling as a marketing

25:20 | Story about the Future

27:39 | Gamifying Work

29:30 | Risks of Technology to Entrepreneurs

31:52 | Learn More About Bonsai Media Group

Knowledge Capsule:

Combining customer knowledge and tech knowledge.

One of the Value Creator’s mantras is to combine deep customer knowledge with specialized technology knowledge to create uniquely valued experiences for customers and thereby build successful businesses.

Jason LaBaw has done this successfully at the company he formed, Bonsai Media Group. He illustrates how it’s perfectly viable to start simply and advance quickly.

  • An early example of a project is one where the company, in customer service mode, transformed a trivia app request from a client into a social contest that engaged users and immersed them in the brand’s story.
  • This evolved into various combinations of the digital and physical worlds through scavenger hunts – which became an exploration of the potential of AR and VR.
  • AR and VR can be further combined with 3D product imaging. It turns out that 3D experiences are hugely beneficial for conversion rates. 
  • Combining his experiences in both the digital and physical realms, he began envisioning ways to create immersive experiences that merge AR and the real world: to make exploring the world as fun as playing a video game, using technology to encourage people to get out and explore the real world around them.

Simple steps towards a complex future.

With these relatively simple business steps, Jason has now advanced to become a futurist of AR, VR, and AI. While some believe these technologies have been overhyped, Jason believes they have tremendous potential to transform human experiences. He emphasizes the importance of human connection and expresses his hope that future generations won’t be locked in virtual worlds. He sees augmented reality, AI, and voice-enabled technologies as key drivers for positive change. For instance, he envisions a scenario where augmented reality glasses enhance meetings by providing contextual information and augmenting reality with relevant data.

The discussion also touched on the concept of gamification. Jason explains how gamifying networking events can facilitate connections and conversations by using augmented reality cues to identify shared interests. He believes gamification can also be applied to work, where incentives and rewards can be used to motivate employees and create a more engaging and efficient work environment.

There are basic economic principles underlying this futuristic scenario.

Empathy

Empathy remains the essential skill for businesses, no matter how futuristic or high-tech. Jason emphasizes the importance of having conversations and conducting in-person interviews with various stakeholders, including frontline workers, managers, and customers. This qualitative data gathering allows businesses to uncover valuable insights and understand how customers perceive their brand and experiences. Jason recognizes the value of quantitative data, such as analytics and user testing, in making informed decisions and improving products, but it’s best when it is in addition to qualitative data,

This way businesses can focus on their customers’ needs, goals, and preferences to create competitive advantages. He suggests that companies can provide value by enabling customers to perform tasks online, like paying bills. 

Planning and budgeting

Planning, allocating budget, and continuously iterating based on customer feedback and analytics are crucial for adapting to change

Jason suggests a general formula for coping with technological change, starting with a budget-focused approach. By analyzing different options and making design and technical decisions based on budget and return on investment (ROI), businesses can adapt to changing technologies. He emphasizes the need for clarity and defining a project’s ROI from the start. By allocating budget or accruing it, businesses can invest in technology iteratively over time, improving functionality, and user interfaces, and switching components when necessary.

Additionally, Jason highlights the significance of having a contingency plan to deal with unexpected events or disruptions. He shares an example of a company that had to pivot quickly when a technology vendor was acquired. Being prepared with alternative vendors or technologies enables businesses to adapt swiftly.

The Value Creators Podcast Episode #2. John M. Jennings: Mental Models Are The Uncertainty Solution

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In a complex world full of uncertainty, all businesspeople and entrepreneurs can draw guidance from shared mental models that help us make better choices. John M. Jennings took this advice to heart and developed a latticework of mental models for financial investing and any other business discipline, which he explained and expanded on in his book The Uncertainty Solution: How To Invest With Confidence In The Face Of The Unknown.

John is a premier thought leader in the wealth management industry and President and Chief Strategist of St. Louis Trust and Family Office, a $15 billion national investment firm. He is also an adjunct professor at Washington University’s Olin School of Business in its Wealth and Asset Management Graduate Program.

In this episode, he not only teaches why we always look for certainty and how we can be aware of certain pitfalls we fall into while dealing with uncertainty but also how to navigate uncertainty to not only come out unscratched but profit from it.

