Anyone got any good examples of organisations which have substantially simplified themselves?? Because I think there’s a fascinating popular social science book waiting to written here (similar to e.g., Collapse). But, the missing piece is good case studies or examples. In the meantime, here’s the setup for I mean by complexity, and why I think it’s a real problem that we need to work out how solve, without using wars.

What is complexity and why does it matter?

Bureaucracy, red tape, inertia, gridlock, overhead, “the swamp”: these are all synonyms for what I mean by complexity. It is any process, law, role or similar that may be well intentioned, or even useful, but has the side effect of making it slightly harder to “get things done” in an organisation.

Let’s look at three examples:

1. Governments

Government complexity shows up in endless laws, regulations, and bureaucracies. Each one imposes a burden—on individuals, businesses, and government itself, in compliance costs and in the increasing proportion of society dedicated to complying with laws and regulations, both inside and outside government. Tax codes are a great example, as are means-tested social security systems: for example, in the U.S., where the process of applying for benefits often costs recipients hours of effort for a payout that equates to less than minimum wage.

2. Businesses

In businesses, complexity tends to emerge as a response to failure: something goes wrong, and a new process is introduced to prevent it from happening again. Individually, these processes seem logical—reviews, audits, change management—but over time, they layer on top of each other, slowing innovation with the organisation. This is one reason startups often outcompete large corporations: they aren’t bogged down by decades of accumulated complexity (see also some other thoughts about how startups beat corporates).

3. Social Organisations

Many social organisations—like religious groups or nonprofits—start with a clear, compelling mission. But over time, they acquire buildings, hire staff, and create processes to manage growth. Eventually, sustaining the organisation itself can overshadow the original mission, with internal politics and inertia becoming barriers to action, or even replacing the original mission of the organisation.

How complexity arises and survives

The key to understanding complexity is recognising how it arises—and why it’s so hard to get rid of. At its core, complexity often results from a mismatch between diffuse costs and concentrated benefits.

Diffuse Costs

The costs of complexity—bureaucracy, paperwork, approval processes—are spread thinly across many people. No single person feels the full burden, so there’s little incentive for any individual to push back.

Concentrated Benefits

The benefits of complexity, on the other hand, are often concentrated on specific groups. For example, a new compliance rule might create a department of specialists whose jobs depend on maintaining that rule. Or a subsidy might benefit a particular industry, which then lobbies to keep it in place. Or a specific example of something that went wrong in the past can motivate a “never again” mindset, at almost any cost.

The Result: Unavoidable complexity!

This dynamic creates three big problems:

1. No Natural Constituency for Simplicity: Few people are motivated to fight complexity because its costs are so widely dispersed.

2. Strong Pushback Against Change: Those who benefit from complexity—either directly or by avoiding past problems—resist efforts to simplify.

3. Weak Incentives for Leaders: Simplifying a system often requires expending political or organisational capital, but the benefits are diffuse and realise only in the long term, while the backlash is immediate and concentrated. Simplification seldom, in practice, wins votes.

How we have historically solved excessive complexity?

Complexity can’t grow forever—eventually, the costs outweigh the benefits, and something has to give. But history shows us that reducing complexity is extraordinarily difficult. In fact, the ways we typically “solve” complexity are themselves extreme:

In businesses or social organisations: Overwhelmed by complexity, organisations often stagnate and are replaced by younger, simpler competitors. This cycle of “creative destruction” keeps the private sector relatively nimble.

But governments are not as easily replaced—they persist. The usual solutions to government complexity are much harsher: war or revolution. Wartime often forces governments to streamline decision-making, while revolutions reset the system entirely.

This last observation leads to the key question: How can we create organisations that can reduce their own complexity? And how can we use this in government, so as not to require periodic wars or revolutions? Given that large-scale warfare is a tragedy for those involved, but also with modern weapons, an existential threat to humanity?

What a complexity-resistant organisation look like?

This is where some really great examples and case studies would be helpful!

There are a few approaches that come to mind—though none (yet) compelling:

1. “Balanced Complexity Budget“

Similar to “balanced (fiscal) budget” requirements, governments could adopt a “complexity budget,” requiring that for every new page of law or regulation, an equivalent amount is removed. This would ensure that complexity is constrained (or allowed to grow only in proportion to, say, GDP or population size). Of course, this approach only works on forms of complexity we can measure effectively (pages of regulation), and not elsewhere.

2. Zero-Based Budgeting

In businesses, zero-based budgeting forces organisations to start their planning from scratch each year, rather than simply adding a percentage on to last year’s budget. But, in practice I’ve seldom seen this approach producing a outcome significantly different to standard budgeting.

Emerging case studies?

Two current examples come to mind, though neither is perfect:

1. Argentina

Javier Milei’s government in Argentina has undertaken massive efforts to reduce the size and complexity of the government, with dramatic effects on, for example, inflation, as well huge unhappiness (as expected) from the affected constituencies. It’s too early to tell whether these reforms will succeed, and anyway, they became possible only after years of near-total economic collapse, so hardly represent an easily-replicable approach.

2. Government Efficiency Initiatives

Efforts like the U.S. Department of Governmental Efficiency (under the Trump administration) aim to reduce regulatory complexity. However, I’m not sure there’s the political alignment in the Trump camp to make them succeed, as seen already in disagreement on the direction (more vs less) of immigration regulation and tariffs, as well as the generally rapid turnover amongst those considered Trump’s favourites.

If you can think of any compelling examples of successful complexity reduction, let’s discuss—drop your thoughts in the comments!

Here’s my very simplified version of what happened to bring down SVB: and specifically, why no-one seemed to have seen it coming. Informed very much by Matt Levine’s excellent writing on the topic. Thoughts are purely my own, not representing any organisation.

