Stefan Michel writes about business strategy, differentiation, and practical ways for small and medium-sized businesses to explore AI. His examples include how a fastener company can compete by solving customers’ operational problems, and how businesses can investigate AI through focused, three-month projects.
Stefan Michel is most useful for B2B strategy thought leadership on differentiation and practical AI exploration.
Best for
A B2B strategy consultancy campaign on differentiation and bounded AI adoption.
Not for
Consumer brand campaigns needing guaranteed reach or a ready-made sponsorship package.
Key takeaways
Bossard shows differentiation can come from inventory and engineering support.
Small and medium businesses can use focused three-month AI exploration projects.
A 1984 Dell earnings statement offers lessons on timing and route to market.
Check first: Confirm partnership formats, requirements, rate card, and audience breakdown before contacting.
Main ideas
No market is commoditized, because the margin sits around the product · When you cannot follow every trend, narrow the scope on purpose · Timing and route to market decide more than the product
Stefan Michel writes about business strategy, differentiation, and practical AI exploration.
Their examples show how companies can compete beyond price by solving customers’ wider operational problems, and how smaller businesses can investigate AI through focused, time-limited projects.
They also use historical business examples, including a 1984 Dell earnings statement, to draw lessons about business models and timing.
Michel makes strategic ideas concrete through cases and practical decisions.
In a post about Bossard, a fastener company, they argue that differentiation can come from helping manufacturers with inventory and engineering—not just selling screws on price.
For smaller businesses weighing AI, they propose focused three-month exploration projects, illustrated with four possible areas for a coffee-machine manufacturer.
In a separate post, they examine figures from an early Dell earnings statement to discuss go-to-market strategy and timing.
Stefan Michel writes about where value sits in a business and how leaders can find it deliberately.
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Three positions recur across the posts: no market is truly commoditized, because margin comes from the costs and problems around the product rather than the product itself; when a company cannot track every trend, it should narrow the scope, giving small teams one defined question and a fixed window; and strategy is often a question of timing and go-to-market rather than product features. They tend to argue through specific, checkable material—a named company, a dated report, a line-by-line reading of a financial statement—rather than general opinion.
No market is commoditized, because the margin sits around the product
Michel's central argument is that a commodity market is a choice rather than a condition.
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Products that look interchangeable—water, gasoline, salt, screws—still support premium pricing and healthy margins.
The difference is what the seller wraps around the product.
In the fastener case, they argue that competing on unit price is the wrong battlefield; the real opportunity lies in operational costs buyers cannot easily see or manage themselves, such as inventory and engineering support.
Michel contrasts Evian with free tap water, Shell V-Power with chemically near-identical gasoline, and Maldon sea salt with interchangeable NaCl.
The load-bearing example is Bossard Group, a Swiss industrial fastener supplier.
They write that they spent 12 years on Bossard's board, and describe the company earning double-digit EBIT margins in screws by selling inventory management and engineering support instead of competing on unit price.
The post says this addresses 85% of hidden operational costs for manufacturers.
The claim is anchored to events a reader can check: Bossard's half-year report on July 22 and a 13% share price rise within five days.
When you cannot follow every trend, narrow the scope on purpose
Michel's answer to small and medium-sized businesses asking how to keep up with AI is to stop trying to follow all of it.
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Instead, build dedicated teams of explorers, each with one clearly defined focus area and a three-month window to investigate how AI could reshape that part of the business.
The narrow scope keeps the analysis deep and the workload manageable, rather than spreading limited resources across the whole landscape.
The cycle ends with a decision, not a report: teams reconvene, the organization chooses which use cases to pursue and defines the focus areas for the next round.
A coffee machine manufacturer runs four teams in parallel: the future of coffee consumption, covering personalization, predicting preferences and automating brewing; smart manufacturing and predictive maintenance, covering production optimization and anticipating equipment failures; AI-powered customer service and marketing, covering chatbots, recommendations, targeted campaigns and sentiment analysis; and supply chain and logistics, covering demand forecasting, inventory and resilience.
