Why Founders Default to Adding More

Picture a founder eighteen months in. Revenue is growing, just not as fast as the deck promised, and the next board meeting is three weeks away. In the planning session, ideas arrive quickly. One person wants a second product line. Another wants a new sales channel. A third says the real problem is headcount. By the end of the hour the whiteboard is full, and nobody has suggested taking anything off it.

Nothing about this scene is unusual, and it is not a failure of character. In 2021, a team of University of Virginia researchers including Gabrielle Adams published eight experiments in Nature showing that people systematically default to searching for additive changes and overlook subtractive ones. Participants were less likely to identify advantageous subtractive changes when the task did not cue them to consider subtraction, when they had only one opportunity to recognize the limits of an additive approach, and when they were under higher cognitive load.

The pattern looks like one of attention rather than inability. According to the researchers, additive ideas come to mind quickly, while subtractive ideas demand more cognitive effort, and the more often people lean on additive strategies, the more accessible those strategies become.

Now look at the conditions inside a growing company. Founders work under constant cognitive load, make big decisions with one shot in front of a board, and operate in an environment that rewards visible momentum. A new product launch looks like progress. A discontinued one can look like retreat. This is an inference rather than something the study tested, since the experiments involved problem-solving tasks and not startups, but it is hard to design a better habitat for the addition reflex.

The argument that follows is narrower than the title suggests. Subtraction is not a growth formula. Additions can be exactly right when they relieve a bottleneck, serve a proven market or capture economies of scale. The claim is that subtraction is a neglected option in any startup scaling strategy, and that the better question is not whether to add or subtract, but whether the next commitment creates more value than the capacity it consumes.

The Hidden Cost of Premature Scaling

Many additions carry two costs. The visible one appears in the budget: salaries, development costs, advertising spend. The hidden one appears elsewhere, in coordination, attention and the decisions the new commitment forces on everyone around it. The mechanism is simple. Growth creates commitments, commitments create coordination and operating costs, and those costs can rise faster than the value they create.

One well-known illustration concerns people. In The Mythical Man-Month, published in 1975, Fred Brooks argued that adding manpower to a late software project makes it later. Part of the reason is arithmetic. If every pair of people on a team might need to communicate, the number of possible links is n(n - 1)/2. A five-person team has 10 potential links.

A fifteen-person team has 105. Real organizations soften this through clear ownership and team boundaries, and engineering researchers have noted that the effects of Brooks's rule can be mitigated, for example by adding people early rather than late. It is best read as an illustration of one source of organizational complexity, not as a law of business scaling.

Products, customer segments and sales channels are not teams, and nothing here suggests their costs follow the same arithmetic. They do share the mechanism, though. Each one fragments attention, adds support and maintenance burden, duplicates some work and creates new decisions about pricing, messaging and roadmap priority.

The best-known startup data on this problem comes from the Startup Genome project, which analyzed roughly 3,200 high-growth technology startups in 2011. It defined healthy growth as keeping the five core dimensions of a startup in balance: customer, product, team, business model and financials. About 70 percent of the startups in the dataset had scaled prematurely along at least one dimension.

Those that scaled prematurely carried teams about three times larger than consistent startups at the same stage, and 93 percent of them never passed $100,000 in monthly revenue. Startups that scaled properly grew about 20 times faster. These figures describe an association in a dated, tech-only sample, not proof that adding resources caused the poor outcomes, and premature scaling covers more than headcount. The findings do highlight the risks of expanding ahead of validated demand. They do not show that every form of early expansion is harmful.

That points to a sharper test of scaling. Growth is getting bigger. Scaling is getting bigger without letting operating complexity outrun revenue. Imagine a business whose revenue rises by a third while its product lines, hires and commitments double. It is growing, but its complexity is growing faster than its income. It is accumulating weight.

Subtraction Strategy in Practice: Apple, Shopify and 37signals

Three well-documented cases show subtraction doing three different jobs, and the differences matter. Apple shows portfolio simplification during a turnaround. Shopify shows the removal of organizational friction. 37signals shows strategic focus held over many years.

Start with Apple in 1997. When Steve Jobs returned, the company was selling a sprawl of overlapping Macintosh models. He told TIME that the company had reviewed its road map of new products and axed more than 70 percent of the projects. According to an Entrepreneur summary of Walter Isaacson's biography, Jobs asked his managers which products he should tell his friends to buy, got no simple answer, and narrowed the range to four: a desktop and a portable for consumers, and the same pair for professionals. Apple had lost $1.04 billion in the fiscal year ending September 1997.

The cost was real. The same account says the cutbacks came, in part, with a workforce reduction of about 3,000 employees. The outcome is also more nuanced than the legend. In fiscal 1998 Apple reported net earnings of $309 million, its first profitable year since 1995, with inventory down to six days, but revenue fell to $5.94 billion, a drop of about 16 percent. The company also exited unprofitable businesses such as printers and the Newton handheld, and it shipped 278,000 iMacs in the new computer's first six weeks.

Simplification was one part of a broader turnaround that also included the iMac, operational changes and a $150 million investment from Microsoft. The evidence does not show that subtraction alone caused the recovery. It shows that cutting cleared the room for the rest.

