Steve Hoy

Product/Market Fit

Steve Hoy — Thu, 23 Nov 2023 00:00:00 +0000

Product/Market Fit has become a truism and mantra in startup circles, with much associated bullshit. Time to simplify.

It was Andy Rachleff, founder of Benchmark Capital, who first put a name to this concept, which was later popularised in 2007 by Marc Andreessen of Andreessen Horowitz, a venture capital firm. The term was coined in order to help understand the reason for startup failures; was it a poor team, or a poor product, or a poor market? Conversely, when a startup succeeds investors want to know why so they can back other companies with similar characteristics. Is there a great team, a fantastic product, a superb market?

The simple concept of Product/Market Fit, which I’ll shorten to PMF, has become commonplace in startup-land. It is now glibly and routinely trotted out by people who work at startups, the VCs who fund them, commentators, and in recent years management theory pundits who, un-content with the simplicity of the concept are complicating things by dividing it into stages and introducing ancillary concepts such as the risible “go-to-market fit”.

PMF just means: are you making sales? That’s it, really.

An established business does not concern itself with talk of PMF; it tests a new product in the market and if it sells, makes more of it and offers it to a wider market. If it doesn’t sell, chalk it up to experience and write off the expense. After all, there are plenty more products in the pipe.

A startup has a different problem, namely survival. It must reach break-even before the ability to raise funds dries up. Instead of conceptualising a startup as a very small established business, with market research, market requirements documents and product specification documents, the whole enterprise is a research project with one aim - deliver a product that people want to buy.

The point in a startups’ life where people want to buy the product is PMF. Before PMF the company is burning money and should only be working on getting to PMF, nothing else. After PMF the startup becomes a scale-up, and should be aggressively selling to anyone and everyone who will buy the product with the aim of reaching break-even. After PMF you have customers for whom your product solves a valuable problem and they will have opinions and feature requests; you need to get your MVP into better shape and regularly turn out high quality product - a very different management challenge.

Face it - a startup is a machine to make revenue, and will exit successfully if the acquirer believes that the machine is an effective system for generating profits from sales. This is obvious and simple. All the talk of making the world a better place or not being evil or whatever other cliché du jour is just bollocks. The task is to make profits.

The way to understand PMF is to break it into its parts: product, market, and fit.

Product#

A product is either an item that does something or a bundle of capabilities, which fulfils a need in the buyer’s mind. The product will have functionalities which deliver benefits.

It is the customer who gets to decide what the benefits are, not the startup. If the product does not deliver those benefits customers will not buy it no matter how impressive it might otherwise be.

Market#

The market is the collection of potential buyers who have needs that are unmet, or poorly met. You might, through advertising, be able to alter the perception of need in the minds of the customers, but they mostly know what they need.

A consumer will buy if the value they assign to having their need fulfilled is greater than the price they must pay. Economists call this the consumer surplus. If consumers do not assign sufficient value to the benefits of the product they will not buy it.

Fit#

‘Fitness’ is a quality, the extent to which a form is shaped right and properly adapted. ‘Fit’ is one of those words with many meanings, such as ‘run’ or ‘set’. For example, a common misunderstanding of the meaning of ‘fit’ is in the phrase “survival of the fittest”. Darwin didn’t mean those physically-fit people who are able to out-compete lesser mortals through strength and endurance. He meant those who are best adapted to their environment, those who fit it better. Such animals have the ability to survive long enough to reproduce, passing along their advantageous mutation, while the animals with lesser ‘fit’ do not survive long enough to reproduce, and so their mutations die out of the species.

In business, the ‘fittest’ company is not the leanest, meanest, most badass company, it is the company with the best products; where ‘best’ here means most profitable. This is not market share, it’s gross margin.

So does the product offered ‘fit’ with the needs of buyers? The answer is very easy - if the company is not making sales, then there is no fit. If the company is making sales then fit exists and it has reached PMF.

Achieving PMF#

Which is more important, product or market? It’s the market of course, because this is business. A great product with no sales is doomed. A startup must adapt its product to the market or die.

A startup will achieve PMF when consumers assign a greater value to having their needs fulfilled than the cost of buying the product (by some material amount in order to be worthwhile). So the process of achieving PMF is one of shaping your product to fit the needs of consumers which they value.

So there it is, all very simple. Two main milestones, PMF and break-even. No sales? No PMF. While you might be able to convince people to give you money to fund your pre-PMF startup, eventually that money supply will run dry. A company that can’t reach break-even will die, although in the strange world of silicon valley startups this can take a surprisingly long time - I’m thinking of Uber here.

“Go-to market fit”, and other bullshit#

The idea of PMF is so staggeringly obvious to an entrepreneur that it hardly needs explaining to them. But the vast majority of people who work in startup-land are not entrepreneurs. The VCs are not, the employees are not, the pundits and advisors and bankers are not either. Natural-born entrepreneurs are few and far between, yet many fancy their chances. Those people need guidance, and there are plenty of others who will happily supply advice in the form of frameworks, checklists, books, counselling and consulting. These suppliers must sex it up a bit, because the basic concepts are just too simple (make sales, break-even). And so we have gradations of PMF, sub-stages and milestones, all presented in neat frameworks with stylish graphics.

We also have stages and sub-stages of the path to break-even, now called “go to market fit”, for heaven’s sake. I couldn’t quite believe what I’d heard when I first came across this phrase, explained in a tone of utter seriousness by a COO who quite clearly didn’t know what he was talking about. He’d read it somewhere. A cargo-cult entrepreneur.

If you have PMF then hire salespeople, plug the batteries in and send them out: don’t bullshit them with a go-to-market-fit process. Also build a team that can reliably turn out high quality outcomes for your customers.

Some might think that simplifying the stages in this way is just too simplistic. Reaching PMF is hard, and the first version of your product might well be a device to get customers to talk so you can find out what they actually value. But simplifying a thing isn’t simplistic. The concept of PMF is simple: make a product people want to buy.