Timing and route to market decide more than the product
Michel reads company history as a basis for understanding business-model choices.
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In the Dell case, they argue that a new direct-to-consumer route to market made the business profitable almost immediately by cutting out several players in the value chain.
Timing carries equal weight in their reading: 1984 was the right moment because demand for personal computers was surging and buyers already knew enough about specifications to order from a catalogue or online.
They also draw a broader point: a single decision can change the course of a life, a lesson taught through a primary document rather than a success-story summary.
Michel walks through the statement of earnings for Dell Computer Corporation, doing business as P.C.'s Ltd., for the three months ending July 31, 1984, when Michael Dell was 19 and running the company from a dormitory room at the University of Texas at Austin before incorporating and dropping out.
Gross sales were $905,070.55 and total revenue $888,821.21.
Cost of sales was $690,453.83, or 79% of revenue, leaving gross profit of $198,367.38 at a 22% margin.
Operating expenses were $63,604.63, or 7% of revenue.
The largest lines were advertising and promotion at $24,203.84 and salaries at $16,130.40 for office staff and $5,500 for officers.
Earnings from operations came to $134,762.75, a 15% operating margin.
Answers the question a strategist asks first: Can a company in a price-driven market stop competing on unit price?
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Start here for the clearest statement of Michel's central argument, built from a claim through examples to a named company with numbers.
Michel rejects the premise that any market is fully commoditized, then stacks four short examples: Evian against free tap water, Shell V-Power against ordinary gasoline, Maldon sea salt against interchangeable NaCl, and industrial fasteners.
The fastener case carries the argument.
Michel writes that they spent 12 years on Bossard's board and describes how the Swiss company earns double-digit EBIT margins by selling inventory management and engineering support instead of screws.
The post says these services address the 85% of hidden operational costs beneath the surface for manufacturers.
It ties the claim to a dated event: Bossard's half-year report on July 22, followed by a 13% share price rise within five days.
The post points readers to a longer newsletter article.
For brands planning a campaign
A consulting firm building thought leadership on differentiation could co-author an article with this structure: a contrarian opening claim, four quick examples readers can check in seconds, one deep case with a financial proof point, and a link to a longer treatment. The argument also offers a ready counter to the objection that every category is a commodity—the belief the article must overturn before it can sell anything.
Answers how a smaller company should approach AI when it cannot track every trend.
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Start here for a method, not just an opinion: it offers a team structure, a time box, and a worked example readers can adapt to their own businesses this quarter.
The post opens with a problem: small and medium-sized businesses lack the resources to follow every AI trend.
Its answer is direct: stop following everything at once.
Instead, build teams of explorers, each given a three-month window, one clearly defined focus area, and a single objective: investigate how AI could reshape that part of the business.
Michel argues that the narrow scope keeps analysis deep and workloads manageable.
A coffee machine manufacturer serves as the worked example, with four teams running in parallel: the future of coffee consumption, covering personalization, preference prediction, and automating the brewing process; smart manufacturing and predictive maintenance; AI-powered customer service and marketing, covering chatbots, recommendations, targeted campaigns, and sentiment analysis; and supply chain and logistics, covering demand forecasting, inventory, and resilience.
After three months, the teams reconvene, the organization decides which use cases to pursue, and it defines focus areas for the next cycle.
For brands planning a campaign
This offers a ready-made workshop or webinar structure: four focus areas, a three-month cycle, and a decision point when teams reconvene. Swap the coffee machine example for a client's industry, keeping the four-area split, to give a consulting firm a concrete agenda instead of a general AI talk—and a natural follow-on engagement at the end of each cycle.
Answers what made a new go-to-market model profitable in its first quarter, and how much came down to timing.
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Start here to see how Michel reads a primary business document line by line rather than summarizing a success story.