Show Notes:

0:00 | Intro

00:28 | Mental Models with John M. Jennings

1:39 | The Uncertainty Solution

02:25 | Defining Uncertainty

03:34 | Predicting the Future

04:35 | Defining Mental Model

6:08 | Unliking Uncertainty & How to Deal With It

8:48 | When Cause and Effect Don’t Work

12:37 | Extrapolating Trends

17:49 | Business Cycles

20:36 | The Result of Our Luck 

24:36 | Exponential Growth

28:42 | The Latticework of Mental Models

33:57 | Loss Aversion

36:38 | Overconfidence is the Mother of all Biases

41:20 | Wrap Up: Philosophical Advice from John M. Jennings

Resources:

(Book) The Uncertainty Solution – John M. Jennings

(Book) Managerial Decision-Making – Max Bazerman

(Book) Scale – Jeffrey West

Knowledge Capsule

In his book, The Uncertainty Solution, John M. Jennings urges each of us to use a latticework of mental models to simplify the complexity we inevitably face. Here’s a summary.

A. Knowledge: Think of information in four categories: data, information, knowledge, and wisdom, and focus on knowledge or wisdom over data and information. 

B. The Quest for Certainty:

  1. Uncertainty: We dislike uncertainty as it causes stress and triggers our fight-or-flight response.
  2. Seek resolution: Resolving uncertainty brings pleasure, but we should recognize and sit with the discomfort instead of seeking closure.
  3. Avoid information overload: Resist becoming an information junkie or relying too much on expert predictions.
  4. Embrace discomfort: Sit in your discomfort and focus on what you can control. 

C. Looking for Causes in All the Wrong Places:

  1. Causation Is Tough to Determine: Assuming one thing caused another can be risky, as coincidence and multiple factors often play a role.
  2. Correlation Does Not Imply Causation: Strong correlation doesn’t mean one thing causes the other.
  3. Regression to the Mean: Extreme events tend to be followed by outcomes closer to the average.
  4. The Law of Large Numbers: Conclusions based on small sample sizes can be misleading; consider sample size whenever causation is asserted.
  5. The Highly Improbable Happens All the Time: Unlikely events occur frequently, so don’t be surprised and caught off guard. 

D. The Stock Market Is Not the Economy:

  1. Economic Growth vs. Stock Market: Economic and stock market performance are not always correlated.
  2. The Stock Market as a Complex Adaptive System: Predicting stock market movements is nearly impossible due to the interactions of intelligent agents.
  3. Economic Indicators Don’t Predict the Stock Market: Economic indicators and market signals often fail to predict market performance. 

E. Market Cycles and the Two Axioms of Investing:

  1. Markets Move in Cycles but Defy Prediction: Market cycles vary in duration and intensity, but no permanent plateaus exist.
  2. Economic Stability Creates Instability: Stability can lead to bubbles and crashes; opportunities arise when stability appears.
  3. Market Timing Doesn’t Work: Timing the market is challenging and requires being right twice—both at the top and bottom.
  4. It’s Okay to Invest in Advance of a Bear Market: Investing before a bear market can be fine if you follow a disciplined strategy.
  5. The Limits of Arbitrage: Being right doesn’t guarantee winning due to the market staying wrong for extended periods. 

F. Beware Experts Bearing Predictions:

  1. Economic and Stock Market Predictions Are Worthless: Investment predictions are often wrong, and investing without relying on knowing the future is better. 

G. Skill and Luck in Investing:

  1. The Skill-Luck Continuum: Luck plays a significant role in investing, and short-term results may not reflect skill.
  2. Most Investment Managers Underperform the Market: Most active managers underperform after fees, so consider the odds before investing with them.
  3. Most Stocks Underperform the Market: Picking individual stocks is challenging, and most fail to outperform the market.
  4. Monkey Portfolios Outperform: Following a different strategy than the market can yield better results, but it requires discipline. H. The Trend Is Not Your Friend:
  5. It Is Difficult to Spot a Trend Early: Identifying trends early is challenging, especially exponential growth.
  6. Trends Don’t Always Turn Out as Imagined: Established trends can change rapidly due to new competitors and technologies.
  7. It’s Difficult to Find a Successful Needle in a Haystack of Competitors: Picking winners among many competitors is challenging, and early pioneers may not be the long-term winners.