At core, we need to look at a simplified model of what banks like SVB do, and especially, what then happens when interest rates change. Essentially, banks:

1. Take in deposits, from individuals and businesses. Deposits are generally low-interest, and as interest rates rise, only a little of that is passed on to deposit accounts.
2. Put all that money somewhere! Broadly, there are two options:
   • A. Loan-like instruments (e.g., home loans, business loans). These are often floating-rate, i.e., their interest rates follow market rates, but they are also very “illiquid” (hard to sell or otherwise turn into cash). If a bank makes a home loan for a specific house, it can’t easily get that money back immediately.
   • B. Bond-like instruments, like corporate debt. These are typically fixed interest rate, but they are liquid (easy to sell).

Now, what happens when interest rates go up? Deposits and bonds rates don’t really change much, but loan interest rates rise. This is an “endowment effect” that leads banks, all else being stable, to make more money when interests rise: their “Net Interest Income” (NII) rises as interest rates rise.

Great! Next question, what happens if, for some reason, a lot of depositors want their money back at once? The bank would eventually run out of cash reserves, and need to sell some bonds (as the loans are hard to sell). But here’s a problem: bonds have a fixed interest rate, but their market value decreases when interest rates rise, because new investors would rather buy new bonds offering a higher rate, than your old low-rate bonds. When a bank holds a bond to maturity, that’s not a problem — they get back the full face value of the bond. But, if a bond needs to be sold early, and the interest rates have risen, the seller will take a loss. At worst case, a bank being forced to sell lots of bonds could make a huge loss, which overwhelms its capital reserves, and leaves it insolvent.

Normally, this is irrelevant, as this only happens if a bank has to sell bonds early, i.e., has a massive outflow of deposits, a bank run. There are many mechanisms to prevent this:

• deep relationships between the bank and it’s customers;
• a wide variety of depositors, many of whom don’t really follow the finer points of financial news and so are fairly “sticky”;
• deposit insurance;
• capital buffers, regulatory supervision, risk modelling, etc etc.;
• and hedges. Let’s talk about these.

Clearly, it would conceptually be useful for banks to be able to deploy cash in instruments that have both floating interest rates (and so do not lose market value when interest rates rise), and also highly liquid. You could imagine two ways to do that:

1. Make loans more liquid, by, let’s say, packaging groups of similar loans into standardised instruments (call them “CDOs”), splitting them into tranches by risk, getting ratings agencies to rate them, and then create a liquid market for them. There’s a problem with though: it removes the risk from the loan originators, leading to perverse incentives that lead to bad quality loans, and you get the 2008 financial crisis. So, let’s not do this.
2. Make bonds that don’t lose market value when interest rates rise. This can, broadly, be done by banks through hedging on interest rates. Then, when interest rates rise, the bonds lose market value, but the hedges make money to roughly counteract that effect, and vice-verse. This is a great idea, in general!

So why did SVB not have hedges in place? It seems that they were worried about what happens when interest rates fall: if hedges make money when rates rise, they obviously lose money when rates fall. Combined with the negative endowment effect on loans, this can make falling rates pretty bad for bank profitability. So, it seems that SVB dismantled much of their hedging in 2022, to take profits and to avoid losses if/when rates fell again. And this would have been fine, as long as we didn’t get both a rise in interest rates and a lot of depositors wanting their money back. Of course, that’s then what happened, and clearly the bank’s risk scenario testing was insufficient.

So let’s put this together into what led to SVB’s collapse:

1. An (unrealised, theoretical) mark-to-market loss on bond holdings, due to:
   • lots of bonds relative to loans, at SVB, due to their client base of startups being relatively cash-rich and loan-light
   • insufficient hedging, due to concerns of the impact of hedges on profitability if rates were to fall.
2. An unprecedented drop in deposits, due to:
   • a depositor base suddenly becoming less cash-rich, due to the sudden slowdown in VC funding to startups
   • a depositor base unusually prone to runs, because most of it was in deposits that exceeded the deposit insurance maximums, and came from depositors that were NOT diverse, as most startups (and especially their VC shareholders) were on the same Whatsapp groups
   • modern banking apps making it way easier to move cash out of a bank — no more queueing on the steps of the bank
   • some communication accidents and mistakes that flagged the theoretical massive losses on the bank’s bond holdings at market price.
3. An inability to find extra liquidity to cover the gap:
   • SVB tried to raise further equity, but this failed and just contributed to the communication of the point just above, i.e., accelerated the deposit flight
   • emergency funding from the Fed, backed by bond holdings, would have had to have been done at market prices for bonds, thereby realising the theoretical mark-to-market losses, and leading to insolvency. Catch-22!

So my guess is, we’ll see regulatory changes and/or focus on requiring banks to model the impact of interest rate changes, not only on profitability and cash flow, but also on a bank’s ability to liquidate assets at short notice, without taking prohibitive market price losses.

We seem to have, today, an unparalleled explosion in young, new companies, pioneering new products or ways of doing business, and thereby disrupting seemingly invincible pillars of our economy through explosive growth — commonly called startups. How is this possible?

Photo by Ian Schneider on Unsplash

Startups face a seemingly impossible challenge: they seek to build successful businesses from nothing. To do so, they need products that are so much better than alternatives that customers choose to use the new products, despite the lack of any brand recognition. These products need to be built on a shoe-string budget (at least initially), and quickly, by a team of founders that are working with limited resources, limited structures and few established commercial relationships. How can this ever work? Why don’t bigger companies, with access to all the same new technologies, lots of resources and skilled staff, a brand, and sales and marketing teams, win every time?

The answer often comes down to two things: startups have a completely crazy idea that actually works, and/or they are unreasonably good at something.