Syllabi at management schools and senior management at perhaps many businesses don’t fully appreciate how information businesses work.

I was chatting with a successful Silicon Valley venture capitalist last week about how we may have under-invested in understanding the impact of technology on our economy. The VC suggested, “macroeconomic modeling generally treats technology as an external parameter like Total Factor Productivity, rather than as an endogenously determined, explicitly engineered system. As a result, conventional models struggle to address the most critical structural issues facing the U.S. and global economy. They neither integrate short-run dynamics with long-run growth considerations nor capture how digital technologies — AI, 5G, robotics, 3D printing, zero-cost digital services — are developed, diffused, and shaped by policy and market forces. This limitation leaves unexplored how these technologies affect productivity, output, time use, education, skill requirements, and well-being.”

The VC sounds more professorial than me but I am not a macro-economist and hence say much about the above statement. However, I suspect the same sentiment applies at the micro level to technology companies or information businesses, more broadly. I suspect that we have not updated our syllabi and course offerings at management schools as much as we should have, after the U.S. lost its crown as a manufacturing powerhouse. I compared the list of course offerings in say 1998 when I started teaching with what is offered today by top business schools. I found a few changes but nothing radical seems to have been restructured. So, what was taught in 1998 and to a great extent today? I conjecture we mostly teach management insights, as practiced in the manufacturing era.

There was a fair degree of excitement about management theories as applied to manufacturing processes back in the day. I am thinking of Fredrick Taylor’s scientific management theories, the Hawthorne experiments, the Japanese ideas of Total Quality Management, lean manufacturing, and GE’s six sigma mindset. None of these ideas, perhaps formulated explicitly for the manufacturing age, fully apply or explain how information companies operate.

Taylor’s Scientific Management Theory

Frederick Taylor is widely recognized for “time and motion” studies conducted in the 1880s where he observed the specific steps a worker takes to lay bricks and the time it takes to go through these steps. The idea is to optimize the number of steps and time taken to accomplish the task. More broadly, Taylor is known for two big ideas: (i) scientific management, based on evidence and observation, as opposed to gut feel and rules of thumb; and (ii) the conflict between management and labor is somewhat unnecessary as both parties would benefit with better productivity which would manifest as higher wages and higher profits.

Taylor emphasized standardized tools and procedures. He wanted managers to set specified goals and assign tasks to workers to motivate workers to perform better. He argued that workers should be paid a bonus of 30% to 100% of wages for learning to do the job as per the principles of scientific management. Taylor also advocated individual work and productivity and was somewhat skeptical of group work. Taylor suggested choosing the worker with the right aptitude as such a worker would be far more productive than the average worker. He also pushed for rest pauses and shorter working hours, especially if the task is hard. Taylorism is perhaps the precursor to a lot of what is taught in operations research, human relations and cost accounting courses in B schools.

I suspect Amazon relied on time and motion studies to understand how to optimize packing boxes in their distribution centers. The idea of choosing the right worker with aptitude for the job is an established tenet in HR (Human Relations) groups all over the world.

Hawthorne Studies

The Hawthorne studies are credited with recognizing the influence of human relations or social factors in motivating workers. The Hawthorne researchers found the workers’ response to a managerial intervention is a function of the attitudes the workers bring to their job, the informal work group they belong to, their personal history and their social situation at work. Worker culture in big tech companies is widely discussed.

Netflix’s culture deck, which potentially owes its inspiration to the early Hawthorne studies, is legendary in Bay area circles. The deck emphasizes the freedom to excel, deciding which worker is a keeper and paying them a premium over their market wage, the idea that the best workers are 10X better than average, and that teams ought to be highly aligned in their goals but only loosely coupled to stay nimble.

The Japanese TQM movement

The Total Quality Management way of thinking aims to make quality the concern of every member of the firm. Customers are the focus of all activities of the firm and improvements in quality are directed at improving customer satisfaction. Such a focus is expected to lead to better financial performance in two ways : (i) in the manufacturing process, we are expected to encounter fewer defects and rework leading to lower costs and more dependable processes and hence better earnings; and (ii) in the product market, more focus on quality is expected to lead to higher market share, less elastic demand, higher prices and hence higher earnings. The idea of lean manufacturing , a related concept, is to deliver a quality product to the customer at a reasonable cost. Incidentally, Trevor Harris , my co-author and emeritus professor at Columbia Business School, tells me that Edward Deming , another CBS professor, pioneered the thinking behind TQM and even the Six-Sigma movement.

I don’t know whether Tesla follows TQM and lean manufacturing but I did come across a help wanted ad from Tesla looking for a quality engineer whose job description sounded similar to what a TQM engineer would do.

GE’s Six Sigma Mindset

In a 1997 annual letter Jack Welch sent to GE stockholders, he explains: "Six Sigma project work consists of five basic activities: Defining, Measuring, Analyzing, Improving and then Controlling processes. These projects usually focus on improving our customers’ productivity and reducing their capital outlays, while increasing the quality, speed and efficiency of our operations….The Six Sigma quality initiative, very briefly, means going from approximately 35,000 defects per million operations, which is average for most companies, including GE, to fewer than 4 defects per million in every element in every process that this company engages in every day.”

Welch goes on to explain how Six Sigma works with the “A” leaders in each function of the company: “In finance, for example, “A’s” will be people whose talents include, but transcend, traditional controllership. The bigger role is one of full-fledged participant in driving the business to win in the marketplace — a role far bigger than the dreary and wasteful budget “drills” and bean counting that once defined and limited the job.