Goodbye, Twitter

Steve Hoy — Mon, 20 Nov 2023 00:00:00 +0000

I joined Twitter in 2007. I am now leaving, and closing my account. You should too.

I haven’t really been using Twitter very much because it just wasn’t that great, to be honest. But since Elon Musk bought it I’ve been hearing much about how Twitter is descending into a pit of conspiracy-theories, racist and misogynistic horror; and so I did an experiment. I spent several hours scrolling through my timeline. There were a few posts by the people I follow. I know they post regularly, but their entries petered out, until the whole feed was conspiracy theories, thinly-veiled anti-semitic rants, other racist excrement, peans to the great leader Elon; on the whole the kind of things I would not want stuck to the soles of my shoes.

A particular low point was seeing some fan-boy generated image of Elon Musk in a superhero costume. I mean… damn. Words fail me.

Life is too short for this so I am closing my Twitter account. If you want to reach me then you either already know how, or you can use Mastodon. I’m at @stevehoy@mastodon.social.

What a sad, tragic, waste.

The Kernel of Good Strategy

Steve Hoy — Wed, 15 Nov 2023 00:00:00 +0000

The Kernel is the basic underlying structure at the core of a good strategy that unites thought and action. It has three elements: a diagnosis, a policy, and a set of coherent actions. No grandiose language, visions or timelines.

All this is in Richard Rummelt’s book, Good Strategy Bad Strategy. I highly recommend buying a copy. (By the way, I get no affiliate income from recommendations on my blog).

Good strategy recognises the true nature of challenges and finds ways to overcome them. Bad strategy chases unattainable goals without a workable plan. I’ll describe only the kernel from the book here - the book has much more including specific things you can do to develop good strategy.

The are three elements to the kernel:

Diagnosis: a definition of the challenge and the most critical aspect(s) of it.
Guiding policy: a clearly outlined approach to cope with the challenge.
Action plan: a set of coherent actions to accomplish the guiding policy.

Diagnosis#

The diagnosis aims to define the primary problem facing your company. Focus on one or two problems only - more means losing focus. Zero-in on the one thing that will affect all the other problems you face.

The diagnosis examines the situation and looks for patterns, resemblances to previous situations, and identifies areas which most need attention. In other words, “what’s going on here?”.

It’s hard to do. Much is uncertain about the present, let alone the future. The problem is probably ill-defined and there will be several levels of uncertainty at once, with some components being completely certain and others irreducibly uncertain, each component’s categorisation varying over time. Getting it wrong can send you in the wrong direction. Different people and groups within the company will have different perceptions of which problems are important, and will argue the case for a diagnosis that suits them. This becomes a leadership challenge: the leader must reject incorrect or self-serving diagnoses and look for a better one. This clarity is the heart of Leadership.

Policy#

The policy is a clearly outlined approach to coping with the challenges identified by the diagnosis.

It is clearly outlined: no grandiose words, visions or timelines. No Mission or Vision statements, and no goals. It is an approach used by staff to guide their actions - what to do and what not to do. It copes with the challenges, directly addressing those and not other things. It focuses the advantages the company has onto the challenges and away from peripheral problems, or minor problems. It discourages ineffective actions.

Coherent Actions#

The Diagnosis and the Policy are not enough. There needs to be a focused action plan, which is coherent.

Coherent means mutually dependent parts making a logical whole which is consistent. There should be no conflicts between actions (one cancelling another, for example).

Focused means the actions should follow the policies and address the challenge identified by the diagnosis. Importantly, there should be no actions which do not follow a policy and address the challenge - this means letting go of things which might draw attention and effort away. This is what Steve Jobs meant when he said “strategy is saying no to 10,000 things” - focus is not saying ‘yes’ to the thing you want to focus on, it’s also saying ‘no’ to the ten thousand other things which compete for attention.

The set of coherent actions (the action plan) coordinates operations to carry out the Policy. Resources are directed to these actions and no other things. The action plan is coordinated and overseen by senior management and guides the actions of all divisions and departments in the company - only a centralised plan can ensure that everyone is following it and not doing work which falls outside the strategy. The strategy must be executed across the board, by everyone.

A coherent action plan that adheres to all policies, implemented by all divisions and departments offers the greatest chance of success.

There’s more#

There is much more to the book, of course. The elements of good strategy are explored, advice is given on how to think like a strategist, and there are plenty of case studies and anecdotes throughout.

This is the definition of Strategy that I use. It helps me see the fluff and strategy-adjacent stuff, and pay those the appropriate level of attention, which isn’t much. “We will be the Number One supplier of choice for our preferred customers” is meaningless in guiding action, so why bother with it? Lists of values, such as “Teamwork, Respect, Integrity, Professionalism” are just words someone found in a list. Staff want to believe the company knows what it’s doing and a properly made Strategy is key to that.

Have A Strategy

Steve Hoy — Thu, 09 Nov 2023 00:00:00 +0000

When a company has a well-thought-out and specific strategy, it has an advantage over its competitors simply because it is better prepared for the challenges that face all rivals in an industry. But the strategy must actually be a Strategy, and there are many things which look like they are a strategy, but are not.

Most companies react to challenges on a day-to-day basis having only fluffy Vision and Mission statements and a set of long-term hopes which they mistakenly call “strategy”. The hopes (or goals, as they are often called) might be expressed in a set of powerpoints and spreadsheets of bewildering complexity created at great expense and which are all strategy-adjacent.