H. The Trivial Many Versus the Vital Few:

  1. The Danger of Using the Bell Curve in Investing: Relying on bell curve statistics may not capture the true nature of the stock market’s behavior, so be skeptical of advice based on such statistics. 2. The Stock Market Is Better Described by Power Law Distributions: Embrace the uncertainty provided by power law distributions instead of relying on projections based on the bell curve. 

I. Navigating Our Behavioral Biases:

  1. The Endowment Effect: We tend to overvalue things we own, including our investments.
  2. The Storytelling Bias: Stories strongly influence our decision-making, so be aware of how they can sway investment choices.
  3. Hindsight Bias: Looking back, we think we should have known the future but realize that infinite possibilities influence outcomes.
  4. Loss Aversion: Losses have a more significant impact on us than gains, leading to risk aversion and irrational behavior.
  5. Overconfidence: We often overestimate our knowledge and abilities, leading to poor decision-making. Recognize and mitigate overconfidence. 

J. Behavior—The Most Important Ingredient:

  1. Choose Inactivity Over Activity: Avoid excessive tinkering and market timing; maintain a long-term perspective.
  2. Prefer Simplicity Over Complexity: Start with a simple approach and add complexity only when necessary to avoid complications and fees.
  3. Establish Simple Investment Algorithms: Create an investment policy statement and follow simple asset allocation and rebalancing rules. These insights aim to provide a clearer understanding of investing and guide decision-making in the complex world of finance.

209. Lipton Matthews: A 5-Way Global Perspective on Innovation and Entrepreneurship in the USA

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Entrepreneurship and innovation are the keys to economic growth and higher standards of living. The USA has long enjoyed leadership status on these dimensions — people see the USA as the land of entrepreneurs and the source of new ideas and advances in business. Is the reputation still deserved? Or is it being eclipsed as part of the general decline in standards and capabilities that we observe? Lipton Matthews is a global economic and geo-political analyst who brings deep knowledge and expertise to address our concerns.

Knowledge Capsule

Borrowing a framework from the Global Innovation Index published by the World Intellectual Property Organization, we can examine the state of entrepreneurship and innovation in the US relative to both other countries and its own history, under the headings of institutions, human capital and research, infrastructure, market sophistication and business sophistication.

Institutions: The private sector institutions of the USA continue to excel for entrepreneurship and innovation.

When we think of American institutions for the encouragement of entrepreneurship and innovation, we must examine private sector institutions, not those of government. Ordinary people in civil society build the institutions that promote innovation. Private scientific research is robust in responding to market signals of consumer and business needs. Financial institutions such as venture capital and angel investors support innovative development. Policymakers mistakenly believe they can conjure up a creative economy by fiat, but they’re wrong. It’s private institutions that support and cultivate innovation. Even if the public sector tries to encroach, the private sector maintains its innovative edge.

Professor Sam Gregg warned us recently that the United States of today more closely resembles a European social democracy than many Americans are willing to admit, but Lipton Matthews is confident that America is still winning the entrepreneurship contests because the forces of democratic socialism can’t overpower the higher-energy force of the private sector drive for creative innovation in return for market reward.

Human capital and research: The ability to execute overcomes any shortcomings in education.

If we look through the declinist lens, it’s easy to become gravely concerned about the state of education at all levels in the US, which directly impacts the development and deployment of what economists refer to as human capital. Do we under-allocate resources to teaching schoolkids business and entrepreneurship skills and tools, and at the college level, do we turn out too many English and philosophy grads compared to market needs, and not enough engineers and STEM grads?

Lipton Matthews cautions us against worrying about the wrong things. The educational qualifications of the products of American schools and universities matters less than their executional and implementational capabilities. America is a nation of do-ers, and that type of expertise is embedded and innate, from the time of the founding fathers and early immigrants who built the America economy. We prize innovators more than inventors — the ones who successfully turn ideas into marketable products and services. Entrepreneurship is action, and American business capitalizes the talent for execution, combining scientific learning with creative action to generate innovation. Executional capacity comes more from a market orientation than from formal learning.

A concern about the research component of the Global Innovation Index’s “human capital and research” classification is, perhaps, more justified. Government-directed research dominates formal research budgets — directed to fields such as climate change — for universities in the US, and the historical evidence is clear that this pool of research is inappropriate for the support of entrepreneurship, despite European aspirations to an entrepreneurial state. Brilliant scholars and researchers who could be entrepreneurs and innovators are diverted into unproductive activities.