Michel presents the statement of earnings for Dell Computer Corporation, doing business as P.C.'s Ltd., for the three months ending July 31, 1984, when Michael Dell was 19 and running the company from a dormitory room at the University of Texas at Austin, before incorporating and dropping out.
They walk through the numbers: gross sales of $905,070.55, returns and allowances of ($16,249.34), total revenue of $888,821.21, cost of sales of $690,453.83 at 79% of revenue, gross profit of $198,367.38 at a 22% margin, operating expenses of $63,604.63 at 7% of revenue, and earnings from operations of $134,762.75, a 15% operating margin.
The largest expense lines are advertising and promotion at $24,203.84, salaries of $16,130.40 for office staff, and $5,500 for officers.
Michel draws three lessons from the document: the direct-to-consumer model cut out several players in the value chain and was profitable almost immediately; 1984 was the right moment because PC demand was surging and buyers knew enough about specifications to order from a catalogue or online; and a single decision can change a life's trajectory.
For brands planning a campaign
Useful for a firm whose audience includes founders and scale-ups.
The pattern—a primary document plus a handful of takeaways—offers a template for evidence-led content that does not depend on opinion.
The timing argument also provides a way to discuss market windows rather than product features, making a harder claim that is easier to remember.
Differentiation through the problem around the product
Michel argues that businesses can escape price-only competition by addressing costs and operational problems customers may overlook.
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In a post about industrial fasteners, they point to inventory management and engineering support as ways Bossard competes beyond the price of a screw, contrasting this with premium consumer products such as Evian and Maldon salt.
Uses familiar comparisons to explain a less obvious B2B case.
For brands planning a campaign
A strategy or B2B consulting brand could develop a co-authored article on finding hidden customer costs and reframing what a business sells. The fastener example gives the idea a concrete industrial application; verify the business figures and case details before using them in campaign materials.
Strategy taught through company history and financial detail
Michel uses an early Dell financial statement to connect the company’s direct-to-consumer model with its go-to-market strategy.
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They highlight quarterly revenue, costs and operating profit, then draw lessons about distribution, market timing and consequential business choices.
Moves from a document and specific numbers to broader strategic takeaways.
For brands planning a campaign
Suitable for executive education or strategy content that teaches through a historical business case. A brand could pair a primary-source document with a short explanation of the business-model lesson; verify historical figures and context before publication.
Practical, bounded exploration of AI for smaller businesses
Michel recommends that small and medium-sized businesses avoid trying to track every AI development.
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Instead, they propose focused teams with a three-month window and one defined business area to investigate. The coffee-machine manufacturer example breaks exploration into customer preferences, manufacturing, customer service and marketing, and supply chain.
Turns a broad trend into a time-bounded process with defined workstreams and a decision point.
For brands planning a campaign
A business technology or consulting brand could create a practical AI exploration exercise or article around focused discovery cycles. If making claims about results, ask for evidence from a completed implementation.
Stefan Michel writes about where value sits in a business and how leaders can find it deliberately.
Read more
Three threads run through the posts: no market is truly commoditized, because margin comes from the costs and problems around a product rather than the product itself; when a company cannot track every trend, it should narrow its scope, giving small teams one defined question and a fixed window; and strategy often comes down to timing and go-to-market rather than product features.
They make their case with specific, checkable material—a named company, a dated report, or a line-by-line reading of a financial statement—rather than general opinion.
Start with the post on Bossard Group and industrial fasteners for the differentiation argument, then read the post on three-month AI exploration teams for a practical method aimed at smaller businesses and the post on Michael Dell's 1984 earnings statement for how they connect business-model choices to financial detail.
For adjacent perspectives, see David Heinemeier Hansson on bootstrapped software businesses, Alfred White on tax and compliance for small businesses, and Todd Gardner on SaaS financial reporting.