Types of things that are not Strategy#

In no particular order:

Woolly Thinking Vague, ill-defined thoughts expressed in grandiose language or filled with numbers and formulas to bamboozle the unwary.
Metrics What are you measuring, and why are you measuring it? Fewer, more useful numbers are better than many noisy metrics. Measuring something alters it - what you measure is what you will end up optimising for.
3-year Plans (or 5-years, or whatever), or any plan Plans are fine up to the point you start acting on them; “…no plan survives contact with the enemy…” (Helmuth von Moltke) and “Everybody has a plan until they get punched in the mouth” (Mike Tyson). By all means have a plan or plans, but they are not Strategy.
Goals, Objectives, Targets Anyone who thinks there is a difference between a goal and an objective, and worse, explains this to you, is seriously missing the point. A goal (or objective, or target, or whatever) is an outcome, and outcomes are subject to uncertainty. Conditions change, fashions change, there are Acts of God; who knows what the future holds? Any professional athlete knows that the best they can do is the best they can do, no more than that. On the day, another competitor may be having a better day than them and there’s nothing to be done about it.
Statements of a future state-of-affairs “Envisioning” a future state might help you understand the delta between now and then, and may even help you derive the actions required on the journey, but this is not a Strategy: it’s a vision, it’s unreal, a creation of fancy from your imagination.
Vision, Mission, Goals We’ve all seen this: supposedly you can derive a Mission from the Vision, and with the mission derive the Goals. Nonsense. Large teams of people will spend ages word-smithing the perfect Vision statement, and then another age perfecting the mission statement compatible with it, and then yet more time specifying the goals. The process of bargaining and compromise between various factions in their efforts to get Vision and Mission statements that all can agree to will render the product anodyne, bland, and useless. The vision will be some woolly, banal statement (“make the world a better place”), the mission will be a triumph of positive thinking, and the goals are actually hopes.
Strategy by template Templates are an excuse. The idea is that when forming a strategy, various tools are dragged out of the toolbox. Porter’s Five Forces. PEST, and PESTLE. Gap and SWOT analyses. McKinsey’s 7S Model, Ansoff matrices, the BCG matrix, the GE matrix, Value Chain Analysis, Business Model Canvas. (That list was from a five-second internet search). These tools may help develop your understanding of the situation, so none are bad per se, but they do not constitute a strategy. The reason they’re an excuse is the people who do these things spend a long time populating their matrices and canvases, and then conclude. There may even be a recommendation for action. These models are intellectually attractive, and in marginal cases may be somewhat useful, but all they do is describe one point of view of the situation you are in, not what you’re to do about it, or how to react as things change.
OKRs & KPIs are obviously not a strategy. They are targets and metrics.
Positive Thinking No amount of motivational language and can-do sayings can stand in for a Strategy, because wanting something doesn’t make it real. There’s an XKCD for that: Dream Girl.

Woolly Thinking, Positive Thinking and Strategy by Template are actively harmful. It’s obvious why bad thinking processes are harmful, and all too often strategy-by-template removes the need to think at all.

Management Consultants and MBAs love this stuff, and they charge appropriately. But all these things are strategy-adjacent, they may help thinking about what your strategy is to be but perhaps not enough to justify the expense.

Challenges and Methods#

A focus on goals is not a strategy nor is a collection of powerpoints and spreadsheets on a drive somewhere; rather the focus should be on methods to overcome challenges. What challenges? What methods? Those are the questions!

Much of the harm from LARPing Strategy comes from a lack of agreement of what strategy actually is, so I’m going to suggest that Richard Rummelt had it right. His book, Good Strategy Bad Strategy proposes a basic underlying structure at the core of a good strategy that unites thought and action, called the Kernel. The Kernel has three elements: a diagnosis, a policy, and a set of coherent actions. No grandiose language, visions or timelines.

Having something like the Kernel is having a strategy. More on the kernel in the next post.

Nobody Knows Anything

Steve Hoy — Fri, 03 Nov 2023 00:00:00 +0000

William Goldman, in his book Adventures in the Screen Trade wrote when it comes to deciding which movies will appeal to the public “Nobody knows anything. Not one person in the entire motion picture field knows for a certainty what’s going to work,” he said. “Every time out it’s a guess - and, if you’re lucky, an educated one.”

So there it is: Nobody knows anything. It doesn’t matter who said it (was it Sam Goldwyn?) it is a truth which ought to be universally acknowledged.

You Know Nothing, Jon Snow#

No matter how smart you are, or how senior, or how experienced; you know nothing. Well, next to nothing, relatively speaking.

It’s easy to see why this is so: the more you know about a subject and the more specialised you become; the more you narrow down your area of expertise and the more areas exist about which you know nothing. Smart people know this and are suitably modest when it comes to areas in which they are not expert.

Less smart people extrapolate their expertise into other areas, believing one or both of

You’ve got to be pretty smart to get to where I am today in my field, and so (this other field) can’t be that hard for me, or,
My skills are directly applicable in (this other field). Tech Bro’s are especially prone to this delusion.

Smart people are modest when it comes to punditry; it staggers me how many people pronounce on subjects about which they have no expertise, or in which no expertise is possible. Very few people properly understand the background to the war in Ukraine, and yet the streams are filled with commentary about what should be done. I’m tired of LinkedIn posts along the lines of “do this thing to achieve this other thing and you’ll be successful” - because they’re clearly dross or silly analogies (‘be like the mighty Lion’ - honestly, while writing this post I looked at LinkedIn and there it was, fifth in the stream. Jeepers.) Worse still (from my point of view) are the strategy templates and frameworks, and needless terminology around the stages of product/market fit.

Besides the hubris of imagining that you are equipped to deal with the current situation because of your previous achievements and status (which might be true, I guess, if you’re doing the same thing again) there is also the likelihood of another, enthnocentric bias, in which situations and problems are evaluated according to priors originated from within your own culture and experience. This is a failure to understand that different points of view, lived experience, priorities and desires drive motivations and actions and prevent courses of action which seem obvious to you.

Chesterton’s Fence#

The person who finds themselves swimming in unfamiliar waters needs to recognise they’re not the expert here, find those who might be experts, and keep a strong sense of humility.

There is a fallacy called Chesterton’s Fence, in which a fence bars the way. Why is it there? It might make no sense being four metres wide and easily walked around, or it’s a ludicrous ten centimetres tall. The urge would be to go around it or step over it or remove it altogether. But, someone put it there, and they had a reason.

