Strategy in the Post-fixed Costs Economy

Strategy in the Post fixed costs economy

Strategy in the Post-fixed Costs Economy

Evaluating strategic options in a world where businesses have never been easier to start, but never been harder to scale

by Ben Robinson, October 2020 | 15 minute read

We’ve talked often about the diminishing importance of supply-side economies of scale. In its simplest expression, digitization flips the industrial age equation. What was scarce in the industrial age was supply; what is scarce in the digital age is demand (attention).

In the industrial age, to scale supply meant mass production to spread the fixed cost of large capital investments over large volumes. And the industrial age was an age of mass produced, relatively standardized goods. This applied to goods and services provided by the private sector, but also to state-provided services, such as education and public services.

Since the advent of the internet, this is changing. We first noticed the shift in industries where both supply and distribution could be digitized (e.g. media) because supply became abundant faster and this highlighted our limited attention sooner.  But it’s becoming increasingly apparent that all industries are being disrupted as software has eaten the world. More and more physical goods have software components to them, making supply more digitized. Where supply cannot be digitized, distribution nearly always can. And where supply-side economies of scale remain important, they can be borrowed.

Renting scale and the end of fixed costs

AWS was not originally intended to be a platform on which third-parties would run their businesses. But, thanks to Amazon’s business model, it was possible to open up that infrastructure service to others. In doing so, Amazon created a massive and highly profitable business which contributes 65% of group operating profits.

But, as big as the impact has been on Amazon, the broader societal impact has been truly dramatic.

Before AWS, companies had to make large upfront investments in computing hardware – a significant barrier to entry. Even buying hardware was a major source of risk: buying too much could bankrupt a company while buying too little could cause a major bottleneck to growth. And so, AWS removed both risk and cost for new businesses. As a direct consequence, it also contributed to the creation and success of hundreds of thousands of new businesses.

This boost to global GDP over and above the value captured by Amazon itself is difficult to calculate, but it’s certainly very significant. It’s probably not an overstatement to suggest, as Charlie Songhurst does, that AWS has been the single biggest factor in the rise of angel investing.

But AWS is not the only internet era platform. From Shopify to Stripe, examples abound of platforms that share their scale economies to remove the cost and complexity of doing ecommerce – allowing companies to form and start trading faster, with reduced risk and at lower volumes than would have ever been possible.

And not all internet-era platforms are providing digital services. As Rita McGrath, Columbia Business School Professor, discussed on a recent Structural Shifts podcast, by helping establish prices and create trust, digitization is making more and more non-digital assets tradeable on marketplaces. As she put it:

“What we’re seeing with the advent of the digital economy is that more and more transactions can be conducted in markets that used to require a firm.”P

Uber was a pioneer in this regard, but we now see this “uber of x” phenomenon everywhere – even in the enterprise market. At aperture, we are very much an embodiment of this, providing strategy and go-to-market as-a-service that enables companies to avoid the fixed costs and risk of underutilization and underperformance in these functions.

In effect, it’s becoming easier to rent all services, physical and digital. All become liquid and on-demand. Capex gives way to opex or, as Younes Rharbaoui says: we have entered the post-fixed costs economy.

“Signs of a post-fixed costs economy are all around us: companies switching to full remote, increased reliance on independent workers & freelancers, on-demand software where cost matches usage, are all creating lean financial structures for growth.”

And, of course, like many other secular trends, the impact of the pandemic has been to accelerate it. If COVID-19 drew a binary distinction between online and offline services, lifting the former and sinking the latter, then it was disproportionately brutal in its treatment of those offline businesses with high fixed costs – oil companies, airlines, hotel chains and so on. From now on, all fixed cost investments will be more heavily scrutinized and, where they exist, variable costs alternatives will be more actively considered. Even Warren Buffett, a regular character in aperture blogs, is starting to consider the wisdom of some high fixed-cost business models.

The fact is, if fixed costs were already becoming passé, they definitely will be in the post-pandemic world – ushering in a faster transition to a new, internet-era economic structure.

Platforms, aggregators and the long tail

For the best explanation of the difference between platforms and aggregators, we recommend this classic essay from Ben Thompson. In it, he uses the Bill Gates platform definition, namely that: “A platform is when the economic value of everybody that uses it exceeds the value of the company that creates it. Then it’s a platform.”

Bill Gates quote platform vs. aggregators

On this definition, the business we have already mentioned – AWS, Stripe, Shopify – are all platforms. They make the large investments in fixed costs – datacenters, fulfilment centers, payment networks, etc. – that mean their clients don’t have to. They make it cheaper and simpler to do business.

It’s this commoditization of supply and associated end of fixed costs that’s now starting to give rise to a long tail of providers. Thanks to lower and variable input costs, it’s possible to make money at lower volumes than in the past, which in turn means a higher number of providers can co-exist.

Take newspaper publishing, for example. The massive costs of producing and distributing physical newspapers gave rise to significant economies of scale and produced an oligarchical market structure. Compare that with today, when a platform like Substack allows independent writers easily and cheaply to publish, distribute, and monetize paid newsletters. These writers can make a living with only a small audience, allowing potentially tens of thousands of them to co-exist – and giving rise to a broader phenomenon, the “Passion Economy”, where more of us can pursue our craft or our talent and make a living from it.

However, the difference between the long tail as it’s conceived now and the original theory, is that supply is abundant, not demand. The constraint on all digital-era businesses is demand and the gatekeepers of demand – the most profitable actors in the digital ecosystem – are aggregators.

In a world of abundant supply, aggregators help match buyers and sellers. They are in a position to do so because they provide interactive content that rises above the noise to command our attention. When in possession of our attention, they can monetize it by charging advertisers to reach us. This has become the biggest cost for many online companies, accounting for 40% or 50% of the investments they make in growing their business.

As Clayton Christensen predicted in the Law of Conservation of Attractive Profits, as one part of the value chain commoditizes, the value is captured elsewhere. As platforms helped generate an economic surplus, aggregators increasingly captured that value – especially Google and Facebook.

While it has become cheaper to start a business, a sharp increase in customer acquisition costs more than offset these savings.

More precarious

But it’s not just high customer acquisition costs that prevent long tail companies from rising to a size where they exploit scale effects. There are other factors at play.

First, the falling costs of starting a business is a double-edge sword. If one online retailer can set up on Shopify, so can any other. Platform companies are lowering the barriers to entry for everyone, making it harder to defend a business than in the past.

Second, if a business model has network effects and a company can grow large enough to exploit them, this market leader becomes more powerful than an industrial-age leader. This is because, unlike supply-side economies of scale, demand-side economies of scale are subject to increasing returns to scale; the more they exist, the stronger they become. And so, where the industrial age gave way to oligopolies with clearly defined industry boundaries, the internet age gives way to winner-takes-most aggregators, large-scale platforms, and a long tail of suppliers operating across the economy in general.

Third, there’s also one important supply-side economy of scale which makes size important even in the absence of network effects – and reinforces them where they exist. This is the ad score. Basically, the bigger a company gets, the cheaper its relative cost of customer acquisition becomes because it pays a lower cost per lead thanks to a higher ad score (the algorithm that advertising platforms like Facebook and Google use to calculate the likelihood of a customer clicking on an ad).

Effectively, the post-fixed cost digital economy is one where is it simultaneously cheaper than ever to start a business, harder than ever to defend and scale it, and where the returns to scale have never been more important.

If it was hard to cross the chasm from startup to large, scaled business in the industrial era, in the digital age it is harder still.

So where to next?

Let’s look at strategic options for new entrants, from where to play to how to scale.

Where to play

Marc Gruber, a professor at EPFL and former podcast guest, wrote a book on “Where to Play”. At the risk of grossly oversimplifying the narrative, it argues that companies spend too little time thinking about which market opportunity to pursue – assuming a good product eventually finds a market – and instead provides a framework to select the right market before commencing activities.

Like Marc, we believe it makes sense to invest the time upfront to consider carefully where to play, even more so in the post-fixed cost economy. Marc’s book provides the methodologies for this choice, so we limit ourselves here to explaining the rationale.

In a digital world, where returns to scale are bigger, incumbents will be harder to displace. Therefore, it follows that any startup should focus either on creating a new market or, more likely, on market blind spots: the niches where consumers are underserved or overserved.

Underserved and overserved markets

In the digital age, underserved markets are likely bigger opportunities than in the past because geographical limitations are removed. A micro market in one country might be a big market when addressing all countries collectively.

B2B marketplaces are a classic example of this phenomenon.

While there are B2C marketplaces for seemingly everything, many entrepreneurs overlook B2B marketplaces because they seem less scalable. They think that it will be difficult to build a big business if your buyers and sellers are very specialized; that there won’t be a generalized pull effect. Buyers of fish are unlikely to be drawn to a specialist marketplace for, say, cement and building materials. But when you are dealing with a global B2B vertical, a two-sided network is more than sufficient to build a massive business: the wholesale fish market, for example, is worth USD150bn!

Another reason B2B marketplaces are sometimes overlooked is because it can be a long game. Many of the businesses we work with are patiently helping incumbents digitize their offering as a precursor to enabling one-to-many transactions. But their ultimate goal is to become a platform for enabling a many-to-many marketplace.

Trade Ledger Business Finance Lending Platform

There are also plenty of opportunities to target overserved customers. As Gary Pisano discussed on another episode of Structural Shifts, companies often push so far with innovation with an existing product or within an existing business model that they overshoot customer demands and leave themselves open to disruption from new entrants providing more user-friendly products or offering more convenience. He gives the example of subscription-based razor blade services like Dollar Shave Club disrupting the overengineered and expensive Gillette razors (“I can only shave so close before it’s scary!”). But this concept of overshooting is especially prevalent in B2B software where, in order to meet the enterprise buyer’s demands, traditional companies have overshot the demands of the end user creating the opportunity for disruptive innovation. This idea is brilliantly expressed in the following excerpt from an a16z article:

“Since effective top-down sales require a highly choreographed (and costly!) dance between pre-sales and the customer, product teams are incented to add more nobs to the product so these teams can sell more value and extract more dollars. Vendors get crossed off the list in vendor discovery if their product doesn’t check all the right boxes for the enterprise buyer, even if many of the boxes don’t actually deliver any value. This often creates a vicious cycle where more complex products give rise to longer sales cycles for more dollars, which then incentivizes even more complex products. For any user of legacy enterprise software, it doesn’t take long to realize that designing a seamless user experience is by no means a top priority for the vendor.”

