Chapter 1 — A Whole New World

Chapter 0 explored the context in which many businesses exist today. The deployment age¹ of information technology and the Internet has brought with it giant organisations, operating at unprecedented scale.

Source: (Bloomberg, A16Z)

Such organisations continue to look for areas of innovation and growth. For instance, between 2011 and 2016, Apple acquired 70 companies, Facebook more than 50, and Google nearly 200.²

However, “unbounded growth requires accelerating cycles of innovation to avoid collapse. Growth is infinite in a finite time. At some time in the future the system collapses”.³

Technology and finance have had, and continue to have, the greatest impact in reshaping business.

Technology has led to:

• Cheaper tools for everyone — the price of starting a company has fallen from an estimated $5,000,000 in 2000 to just $5,000 today.⁴ Incidentally, scaling a company is becoming more expensive due to the reliance of building on platforms. For many, Google, Facebook, and Amazon control distribution.
• The Internet — everyone is now connected, with over 3.5 billion people having access to the Internet in 2017.⁵
• Software eating the world — the rise of intangible assets and increased malleability of business.

Technology has shifted business and the economy from a supply-driven world to a demand-driven world (consumerisation, the growing importance of demand over supply, and a world of abundance).

Finance has served as an important catalyst for funding new innovations and deploying capital at scale in new enterprises

(i.e. the joint stock company, or junk bonds). However, evidence suggests that finance is now less in service of the real economy (‘Main Street’) but in service of itself — this is ‘financialisation’.

According to Rana Foroohar, “Only 15 percent of the money flowing from financial institutions actually makes its way into business investment. The rest gets moved around a closed financial loop, via the buying and selling of existing assets, like real estate, stocks and bonds”.⁶

Finance tripled its share of the US and UK economies between 1950 and the 2000s. On average, across advanced economies, private sector debt increased from 50 percent of national income in 1950 to 170 percent in 2006.⁷

These shifts change the ontology, the underlying assumptions and nature of business.

“The emerging heuristic routines and approaches are gradually internalised by engineers and managers, investors and bankers, sales and advertising people, entrepreneurs and consumers. In time, a shared logic is established; a new ‘common sense’ is accepted for investment decisions as well as for consumer choice. The old ideas are unlearned and the new ones become ‘normal’ ”.⁸

It’s Complex

“We are deterministic creatures living in a probabilistic universe”, Amos Tversky.⁹

The world is not linear but rather consists of a vast number of complex adaptive systems, all interacting with one another. However, people’s natural instinct is to think linearly. Historically, this has had less of an impact, as systems acted on a much smaller scale and operated at a slower pace.

This is no longer the case, “we are experiencing a technological non-linearity. The realm of possibility for mankind is expanding rapidly due to the extraordinary power of digital technologies”.²²

As noted earlier, technology changed everything:

1. The internet and the smartphone:

• In 2016, approximately 1.5 billion smartphones were sold.² “For the first time in human history a near majority of the world’s adults are now connected.”
• Human networks scale at a rate which is super linear. They have positive feedback loops, which accelerate the pace of change.
• The Internet was the game changer, creating a global network. The pace of change grew exponentially faster, as ideas and information could be shared, spread and combined in new ways. Sites like Product Hunt created a community of early adopters, accelerating the process of innovation diffusion and the adoption of new products.
• “Human beings innovate by combining and recombining ideas, and the larger and denser the network, the more innovation occurs”, Matt Ridley.¹⁰

2. Software is eating the world, and the rise of intangible assets:

• Software is malleable. As it eats the world, everything becomes more dynamic. The world is indeed dynamic and not static. To illustrate, texts and books were previously fixed, but now Wikipedia is constantly updated. The lifeblood of organisations; data, money, and people continuously flow.
• One estimate found that Microsoft’s physical assets accounted for just 1% of its market value. The expertise of Microsoft’s engineers and the code they use were far more important.¹¹

3. Demand-driven, not supply-driven world:

• Everyone is now a segment of one. All information is specifically tailored to one’s newsfeeds, Spotify playlists, Netflix recommendations, et cetera. Scale versus personalisation is no longer a trade-off.
• As a result many brands and services have become a commodity, interchangeable to the consumer, profit has shifted to those that own the customer relationship (demand), not the supply.
• A world of abundance.

Source: Chris Anderson²³

The Dawn of Giant Networks

As Chapter 0 explored, industries are increasingly becoming winner takes all, where a handful of companies dominate. The question is why?

A number of interrelated characteristics to consider include:

1. Structure
2. Economics of digital
3. Super-linear scaling
4. Adaptability over efficiency

“The extraordinarily efficient pyramidal structures with clearly defined roles and tasks that handled growth and innovation in the mass production paradigm of the 1950s are seen as bureaucratic dinosaurs next to the dynamic global networks digitally interconnected with multi-skilled personnel and high levels of autonomy of the flexible production paradigm of the current Information Technology revolution”.⁸

Structure. Though the tech giants have led to the centralisation of the Internet, under the hood, they are inherently decentralised in nature. They have departed from the traditional ‘command and control’ structure.

G. Pisano puts it this way: “Just as firms compete in product markets, they also compete to create technological, operational, and organisational capabilities that provide them advantage in those product markets”.¹⁵

Amazon’s autonomous “two pizza” teams operate without the need for every decision to be approved, yet with the capabilities and freedom to develop new product lines, new features. Amazon estimates 35% of its sales are from cross-selling activities.

Corporations don’t need ‘cross-silo’ teams. In contrast, they need to redesign their organisation and breakdown the previously artificial distinctions put in place, often dictated by complex legacy software.