StrategyDifferentiationCommodity marketsBusiness model innovationAI adoptionGo-to-market strategySmall and medium-sized businessesB2B leadersCase study analysisFinancial statement reading
Both argue that business-model choices matter more than following the default path.
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Heinemeier Hansson makes the case that small teams can build profitable companies without investors, while Michel shows how a fastener supplier escapes price competition by selling services around its product. Both write as operators or board members, using a specific company as evidence.
Heinemeier Hansson's posts center on software and media entrepreneurship, open-source ecosystems, and a founder's take on industry culture. Michel focuses more on industrial B2B cases and financial documents, shaping them into structured strategy lessons rather than founder commentary.
Both address owners of small and medium-sized businesses with practical, decision-oriented advice.
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White walks readers through tax compliance and audit-risk areas, while Michel gives small businesses a defined way to explore AI. Both teach by naming specific risks or actionable steps.
White focuses on tax, bookkeeping, and IRS compliance, often using a story or a numbered list of risk areas. Michel ranges across strategy, differentiation, and market structure, supporting their points with company cases and financial statements.
Both analyze business decisions through financial and structural evidence.
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Gardner reviews SaaS financial statements and flags reporting weaknesses, while Michel reads an early Dell earnings statement and Bossard's margins to show how strategy appears in the numbers. Both use numbered points and concrete criteria.
Gardner writes for SaaS operators and investors, with red-flag checklists and accounting details such as gross margin, bank reconciliations, and MRR. Michel addresses business leaders more broadly, using historical or industrial cases to make a strategy argument.
Stefan Michel’s LinkedIn posts address business strategy, differentiation and practical AI exploration for small and medium-sized businesses.
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They may suit a thought-leadership campaign aimed at turning commodity offerings into higher-value services. Before planning, request recent audience results relevant to that campaign and survey data or another documented source on followers’ industry, role, seniority and geography.
The posts contain no sponsored-content disclosure, rate card, audience specification, or partnership intake link.
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One directs readers to a newsletter article and an IMD program page; another tags Bossard colleagues and industry names and describes twelve years on Bossard's board, a governance role rather than a paid engagement. Ask for partnership formats, requirements, and an inquiry route.
Good fit: a B2B strategy consultancy seeking thought leadership on differentiation and AI adoption.
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Michel’s post on Bossard argues that manufacturers can compete on more than unit price by addressing costs such as inventory management and engineering support.
That gives a co-authored article a specific strategic argument and a concrete industrial case.
In a separate post, they propose three-month AI exploration cycles, with focused teams investigating defined business areas before deciding which uses to pursue.
Together, these examples support a campaign connecting differentiation with practical, bounded AI exploration.
Confirm partnership availability and terms before planning production.
The posts don’t state the account’s professional audience composition, so request relevant audience information before committing to a distribution goal.
Poor fit: a consumer brand seeking a documented sponsored-post package with guaranteed reach among a specified demographic.
The posts provide no sponsorship formats, rate card, intake link, audience breakdown, or reach guarantees.
They cover strategy and business technology, not consumer promotion.
Don’t treat company tags or their description of a board role as proof of a paid partnership.
When to choose a specialist
A campaign that depends on a verified audience segment, guaranteed impressions, or a ready-made sponsorship package is a poor fit based on the available posts.
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They provide no audience breakdown, reach guarantee, rate card, or partnership intake route. If those details are essential, request them directly and assess them before proceeding; otherwise, choose a creator who provides audience and commercial information.
A worked campaign example
Campaign angle: “From commodity product to valuable operating solution: where AI can reveal the next source of differentiation.”
Co-author an article for B2B leaders, opening with Michel’s Bossard example: the post says the company competes through inventory management and engineering support rather than on screw price alone.
Then show how a manufacturer could use a focused three-month AI exploration cycle to examine an adjacent source of customer value.
For example, a team could investigate whether demand forecasting or predictive maintenance addresses a costly customer problem; at the end of the cycle, leaders decide whether to pursue the use case and set the next focus area.