Direct to consumer

Targeting underserved and overserved customers is what Clayton Christensen refers to as “disruptive innovation” and, as he tells us in the Innovator’s Dilemma, disruptive innovation is about simpler and cheaper products, but it’s also about marketing:

“disruptive technology should be framed as a marketing challenge, not a technological one”

This is even truer today than when Christensen wrote it because digitization opens up new routes to customer. As a result, product, monetization and customer acquisition have to align seamlessly around these new distribution opportunities.

The big trend is direct-to-consumer.

In the retail space, this mostly refers to the phenomenon of avoiding any intermediation – retailers or wholesalers or even any physical retail footprint – to sell directly to the consumer.

In the enterprise space, direct-to-consumer is different. Historically, it was not worth going directly to end users because they didn’t have much influence – or budget. Therefore, it was necessary to go through procurement teams and the choreographed dance of RFI, RFPs and workshops mentioned above.

But what is changing now is that technology products are not just sold directly, but are consumed directly. This makes software-as-a-service a much more disruptive phenomenon than people think: it’s more than a cheaper deployment method, it is a way to circumvent the central buying function and reach the end user.

In this context, it’s clear SaaS companies should have products marketed to end users, simple enough for them to consume without heavy configuration, and priced so they won’t appear on the central procurement team’s radar (e.g. freemium models to test and deliver value ahead of the paywall).

Slack is the example many cite. It markets directly to end users, who can try it for free. Once it has taken hold in an enterprise, it spreads virally thanks to strong network effects (even across enterprises). All the while Slack reaps the benefits by having a pricing structure that reflects usage.

Some argue that it’s harder to make this bottoms-up, direct-to-consumer approach work in areas like fintech, where regulation is important and IT security teams have more muscle. But we see it happening everywhere.

One fintech example that we came across recently, in the context of our upcoming wealth management report, is Hydrogen.

Hydrogen offers a classic bottoms-up approach: a user can provision for themselves a free sandbox environment from the Hydrogen website, pre-integrated with the services they’ll need (like Plaid). The customer only begins paying once they cross certain thresholds, such as API calls. In addition, that also take a jobs-to-be-done approach to solving end user problems by offering discrete services as no-code plug-ins to existing applications, meaning an end user can add a service like tax optimization in minutes.

Blake Bartlett OpenView partners quote

Avoiding the aggregator tax

Going direct to underserved or overserved consumers is the new playbook for disruptive innovation, but it doesn’t mean companies can avoid the aggregator tax. In fact, costs just get reallocated: in retail, CAC is the new rent, while in enterprise, CAC is becoming the new senior sales rep.

Nonetheless, while unavoidable, businesses can minimize the aggregator tax.

One way is to invest in brand.

A lot of startups seem to believe investing in brand is a luxury. We don’t agree. Marketing is like a pump: first, you have to fill it, if you want to draw it down. Sure, you can generate some leads from well-targeted paid campaigns, but it’s not a sustainable endeavor and you’ll end up paying more to aggregators over time. Instead, you want to run paid campaigns into a customer demographic that’s heard of your company and thinks positively about it, which will improve your ad score and lower your ad cost.

You should also invest in data. Going direct to consumers means you know more about your customers than your industrial age predecessors ever did. It’s critical to capture this information in order to:

– build proprietary routes to customers

– learn more about your users to better target and to aid self-discovery through recommendations

– learn how consumers use the solution so you can constantly improve the utility of the product, everything from ease of purchase to completeness of solving user’s problems.

You must leverage the power of networked buyers.  At the most basic level, your product should be differentiated enough that customers will want to advertise it on your behalf. That customer advocacy might come in the form of a positive review or post, but as former podcast guest Julian Lehr highlights, it may also come in the form of signaling.

In addition to advertising, the networked customer can be an acquisition channel.

Wherever possible, you should try to build into your solution the viral features that make the product better when it’s used together with others (e.g. messaging), that lead to customers acquiring other customers. And, even when it’s not possible to build these viral features into the product, it’s possible to build them around the product. A Nike running shoe has no inherently viral features, but the community it has built around its products, the millions who share fitness information, definitely does. And it’s not just consumer brands that can create communities. Consider Salesforce, for instance, which has a community of over 2 million organizing events and sharing content. This attracts others, but also binds together the users in a way which makes it hard to leave the community (by choosing a different product).

Don’t just rent commodities, rent luxuries

If you’ve read this far, it probably won’t come as a surprise that we advocate for renting commodities. Don’t buy your own servers, for example, or write your own accounting software. This will keep operating costs low and variable.

However, we also advocate for renting specialist skills. It allows more cost flexibility and avoids underutilization, but it also reflects a structural shift.

The best people increasingly don’t want to work for a single company. They like the variety and the speed of learning that comes from working across multiple companies and projects. And, platforms are emerging that go further than just matching companies with freelancers – platforms that put together, manage and take responsibility for (the output of) interdisciplinary teams. Effectively, they give businesses greater flexibility and quality at scale and specialists the security and freedom to keep learning.

Achieving internet escape velocity

Brett Bivens, a venture capitalist at TechNexus, came on the Structural Shifts podcast earlier this year to talk about his theory of “Internet Escape Velocity”.

Essentially, internet escape velocity is what happens when a company successfully executes the strategy playbook described above. That is:

– it identifies an underserved or overserved niche

– it leverages internet distribution to reach those customers directly

– it unleashes a growth loop by combining the reinforcing properties of product, distribution and monetization, and

– it uses data and marketing to avoid the aggregator tax

At that point, it hits internet escape velocity, becoming capable of crossing the chasm of precarious long tail supplier to become an aggregator itself, using the pull of its loyal customer base to pull in more suppliers or to launch new own-label services. Brett uses the example of Spotify, which he describes as follows:

“over time, as they expand and gain leverage, podcasts are a higher margin business, social products are a higher margin business, marketplace products are a higher margin business for them. And so, by owning the consumer demand via the lower margin streaming business, they have the opportunity to expand into those areas.”

When a company hits internet escape velocity, it also has the option to invest in fixed assets. As we showed in a paper we wrote with Dave Galbraith in 2016, internet-era companies tend to become asset heavier over time as they seek to entrench their position and deliver better customer fulfillment. But the critical point is that they invest after they achieve a sustainable route to customers. Assets grow like the roots of a tree, downwards from distribution rather than upwards from production.

If, however, a company that hits internet escape velocity doesn’t want to invest in fixed assets, the good news is that it’s never been easier to rent supply in the post fixed-cost economy.

What we learned from doing the Structural Shifts Podcast

What we learned from doing the Structural Shifts Podcast

What the world looks like when seen through “a great series of conversations with people who are building the future”
September 2020 | 5 minutes read

In the break between seasons — season 2 starts again on September 24th — we thought we’d take stock and reflect on some of the things we’ve learnt from making our podcast.

When we started Structural Shifts (initially without a name, that came from episode 14), it was just an excuse to reach out to and chat with people whose life and work we found interesting. What surprised us was two-fold: firstly, that people liked it and recommended / introduced other people we should interview, making the whole endeavour sustainable; and, secondly, that many of the evergreen topics we set out to explore bubbled up to the top of the people’s agenda and consciousness.

The fundamental transformations that used to quietly shape our world — over years or decades — suddenly became topics for mainstream conversations. The acceleration everyone’s talking about — we felt it too and it has influenced how we make and develop the podcast.

It’s safe to say that doing the podcast has taught us valuable lessons.

“I found this podcast borderline post-modern, and refreshingly frank. A profound look into what’s next. Love every bit! The guests, the music, the format.” — Simone Cicero, Co-Creator of Platform Design Toolkit

A crisis can be clarifying

The worldwide lockdown had wide-ranging effects, some of them even on the positive side. For example, it enabled us to interview thinkers we greatly admire, but who are geographically remote — like Rita McGrath and John Hagel — as well as to grow our audience.

In a world already hungry for meaning, the pandemic triggered a pressing need for strategic thinking. First, it made people pause and reflect on what truly matters — for their lives, work, for the planet.

Then, because institutional and private reactions to the pandemic left many disillusioned, they became determined to gain a stronger understanding of big topics — fintechinternet business models, geopoliticsthe climatethe future of work.

We had profound, unhurried conversations with people who are thinking and doing things differently. Their thoughtful observations, distilled from decades of practice and reflection, challenged our received wisdom on a range of topics — from innovation to marketing — as well as encouraged us to entertain contrarian viewpoints.

Instead of a just-do-it mentality, the pandemic reinforced the timeless value of reflection and flexibility, reflexes that all our podcast guests share. If you keep an eye out for it, you’ll notice that in every episode we publish.

Good questions are catalysts for change

Good podcasts depend on two key ingredients: interesting guests and good questions.

Our listeners increasingly took care of introducing us to great thinkers, some of whom — like Brett Bivens or Julian Lehr — we caught on the rise to becoming big stars. And we concentrated on trying to get the best out of the conversations.

In the past six months, we’ve spent a lot more time on research. As our audience grew, so did our sense of responsibility to get the best out of every conversation. Many weekends and late nights were spent reading the books our guests had written, which made us well-prepared — and hopefully improved our the return on our listeners’ time.

Some of the book authors we had invited at Structural Shifts podcast

Our goal was also, for ourselves and our listeners, to delve into diverse topics such as the ethics of technological change or building a safety net for the self-employed. A risk because many podcasts listeners like to keep digging into a given topic like investing, we hoped to create the context for the cross-pollination of ideas, frameworks, and viewpoints that can serve both professional and personal pursuits.

As the inner workings and implications of the networked age leapt into view for the entire planet, we developed an even keener focus on asking questions that help us have better, more stimulating conversations. Questions are essential to decode, deconstruct, and rebuild our vision of the world as it is — and as it might become.

The case for techno-optimism is one of our favorite examples of such a conversation, providing signposts to use when engaging in mainstream conversations around key topics in tech and their society-wide impact.

“A great series of conversations with people who are building the future. Each one is like having a dinner conversation with a smart friend who has come back from a voyage. I listen when driving or jogging — the miles just melt away and I arrive with a refreshed mind.”

It’s easier to connect when you share purpose and focus

Another thing we noticed while doing the podcast, especially in the past 6 months, is that people who share the same principles tend to resonate (or “click”) more easily when having conversations remotely.

It was surprisingly easy to delve into complex topics with them because everyone was eager to dive in. Maybe you’ve also noticed how small talk takes less and less time in online meetings as we have more of them.

This desire to have important conversations, to support clarity and good decision-making translated into our guests sharing personal perspectives more openly.

What’s more, it was easier to connect with new guests who dedicated even more time than before to share their expertise and experiences. We’re grateful for every minute they spent with us!

Capturing attention in a roaring world is a big challenge

As Herbert Simon predicted, a wealth of information gives way to a poverty of attention.