It’s difficult to quantify private sector R&D; we must hope that it is sufficient to counter-balance the state’s diversion of research funds. In fact, Lipton Matthews points out, we must expect the state and innovators to be in competition. The former prefers control and stability versus the latter’s pursuit of disruption and change.

Infrastructure: Think local and regional, not national.

We are frequently presented with stories about the crumbling of US infrastructure. That’s the wrong level of focus, according to Lipton Matthews. First we should compare US infrastructure to other countries, where the quality of engineers and engineering may be lower, and so roads, bridges and communications networks are inherently superior in the US. Second, we should focus on infrastructure in our localities and regions. Local communities can manage infrastructure well in support of local businesses. Some towns and cities will have better-managed and better-maintained infrastructure than other parts of their state, and businesses will be attracted there.

Market sophistication: capital flowing to best entrepreneurial uses.

Lipton Matthews interprets the Global Innovation Index’s category of market sophistication to refer to the financing of startups, scale-ups and innovative entrepreneurial businesses. American deployment of venture capital and the widespread networked access to investment funds are examples of market sophistication in practice. Ordinary people can invest in startups and innovation, and entrepreneurs at every stage of their journey can arrange access to investors.

While these investment funding networks may not be perfect, and while we may encounter some challenges in moving capital to the bottom of the pyramid, nevertheless, the private financial sector in the US is effective in directing funds towards innovation. While there may be some erosion of purpose, from long term funding of innovation to making money via short term trading in-and-out of markets, this does not detract from America’s lead in market sophistication.

Business sophistication: The ability of business to absorb new knowledge and use it to innovate.

Bart Madden called knowledge-building proficiency the central differentiating function of the successful firm. Our businesses are learning machines, continuously generating new knowledge via R&D, marketplace experiments, interactions with customers and feedback from all business activities. While it’s possible that Americans might be eclipsed by some other countries in the race to produce patents, this is not a relevant measure. Marketplace innovation is the test of business sophistication, not patent registration. Knowledge accumulation must be accompanied by knowledge application.

America’s entrepreneurial nation of doers not only engages in eternal learning but in the adaptive entrepreneurial method of act-learn-improve. The rest of the world has not fully caught up.

Summary

In Lipton’s eyes, America was oriented for entrepreneurial success by the founding fathers and early immigrants, and will continue to innovate and grow as a result of entrepreneurship. Only if we get in our own way through excessive statism, regulation and government intervention that misdirects our energy and resources will we break the well-established historical track record.

Additional Resources

Global Innovation Index: Mises.org/E4B_209_Index

“For Now, Entrepreneurship And Innovation Still Hold A High Place In The USA” by Lipton Matthews: Mises.org/E4B_209_Article

208. Melissa Swift: Human Action To Build A Powerhouse Workplace

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What can economics tell us about designing fulfilling jobs and productive workplaces? Quite a lot if we apply the economics of subjective value and empathy. Melissa Swift is the author of Work Here Now: Think Like A Human And Build A Powerhouse Workplace. She discusses her research on the Economics For Business podcast.

Knowledge Capsule

Poorly designed jobs and workplaces are dangerous, dull, annoying, frustrating and/or confusing.

The results of academic research have confirmed how alienated many workers are from their jobs, and the trends in these findings are worsening, not improving. During the pandemic, many of us had the opportunity to stand back and survey this situation, and realize that it’s a problem that we need to address.

We can do better by applying Austrian economics principles of subjective value and empathy.

The economics of subjective value should point employers in the direction of asking how employees feel about their jobs and the sense of purpose and meaning they derive from them. Why do these considerations not arise, or why are they insufficiently acknowledged? Melissa Swift sees what she calls a wall between how human beings operate and how the world of work operates. We think in discrete terms about “work” on one hand, and “people” on another, and don’t integrate them well.

Managers have demonstrated a penchant for intensifying work (doing more in less time and with fewer resources) and for pressing for over-collaboration (too many reports, checkpoints, meetings and interactions and exchanges, and belonging to too many teams) with the ultimate result of detracting from an individual’s capacity to get things done. Managers don’t necessarily tie the design of work to impact delivered or value created.

In fact, much work is performative, putting on a display of work that is not necessarily productive (writing impeccable but essentially useless reports, for example).