This angle draws on the two approaches Michel presents without claiming that the AI process has already delivered measured results.
Before publication, verify the Bossard figures and case details, agree on the consultancy’s role and claims, and confirm Michel’s availability and campaign terms.
Choose David Heinemeier Hansson when the co-authored article should speak to founder-led software and independent businesses rather than manufacturers.
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Both posts argue that small teams can outperform larger ones when they accept constraints, that bootstrapping lets a business avoid the investor race, and that founder leadership keeps a company technically sharp.
The Shopify post builds that case around a $6.2 billion Black Friday and the framework contributions the company funds.
For a thought-leadership piece aimed at technical founders weighing outside capital against self-funding, these posts give the argument a tested, specific shape.
The demonstrated subject is bootstrapped software, open-source stewardship, and the economics of venture-backed versus independent companies.
There’s no differentiation framework or AI adoption method, so the consultancy would need to supply one.
That shifts the campaign toward founder-engineering audiences rather than B2B strategy leaders, and away from Stefan Michel’s industrial fastener example of selling an operating solution instead of a commodity unit.
Choose Alfred White when a campaign for small-business owners should reframe differentiation as risk reduction.
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The posts teach tax topics in a plain client-education voice: one uses a Willy Wonka story to argue that experts must walk clients through a process; the other lists five audit risk areas and ends with a concrete next step. The AI-and-differentiation theme would give way to compliance, documentation, and expense-discipline content, delivered as checklists and starting plans readers can act on immediately.
The posts focus on tax topics for owners handling their own taxes, not product differentiation, premium positioning, or AI adoption for B2B strategy teams.
That shifts the article from market strategy to tax exposure and changes the claim the consultancy can credibly co-author.
Ask for a comparable example of turning a commodity into a premium industrial solution, such as Stefan Michel’s case.
Choose Todd Gardner when a campaign about AI should target SaaS finance leaders, CFOs, and investors rather than manufacturers.
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One post catalogues red flags from reviewing over a thousand SaaS financial statements, including gross-margin definition, bank reconciliation failures, mixed cash and accrual accounting, and MRR that does not tie to the income statement.
The other asks whether AI resembles open source in its effect on application software and argues that service, implementation, and accountability still carry weight.
Together, the posts support a co-authored argument about how AI changes software economics and what diligence teams will demand.
The material is diagnostic and focused on finance functions.
It does not cover differentiation strategy, premium positioning, or a head-to-head method for turning a commodity into a valued solution.
A B2B strategy consultancy would be writing for a finance and SaaS audience on unit economics and controls, rather than using the industrial campaign angle in Stefan Michel’s Bossard example.
Ask for a comparable method for making a commodity more valuable.
This profile draws on the text of three posts published from Stefan Michel's LinkedIn account.
One argues that commodity markets can be escaped, using Bossard Group, an industrial fastener supplier, as the main case and citing its July 22 half-year report.
One proposes that small and medium-sized businesses run dedicated three-month AI exploration teams, each with a single defined focus area, illustrated by a coffee-machine manufacturer.
One reads the earnings statement of Dell Computer Corporation for the three months ending July 31, 1984, and draws lessons about direct-to-consumer go-to-market and timing.
Six posts from three other creators were read only to judge how Michel's work compares with adjacent writers: David Heinemeier Hansson on bootstrapped software businesses, Alfred White on tax and compliance for small businesses, and Todd Gardner on SaaS financial reporting.
Those posts support similarity and difference judgments, not claims about Michel.
The posts carry no publication dates, so the profile does not assign dates to them or claim they represent Michel's most recent work.
A longer newsletter article linked from the Bossard post was not available, and the posts here do not mention partnership formats, a rate card, an audience breakdown, or an inquiry route.
Those remain unknown.
Statements about Michel's board role and about company figures are reported as the posts state them, without independent verification of credentials, margins, or share-price movements.