Our response to this has never been to compete on giving information, but to focus on carefully curated insights. A great fan of craftsmanship, we meant for the conversation — except for maybe the couple we did on previewing the post-pandemic world — to be timeless; as relevant now or in two years’ time as they were the day they were recorded

We also found that the lockdown period — or more specifically the extra time that many people gained through not travelling and commuting — opened up more demand for the long-form product we offer.

“Always insightful and informative. It is a relaxed conversation with people who have had interesting experiences and something to say. Ben Robinson, brings out the best in each guest.”

The Structural Shifts podcast remains one of our favorite projects, in which our enthusiasm for the topic and our guests’ generosity combine to help you see farther — and more clearly.

Helping ourselves and our network to move from scalable efficiency to scalable learning and, in do doing, to prosper in our networked age is why we do the podcast.

We hope it helps you achieve the same.

“I really love this podcast series. There’s not much content like this coming out from Europe. Should serve as an example to others” — Bozidhar Hristov

Our thanks to all of our guests and listeners and to Sarah Mikutel, our podcast editor. In series 2, we’ll be back with more mind-expanding conversations, covering the token economy, the future of finance, the end of globalization, the startup community way, the new precariat and much more…

To turn Adversity into Advantage, Banks need to Renovate in Winter

Renovate in Winter

To turn Adversity into Advantage, Banks need to Renovate in Winter

by Ben Robinson | March 30, 2020 | 8 minutes read

Crisis is not the time to stop all IT projects, but to double down on the ones that really matter.

Don’t pull up the drawbridge

Beware risk and opportunity cost

Bag some quick wins

Enterprise Software Stack Systems of Intelligence
How the Banking Enterprise Software stack is splitting

Consider Impact on the future

The Future of Banking
The Future of Banking and the Strategic Imperative

This a data play. It requires understanding customer context (interaction preferences, financial situation, needs) and be able to match to the right offering. In the first instance, financial services companies will do this for their own labelled services, but increasingly — to maximize utility and convenience — they’ll need to do it for third-parties services as well (requiring an extensible product catalog) and intermediating and bundling if necessary (which necessitates managing real-time risk). As a third phase, these same institutions can then orchestrate value between the different parties on the platform, stepping back from intermediating and becoming a system of collective intelligence.

Don’t waste a crisis

Articulate the change narrative

Use stop/go triggers

In summary

The new moat in financial services (and why P. Thiel, not W. Buffett,…

The new moat in financial services

The new moat in financial services (and why Peter Thiel, not Warren Buffett, is the new investment wizard)

by Ben Robinson | July 26, 2019 | 11 minutes read

In the networked age, scale of production is no longer a moat. Instead, network effects are the new moat. Peter Thiel gets this; Buffet doesn’t.

I look for economic castles protected by unbreachable ‘moats’ –Warren Buffett

The quote above from Warren Buffet, a statement he first made in a 1996 investor letter, is one of his most famous. It neatly encapsulates his investment approach: invest in giant companies that can achieve a “moat” by operating at a scale that others can’t reach.

By spreading the fixed costs of expensive, non-transferable assets like machinery or a banking licence, as well as highly-geared operating expenses like brand marketing and regulatory compliance, over a larger revenue base than competitors, these companies could be better known and cheaper. And, if you look at Buffet’s portfolio, it’s full of companies operating in industries with high fixed costs and high operational gearing: capital goods companies like BYD, consumer goods like Coca Cola and, above all, financial services companies like Wells Fargo, Amex and Bank of America.

The investment approach was massively successful — until it wasn’t. In the period 1979 to 2008, Warren Buffet outperformed the S&P 500 by 12.6% a year on average, cementing his reputation as the Wizard of Omaha, the most successful investor of all time. But — a less known fact — since the financial crisis, Warren Buffett has underperformed the S&P. One might be tempted to attribute this relative under-performance to the heavy financial services weighting in the Berkshire Hathaway portfolio. However, while a factor, deeper structural changes are at play.

Problem number one with the Buffett investment philosophy is that, in the digital age, critical mass is within most companies’ reach. Critical mass — or minimum efficient level of scale — is the scale of production a company needs to reach where it won’t have a major unit cost disadvantage compared to its competitors. After this point, diminishing returns to scale kick in, which means that even if a competitor has greater volume it won’t translate into the same order of magnitude differential in unit costs.

However, as we’ve written before, companies can now plug into the scale economies of third-parties like AWS, which spread fixed costs over the volumes of all customers, to get to scale faster. In banking, you see the emergence of banking-as-a-servce providers, like Railsbank or SolarisBank, levelling the field for new entrants. All in all, this means that scale does not represent the barrier to entry it used to.

Scale can become a hindrance

The second problem with Buffet’s investment philosophy is that diseconomies of scale, or negative returns to scale, manifest themselves more frequently and earlier.

In the industrial age, the trick to achieving an unbreachable moat was to produce standardized goods at mass scale and then invest in marketing to create sufficient demand to sell all of these goods. The challenge now is two-fold. Firstly, the broadcast channels that companies used to advertise are being eroded at the same time as there are many more demands on the consumer’s attention, making it harder to engage in the same type of mass-marketing.

The second issue is that, since consumers are now online, we can know much more about them, as well as have a direct relationship with them. This means that at the same time as it’s become possible to operate profitably at smaller scales of production, it’s become possible to produce goods which cater to smaller customer demographics, and to reach these customers directly — which explains the rise of artisanal goods and direct-to-consumer brands.

But, for digital goods, it goes further, artificial intelligence increasingly allows platforms to match services to customers as well as personalize services to each customer.

To put it another way, in the digital age, the mass consumer is dead.

The new moat

This begs the question, is it still possible to create a moat in the digital age? One answer could be that the idea of a moat is obsolete, a relic of the industrial age, sort of what Elon Musk said when he challenged Warren Buffett recently. But, the reality is a new moat is possible and it’s the diametric opposite of what came before.

Scale isn’t the barrier to keep out new entrants, scale is what attracts new entrants to work with you. Scale doesn’t allow you to push a mass produced product to the mass consumer, scale is what enables you to tailor an individualized product to every consumer.

“I think moats are lame. If your only defense against invading armies is a moat, you will not last long” – Elon Musk

This definition of scale is one that accepts and capitalizes on the new realities of the digital age. Maximizing production scale by itself is less of a competitive advantage and, increasingly, a competitive disadvantage. But the fact that consumers and business are connected means that a new competitive advantage can be achieved by maximizing network size.

Where a network has strong social engagement, like Facebook, adding more users increases the value of the network for everyone. Where a network matches buyers and sellers, like Amazon, increasing the network size increases choice and, by extension, value. Where a platform analyzes data to serve up the best results, like Google, the more data that comes from adding users, the better the results become. And most platforms are a combination of these social, two-sided and data network effects.

What is more, the new moat is a superior moat. Supply-side economies of scale, while a formidable barrier to entry in the industrial age, always suffered from diminishing returns.

Demand-side economies of scale, however, are subject to increasing returns to scale since more users create more value for other users in a self-reinforcing positive cycle. This is why in markets where network effects are strongest, there are winner-takes-all dynamics.

Does this mean that supply-side economies of scale are irrelevant? Not at all, as we wrote a few years ago, these platforms based on demand-side economies of scale (network effects) often become asset heavy as a way to reinforce the strength of these network effects and maximize profitability. But the difference is that maximizing scale economies was not the goal in itself. Instead, these companies found a route to mass adoption and, from there, put in place the assets to sustain the network. In other words, a business grows its assets top down like the roots of a tree.

If the new moat is to achieve network effects, how can these be achieved in banking? In our mind, this is probably asking the wrong question. Banking is inherently a transaction-based activity. This makes it unsuitable to most types of network effects.

For example, most companies that have tried to build social network effects into banking, either as part or whole of their USP, have failed. We don’t want to chat with our friends specifically about money, we don’t want to share all of the information on our assets and liabilities. Which means that, although the new banks sprouting up might be cheaper and more convenient than what came before, they aren’t able to arrive at meaningfully and sustainably lower costs of customer acquisition numbers once they’ve gone beyond the early adopter audience.

It is possible to create marketplaces for financial services, but because banking is transaction-based (and fundamentally not a social activity), the surface area around which to create a marketplace is limited. Basically, we don’t spend much time on banking apps, which makes it difficult to introduce us to other products and services, which we then don’t purchase frequently anyway.

This podcast was recorded at FinTECHTalents’19 Festival: we’re exploring the potential of unleashing network effects in financial services. Ben Robinson is joined into the conversation by: Evgenia Plotnikova (Partner @ Dawn Capital); Martin McCann (CEO at Trade Ledger); Oliver Prill (CEO at Tide Business Banking).

Some banks and fintech providers get round this by targeting specific demographics and then giving them the tools they need to run their business/life, such as Tide, which understands that freelancers and small businesses will send invoices and submit expenses more frequently than they’ll apply for a loan. But, these business are niche.

When this is attempted on a bigger scale, it comes back to the same problem of unit economies: high CAC in the absence of social network effects and low lifetime value in the absence of the engagement.

The mistake we think many people make when they think about banking and network effects is to apply the following logic: banking is a massive market, therefore we must target it and find a way to generate network effects. We believe it is smarter to turn the logic on its head and think about how to put banking into channels and services that have high engagement and strong network effects, what Anthemis calls “Embedded Finance”.

As Amazon is showing, the goal isn’t picking off a few high value revenue lines, but making value flow ever more easily within the Amazon ecosystem, removing friction and making it easier for buyers and sellers to trade. Similarly, the Alibaba and WeChat models both serve a higher purpose: to embed financial services into people’s lifestyles.

The direction of travel can go in the other direction too: that is, starting with banking and seeking to embed it in other services with higher engagement. This is what Moneo is trying to do and what TinkOff Bank in Russia has done so successfully. Through partnerships as well as launching its own products, Tinkoff has created a super app akin to WeChat in China where consumer can do everything from booking theatre tickets to giving their kids chores.

But, in general, it seems more probable that banking will get embedded into other services than vice versa for the reasons already stated: it’s a high CAC and low engagement starting point from which to build out an ecosystem or Super App.

That doesn’t mean that there won’t be plenty of opportunities to build big businesses in banking, that enjoy strong network effects. But, to our mind, these are unlikely to be directly client-facing.

Earlier this year, we wrote a piece about systems of intelligence in finance. The piece looked at these systems mostly from a supply-side and architectural standpoint, arguing that solution architecture needed to change in response to the split of distribution and manufacturing and to capitalize on open banking. It concluded that systems of intelligence would emerge as the most valuable parts of the Enterprise IT value chain.