Until you know the history and the reason for the fence you should leave it alone. Until you are sufficiently knowledgeable in the area in which you now find yourself, you should resist the urge to do the common-sense thing and get rid of it. Instead, ask questions until you find the actual experts in this field who know the history of the fence. The reason for it might still be valid and if that’s the case, you have gained new knowledge in this domain. Maybe the reason was valid but now isn’t and so the fence can be removed without harm.

It may also be the case that no-one can remember why the fence is there. You may think they’re all idiots for not getting rid of the thing before, but they were actually respecting the limits of their knowledge. Before removing the fence you would be wise to think through all the possible repercussions, talking widely about your intent (so as to surface the likes of Bob, the beardy guy in the corner that no-one listens to but who remembers the specific Law this fence was put in to comply with, a Law with severe penalties for breach).

Bias#

The ethnocentric bias is where current situations are experienced and reasoned about mostly through the lens of one’s own culture and experience. A Lawyer sees business problems in terms of rules and contracts, risks and liabilities. An Accountant reduces everything to numbers. A software programmer sees code. A Tech Bro sees everything through a technocratic lens.

Overcoming your own biases starts by accepting that they exist and are powerful. They will blind you to pitfalls and opportunities. It might seem harsh, but if you set out to explore your current situation with an open mind and an acceptance that you know nothing, you can bring your skills and experience to bear more effectively, avoiding error along the way.

Risk & Uncertainty - Introduction

Steve Hoy — Wed, 23 Aug 2023 00:00:00 +0000

Four posts I made yesterday relate to Risk & Uncertainty. Here's the main theme and the order in which to read them.

Coin Tossing #

Understanding the difference between risk and uncertainty should lead to more careful thought about the consequences of our decisions, including that outcomes will be unknowable most of the time. This can be hard to accept, especially in Business.

Physics Envy #

Economics and Business are poorly served by the overuse of confusing jargon and mathematics to seem more rigorous than is actually possible. Many try to reduce these fuzzy subjects to formulae and frameworks, and while this can help understanding, more often it is just a veneer of nonsense over something unknowable.

Known Knowns #

The nature of knowledge and ignorance is a serious philosophical problem; for decision-makers, it is a gnarly practical one too. Making important decisions in the face of uncertainty is unsettling and difficult. Few are up to the task.

What To Do?#

Since it is not possible to measure uncertainty in quantitative terms, positioning is the correct response. Have a strategy, and be prepared for the next big thing.

Coming Up#

I'll write some more on Strategy. There is much fluff passing for strategy in all walks of life, but it's especially rife in Business. I'll then start focussing on one of my areas of expertise - Partnerships.

Coin Tossing

Steve Hoy — Tue, 22 Aug 2023 00:00:00 +0000

Often in business we are asked for our opinion on the odds of something happening, and we may be tempted to say “I’m 90% sure x will happen” or some-such. But what does this mean? Have we carefully determined all possible outcomes and after detailed analysis assigned probabilities to each? More likely this is just an opinion where we really mean “I’m nearly certain x will happen”. But putting a number on a possible outcome obscures more information than is revealed. Without the underlying analysis this sort of number is very likely to mislead.

"Probabilities disguise uncertainty in a way that obscures more useful information" Barack Obama

Risk & Uncertainty#

In a 1921 paper, Risk, Uncertainty, and Profit, Frank Knight defined uncertainty as a lack of knowledge which is immeasurable and impossible to calculate. This is called (in economics) Knightian Uncertainty, the kind of distinction economists love to make; taxonomies of uncertainty to assign probabilities and probability density functions to try to measure it. This is par for the course with economists in general, who tend to believe everything in their social ‘science’ can be expressed as a number; economics has a very bad case of Physics Envy. Frank Knight had a different view, which I think is useful.

When the probabilities of all possible outcomes are known (such as when tossing a coin or throwing a dice), we call it Risk. Where the randomness of outcomes cannot be expressed in terms of specific probabilities we call it uncertainty.

Tossing a coin is less random than we think#

When we toss a coin we’re trying to fairly and randomly choose something. But tossing a coin does not create a random outcome; in fact, a coin toss is governed by the laws of mechanics and is fully deterministic. For example it is possible to build a machine to consistently toss a coin so that the outcome is certain every time.

Where we get fooled is by the abstraction of probability. In a probabilistic sense a fair, two-sided coin of zero thickness will come up heads or tails with 0.5 probability. However, when we toss a coin, we use an analogue of the theoretical and perfectly fair random process in which uncertainty is introduced by the human factor. Chaos is added by the variations between coin tosses by humans. These are known unknowns (we know what the factors are but we cannot yet measure them or decide how much weight to give to each). We know the mechanical process can be manipulated, so we have rituals to guard against the skilled coin-tosser:

One to toss, the other to call.
The toss before the call: The tosser flips the coin and slaps their other hand on top of the coin so that the caller can observe the toss before choosing (and maybe dispute a dubious flip).
The toss after the call: the caller calls and then the coin is tossed and allowed to fall to the ground and bounce around. (Sporting events may get a child to do this on the basis that children have less guile and skill, and presumably little invested in the outcome of the toss. Also good publicity, possibly).

So in this Laws of Physics view, the coin toss is not random, but there are so many variables it might as well be in practice. It is the introduction of uncertainty which makes a deterministic, mechanical process become sufficiently random. Risk is the 50/50 bit, uncertainty is the chaos.

Understand what is actually going on#

Tossing a coin is suitably unpredictable for decisions where the outcomes are equivalent, such as how to have your eggs for breakfast, or which player gets to serve first. On the other hand, where the outcome is material we want a bit more thought than just flipping a coin. A careful study of random phenomena is truly difficult, and Decision Theory has many heuristics to assist, but in business there are so many variables and uncertain factors that assigning probabilities is mostly futile.

Many disputes between people boil down to the meaning of words, so for this blog I thought I'd set out what I mean when I use "Risk" and "Uncertainty".

Things we take for granted can be more involved than they seem. Next I’ll talk a little about Physics Envy; vain attempts to quantify the unknowable.