Managers should be actively looking for and rooting out problems of bad jobs and poor work environments.

Melissa Swift’s formula is to be humble and curious in asking how work feels to those who are doing it. Employees know their work better than managers do (an observation which, of course, turns management science on its head).

There are a couple of “monsters” that can be identified and tamed. One is the anxiety monster – we all feel anxiety about whether we are productive enough, or doing good enough work, or being viewed in a favorable light. Anxious managers stand over people, telling them to work harder and faster. We must shut down all the anxious stories that are in our heads.

Employees can be over-anxious about customers, too. We may tend to over-deliver on customer care and customer expectations, to the point where we train them to be so demanding that they go beyond the point where the corporation is capable of fulfilling its own promises.

Once “monster” jobs — those that generate excess anxiety — are established, there’s a tendency for the HR “copy machine” to copy-paste them throughout the company, so that more employees become stressed.

Listening for job stress and devising better ways of working is an entrepreneurial task.

The entrepreneurial mindset is to listen to customers (in this case, job incumbents), to identify unmet needs, which are aways based on emotion and can never be articulated perfectly clearly, to creatively design new solutions to the customer’s felt problem, and to institute positive change using the new solution. This implies continuous adaptive change in job descriptions, performance expectations, structures, team and tasks.

The entrepreneurial approach is often hard to apply in the corporation. One reason is that incentives are lined up to favor what Melissa Swift calls “smooth”. Management incentive schemes are often designed to encourage “smooth” — no drastic changes or turns, steady progress. Yet the adaptive entrepreneurial system does not promise smooth, and can’t delver it. Innovation in response to changes in customer preferences or competition can be bumpy. And many organizations suffer from autoimmune disease — the defenses go up as soon as something unknown or unprecedented is encountered.

Good leadership can counter the auto-immune response — but it’s leadership that does less rather than more, relaxing constraints and letting those closest to customers and markets to make any needed adjustments and to respond at the rate of change that the market demands. Business school concepts of leadership have goaded executives into over-managing and over-controlling, and reversing the over-active concept of leadership is one of Melissa Swifts core prescriptions.

The HR Department is a big part of the problem.

The deep history of HR is dark. The function was founded to quell violence between labor and management. HR was to stand in the middle and to keep a lid on a boiling pot, as Melissa picturesquely expressed it. Performance management — mechanically measuring humans’ output in these toxic adversarial environments — was never a warm or supportive concept. As big business became more centralized, HR simply became more empowered and widened its scope. There was never much humanism in HR.

HR departments are not typically thinking about work and how work is changing and how to make it a better experience for people. If they were, they’d be thinking differently about matching talent to jobs, thinking more deeply about how alienating and constraining automation technology can be to those who have to use it. They know they are being monitored and measured and assessed.

Melissa recommends couples therapy for technology and those who work with it — to stop each party from driving the other crazy.

Asynchronous work, deconstructed work, transparent work.

Melissa’s book has 90 strategies for organizational level and team level problem solving actions and adjustments. We discussed three directions for better work.

Asynchronous work: fewer meetings, which provides greater flexibility for workers, it naturally de-intensifies (you don’t have to have the report ready for the regularly scheduled Thursday meeting), and it makes for more relaxed collaboration across time zones. Asynchronous work tends to be better documented and more permanent.

Deconstructed work: start with tasks to be done rather than job descriptions; assemble the optimum combination of humans and technology to get the tasks done; let talent flow to the work, i.e., it doesn’t matter if it is full time employees, part-timers, project specialists or gig workers or agencies or consultants doing the work, so long as the tasks get done by the best-qualified talent.

Transparent work: make all information available to all employees at all times, nothing hidden or out-of-bounds. As a result, employees and teams have all the information they need to do their jobs, with no need for hierarchical or administrative intervention. Accountability and empowerment are enhanced, and new talent may emerge when you don’t hire for information but for skill in using it.

Additional Resources

Work Here Now: Think Like A Human And Build A Powerhouse Workplace by Melissa Swift: Mises.org/E4B_208_Book1

Bullshit Jobs: A Theory by David Graeber: Mises.org/E4B_208_Book2

The True Story Of Capitalism.