Here we make the same argument, but from more of a market standpoint. If we accept that banking will become increasingly embedded in third-party services and channels, it doesn’t necessarily follow that, as many people argue, banking will become completely commoditized.

As markets digitize, two types of intermediaries tend to emerge: those that seek to internalize network effects by commoditizing supply, aggregators like Amazon or Facebook, and platforms that externalize network effects by empowering suppliers, like the Apple AppStore or Shopify (Ben Thompson sets out this distinction very well in this much recommended post).

In financial services, then, the same pattern will play out: aggregators like Amazon will commoditize financial services suppliers, while platforms will emerge to intermediate between suppliers and distributors in a non-zero-sum, value accretive way. These platforms will be systems of intelligence.

Systems of intelligence are evolving. Today, most systems of intelligence are deployed for individual clients and with the end of digitizing services. But this is just the first step. Digitizing services makes them consumable through non-proprietary bank channels, but it also generates a new stream of data that can be used to make the services better fit consumer needs. So the next step will be that systems of intelligence will then use that data to help providers more intelligently price and package financial services.

But once that has been achieved, the opportunity will exist to then serve up the right service to the consumer at the moment of need, which mean systems of intelligence become systems of network intelligence, matching the needs of consumers with the inventory of suppliers in the smartest way.

This is the evolution we observe happening at companies like additiv, Assure Hedge and Trade Ledger. Trade Ledger is digitizing the origination of credit services so that lenders can supply credit at the right price and with the speed needed by fast-growing SMEs. But beyond that, it is able to use data to give lenders a real-time picture of asset quality, even for intangibles assets, allowing lenders to offer new types of services better matched to changing customer needs. But, ultimately, the opportunity exists to then link lenders with the different players in the ecosystem, helping embed banking into whatever is the right channel to serve the customer at the point of need. Martin McCann, Trade Ledger CEO, puts it well in this excellent blog:

“Within business finance, the opportunity exists not just to connect banks with their customers, but banks with banks, corporates with corporates, corporates with complementary third-party services providers and so on.”

If Warren Buffett has missed the shift from supply- to demand-side economies of scale, there is one investor who most certainly hasn’t. That is Peter Thiel. His investment in Facebook, a business underpinned by massive network effects, made him a billionaire. Conversely, Buffett passed on Facebook, like Google and Amazon, because he couldn’t get comfortable with the valuation, saying “I didn’t understand the power of the model as I went along.”

And the performance of the two investors also couldn’t be more divergent. Whereas Buffett has underperformed the S&P since 2009, Thiel’s Founders Fund has more than two-fold outperformed the VC fund industry since 2011 (the only figures we could find in the public domain). Since 2011, the Founders Fund is up by $4.6 for every $1 invested.

And where is Peter Thiel investing now? If you look at his holdings, there are many B2C companies there for sure. But, more than anything, there are systems of intelligence — across many industries, but especially in financial services. This leaves Peter Thiel well-placed to capitalize on what Matthew Harris, another venture capitalist, sees as the fourth major wave of digitization after internet, cloud and mobile; one that, in his view, will create more value— $3.6 trillion — that its three predecessors combined.

So, you don’t need to believe us that systems of intelligence are the next big thing. Just look to Peter Thiel, the new investment wizard.


Do Traditional Banks Really Still Own the Customer Relationship?

Do Traditional Banks Still Hold Customer Relationship

Do Traditional Banks Really Still Own the Customer Relationship?

by Emma Wadey | Dec 11 2019 | 8 minutes read

Conversations and sessions at FinTECHTalents last month covered many hot topics, but one theme dominated: the customer relationship is at stake.

Banks continue to draw a false comfort from retaining customer current/checking accounts, without realizing that data, engagement and monetization opportunities are seeping away to other players.

Despite many banks having already embarked on digital transformation projects and despite many having launched an array of fintech/tech partnerships and initiatives, more is needed for them to prosper in the digital era. During FinTECHTalents, Jim Marous put it frankly:

“Banks have willful blindness; they don’t realise that they are losing business. Just because bank customers don’t switch doesn’t mean that they love you.”

Jim Marous, Digital Banking Report CEO, The Financial Brand Co-Publisher and Forbes Contributor speaking to Ben Robinson of Aperture.co

This ‘blindness’ comes from studying attrition rates which don’t show the bigger picture. Jim explains how this gives false comfort by talking about his own banking arrangements: “With my business bank, I still give deposits and get withdrawals, but most transactions are handled by PayPal, they understand my business intimately. PayPal can offer me a pre-approved business loan instantly. If I went to my bank, it would probably take me 4 maybe 5 days to get approval and that’s assuming that they will approve it at all. I can get this immediately from PayPal. My bank may have my business, but they don’t have my relationship.”

This view was further reinforced during the keynote session on Day 1 of the event when Aritra Chakravarty, Founder and CEO of Project Imagine and Dozens highlighted that:

”The number of customer accounts a bank has doesn’t reflect customer behaviour. People change partners more regularly than their bank; just because you have a large customer base it doesn’t mean that they are engaged and profitable.”

In short, then, for the incumbent banks, headline customer might hide the extent to which their business are being disrupted by new competition. So, what is needed for banks to truly engage with the millions of headline customers?

“We spend 3 hours a day on our mobile phone. On average we look at our phones around 80 times. We scroll through 300 feet of news-feed every day, that’s the equivalent height of Big Ben!” said Russell Pert, Industry lead, Financial Services at Facebook on Day 1 of the conference before concluding:

“people want to do their banking through the services where they live their lives.”

The point being made here is a profound one. It is easier to embed financial services into a service where customers already have a lot of engagement than trying to create engagement in a banking channel. Think how many times you visit, say, WhatsApp (another Facebook property) compared to your banking app.

Also, where banks are using artificial intelligence (AI) to understand customers better, they’re often introducing more, not less friction into the customer relationship. As innovation and entrepreneurship professional at RBS, Roshan Rohatgi said in the Behavioural Science panel,

”Stopping a card transaction due to a possible fraud risk may protect the customer, but can lead to embarrassment and negativity with the bank.”

Bradley Leimer and Theodora Lau, Co-Founders of Unconventional Ventures speaking to Ben Robinson of Aperture.co

And it has never been easier to embed banking into other services. Open Banking opens up access to customer transactional data, creating a unique opportunity for third-parties not only to serve embed banking into their services, but also to do it more personally by meshing up contextual and locational data with bank data. As Bradley Leimer put it to us,

“The promise of open banking to a High Street bank is a degradation of their relationship with the customer. For a fintech, it’s an inroad into a relationship. For a tech provider, it’s a way to take more data in, understand and profile a customer better, and further entrench them into the ecosystem.”

So should banks despair? Not all, sometimes the answer is to go back to basics, rather than to try to emulate Facebook or WeChat.

Roger Vincent, Chief Innovation Officer at Trade Ledger pointed out there is a global funding gap of £1.2 trillion, defined as the shortfall between the capital SMEs require to grow their businesses and what they receive in lending, and that gap continues to grow.

Roger Vincent, Chief Innovation Officer at Trade Ledger

The problem, says Roger, is that

“the economy is becoming increasingly intangible, but banks aren’t yet comfortable lending against these intangible assets, which requires them to capture and process new datasets in real time.”

But taking advantage of new datasets to get credit flowing to SMEs is exactly the kind of opportunity banks should be seizing with digitization.

Likewise, helping to create financial services that are better moulded around people’s changing lifestyles is another major opportunity. As Dharmesh Mistry put it, the way to create a deeper relationship with customers is give them “everything they need for a given context”.

He used the example of a freelancer: banks should adapt their own services, for example, by giving access to credit to top up volatile incomes, but in addition they should provide all of the ancillary services that a freelancer might need such as filing taxes, raising invoices, submitting expenses and so on.

James Perry of BUD at FinTECHTalents
James Perry, Head of Client Delivery at Bud speaking to Ben Robinson of Aperture.co

This might entail a move to more of ecosystem-based business model, but platforms are emerging to facilitate these models. Trade Ledger is building a platform that could easily facilitate this, while Bud is doing this now. As James Perry, Head of Client Delivery at Bud, says:

“We open the platform where banks don’t have to do procurement for 8 to 10 providers, you only have to do it with Bud. We open the door to a network and allow lots of different providers to come “

But going back to basics even further, the route to more meaningful customer interaction may lie simply in helping customers to make better decisions.

Banks sit on rich datasets, but when they’re used well (if at all), it tends to be in the pursuit of up-selling and cross-selling. In part the issue is that customers might get the wrong products for their needs and also that they might find it intrusive — as Poojya Manjunath from Lloyds Banking Group said within the Behavioural Science panel,

“when a personalised message forces the client into a transaction/money exchange that’s when the customer will often back off.”

But the issue is bigger, the products might end up reinforcing bad behaviours.

Like the Facebook algorithm that serves us up more of the content we like, serving up more loans to an over-spender can perpetuate their problems and amplify the cognitive biases from which we all suffer. Instead, banks should help customers to understand themselves better and help them to achieve their long term goals.

Dr. Peter Brooks, Chief Behavioural Scientist at Barclays, put it well on the Behavioural Science panel,

“If our customers aren’t managing their money well, it is our job is to help them to manage it better. The result is that they will become better customers and their lives will improve and they will become stronger economically which helps both banks and society as a whole.”

And he went on to say that the problem often sets in with the product design, “the typical focus of a product manager is about delivering the end product and launching, rather than how to design it in the first instance. You need to get the design right first. Look at the customer journey, look at how the customer uses the product and ask if it encouraging positive behaviours.”

Pol Navarro, Digital Director at TSB with Ben Robinson of Aperture.co

In terms of using data to put the customers’ needs first, Pol Navarro, Digital Director at TSB, used a good example from the SME space.

“There are lots of opportunities to anticipate things. Imagine with Open Banking where you can easily get data from all your accounts wherever they are, and combine that with your accounting software in the cloud, banks can easily help customers predict their cashflow, for example, saying that in two weeks there are all these payments coming but you do not have sufficient funds and therefore something must be done whether it be taking out a loan or bringing money in from another account to avoid an impact in your cashflow.”

The imperative to make this shift to helping customer make better financial and commercial decisions was underlined starkly by Bradley Leimer, who sees it as the existential challenge:

“Banking is an industry today that continues to take profit rather than give profits. It’s a value proposition that’s about how much value I can derive from you rather than how much money I could derive for you. That to me is the biggest opportunity — along with a long term view — that the industry needs to shift or it will completely give up and recede the relationship entirely to big tech and a series of platforms that banking itself will no longer be a part of.”