Known Knowns

Steve Hoy — Tue, 22 Aug 2023 00:00:00 +0000

“…there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we don’t know.” Donald Rumsfeld

In 2003 The Plain English Campaign gave Mr Rumsfeld its annual Foot in Mouth award for this. However, far from being an incoherent jumble of words, it is a complex, almost Kantian thought.

I would add to this the unknown knowns - things we don't know we know. Often in an organisation, large or small, many things are known by individuals or groups but the communication channels do not exist to surface the information and make it known to the institution. The US had all the information needed to detect the World Trade Center attacks before they happened in 2001, but the information was distributed. Even if the channels exist to allow information to move to the ‘corporate’ understanding, there are few effective filters to determine what might be relevant to any given scenario.

It’s good to see a senior politician, even one who divided opinion as Donald Rumsfeld did, think and speak publicly about the nature of knowledge. Politicians often need to appear to be “Men of Action”, doing things, making changes, rather than talking about what they cannot know. It’s their tragedy that we, the populace, require this of them because we need certainty. In business too, we defer to those who are the most certain, even if we should know better.

The “Man of Action”#

There is a continuum, I think, from those who busy themselves only with ethereal concerns such as religious thinkers or philosophers, through the “Men of Action”, to those too idle or stupid to think at all. I should say that many of those who ‘do not think’ actually do, but are unconcerned about the matter at hand - they show up to work, do their thing, and find their love at home. They do not care very much about the company, except when it lays off a ton of people (or goes bust) when the senior management in their firm screw up. Also spare a thought for the smart person with their face pressed to the greasy pole of corporate or political advancement: they may be smart, high-achieving people who have hobbies and are good parents (otherwise normal people), but they are professionally required to be a “Man of Action” at work.

The “Man of Action” is in quotes because it is a gendered phrase used here to denote those people, men and women, for whom the need to act precludes humility or introspection. It plagues men more than women, I believe. You’ll find them everywhere in Management.

Sicklied o'er with the pale cast of thought#

Uncertainty is anathema to the “Man of Action”. They cannot cope with it, for it prevents them from Acting. They would be required to confront the limits of their knowledge and start to reason in the presence of uncertainty, and even if they’re capable of it they know the people who pay them and those they manage are looking to them for ‘Leadership’, and if they fail to provide it others will take their place.

So it is rare to find a corporate or political ‘leader’ sicklied o'er with the pale cast of thought. Most are not capable of it. It's just not in them to be reflective and introspective in an intellectual sense. They have no interest in why things are the way they are. Rather, they spend their energies on understanding how they can take advantage of the way things are. This succeeds in defined areas such as banking, but fails badly in start-ups.

In a start-up the business is trying to find a successful product and so start-ups require a lot of thinking and listening, not skills a “Man of Action” is renowned for. I argue that in Business generally, there’s just not enough thinking and listening, no matter how much companies talk about it.

Gnarliness#

Any decision in the presence of uncertainty is, well, uncertain. Understanding that there’s a lot which is not known and is possibly unknowable is key to navigating uncertainty. It is this understanding that eludes the “Man of Action”. The skills of introspection and reflection are necessary to processing uncertainty and are not highly regarded in business, but they are needed when creating a strategy.

Physics Envy

Steve Hoy — Tue, 22 Aug 2023 00:00:00 +0000

Part of my distrust of economics as a subject and profession is its overuse of mathematics. Economists like maths because it lends an aura of certainty which doesn’t exist. To establish the sort of certainty that this is so, economists look to the harder sciences, especially Physics which uses maths to describe actual deterministic things which can be reliably reproduced in experiments. The fact that this can’t be done in economics cannot be allowed to get in the way. This is Physics Envy.

Andrew Lo and Mark Mueller wrote a very entertaining paper, Physics Envy May Be Hazardous To Your Wealth! in which they say that predictive models of economic systems create a false sense of mathematical precision. They argue that the kind of uncertainty affecting economic interactions is critical in determining the successes and failures of the models created by economists. They propose a six-level taxonomy of uncertainty, which is very entertaining.

By the way: they use the correct meaning of uncertainty as being Knightian Uncertainty. Not that this distinction should make the slightest bit of difference.

Level 1: Complete Certainty
All past and future states of the system are determined exactly if initial conditions are fixed and known—nothing is uncertain. However, any system with even a small amount of complexity cannot be completely certain because small perturbations in initial conditions can lead to large changes in the evolution of the system. Some Physics models sit here, such as Newton’s three laws of motion, but nothing in business and economics can be Level 1.
Level 2: Risk without Uncertainty
This level of randomness is Knight’s definition of risk: randomness governed by a known probability distribution for a completely known set of outcomes. At this level, probability theory is a useful analytical framework for risk analysis. The modern axiomatic foundations of probability theory is given precisely in these terms, with a specified sample space and a specified probability measure.
Level 3: Fully Reducible Uncertainty
This is risk with a degree of uncertainty, an uncertainty due to unknown probabilities for a fully enumerated set of outcomes which is completely known. By “fully reducible uncertainty”, they are referring to situations in which randomness can be made arbitrarily close to Level-2 uncertainty with sufficiently large amounts of data using the tools of statistical analysis.
Level 4: Partially Reducible Uncertainty
By Level-4 or “partially reducible” uncertainty, we are referring to situations in which there is a limit to what we can deduce about the underlying phenomena generating the data. There is a non-trivial degree of uncertainty regarding the underlying structures generating the data that cannot be reduced to Level-2 uncertainty, even with an infinite amount of data. Here, we depart from the certainties of the hard sciences; markets are tools developed by humans, not immutable laws of Nature, and are subject to all the complexities of human behaviour.

While Bayesian statistics, in which probabilities represent degrees of belief can be useful, we have no way of knowing the full range of factors contributing to the complexity of the situation. Mathematical models are useless (except to other mathematicians), and very likely deceptive for a non-mathematician.