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Many people today are skeptical about capitalism. Suspicious of it. In some cases, downright hostile. These people believe – or have been led by others to believe – that capitalism is bad for society overall. They believe that capitalism is extractive – it extracts work and effort from masses of people to produce financial reward for a narrow few, with limited benefit (or maybe a net deficit) left for those who do the work. A particular sliver of the financial elite has some specific techniques for extracting the vast bulk of available value for themselves via special tools such as hedge funds, currency trading, and all kinds of esoteric instruments. They believe the biggest corporations extract wealth for shareholders and executives to self-reward themselves with stock awards, stock options, share buybacks, and dividends. They believe that there is monopolistic control over markets exerted by these large-scale corporations. They believe that first-world countries and corporations take value from less-developed countries via resource extraction, cheap labor, and short-term economic activities that don’t leave behind long-term infrastructure or institutions. They believe the inequality of wealth and income in capitalism is deliberately and malevolently manipulated.

But none of this is the true story of capitalism. There are two good places to start in telling the real story. The first is 19th-century America. After the Civil War, the US was in economic expansion mode. The population was growing, supplemented by immigration, and was economically mobile, moving West, establishing cities, starting businesses, learning how to enjoy new lives. Technology was evolving, bringing new enablements for those new lives, including affordable illumination (from oil refining), rail transportation (from steel making and steam engines), better clothing (from sewing machines and new fabric technologies), better food (from mass manufacturing and mass distribution made possible by factory organization) and more. It was in this environment that great entrepreneurs invented customer capitalism. They identified the unstated, unmet needs of customers – such as affordable light for families at home at night for a better quality of life and extended productivity, safe and nutritious food, soaps for more hygienic washing, better communications – and designed systems of unprecedented scale and complexity that could be implemented to meet those needs. Factories, production lines, precision machines for manufacturing, international supply chains, secure packaging, mass distribution and mass marketing – these were all innovations of the times to serve customers in better and better ways. The energy behind these innovations came from a new invention, unique to America at the time: the corporation and its managerial methods. The entrepreneurs invented the managerial corporation because it was necessary to do so to harness the vast potential for value creation of their machines, factories, supply chains, and transportation and distribution networks. The challenge had never before been encountered, but the coordination enabled by new decentralized corporate management systems solved the problem. 

Customers were learning what they could want in the new world of technology, manufacturing, and economic expansion. Those corporations that were able to fulfill those new wants were the ones to thrive and grow into powerful commercial entities of a new type, size, and form. They became the engines of capitalism, doing far more to advance the capacity and achievements of the new country than anything than government could. 

At the same time, in the heart of Europe, a group of researchers in economics were discovering the principles that would guide the further development of customer capitalism as a system of organizing the economy. First, they established the principle of value that guides all economic production: value is in the mind of the customer. It’s not a number or a price, it’s a flow of life enjoyment, a flow of experiences becoming better and better over time, satisfying ever more needs and fulfilling ever more wants. The job of the corporation is to facilitate and sustain this flow.

The method of doing so, identifying value (what the customer is learning to want), and designing new and innovative ways to enable them to enjoy the future experience they are anticipating via a method called entrepreneurship, was another discovery of these economists. Another of their principles, a crucial one, is that entrepreneurial value generation is an adaptive, experimental and creative activity, and can’t be planned in advance or from the top down. This excludes government, as a central planning agency, from any role in customer capitalism, and also guides the private corporation in the design of their organization and processes to make them adaptive to feedback from customers and markets. Those that become bureaucratic and unresponsive are condemned to fading and failure. Continuous innovation is the only route to sustained success.

The early research came from the University of Vienna and has inherited the name Austrian economics over time. But the research tradition has continued in the US after many of the pioneers fled Europe to do their work in universities in the US. The continued further development of Austrian economics in the USA nurtures and enhances the innovative free market traditions of customer capitalism.

These two parallel streams of corporate commercialism in the US, harnessing technology and organization to profitably serve customer needs, and the continuous refinement of free market economic principles and institutions to make that commercialism viable, combine in the true story of capitalism. Capitalism is for the benefit of all: first and foremost for consumers, whom corporations and other producers are aiming to serve and please. The economic activity of doing so creates jobs and meaningful employment for many. Corporations aim to gain the support of the communities in which they establish offices and factories, improving community life, especially for the families that live and work and school their children there. And for investors, the success of corporations in serving customers can result in the profits that pay dividends and spark stock appreciation. And the system requires the institutional support of a prevailing set of economic thinking to strengthen the culture and mindset that attracts the best people to roles as entrepreneurs, managers, investors and workers.