In engineering, “A’s” are those who embrace the methodology of Design for Six Sigma. “A” engineers can’t stand the thought of “riding it out” in the lab, but rather relish the rapid pace of technological change and continually re-educate themselves to stay on top of it.

In manufacturing, “A” players will be people who are immersed in Six Sigma technology, who consider inventory an embarrassment, especially with a whiff of deflation in the air — people who understand how to drive asset turns and reduce inventory while at the same time increasing our readiness to serve the customer.

In sales, “A” players will use the enormous customer value that Six Sigma generates to differentiate GE from the competition, to find new accounts, and to refresh and expand the old ones — as contrasted with “C” players whose days are spent visiting “friends” on the “milk-run” circuit of customer calls.”

Amazon reportedly relied on Six Sigma type ideas to reduce the error rate on their package delivery to minuscule levels considering that they processed 5.9 billion packages in 2023.

How Are Information Businesses Different?

As stated, modern information businesses, such as Amazon, Google, Meta, Netflix, and Uber, rely on many of these ideas inspired by manufacturing. But these tech businesses also do not seem to fit the traditional mold of management theories well.

Do Our Syllabi And Course Offerings Reflect Such Thinking?

Financial Accounting

Not quite. Let me start with my home field. Trevor Harris points out that statutory reporting, that is done once a quarter in a rigid regulation bound format, is a relic of a bygone era. Good businesses have a dashboard to track the key KPIs that matter for value creation. Why don’t we ask firms to disclose that dashboard on a more frequent cadence to investors? Of course, there are concerns about proprietary costs and so on, but I have not seen many creative conversations about how to leverage technology and/or better reflect the economics of technology and information businesses in our textbooks and syllabi.

Cost Accounting

I have not seen a good treatment of how cost accounting should think about supply and demand side economies of scale, standards, systems effects and computer mediated transactions. A critic may argue that the basics of cost accounting have not changed. But one must wonder whether the field is stuck around the time manufacturing left the U.S. for Asia.

Have we updated thinking in cost accounting for the bundled information products, why some of Amazon’s divisions are never supposed to make money (free shipping, Kindle) so that they can cross-sell other products in the retail store, how does Amazon price the time of developers working on features and software products or how does a firm value its data or the data acquired in an M&A transaction?

What kind of cost data does an Amazon, or an Uber collect? Do they conduct cost-volume-profit analyses to determine breakeven sales quantity for a product, given the extent of bundling and portfolio type thinking necessary to accomplish this? How does Amazon calculate the lifetime value of a customer? How is common overhead across segments and how did that practice potentially fund Amazon’s internal capital markets such as books leading to video to music to third party selling to AWS? How does one think about budgeting and sales and cost variances for a modern tech business?

Corporate Finance

A related problem in finance has been the persistent puzzle on how to value intangibles. Absence of even modest accounting data to perform such valuations is a big hindrance. Do frameworks such as real options plausibly explain the valuations of a Tesla or an Amazon or an Nvidia ? How does one stress test or falsify these black box valuations?

Have the low-interest rate environments, coincidental with the rise of Big Tech, defaulted us to faith-based valuations? How has corporate finance changed with the rise of information businesses? Is capital less of a constraint than skilled labor?

How does one come up with capital budgeting for information products or bundled systems? How has cash and liquidity management changed? Has big data and AI improved scenario planning and hence enabled better capital allocation? Has granular data made it easier to dissect why some acquisitions succeeded while others failed?

Now, I stray into areas that are not my own and hence rely on observation, as opposed to deep analysis.

Marketing and Operations Research are arguably the two disciplines in a B school that have adapted and embraced the practices of Big Tech firms better than other units. There are tons of classes on digital marketing, social influencers, ad platforms, AI offered by these two groups.

Human Relations: Jensen Huang’ statement illustrates the profound change that HR groups are/will experience in the near future: “In a lot of ways, the IT department of every company is going to be the HR department of AI agents in the future.” That is, the IT departments of the future will train and “onboard” AI agents as though these were employees to ensure that such agents work to enhance human workers’ productivity. Recruiting is already mediated by AI algorithms, for better or for worse. Work from home, enabled by technology, is not going away. This is already creating profound challenges on how to integrate younger workers into a company. Many of these workers were hired on a zoom call and will potentially not get promoted by senior leaders who don’t know them as individuals or human beings.

Ironically, I would suggest that we need to invest more in traditional HR. Do our newer leaders have the training and outlook to look a worker in the eye and say to them in a respectful way that they are being laid off? If they did, we would not come across so many cases of mass layoffs via email or zoom.

What About Management Practices At Non-tech Firms?

Our slowness, in the B school, to adapt and teach management practices of Big Tech or enabled by technology in general, would be less of a concern if these considerations only mattered to a handful of tech giants. But that is certainly not the case. I routinely come across senior managers of companies that are both enthusiastically and reluctantly digitizing without fully understanding the profound change that Varian’s forces will have on their firms.

This is not to say that people have not worked on documenting management practices at Amazon or the other technology firms. I have not seen a book or a manual or a coherent framework that one can hand to future managers of non-digital firms to prepare for a digital/tech leavy/information dense tomorrow.

Constructive comments welcome, as always.