Level 5: Irreducible Uncertainty
Lo and Mueller say that irreducible uncertainty is “the polite term for a state of total ignorance; ignorance that cannot be remedied by collecting more data, using more sophisticated methods of statistical inference or more powerful computers, or thinking harder and smarter”. I think the language goes too far: the total ignorance they are referring to is the unknowability of certain factors (either their presence or their influence or how to measure them).
Level ∞: Zen Uncertainty
“Attempts to understand uncertainty are mere illusions; there is only suffering”. Physicist humour, I guess. Illusion and suffering are poor translations from Sanskrit and describe philosophical concepts which I think we’d all be better off understanding more.

So, any given phenomenon may contain several levels of uncertainty at once, with some components being completely certain and others irreducibly uncertain, and each component’s categorisation can vary over time as the situation changes, technology advances or our understanding deepens.

The other key point in Physics Envy is that physics papers are written for other physicists, and mathematical papers are written for mathematicians. These people have training and experience in their fields, and are all too aware of the boundaries of their knowledge.

Nothing in Business, or Economics, or other social ‘sciences’ can be Level-3 or below, which means that we are always dealing with uncertainty. Business Strategy has a bad dose of physics envy, with five-year plans, metrics and measurement, and cost-cutting efforts.

Economics though, has by far the worst case. Much of it is written in mathematical terms but it uses stupid simplifications to get the models to work. Economics has a steely grip on thinking about social issues, including Business. Business leaders and politicians, educators and writers, pundits and LinkedIn influencers are nearly all enslaved to the theories of some long-dead economist, to paraphrase John Maynard Keynes.

Lots of things cannot be reduced to numbers, because they are uncertain. Formulas and frameworks can help with understanding a process, but they are poor tools when used as a substitute for understanding Uncertainty.

We need to consider uncertainty; the things we know we don’t know, and the things we don’t know we don’t know. Most people simply can't do this, through hubris or ignorance or incapacity; and often it's just too hard to explain upwards that these things are uncertain and possibly unknowable.

What To Do?

Steve Hoy — Tue, 22 Aug 2023 00:00:00 +0000

Since it is not possible to measure uncertainty in quantitative terms, positioning is the correct response. Have a strategy, and be prepared for the next big thing.

The common response to uncertainty is to pretend it does not exist. Uncertain elements are given numbers which are then included in calculations, the rest are airily waved away as ‘nothing to be done’ in a fit of magical thinking. Magical thinking comes to the fore in business strategy, which is a mix of woolly thinking, hopium and sloganeering, among other things.

Woolly thinking obscures the hard parts of strategy, especially making choices and not doing things. It’s hard to say no to something when you’ve a bunch of VPs whose jobs rely on it being included in the strategy - so your strategy will mirror the existing organisational structure of the company (a sort of twisted Conway’s Law).
Hopium arrives when hoping saying a thing will be so is enough to make it so. This is a real problem today, especially in the PMC, but I’ll get into that more in later posts. Here, it’s management simply stating an outcome, such as ‘being number one’, and then expecting the firm to somehow conjure it up.
You will have seen slogans around (did you write them?) perhaps on posters in corporate hallways, with sayings such as “We’ll be the Number One supplier of choice for our preferred customers”. What does this even mean? How could it possibly help your staff make decisions to support the strategy? Lots of uplifting statements on posters, in all-hands meetings and management briefing sessions is not having a strategy.

Have a strategy#

The fact is, it is hard to arrive at a decent strategy. Not because it’s technically difficult for an imaginative person to do (though there are few enough of those in business), but because having a strategy involves properly understanding the problem in all its complexity and uncertainty and then making choices about what to do. The clamour will be for action, even if waiting is the correct response. It takes a very strong leader to resist this clamour, which you might get in a startup controlled by its founder, or with especially charismatic leaders like Steve Jobs, or when the company is facing an existential crisis (and in that case very often there’s too much momentum to save it).

The people typically required to come up with a strategy are exactly those who will be worst at it. The Action-oriented types will have no time for the conceptual grappling needed and will simply want to get on with things. It is also mostly beyond a general class of educated person who once were educational high-achievers and who now float around in organisations saying that something must be done, demanding it even, but when pressed bring nothing. These people think that management is a skill independent of the subject, probably learned after a year in a sausage factory and then an expensive MBA. For them ‘perception is reality’, and their core skill lies in swimming in the tide of the organisation - a purely social affair - not necessarily doing good work. They are often bullshitters in the strictest meaning of the word.

Corporate strategy also has a bad case of physics envy, with its reliance on projects and plans, numbers and projections, risk assessments and utterly pointless DCF projections. This is all part of the performance of strategy and is the best you can expect from a deeply unimaginative cadre. What you will get is a cargo-cult strategy.

Cargo Cult#

A cargo-cult strategy has all the decorations of an actual strategy. There are SWOT analyses, 5-forces drawings, DCF and ROI, ARR and CAC, throughputs and burn-down rates, multi-year plans: a salad of strategy-adjacent stuff which looks impressive, but which says little. The trouble is the future is uncertain, most of the present is also uncertain, and reasoning in the presence of uncertainty is hard and most people are crap at it.

Very likely your managers are tuned to turning out day-to-day outcomes and simply cannot think in a strategic way. It’s highly unlikely that a decent strategy can emerge from these people because they’re just not configured that way. Best to leave them in middle management, although they will be very unhappy with that.

Or perhaps you have professional strategists on board who learned their craft at a management consultancy, where success is rewarded through achievements with PowerPoint (nearly always works of fiction) and who at best can talk only in theoretical terms.

No, a genuine strategy involves a clear-eyed look at the actual situation in all its complexity and uncertainty and which produces a policy and actions (including things to stop doing).

Take a position#

Richard Rumelt, a professor of strategy at UCLA’s Anderson School of Management, when asking executives about their corporate strategies said he heard “a lot about doorknob polishing. They were doing 360-degree feedback, forming alliances, outsourcing, cutting costs, and so on. None of them even mentioned taking a good position quickly when the industry changes”. Contrast this with Steve Jobs, who in 1998 said to Rummelt, “I am going to wait for the next big thing”. Jobs wasn't focusing on a series of strategy-salad items. He was waiting for a suitable opportunity, which came with the iPod and then the iPhone.