Any bank looking at headline customers numbers and giving itself a pat on the back should be wary that disruption continues to abound. There remains the big threat, heightened since the advent of Open Banking, that the large technology platforms will eat their lunch.

But the challenge seems to be at one more profound and simpler. Banks more than anything need to change philosophy by promoting customer need above their own. Practically, this means using data to help customers understand themselves better and, in turn, helping introduce them to the services they’ll need and the banking services to support it. Trying to be Facebook won’t work, just try to be better banks.

To see the full interview with James Perry from Bud click here.

Digital Era Banking Systems

Digital Era Banking Systems of Intelligence

Digital Era Banking Systems

by Ben Robinson | Dec 17, 2019 | 11 minutes read

The banking software market is reconfiguring around the demands of the digital economy — and value is accruing to new systems of intelligence

In Clayton Christensen’s Law of Conservation of Attractive Profits, he talks about the “reciprocal processes of commoditization and de-commoditization” that occur in technology value chains when product architectures change:

“The law states that when modularity and commoditization cause attractive profits to disappear at one stage in the value chain, the opportunity to earn attractive profits will usually emerge at an adjacent stage.”

Our view is that this same process of commoditization and de-commoditization is playing out in the market for banking software. Changes in technology (cloud and AI) as well as changes in regulation (real-time payments and open banking) are causing a formerly integrated system to become modularized and new players are emerging to exploit this shift— new core banking systems but also new systems of intelligence that, akin to operating systems, orchestrate value across their networks.

A brief history of banking software systems

When we look at the technology debt in the banking industry, we might forget that banks were once IT pioneers. Banks were among the first industries to use software, adopting branch accounting systems to keep records of customer bank balances as well as to calculate interest, fees and tax.

But, because banks were such early adopters, they wrote their own applications — there was no software industry at that time from which to buy applications. This might not have been a problem except that 1/banks didn’t stop writing applications when commercial software arrived and 2/they have kept and extended those same branch accounting systems ever since — producing the kind of unwieldy system architecture depicted below.

A typical universal bank system architecture (source BCG)
A typical universal bank system architecture (source BCG)

Smaller and newer banks (from the 1980s onwards) skipped the branch accounting system and instead moved to packaged software, integrated core banking systems. These systems had many advantages: they could run on much cheaper hardware (and software) than S/360 mainframes; they could keep separate records based on parties and products (so that it was possible to have the same customer across branches and products and to provide consolidated views of customer holdings); and, they were integrated front-to-back — from the teller to the general ledger — meaning that changes could be applied across the whole system, reducing significantly both the run-the-bank and change-the-bank costs. And so banks running integrated core banking systems were in a position to achieve scale economies as well as to cross-sell effectively and, when product builders were added, to launch new products to market quickly.

System S/360

Bank systems in the internet era

With the arrival of the internet, banks opened up proprietary channels (apps and internet portals) which allowed customers to query their own bank records and set up payment instructions. But that was the extent of the upgrade: neither branch-based accounting systems nor integrated core banking systems were significantly re-architected in response to internet banking. In fairness, some core banking systems were already real-time and most have been scalable enough to cope with the rise in customer interactions. But the situation is changing.

Integrated to Internet Banking

The open banking era

In most industries, product manufacturers have a choice about whether or not they sell through distributors. In banking, in Europe and an expanding number of other places, this agency is being lost. Open Banking legislation is forcing banks to put their inventory online by obliging them to share customer transactional data with third parties (where customers give consent). In effect, banks face a stark choice: become aggregators of own-labelled and third-party products or risk being disintermediated by other aggregators, whether from inside the industry or outside (e.g Amazon or Alibaba).

The Open Banking era
CB Insights showing the spread of Open Banking legislation across the globe

In addition to open banking regulations, most jurisdictions have enacted — or are enacting — legislation related to real-time payments. This will likely have a profound impact on value chains outside of just banking — for payment schemes, for instance — but in banking it will usher in an era of not just higher volumes, but lower fees per transaction, requiring a step change in scalability if banks are to be able to keep up — and to do so profitably.

In response to these two changes, the integrated nature of most banking systems is unsustainable. If banks are to distribute third-party as well as own-labelled products, they will need a separate system for distribution. If banks are to cope with the demands of ever-increasing payment volume as well as continually rising interactions, they will need to separate channels from manufacturing to boost straight-through processing (STP). To put this last point in context, if a bank moves from 99% STP to 99.9% STP, this would likely translate not to a 1% reduction in costs but more likely a 10x reduction in costs.

The future model for banking systems could be the retail industry where the major players have all created distribution systems independently of accounting systems. But there is precedent that is much closer to home: when regulators pushed for higher STP in capital markets in the early 2000s, the industry very quickly split between front office (the buy side) and middle office (the sell side) and systems were re-architected accordingly. And, whereas in capital markets there was a push for faster transactions, in banking there is both a push for faster transactions and a push to open up the industry to new competitors. As such, this split seems all but certain.

Systems of intelligence

At the moment, there is a tendency to try to put more and more logic into banking channels, but this is flawed. Proprietary banking channels are likely to disappear as banking becomes more “embedded” in other products and services (such as WeChat), making these investments increasingly pointless.

Instead, this logic needs to sit somewhere else, where it can be used to produce a high level of engagement across multiple channels, where it can be combined with data from multiple other parties and systems, and where it can handle inquiries independently of orders and order entry asynchronously from order execution. This somewhere else is a system of intelligence.

Systems of Intelligence Basic.png

We borrow the term “system of intelligence” from this seminal article from Jerry Chen, a Partner at Greylock. In his article, Jerry describes how application software is splitting into three layers: systems of engagement, systems of intelligence and systems of record. If we apply the same taxonomy here, customer channels are the system of engagement (although we prefer to use the term system of interaction because we see these as thin clients, integrated using REST principles); core banking systems are the principal system of record; and distribution systems are the systems of intelligence.

In Jerry’s article, he highlights the importance of technology changes in creating the opening for new systems of intelligence. One is cloud in that it adds a new level of scalability on which to build these systems, but the more important is AI, which fundamentally changes the amount of data we can process and the insights we can draw from it. Echoing Clayton Christensen, Jerry Chen says that, because of AI, 

Systems of intelligence in banking

In Jerry Chen’s article, he makes the point that providers of systems of record often have an advantage in creating systems of intelligence because they have privileged access to their own data. This is true for banking also, although open banking removes part of this advantage (for transactional information). A bigger advantage for incumbent banking software comes by dint of serving hundreds or, in some cases, thousands of banks; creating the pull to attract other data sources to mash up with data from their own system of record.

The playbook for incumbents, regardless of industry, remains Salesforce. A lot of people get excited about the Salesforce AppExchange, a marketplace for complementary applications, since it created a platform business model with two-sided network effects. But at least as important in amassing the data to become a system of intelligence are Force.com (now the Lightning Platform), its platform-as-a-service on which third-parties build native applications, and Mulesoft, its API integration platform, which allows third-parties to integrate their existing applications and datasets. Lightning and MuleSoft don’t just provide a route to data but lock-in and switching costs around that data. And then, working on this data and giving an additional incentive to share the data is Einstein, the Salesforce system for artificial intelligence, deriving insights for Salesforce and its customers. We would argue that it is ensemble — MuleSoft, Lightning, AppExchange and Einstein — that makes up the system of intelligence.

Salesforce’s system of intelligence

And so in banking it is unlikely that creating an AppExchange equivalent will be sufficient to create a system of intelligence.

It is likely to need all of the above components: an API platform, PaaS, AI and an app store. And let’s not forget that because of open banking, the distribution play for a banking system of intelligence goes further than distributing apps — to helping banks distribute third-party banking services.

This extends the list of necessary capabilities to include, for example, order management and an extensible product catalogue, as well as customer engagement tools that, among other things, would help identify the right content and services to offer up to customers at the right time and over the right channel.

In addition, we believe a key component of successful systems of intelligence will be to share intelligence across their ecosystems.

The idea, very well articulated in this blog by Peter Zhegin, is that the source of competitive advantage (the moat) is constantly shifting. Processes— and software — are declining in importance relative to data. And within data, Peter argues that the moat is moving away from data collection — amassing the largest possible data set with which to train a model that benefits the company’s product — to improving the collective intelligence of the network.

In banking software, therefore, advantage is moving from having the best application to having the most value-added ecosystem around that application (app store) to helping customers make smarter decisions (system of intelligence) to helping the whole ecosystem perform better (a system of network intelligence).

As a practical example, this could mean moving from providing independent banks with the best credit scoring model to facilitating an open banking network.

Commoditization and de-commoditization — the emerging vendor landscape

As in any market where the value chain is being broken up, there is likely to be a significant shake-up in the competitive landscape for banking software. The keenest fight will be to dominate the market for systems of intelligence, since this is where value will accumulate. But we are also seeing new entrants into the core banking market.

Since the system of intelligence aggregates logic away from the system of record, the system of record is required to do less. Effectively, the most important characteristics of the system of record will increasingly become speed and cost.

As a result, these systems will be re-architected for speed (into microservices) and they will be deployed in the public cloud. And it is no surprise, therefore, that we are seeing the arrival of new cloud-native core banking systems such as Mambu, one of the first and the most successful so far.

Furthermore, as the need for scalability increases, we predict that we may even see these systems further fragment, with the accounting capabilities (fees, limits, etc) splitting from the manufacturing capabilities, which, incidentally, seems to be how Thought Machine is architected.

Digital Banking to Real-time Banking

As regards the systems of intelligence, we foresee a three-player race.

The first players are horizontal systems of intelligence. Insofar as the system of intelligence is like an operating system (nCino actually calls itself “a revolutionary bank operating system”) — providing a consistent set of interfaces, mashing up and running analytics on multiple data sets — these systems do not need to be as domain-specific as systems of record.

Accordingly, there is the potential for horizontal players to make bigger inroads into banking software — such as Salesforce, which already has good traction in wealth management and is pushing aggressively into retail banking.

The second players are the incumbent providers of systems of record. Many are well-positioned — having the pull of large customer bases and investing in the tech infrastructure. Finastra, for instance, has assembled many of the underlying components of a system of intelligence — an app store (Fusion Store), a PaaS (Fusion Operate) and an API platform (Fusion Create). The bigger question is likely to be whether management at these companies will place enough importance on a platform strategy to be able to overcome the immune system challenges.

The third set of players are the new entrants. With a couple of exceptions, such as nCino, these are chiefly vertically focused: for example, Additiv is focused on wealth management (and increasingly credit), The Glue is focused on retail banking, and Trade Ledger on lending. While there are likely many more shared than vertically-specific components in banking systems of intelligence, which makes a cross-banking strategy possible, an initial vertical focus makes sense to build a network quicker (the micromarket strategy to overcoming the chicken-and-egg challenge) and conforms with the pattern of disruptive innovations, which are typically commercialized first in smaller and emerging segments.