Shopify's example is smaller in scale and different in kind, because what it removed was friction. In January 2023 the company purged recurring meetings involving more than two people from employee calendars and banned meetings on Wednesdays, removing about 10,000 events, or more than 76,500 hours of meetings, according to a company spokesperson. That figure measures meeting time taken off calendars, not verified productive work recovered or money saved. Context matters too.

The purge came months after Shopify cut roughly 10 percent of its workforce in July 2022, once pandemic-era demand cooled. It reads best as a correction of accumulated drag, and a reminder that organizational drag can build quietly when processes are never reviewed.

37signals shows focus as a long game. According to a May 2014 profile in Built In, once Basecamp began out-earning the company's web design business, the founders quit client work and focused on software. After a 2012 redesign of Basecamp became a hit, they stopped building other products to concentrate on it. Co-founder Jason Fried said the fundamental reason was that they wanted to remain a small company, and that maintaining several platform versions of several products would have forced them to hire.

At the time of the profile the company had been profitable for 15 years with a staff of 30 to 40 people. Those figures are a decade old. The case also reflects a business model and a set of founder preferences. It does not show that a small team or narrow portfolio is right for every company, least of all one built for rapid, venture-funded expansion.

Clutter vs. Capability: How to Decide What to Cut

None of this makes subtraction a formula. The cuts that worked are the ones we study, while companies that cut the wrong things rarely become case studies. Survivorship bias flatters the story, and a founder who removes the wrong thing can do real damage.

The best large-scale evidence on the risk comes from a Harvard Business Review study of 4,700 public companies across the recessions of 1980, 1990 and 2000. The authors sorted companies by how they shifted resources during the downturn, and defined breakaway performance as beating rivals by at least 10 percent on both sales and profit growth afterwards. Prevention-focused companies, which made mainly defensive moves and cut more than their competitors, had the lowest odds of breaking away, at 21 percent, and grew sales 6 percent and profits 4 percent on average, against 13 percent and 12 percent for the progressive group.

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Progressive companies, which had a 37 percent chance, cut selectively, mostly by improving operational efficiency rather than reducing headcount, while still spending more than rivals on marketing, R&D and assets. Companies that relied solely on workforce cuts had only an 11 percent chance of breaking away. The study concerns recessions and classifies companies by resource allocation, so it works as an analogy rather than direct proof about startup scaling. The lesson still transfers: indiscriminate cutting is not focus. It is panic.

The distinction that matters is between clutter and capability. Clutter is what a new hire would struggle to explain: the product two customers use, the weekly meeting no one remembers starting, the channel that produced one lead last quarter. Capability is what the core customer would notice missing: support quality, reliability, the engineering that makes the product work. Cutting clutter frees capacity. Cutting capability spends it.

Telling them apart takes more than instinct, and five questions help. The first is economic contribution: what revenue, gross margin, retention or other measurable value does the activity produce relative to its fully loaded cost, including the management time it absorbs? The second is customer consequence: if it disappeared tomorrow, which customers would notice, and would they leave, pay less or simply complain? The third is strategic fit: does it strengthen the company's core advantage, support a capability the business needs, or serve a credible future opportunity?

The fourth is complexity cost: how much coordination, support, maintenance and attention does it consume, and who pays for that? The fifth is reversibility: can the company pause, consolidate or trial the removal before making it permanent, and what would be expensive or impossible to rebuild?

These are not a scorecard to be tallied mechanically. A cut deserves serious consideration when an activity absorbs meaningful resources, delivers little demonstrated value and does not protect a capability the company will need. Where the evidence is uncertain, a reversible experiment, such as pausing a channel for a quarter, is usually more defensible than an irreversible cut.

People belong in this analysis too. Apple's job losses are a reminder that subtraction has human costs, and that how a company cuts shapes whether the people who remain trust the direction. A clearly explained, carefully sequenced cut is different from one announced without warning.

The Investor Lens: How to Read Startup Focus

For investors, subtraction poses a reading problem. A portfolio company that drops a product line can look like a company in retreat, while one that announces three new initiatives can look like a company in motion. The Startup Genome research suggests the second signal deserves more scrutiny than it usually gets. It also lists raising too much money as one way to scale prematurely, because excess capital can leave other parts of the business room to run ahead of the customer. Capital is not neutral. It can fund discipline, or it can fund the addition reflex.

The more useful questions concern the pattern behind a cut. What was removed, and how quickly? What was explicitly protected? Does the founder tie the decision to unit economics, retention, customer concentration or capacity, or to a mood? A founder's explanation is a starting point, not proof, so the sensible follow-up is to ask for the numbers behind it. For founders, the framing matters as much as the cut. Subtraction presented as a strategy, with a thesis and a measurable target, reads as confidence. Presented as damage control, it reads as failure, even when the underlying decision is identical.

The Question Every Founder Should Ask Before Scaling

The Nature researchers found that subtractive ideas surface more often when people are explicitly cued to consider subtraction. That may be the most practical finding for anyone running a company. The reflex to add will not go away, but it can be interrupted by a better question.

So here is one worth sitting with before the next planning session. Somewhere in your business there is a product, a customer segment, a channel, a ritual or a role that persists mostly because it has always been there. Measured against its full cost in money and attention, does it still earn its place, and what would the business do with the capacity it returns?

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