Uncertainty is all around#

One could argue that the Russian incursion into Ukraine was highly predictable (NATO's efforts to bring Ukraine in and Russia's stated objections). This was Risk. What could probably not have been predicted was the EU's decision to stop buying Russian gas, greatly increasing the cost of German industry and likely forcing relocation to the US. This was uncertainty. How would this have shown up in corporate planning? Maybe a consultant’s scenario planning might have come up with it. Probably not.

The only correct response to uncertainty is to position yourself and your company for the eventualities which may emerge, good or bad. Make bets, sure, but don’t bet the company. Above all, have people on board who are mentally equipped to deal with uncertainty.

It’s simpler for startups. You only have one bet: your product, and if you’re not yet making sales you are burning investor cash. It's exactly your job to find the fit between your product and what the market will pay for.

Trying to put numbers on uncertainty is very foolish#

Climate scientists warn that a 2°C to 4°C global average temperature increase will be an extinction-level event for humanity and most other life on Earth, and yet the economics chapter of the IPCC’s Sixth Assessment Report, “Key Risks across Sectors and Regions”, predicted a 10-23% fall in GDP from 4°C of warming by 2100. Since economists also assumed that economic growth would continue over this 80-year period, this 10-23% decline would still result in a per capita GDP of the order of four times higher than today.

So which is it? The end of humanity, or slower GDP growth? I’m with the hard scientists here; climate change must be treated as an existential threat, rather than an issue which is suitably addressed by economists putting numbers on Uncertainty and ignoring what they do not know.

SWIFT is Not a Payments System

Steve Hoy — Sun, 23 Jul 2023 00:00:00 +0000

I have often heard people who should know better talk about 'sending a SWIFT payment'. Later, when I moved into FinTech I was not surprised that many people did not know the difference between sending messages and moving money, so here's a quick & dirty explainer.

Actually transferring money is different from sending messages, and SWIFT is a messaging system (it's in the name, after all¹).

Moving Money#

From the Bank's perspective, all payments fall into three broad categories; on-us, domestic and cross-border.

On-us payments are where the payer and the beneficiary bank at the same Bank. All the Bank has to do to effect the payment is make the relevant accounting entries in their core-banking system, debiting the payer and (ultimately) crediting the beneficiary. There might also be some transaction reporting or other requirements, but that's pretty much it, no need to send payment instructions. Importantly, the Bank's liquidity position is unchanged and money does not move through the payments system.
Domestic payments are when the payer and the beneficiary accounts are with different Banks domiciled in the same country. In this case, the Bank debits the payer's account and then moves the money to the beneficiary's Bank via the Central Bank. The receiving Bank debits the due-from-banks account in its books and credits the beneficiary's account. Money actually moves off the balance sheet of the sending Bank and onto the balance sheet of the receiving Bank, meaning the sending Bank now has less liquidity and the receiving Bank more.
Cross-Border payments are when the payer and beneficiary accounts are domiciled in different countries. Here the Bank needs a correspondent banking relationship with another bank which is based in the beneficiary's country. Correspondent banking is one of the oldest arrangements in the Banking World and is complicated. Simply put, the money moves from the payer's Bank to the beneficiary's correspondent bank in the same country, while a parallel transaction occurs in the beneficiary's country, both sets of transactions using the respective domestic payments systems. Which Bank gets to do the FX is another matter².

As a heuristic, think that currency never really leaves the sovereign state that issued it (excluding dodgy bags of cash carried through airports, which is mostly illegal).

Sending Messages#

When a Bank is presented with an amount of money by the payments system, it has to know what to do with it. If it doesn't know, it should DK³ the payment and return the money to the sender, via the payments system. The receiving Bank gets to know what to do with the money because the sending Bank has sent it a message telling it to expect the amount and who the intended beneficiary is.

This is what SWIFT does - it moves messages between Banks. The actual movement of money – settlement – is done by the domestic payments systems involved (Faster Payments or CHAPS in the UK, TARGET in the eurozone, those sorts of things; every currency has at least one).

In the Olden Days Banks used Telex to send messages to each other; the Tested Telex. After striking a Correspondent Banking Agreement, the two banks would agree a 'test key' to authenticate their messages. Typically, this would add all the numerals contained in a message (such as amount, and value date), apply some form of salt (possibly just a sequence number and a 'secret' number), and add the resulting string to the message. The receiving bank would first verify the test key against the message before passing it to the relevant department for (manual) processing.

Telex is slow (c50 baud) and the messages are free-format over an insecure connection. Messages had to be managed by hand. So, in 1973 SWIFT was founded as a bank-owned cooperative in Belgium. Its job is to move messages between banks in a secure, fast and reliable manner, using known standards and is now so dominant that in order to be a Bank you pretty much need a BIC (Bank Identifier Code, issued by SWIFT).

SWIFT handles messages of many types, more than just payment instructions. Confirmations, statements, and free-format messages are all catered for; covering payments, foreign exchange, securities, trade documentary credits, metals - practically any Banking activity.

So SWIFT handles the transmission and exchange of payment instructions, while settlement of the payment is done using the payments systems of the countries concerned. SWIFT is not a payments system.

Down the rabbit hole#

When I was learning about this stuff, a long time ago, I wondered how foreign-to-each-other Banks managed their liabilities. This led me to the Bank for International Settlements (BIS) and their strange currency, SDRs. Going deeper, you get to Purchasing Power Parity and tectonic shifts in fundamental exchange rates before finally confronting the Abyss and realising that it's all made up, money isn't real, and all is illusion.

SWIFT is an acronym for Society for Worldwide Interbank Financial Telecommunication.

If the beneficiary is receiving an amount of domestic currency (that is, no FX conversion, just one currency), then the receiving Bank just has some book entries to do.

DK means "Don't Know". DKs should include a message sent to the sending Bank stating that an amount has been received but the receiving Bank cannot apply the money to a beneficiary's account.