To sum up…

In response to regulatory and technology changes, the banking market is undergoing a digital upgrade with new networked business models emerging.

The most successful banking technology companies will be those that align themselves with — and enable — this change.

Our bet is on those that can create the best systems of intelligence.

What is a Challenger Bank for?

What is a Challenger Bank for?
The battle is on to see which firms will dominate the internet-era banking market

What is a Challenger Bank for?

by Ben Robinson | Sep 18 2019 | 13 minutes read

The last couple of months have seen JP Morgan close its digital bank Finn, as well as BPCE close the UK arm of its digital bank, Fidor. This has led to a lot of speculation about whether it’s possible to run a disruptive business within an incumbent organisation. But, it also raises a simpler point. When does it make sense to launch a challenger bank?

Challenger banks are definitely in vogue. In the aftermath of the financial crisis, regulators sought to introduce more competition into their domestic banking markets. One of the most progressive was the UK regulator, which lowered capital requirements for start-up banks as well shortened the application process, leading to a influx of new competitors. But many jurisdictions, including the UK, also introduce Open Banking legislation, which obliges banks to share customer data with third-party providers, also increasing competition.

The Open Banking era
This graphic from CB Insights shows the spread of Open Banking legislation across the globe

In addition to the regulators’ efforts, technology has also lowered barriers to entry. Infrastructure services like AWS have reduced start-up costs while smartphones have opened up distribution at the same time as making possible new digital features, such as remote, paperless customer onboarding.

The result has been an explosion in the number of new companies offering banking services — 17% of all companies having been created since 2005, according to Accenture.

Accenture Beyond North Star Gazing Open Banking
Source: Accenture, Beyond North Star Gazing
Challenger Banks a Global Phenomenon

But digital banks are not just banks without branches. They are offering something different. Part of this is about customer experience — they have built their offerings from scratch, taking advantage of new technology to mould their services around people’s lives. But part is also around business model.

A look at the latest Monzo annual report illustrates this well. It has over 2m customers, but it makes significant losses. It has over 2m customers, but makes net operating income of only £9.2m (£5.7/customer). The majority of its money comes from fee income, not interest income. And, despite heavy losses, it is ramping up marketing expenses (up 700%) and pushing forward with international expansion.

Note: Monzo reported 2m customers as of May 2019. However, most of the metrics above are calculated based on the total number of customers (1.6m) at the end of fiscal year, Feb 2019

In this regard, Monzo — like the other challenger banks — is operating a classic digital-era business model. In contrast to traditional banking models, it recognizes that distribution is not the primary point of differentiation in the value chain; but, instead, customers are.

Number of Customers per Challenger Bank

It is this desire to maximize customer numbers that explains why, despite a historical customer acquisition cost of less than £3, Monzo is engaging in TV ad campaigns. This explains why its investors are prepared to cover its losses and fund its international expansion. And lastly it explains why most income comes through fees, not interest income. Because this is a business where, with low customer acquisition costs, low churn (NPS is +80%) and low cost to serve (GBP30 per account at present and falling fast as scale economies kick in), the incentive is to maximize lifetime value.

Valuation per customer Challenger Banks

Monzo, like other challengers, will seek some direct customer monetization for sure — Monzo is now offering loans — but this is likely to be levied on those who can most afford it, in the shape of premium subscriptions, ensuring that most services remain free (current account, foreign ATM fees) to attract as many new customers as possible. Instead, most of its monetization will be indirect, using the pull of its large customer base to bring in third-party fees. At present, most of its fee income comes from interchange fees as its customers spend money using their Monzo debit card, but over time other routes will make more meaningful contributions. Monzo has said that it wishes to become its customers’ “financial control centre” by introducing them to the best possible third-party financial services and, although the resulting commissions from these introductions are small at present (just £85k), this will grow as two-sided network effects materialize.

Monzo customer contribution margin

For incumbent financial institutions, it is difficult to match the challenger bank model. Their businesses were created for a different age, where distribution was the choke point in the value chain. The need for a costly and difficult-to-achieve banking licence plus a network of physical branches kept out new entrants, meaning banks could push undifferentiated, expensive products to captive clients. And now it is extremely difficult for banks to change course and match challenger banks like-for-like — they don’t have the cost base, the financial incentives or innovation capabilities to do so. And so many banks are starting to launch challenger banks themselves.

Incumbent Banks Offering
The now defunct universal business model where banks were able to mass produce undifferentiated products

However, the bank-within-a-bank model is also difficult to pull off.

Firstly, as Aperture-subscriber John Hagel so eloquently describes in this piece, you have the problem of the immune system fighting off anything that threatens the business model and revenue streams of the body corporate (what in more successful companies might be described as the Innovator’s Dilemma). This likely contributed to closure of Fidor UK and explains why the rest of the business is up for sale. But the challenge to incumbents is very real. As the following table from Citi shows, banks’ RoE is much more sensitive to falls in revenue than reduction in costs, meaning that with stubbornly high costs — and in the absence of business model change (see below) — it will be difficult for banks to countenance a strategy that cannibalizes existing revenue streams.

Source: Citi GPS Research

Assuming that the immune system can be countered — by creating a completely separate organization, with different people, processes, tech, brand, incentives and reporting directly into the CEO — then you have the problem that innovation is hard. This seems to have been more of the root issue at Finn. Built on the bank’s existing IT infrastructure, its objective was more around putting a new UX on traditional products than using the virtues of digital to create a unique offering. As a result, it didn’t manage to attract large numbers, let alone introduce viral features that leverage the power of networked consumers, as Revolut has successfully done.

Revolut

The last problem is one of strategic intent. If a bank launches a digital bank because its strategy is a) to defend itself against challenger banks; b) to lower cost to serve by using digital channels; c) to improve User Experience; d) to capitalize on Blockchain/AI/IoT/Cloud or e) to change its perception among younger customers, it’s probably going to fail.

Launching a digital bank is about launching a digital era business model, which goes way beyond changing brand perception, user experience or moving customers onto cheaper-to-serve channels. As noted above, it is about maximizing customer numbers and engagement to activate demand side economies of scale. This requires clear strategic intent because, in turn, it requires organizational transformation. Launching a challenger bank can be a (faster and less disruptive) route to digitization, but it is neither an easy option nor a panacea.

Our view is that a challenger bank strategy has a higher likelihood of success if is underpinned by one (or more) of the following six objectives.

It is interesting to see Goldman Sachs’ digital bank Marcus referenced in so many of the articles on Finn. For us, it is very different. For instance, it is built on a new technology stack. But most importantly, it moves Goldman into a completely new space, consumer finance, where it does not have the cannibalization concerns that trigger the corporate immune system. This allows it to operate under very different constraints and, like other new entrants, challenge the status quo with a proposition that includes market-beating interest rates, no origination or late fees as well as customizable payment dates and payments. And it’s working: Marcus had 4 million customers and $46bn in deposits at the end of March 2019, two and half years after launch.

In the same way as entering new markets allows the new business to operate more freely, so does entering new countries. It is also a less risky strategy than M&A, which made sense at a time when distribution was the barrier to entry, but now encumbers the acquirer with all of the legacy issues they inherit. And this is why the challenger-led strategy is being pursued by many banks, including DBS, which has launched digibank (“a bank in a smartphone”) in India and Indonesia with already over 3m customers — and why it is looking to do the same in Vietnam.

Launching a challenger bank with the purpose of bringing banking to the unbanked is by definition the antithesis of cannibalization — because no one was providing these services in the first place. And, as banks like CBA in Kenya have shown with M-Shwari and now Stawi, when you combine mobile distribution with low costs and intuitive user experience, you can succeed in bringing financial services to millions of people. But, as demonstrated below, while countries like Kenya and China have very successfully leveraged digitization to tackle financial inclusion, there still exists massive scope to do the same in populous counties like Egypt, Indonesia or Pakistan.

The Financial Inclusion Opportunity

Another reason for launching Marcus was that Goldman Sachs can use retail deposits to lower its group cost of capital. But a business where this is more transparently the objective is EQ Bank in Canada. It is a subsidiary of Equitable Bank, which provides residential and commercial real estate lending services, and the bank uses EQ customers’ savings to fund its lending, allowing it to start to increase its net interest margin (now at 1.6%) in a low interest environment. Structuring the group like this not only creates complementarity between the bank and its challenger brand, as opposed to a cannibalization threat, but also reinforces incumbency advantages. EQ Bank can sustain its above-market deposit rates thanks to its parent’s large lending book.

Equitable EQ Bank Funding Mix

Another reason to launch a challenger bank is to attempt lower-risk and faster-to-value technology renovation. Banks sit on decades of technology debt, batch-based legacy systems built around products not people that have been continually added to over time, resulting in massive cost and massive complexity. If banks are to compete on price and on user experience with digitally-native challenger banks, then they will have to address this technology debt. But doing so is expensive and risky, which why it is tempting for many banks to start again — create a new bank with new technology.

A typical universal bank system architecture (source BCG)
This BCG image shows the mass of interdependent systems and interfaces within a typical universal bank

This “build and migrate” strategy is still somewhat unproven , even though it looks like some banks like Santander, with Openbank, may be going down this route (its annual report states that Openbank is “the testing ground for our future technology platform”).

For banks considering this strategy, they should be mindful that they will have to run two IT platforms in parallel for a good while (it is unlikely that regulators would let incumbents close all branches — or indeed the bank itself — for a long time). They should also be aware that there will be customer attrition in the base business as they divert investment into the new bank and also likely attrition when they try to move across customers to the new bank. In addition, they should start small, that is, with a single product offering like savings, which will enable them to test the market proposition before committing big expenditure, get fast RoI on the initial capital expenditure and minimize the risk of rejection from the corporate immune system — at the same time as probably lowering cost of funding (or, in the case of one challenger bank we consulted, whose first product will be to lend boomer savings to millennials, increase asset yield). Furthermore, if the technological renovation is successful and the bank creates a great platform, then, as Starling, OakNorth and Ant Financial have done, it can sell this to other banks — the “make yourself the first customer” model of creating an exponential software business.

Oak North, a unicorn SME challenger bank, sells its lending analytics platform to other banks

The counterargument to the “build and migrate” strategy is two-fold. Firstly, modern core banking systems are modular, meaning that progressive renovation is possible — replacing systems one by one — to combat risk and speed up time to value. In our experience, however, these projects tend to more complex than they seem and subject to the same issues as all in situ transformations, such a scope creep. A better argument for not executing a build and migrate strategy is that it is increasingly possible to achieve what banks want — improve customer user experience, launch digitally-native products, run advanced analytics and open up to third-parties — without replacing all of their back-office systems, as vendors like Additiv and The Glue are helping institutions to do.