Customer-focused corporations and the economics of entrepreneurial value creation are the true story of capitalism.

No businesses are “small”. They’re all productive nodes in a tightly connected knowledge-building value-creating network.

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There are roughly 32 million businesses in the US, of which 99.9% are what the government calls “small”. This classification of business accounts for about half of GDP and of total employment (making it just as productive as “big business”), and usually more than half of new job creation (making it more dynamic than big business). It’s often where innovation first enters the market, since small business is more open to risk taking than big business. If we remove the Fortune 500 and the Russell 5000, we’ve still got 32 million, rounded up, so let’s think of them as a community.

Within the 32 million, there is a wide range of size, whether measured by revenue or number of employees. The government in the form of the SBA (Small Business Administration) uses a range of up to 500 employees and a revenue of $7 million per year. But they also relax this range in different classification categories; their “small” financial and insurance business range goes up to 1,500 employees and $38.5 million in revenues. Clearly, there’s no consistency or integrity in their definitions, and not much useful information.

A better way to look at these businesses is as an integrated network of productivity, information flow, knowledge-building, innovation and value creation. 

Productivity:

Dr. Samuel Gregg in his book The Next American Economy identifies the decline in the formation of new entrepreneurial businesses as responsible for the significant decline in American productivity. These businesses have an intensified motivation to be productive; it’s hard to get capital, so they need to make the most of what they’ve got and find agile ways to borrow, rent or originate capital. They can’t afford productivity-sapping bureaucracy. They find ways to accelerate cash flows. They adopt new technological innovations quickly so as to take advantage of productivity enhancements. Productivity is essential for them.

Knowledge-building:

Bartley J. Madden in his book Value Creation Principles, identifies knowledge-building proficiency as the fundamental driver of firm performance. In the integrated 32-million strong network of businesses we are analyzing, information flows faster and more freely as a result of more network nodes, more connections between nodes, and lack of barriers to learning such as bureaucracy. These businesses know they must learn at speed, apply their learning fast and use it to serve customers better. There’s no learning time to lose.

Dynamic Efficiency:

Efficiency is an economic concept that hasn’t been very helpful for business in general. It tends to mean doing less with less: cutting costs, saving on inputs, not risking innovation, not attempting experiments with uncertain outcomes. But economist Jesus Huerta de Soto developed the contrasting concept of dynamic efficiency: fast adaptation to changing customer preferences, and rapid creation and adoption of new market knowledge, with an economy of time and agile decision-making.  This is the entrepreneurial method, and the way that the 32 million competes effectively with larger, better resourced but less agile firms.

Pure value creation:

Businesses generate cash flow as a result of the valuable customer experiences they enable. The value that customers perceive turns into willingness to pay, resulting in cash flow that is the life blood of small businesses who have less access to credit and debt to fund their working capital needs. The 32 million are acutely sensitive to cash flow, and therefore to customer value. They remove all obstacles to customer value, including bureaucracy, complicated service arrangements that obscure value visibility and take time, and any other obstructions they can identify. These businesses know that they must pursue pure value creation.

Customer focus:

The disciplines of dynamic efficiency and pure value creation demand an intense customer focus. The 32 million choose their customers carefully, develop a deep knowledge of them and their needs, nurture empathy to get on the same wavelength with customers regarding those needs, and are constantly listening for feedback and adjusting to any new signals that come through the feedback channel. This intensity of customer focus sustains the innovation and elevated quality of service that, in turn, secures continuity and strengthening of business relationships. That’s why these businesses are the backbone of the economy.

Unentangled with government:

The greatest barrier to all business-driven economic growth, progress and innovation is government. Both taxation and regulation are business-killers by intent. Big business becomes entangled with government. They develop big bureaucracies to comply with regulation, keeping them close to government and saddling the 32 million with disproportionate compliance costs if they’re forced to match big-business compliance practices. And big businesses assemble lobbying forces and budgets to design, write and pay for government approval for regulations that protect them and over-burden others. It’s this entanglement with government that condemns big business to permanent inefficiency, and also results in the kind of government-directed surveillance scandals that are currently being uncovered.

The 32 million is in no way small. It’s the vital, leading edge group that brings innovation, growth, development and dynamism to the economy. Let’s find another term than “small business”.