Update

Steve Hoy — Sat, 22 Jul 2023 00:00:00 +0000

I admit I haven’t posted as much as I intended. In mitigation, I’ve done some major renovations to my house and got involved in a project using Petri-Nets in Rust. But I’m back.

ChatGPT is a Bullshitter

Steve Hoy — Thu, 08 Jun 2023 00:00:00 +0000

ChatGPT is a Bullshitter and if you use it to communicate with other people you will be too.

My timelines have filled with gushing reports of the fantasticness of ChatGPT, which is depressing. There is breathless talk of using it for everything, and of how many jobs our AI overlords will replace.

"It's like a calculator for words" - No, it isn't; calculators give correct answers and we throw out calculators which don't.
"It'll answer my emails for me" - Well okay, if you want to bullshit people.
"It'll write my 'cold emails' for me" - Oh dear god no; the thought of industrial-scale bullshit spamming my inboxes is enough to make me reach for my revolver.

Get the bandwagon rolling#

Many of the crypto types who previously filled the timelines with 'Web 3.0' nonsense have now re-invented themselves as AI bullshitters. But there is no such thing as Artificial Intelligence, it's a badly-coined phrase from the 1950s. What LLMs such as ChatGPT are doing is 'statistics', or 'Machine Learning'. It's not artificial; LLMs are trained on the output of millions of real humans, also consider the awful pay of the people who pre-trained the transformer. LLMs are not intelligent. Mere pattern-matching is not enough; intelligence synthesises and draws conclusions, has beliefs, and knows what it knows.

The language used to describe LLMs is deliberately anthropomorphic. Take "Hallucination"; LLMs use the exact same process when 'hallucinating' as when producing accurate content, so in what sense is it hallucinating? Human beings hallucinate, machines are just wrong. Also, the first person singular is not appropriate - "as a large language model I… " - it's not a person, it's auto-complete.

The demands to regulate the coming 'super-intelligence' is self-serving claptrap from companies looking to profit from the implied importance and increased barriers to entry regulation provides. All part of the hype.

But it's a bullshitter#

Harry Frankfurt, a philosopher, wrote an essay (On Bullshit) defining this rhetorical style as persuasive speech whose essence is a “lack of connection to a concern with truth—this indifference to how things really are”. LLMs are designed to produce bullshit: persuasive speech with no concern for the truth.

A Generative Pre-trained Transformer (GPT) model is a next-token optimiser. The tokens are words and the optimiser seeks plausible text which is grammatically correct, not truthful. LLMs cannot ascertain truth - they merely manipulate symbols (tokens). LLMs cannot generate new information either, they're not intelligent or informed, so insights must come from you. Since an LLM cannot draw new conclusions or insights, and if you use ChatGPT to write for you, your writing will not contain any new information. So why should I bother with your messages?

LLMs produce the bland, insipid text of corporate-speak; the measured, authoritative style used by PR flacks, LinkedIn influencers and MBA-ists writing of the hard decision to let go 10% of the workforce, or claiming they take the security of personal data extremely seriously just after the data breach has finally gone public.

If you're an SDR who has to send a lot of emails and thinks LLMs are your saviour, well, you're going down the quality curve, probably proving that a machine can replace you, and you'll sound like a bullshitter. I mean, there's enough spam as it is. LLM output is likely to make the work of spam filters much harder. Face it: if your job could be done by a LLM such as ChatGPT then you're in a bullshit job, and your employer is definitely aware of this.

Another thing: your prompts may disclose PII or proprietary information. Suppose you send a set of composite prompts with "name", "engaging event", and "call to action". What have you revealed to a third party? There is little protection provided by the privacy policy (you divulged it, after all). Is using ChatGPT a reasonable use of PII for internal business purposes?

Write like a person#

The current mania around LLMs will pass as other fads do, by settling into a few specialised use cases where they genuinely add value or become grassed over and forgotten. Perhaps as a search or summarising tool on scoped data with a definite notion of truth, such as policy manuals, or Customer Service and Support queries. Or maybe you're stuck when you need something to say, and your hangover means you're under par this morning. In which case okay, get your LLM of choice to generate something, then refine the text into something else that's genuinely yours.

Bullshit and the bullshitters who spout it will always be with us, but decent use cases will emerge. After all, it's early days.

It is often a struggle to express your thoughts properly in writing. Writing is hard, but it is a skill that can be learned. Writing well takes talent, and a machine will remain a machine. However, the process of writing to another human being and persuading them into a course of action is a personal thing between people; don’t be a bullshitter.

Things Change

Steve Hoy — Mon, 30 Jan 2023 00:00:00 +0000

Hi!

I've decided to start writing about all the various things I've been talking about over the years. Covering financial services, technology and fintech in general. I will share what I know and write my opinions - hoping occasionally to persuade you, and to plead in favour of various courses of action.

Steve Hoy

Product/Market Fit

Product#

Market#

Fit#

Achieving PMF#

“Go-to market fit”, and other bullshit#

Goodbye, Twitter

The Kernel of Good Strategy

Diagnosis#

Policy#

Coherent Actions#

There’s more#

Have A Strategy

Types of things that are not Strategy#

Challenges and Methods#

Nobody Knows Anything

You Know Nothing, Jon Snow#

Chesterton’s Fence#

Bias#

Risk & Uncertainty - Introduction

Coin Tossing#

Physics Envy#

Known Knowns#

What To Do?#

Coming Up#

Coin Tossing

Risk & Uncertainty#

Tossing a coin is less random than we think#

Understand what is actually going on#

Known Knowns

The “Man of Action”#

Sicklied o'er with the pale cast of thought#

Gnarliness#

Physics Envy

What To Do?

Have a strategy#

Cargo Cult#

Take a position#

Uncertainty is all around#

Trying to put numbers on uncertainty is very foolish#

SWIFT is Not a Payments System

Moving Money#

Sending Messages#

Down the rabbit hole#

Update

ChatGPT is a Bullshitter

Get the bandwagon rolling#

But it's a bullshitter#

Write like a person#

Things Change

Coin Tossing #

Physics Envy #

Known Knowns #