In a blog we wrote last year, we set out what we thought were five viable banking business models for the digital age. However, at least three of these new business models were off limit to banks given their organizational constraints. Launching a challenger bank removes those constraints and allows banks to unbundle themselves by launching a narrowly-focused digital proposition (in terms of product offering as well as demographics) and then to rebundle themselves around this proposition. This is what fintech companies like Transferwise, Robin Hood and Zopa have done successfully and we are starting to see banks do the same — like Imagine Bank from Caixa which successfully attracted a new customer demographic with a convenient and high margin savings product and has since rebundled a whole set of own label and third-party services.

Unbundle to Rebundle

There is also the possibility to do this unbundling to rebundling via a holding company model. This represents the digital equivalent of the traditional universal banking model but where each product offering is run by a separate subsidiary. Doing this keeps each unit nimble enough to compete to respond to market shifts, permits partial customer acquisition, but also allows the overall group to achieve economies of scale (both supply-side, like IT, and demand-side, like customer data insights). In banking, the best example of this seems to be Pepper from Bank Leumi, which is building up a set of discrete product propositions.

If an incumbent bank chooses not to launch a challenger bank, what are its options?

It could choose to do nothing, essentially pursuing a mix of tactical options like cutting discretionary spend, shrinking risk-weighted assets and lobbying the regulator to slow, or reverse course on, new legislation. But, even though this might get management through to its next stock option vest, this isn’t a long-term remedy.

Another option could be to go upstream. We see this a lot in wealth management. Since HNWIs want a somewhat bespoke service and interaction with a relationship manager, then a lot of banks are moving to serve exclusively these HNWIs and UHNWIs where they think they can earn good fees for the foreseeable future. However, since many banks — as well as independent asset managers and family-offices-as-a-service focus on the same market — fees are gradually eroding. But more importantly, it leaves the banks open to classic disruptive innovation as the providers who now serve retail and mass affluent customers with digitally native services start themselves to move upstream.

In our view, for the banks that don’t want to launch challenger banks, there are only really two options. One is to become a bank-as-a-service, offering their back office and compliance to other banks and fintech providers, as banks like Bancorp in the US have done. But, this is a low-margin business. A better option is what we call the thin, vertically-integrated bank, where a bank starts to offer third-party services alongside some of its own products, capitalizing on its advantages —a bank licence, trust, the pull of a large customer base — to give its customers more choice. The challenge here is, of course, that this is a radically different business model which is likely to activate the corporate immune system.

Vertically integrated digital bank

So, the conclusion seems to be: if a company can dismantle the corporate immune system for long enough to adapt its existing business, then a challenger bank might not be the right option. Otherwise, it probably is.

Is Spotify the new MoviePass?

Is Spotify the New MoviePass
Are US subscription-based business models an innovation, or a compromise?

Is Spotify the new MoviePass?

by Ben Robinson | Jun 7, 2019 | 9 minutes read

Have you ever wondered why the social features on Spotify aren’t better? It’s not difficult to imagine a more engaging experience if, say, it was easy to co-create playlists or you got updates on what friends and artists were listening to. One explanation could be that it is hard to build siloed social interaction — outside of horizontal apps like Facebook or WhatsApp. But my hunch is that, while Spotify wants to maximize users, it doesn’t want to maximize usage. Why? Because unlike most aggregation platforms, its marginal cost grows with usage, meaning that — like MoviePass — its best customers are actually its worst customers. That’s why it’s struggling to generate profits, why it’s struggling to protect itself from rival streaming services and why it needs to become the pre-eminent platform for podcasts.

The move to subscriptions

Source: Zuora

Is a subscription model right for Spotify?

Spotify vs Netflix

Netflix vs. Spotify
Netflix business model vs. Spotify's Business Model

Spotify as Netflix

Spotify vs Amazon and Uber

Uber creating consumer surplus

Spotify vs Tencent Music

A new way?

Is Blockchain the internet of finance?

Whether the solution comes through crypto or an infrastructure upgrade, not being able to execute on micropayments-based business models is bad for business and bad for consumers. Furthermore, it is likely to give a growing advantage to Chinese vs American internet giants as they battle to colonize the rest of the world.

The Internetworked Nation

The Internetworked Nation

The Internetworked Nation

by Ben Robinson | May 23, 2019 | 9 minutes read

In one the most notorious scenes from cinema history, Harry Lime, a racketeer played by Orson Welles in the The Third Man, compares the cultural achievements of Italy and Switzerland. He says,

“In Italy for thirty years under the Borgias, they had warfare, terror, murder, bloodshed. They produced Michaelangelo, da Vinci, and the Renaissance. In Switzerland, they had brotherly love, five hundred years of democracy and peace, and what did they produce? The cuckoo clock.”

Still image from Carol Reed’s The Third Man
Still image from Carol Reed’s The Third Man

It’s probably unfair to suggest that this stereotype of Switzerland as safe and sterile originates directly from the film, but it has certainly helped to perpetuate it. According to its purveyors, the stereotype holds that Switzerland is too rich to take risks, too boring to be creative, and officiously obsessed with petty rules governing everything from rubbish collection to toilet flushing — in short, the antithesis of innovation.

However, not only is this stereotype misplaced — Switzerland invented the internet, not the cuckoo clock— but Switzerland’s networked, outward-looking economic model sets it apart from other nations and provides a blueprint for how to succeed in the digital economy.

While it is high time to debunk some myths about Switzerland, Switzerland’s success should still be seen on its own terms. If we look at the start-up scene, for example, it bears little resemblance to Silicon Valley. Tech companies here tend to ramp up slowly. According to startupticker, Swiss tech start-ups take about 10 years to reach scale and grow almost twice as fast in their second decade as in their first. Without a large domestic (consumer) market to sell into, they look to sell to corporations and they seek to internationalize early, with the majority exporting within the first three years of their life. And, they tend to take comparatively little external capital with most businesses becoming stable, moderately growing SMEs rather than blow-out exits or IPOs.

Still image from Carol Reed’s The Third Man

Looked at on these terms, we could cast Switzerland as small-scale and parochial. It is a long way from blitzscaling and moving fast and breaking things. Instead, it is very much the slow and steady model of measuring twice and cutting once that leads to fewer unicorns and billionaire celebrity founders, but which also produces fewer negative externalities and inequality.

Should Switzerland be aiming to become the Silicon Alps?

The fact is that drawing a comparison with the US tech scene is wrong and Switzerland should resist portraying itself as “Silicon Alps” or the “Silicon Valley of [insert term here]”. Like Operation Libero, the Swiss political movement that punctured the rise of the far-right Swiss People’s Party by reframing the political debate, Switzerland should not define its credentials in terms set by others. Instead, it should present the uniqueness of its model: a complex, adaptive system that combines lasting quality with cutting edge innovation and that marries economic growth with inclusiveness.

Flavia Kleiner, of Operation Libero, on the importance of narratives

A complex adaptive system is one made up of a network of interdependent actors that collectively adapt quickly to changing environmental factors. For Switzerland, this system is made of a series of layers – from government to brand – each resilient and adaptive, which, as a whole, both reinforce the strength of the overall system and leave it well positioned to capitalize on the future.

Switzerland is a complex adaptive system
Switzerland is a complex adaptive system

A distributed political system. In Switzerland, political power is distributed between the federal, cantonal and communal governments. This allows for a high degree of adaptiveness by keeping government nimble and localized enough to respond to diverse needs. In addition, it encourages competition between the different cantons and communes that promotes good governance and which, in practice, results in policies which are both pro-business, such as low tax and low employment regulations, and pro-citizen, such as a strong safety net, and which overall create the conditions for entrepreneurial risk-taking and shared prosperity.

An inclusive culture. It is testament to its inclusiveness that Switzerland is able to seamlessly accommodate four different language groups and a population with 25% foreign-born residents. But, it is in its ability to meld the high-tech and the rural, the modern and the traditional into a coherent, confident whole that it really excels. In much of the world, digitization is leaving behind rural areas, but not so in Switzerland.

Switzerland Rural Modernist
Switzerland Rural Modernist

A robust industrial set-up. Switzerland has a unique ecosystem, spread across multiple cities as opposed to one single dominant center. In place of unicorns it has lions, top-of-the-food-chain organizations that act as key nodes in the network. These include multinationals (Switzerland has more per capita than any other nation), top class universities (one in the top 10, two in the top 25), NGOs (including the UN) and scientific research hubs, such as CERN.

The Rolex building at The École polytechnique fédérale de Lausanne

These organizations support a much larger network of SMEs, which form the backbone of the economy and middle-class employment, and attract key flows of capital and information. This last point is critically important since globalization is entering a new phase, one centered on virtual not physical flows. In practice, this means that big is not necessarily best, that the future probably doesn’t look like our popular imaginings and that small countries, like Switzerland, can have outsized impacts.

Switzerland, a landlocked country, is the second biggest shipping power in the world
Switzerland, a landlocked country, is the second biggest shipping power in the world

Cutting-edge technology. Switzerland didn’t invent the cuckoo clock, but it did invent acid. In a whole range of fields, from micromechanics and hardware to life sciences and pharma, Switzerland is world-leading. Its high-tech economy is supported at a foundational/high-risk level by strong government spending on R&D (as a % of GDP it is behind only Korea and Israel, the latter a big military spender) and then a combination of top universities, research centres and high-spending corporations take it from there: Switzerland tops the Global Innovation Index.

Climeworks, an ETH spin-off, commercialized the world’s first carbon capture technology

International connections. Its outward focus is symbolized through its international organizations as well as the annual Davos gathering, but it is supported bottom up through over 40 free trade agreements. International trade accounts for over 120% of GDP and the 2019 Freedom Index ranks Switzerland the fourth most open economy in the world, the most open in Europe. But its internationalism is also down to geography: if you draw a circle around Zurich into neighboring southern Germany and northern Italy, you realize it stands as the pinnacle of the global center for high-end, family-run design and manufacturing — everything from machine tools to Ferraris.

Which other country in the could attract all of the world’s leaders to a small mountain village

A world-renowned brand. Switzerland wraps this adaptive system with a timeless, global reputation for quality epitomized by precision engineering and intricate design; more Zenith watch than cuckoo clock.

Swiss Innovation
On the left, the precise mechanics of a Zenith luxury watch; on the right, Solar Impluse, a solar-powered plane attempting to circumvent the globe

One paradox of Switzerland is that it’s in the heart of Europe, yet not in Europe (the European Union, that is). But a greater paradox is that, though not in the EU, it represents the best model of how the EU should work.

Just as Switzerland should not compare itself to the US, nor should Europe. North America embodies a libertarian model where winners take all and corporations rule supreme.

Similarly, the Chinese model is not the European model, either. The Chinese model is one of planned economic activity. It can deliver fast growth, but at the expense of individual freedoms. Here corporate surveillance gives way to state surveillance, but the surveillance persists.

Technology makes it possible to design complex societies following series of recipes, not inorganic blueprints
Technology makes it possible to design complex societies following series of recipes, not inorganic blueprints

Europe seeks to forge a different path. A Goldilocks model of balanced freedoms and inclusive growth. The challenge is that Europe hasn’t yet found the recipe to make this happen. However, that recipe might well be the Swiss one: business friendly to promote growth, but with the welfare state to lift all boats; a federal model to allow for self-government and pooled sovereignty; a focus on science and lasting value that creates a prosperous middle class; and, an open model attracting the flows on which the next phase of globalization will be built.

While objectively a global success story, there could still be room to improve. A recent report from McKinsey highlighted, for example, that Switzerland is losing attractiveness as a home for MNCs, a key constituent of the ecosystem. Here are three measures that could help.

Unleash the capital. As should be clear, we would not advocate turning Switzerland into some sort plastic replica of Silicon Valley. However, that does not mean that more risk capital wouldn’t be helpful.

Last year, Swiss companies raised over USD1bn in venture financing, a 32% annual growth and the highest amount ever. Moreover, the money went to fund more companies in a more diverse range of sectors than ever before. But USD1bn is low relative to most other developed countries and very low relative to, say, over USD1 trillion that sits in the national Swiss pension pot.

Analog Flows vs Digital Flows
From “Swiss Made” to “Swiss Designed” | Pictured left — daily commuters from France to Geneva (c. 85,000 per day) | Pictured right — next level of globalisation is about digital flows

Furthermore, not only does venture capital have significant economic multiplier effect, but it is also filling the vacuum left by traditional lending which is not adapting to the increasingly intangible nature of modern economies. As such, it would highly beneficial to get dormant Swiss capital moving. This might come naturally from tokenizing illiquid assets like real estate, but it might also require the hand of the state by, for example, creating the conditions for a new financing vehicle to emerge —one that promotes long-term, sustainable investments.

Foster the holding company model. Our view is that this networked organization of the future looks a lot like Ant Financial or Amazon, operating what we call the “holding company model” . This model allows group companies to remain small enough to cater to specific customer demographics and agile enough to respond to market changes. But, the holding company structure leverages growing financial muscle, shares supply side economies of scale, like IT infrastructure, and shares data network effects via APIs. Given the structure of the Swiss economy — as the world capital par excellence of holding companies — as well as the importance of holding companies to attracting data flows, it is vital that Switzerland makes this model as viable as possible before Singapore and others usurp it. Part of this relates regulations on data, but at least as important are rules on tax, especially around how capital flows between entities get treated.

The future is invisible
Which view of the future looks more likely?

Scale the brand. The future is small and invisible. It won’t be the future of flying cars and Fritz Lang’s Metropolis. And for Switzerland, nor could it be. A country of 8 million people, its future always had to be true to brand: high-end and high-quality. But there is a way to make this brand do more and we believe it is by pivoting from “Swiss Made” to “Swiss Designed”, accepting its increasingly intangible asset future, placing manufacturing closer to consumers and scaling its addressable market in the process.

When you transit between terminals at Zurich airport, you are presented with a hologram of Heidi set against a mountain backdrop and accompanied by sounds of nature, yodeling and the Swiss horn. This is the manifestation of a society at ease with itself, the confident projection of a multi-faceted nation that can be at once modern and traditional, high-tech and rural.

The nature of our economies is changing. Our future will be increasingly networked. Switzerland as a complex adaptive system looks set to re-calibrate for this new phase of globalization.

While it might not have invented the cuckoo clock, it’s probably in for another five hundred years of peace and sisterly love.

An immersive image of Heidi in-between train stops at Zurich terminal

Introducing Aperture

Introducing Aperture Herbert Simon
Herbert Simon advocated for insight, not abundance

Introducing Aperture

by Dan Colceriu | May 14, 2019 | 7 minutes read

We use them to look at organisations, at markets, at societies, at the world. They absorb information. We use them to choose what to see, and more importantly, what not to see. By doing that, we understand trends and create recommendations and plans that organizations of all kinds can follow.

Looking at the same information from different vantage points reveals key insights. As such, we often hear strategists ask — what if we look at this through a different lens? And so yes, we do like to change lenses often, so that we can absorb information differently. Some do it to be able to absorb more information, or to see it differently, and some do it in order to adapt to the zoom in / zoom out approach to strategy eloquently described by John Hagel.

As Hagel pointed out, since we’re facing a socio-economic shift, organizations must find an alternative approach to strategy which looks at the world from a dual perspective — one focused on the near-term, six to twelve months, and the other focused on the much longer term, ten to twenty years ahead. The key is then to focus on these two horizons in parallel and iterating between them.

This latter approach to strategy is designed to account for the increasing speed of change, but also to enable a link between long-term strategy and execution. It is without doubt one of the major upgrades to strategic thinking that we’ve lately.


But does the zoom in/zoom out framework go far enough? It still assumes that markets, organisations, societies, if they change, somehow change towards a point of equilibrium, from where it won’t have to change anymore, at least for a while. In practice, however, this state of equilibrium that we seek through our lenses, is, in fact, constant change.

Therefore, strategists are faced with the risk that the tools they use are downplaying two major areas:

· one is speed of change: the world moves at unprecedented speed, which requires more agility than organizations think they need.

· the other one is in the nature of information: it is either abundant in such a way that it creates a poverty of attention. Or it is scarce, in a way that creates a poverty of actionable insight.

One condition makes it hard to change lenses on the go — due to the time this takes — and the other makes it more difficult to use the lens you currently have with any meaningful results.

And in practice, smaller companies can only afford to resource themselves with only one lens anyway — as the privilege of having multiple, interchangeable strategy lenses exists mainly within large organisations.

As my colleague Ben Robinson wrote, we now face the conditions where strategy should pivot to a function that creates the conditions for maximum agility so to impose as few of these constraints as possible; from a preservation strategy to a continuous growth strategy.

This creates the imperative for strategists to develop more execution skills, as they are faced with the task to create the conditions where organisations can experiment at fast speed.

Faced with these conditions, strategists need to transform their lens from a static window of the world, to complex adaptive systems — which account for speed, execution and feedback loops, as well as experimentation. Specifically, they need upgraded skills that allow for filtering abundant information (or expanding insufficient information), while also creating the right depth of insight, but at much higher speed than before.

In other words, in search for meaning where equilibrium is represented by constant change, strategists will need to up their game and learn also to use the aperture of their lens. Or find people who do.


In the new networked world, the best talent, resources, and sources of information sit both inside and outside organizations, not exclusively inside them anymore.

Jet d’eau de Genève, captured right before evening shutdown, May 2019 | Photo by Dan Colceriu, on film - because some noise is good

With that being the case, there is a gap, and need, for some kind of vehicle that could bring together information about how the world is changing from people making this change happen. And this is how, brainstorming on the shore of Lac Léman with Ben Robinson, we conceived the platform we’d wanted to join but couldn’t find and which we believed was critical to exposing new thinking from a newly-forming community.

Aperture is an independent content hub and a community, built on the exchange of ideas around technology, strategy and the dynamics of the platform economy.

It is both a virtual community — sharing and discussing ideas through articles, podcasts and news digests — and a physical one, organizing meetups in Geneva, Zurich, Berlin and Bucharest.

It brings together strategists, marketeers, growth enablers, entrepreneurs, investors and policymakers. And its content platform has a clear focus on highlighting the ideas of those thinking and doing things differently — we like to call them theorist-practitioner professionals. It therefore bridges the world of strategy with the world of execution.

Its aim is to improve collective intelligence by subjecting ideas to multiple exposures — establishing the right context, narrowing down the arguments and encouraging contrarian viewpoints — all within a safe, non-polarizing environment.

Because as much as we like to think that with the advent of social media, we have that kind of environment, we do not. In fact, social media as we know it has already peaked, creating the space for small-scale, networked communities that interact in a more orchestrated manner, allowing for sequential narratives to form.


Aperture | Hub is no technological revolution.

It is merely calling it as it is: the two main vehicles for professionals to seek meaning and make sense of the world are flawed.

One is the corporate stamped collateral (reports, events) that are either too self-serving or way too edited (in other words, censored). These are stable environments, but lack vibrancy, to quote Ian Hathaway.

The other vehicle is the wild, wild west of social media, which is neither self-serving nor censored, but the trade-off for these features is that it is polarizing, aggressive and built on the wrong engagement mechanisms that promote information abundance over return on attention. It is stuck in instability. Most people simply back out from engaging through it — creating the conditions for group-think and self-enforced bubbles.

The biggest confusion that we see is that, in order to build up social capital for the fast-changing business environments of today, strategists and by extension other professionals plug themselves into sources of instant and real-time information. But, despite popular opinion, doing so does not lead to self-empowerment, but rather diminishing utility, for the sake of social status.

While we do not oppose any of the two major forms of organizing communities, we do feel there is space for a healthier layer on top — one that introduces instability for the benefit of vibrancy, but with a path of becoming more stable in time. One that is more inclusive and co-creates for and on behalf of its audience, re-introducing utility back into networked communities.

Hence, what strategists need is reputational devices, and Aperture | Hub, through its content and events, aims to be one, by bringing transparency to the act of professional self-publishing and creating context by adopting a much calmer approach to how everyday events are being digested. It aims to inspire and to satisfy people’s intellectual curiosity, as well as to be execution-oriented by facilitating best-practices.

Consequently, by creating the perfect conditions where noise is good, we aim to create a content platform that offers voice to professionals that sit inside organizations — to be able to share expertise and projects they are passionate about in a free manner — and empowerment to the ones who sit outside organizations, such as freelancers and independent consultants — so that they can continue to learn from interaction, while also differentiate their work through mechanisms that are more complex than 5-star ratings.

Aperture | Hub is a place that fosters the right patterns of interaction and crowd-sources the right content for strategists and growth professionals to learn how to properly use their strategic lenses.


Aperture is committed to distributing the best and most diverse content, regardless of the status of the user producing it. As well, we’re committed to distribute the work of individuals, rather than more established brands. This means including our readers in mechanisms that enable them to become content producers.

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