These tech giants have developed dynamic capabilities and proprietary datasets that allow them to build empires that transcend traditional industry lines. Google’s shift to Alphabet is the most prominent example of developing capabilities that can be pointed at new problems.

G. Pisano further notes, “A capabilities-based perspective asks practitioners to consider: what capabilities should the firm nurture to gain a competitive advantage? Because most capabilities are cumulative and develop over time through a series of coordinated investments, they involve commitments to “paths”, rather than discrete projects. A key strategic problem for firms is to identify and commit to paths for capability creation that lead to competitive advantage”.¹⁵

This notion of “paths” is at the heart of strategy and competitive advantage. Moreover, competitive advantage depends on a tangled web of interdependent choices and capabilities. The trade-offs and capabilities required are extremely different in the digital world.

“No cookbook or expert system can reliably churn out winning strategies. By definition, strategy is about creating something unique, making a set of choices that nobody else has made.

Trade-offs are the strategic equivalent of a fork in the road. If people take one path, they cannot simultaneously take the other. Similarly, adjustments arise in products, and meeting the needs of customers requires companies to make choices about the product. There are then compromises in the activities to deliver the product. Another trade-off is the consistency of brand and image because compromises are choices that make strategies sustainable because they are not easy to match or to neutralise. Hence, trade-offs make strategy more difficult to imitate.

Good strategies depend on the connection among many things, on making interdependent choices. Where possible, each choice should enhance the value of others”.¹⁶

The structure of these firms has not just changed how they operate internally, but the relationship with other organisations.

The shift to cloud and modular operating models is redefining the nature of the firm, giving rise to the “API economy” and “evolutionary architectures”. Firms do not exist in isolation but become increasingly connected in helping customers achieve an outcome.

“In the twenty-first century, the supply chain is no longer the central aggregator of business value. Now networks connect business and individuals, enabling them to exchange value among themselves. Linear business models focus on creating value internally and selling that value downstream to customers. As the world becomes more connected, what a company owns matters less than the resource it can connect to. Platforms don’t own the means of production — instead, they create the means of connection”. — Alex Moazed¹¹

Economics of Digital.

The economics of digital and platform business models naturally create winner takes all outcomes.

“Platforms have a number of important properties. They allow easy participation, exhibit network effects that increase in value as participation increases, and typically capture and generate huge amounts of data that enhances the value of the platform to all.

We are now at a point of technological advancement where the increasing sophistication of key technologies, enabled by software modularity, massive data processing capacity and network connectivity, has led to the emergence of a new generation of platforms of increasing complexity. These next-generation platforms are well-positioned for disruptive change”.¹³

“As a result of the rise of the platform, almost all traditional business management practices… are in a state of upheaval. We are in a disequilibrium time that affects every company and business leader”.²

Information goods, those made of bits rather than atoms, are free and perfect. It’s essentially free to make an additional copy, and a copy is as good as the original. The economic power of information good increases once a network is available because networks add a critical third attribute: being instant. Additionally, networks allow distribution of a free, perfect copy of information goods from one place to another, virtually immediately. This shift is now taking place in the physical world, with Uber and Airbnb demonstrating that platform companies can translate to coordinate tangible assets in a network.

Christian Catalini further remarks, “Physical scale and unique intellectual property no longer confer unbeatable advantages; increasingly, the economic leaders are enterprises that act as ‘keystones’, proactively organising, influencing, and coordinating widespread networks of communities, users, and organisations”.¹⁴

Super Linear Scaling.

The characteristics of digital inherently support super linear scaling. In addition, the world of atoms and physical products depreciate with use. Nevertheless, software and data-driven products appreciate with use by individuals. Also, platform companies have created business models with positive feedback loops to support these characteristics.

This is evident in Netflix and Amazon’s famous “virtuous cycles”:

Adaptability over efficiency.

Traditionally, businesses have scaled sub-linearly. Most evident in the S-Curve shaped growth of companies, businesses scale quickly (blitzscale) and then taper off as they mature.

In their inception companies are dominated by a spectrum of innovative ideas as they seek to establish themselves in the marketplace. However, as they grow administration and bureaucracy typically take over. As an illustration, Geoffrey West argues, “Economies of scale and sub-linear scaling, reflecting the challenge of efficiently administering a large and complex organisation, dominate innovation and ideas encapsulated in super-linear scaling, ultimately leading to stagnation and mortality”.³

Change, adaptation, and invention become increasingly difficult under a top-down administrative rule, especially as the pace of change continues to accelerate.

This is not simply a structural problem, but a human one. Much of the activity that takes place in large organisations today is ‘arse covering’ masquerading as rigour. As the stakes get higher in the decisions made the ratio of activity that goes into justifying a decision versus creating value shifts dramatically.

This is why “you never get fired for buying IBM”, or as Freek Vermeulen points out; many so called ‘best practices’ still exist. Management practices such as Lean and Six Sigma in the short-term lead to better results, boost efficiency, productivity and quality, but in the long-term, they deprive a company of learning opportunities, or the ability to question conventional wisdom.

The language within the organisation also begins to change, focusing on efficiency rather than creation. As companies focus on efficiency, they become optimised for the world as it is today, making them less resilient.

Source: MIT: The Truth about Business Model Innovation (Clayton M. Christensen, Thomas Bartman, and Derek van Bever)

As companies mature, the four elements of a business model become more interconnected and rigid, therefore making it harder to adapt.

This is a natural lifecycle of business models. Therefore, when evaluating new general-purpose technologies, such as machine learning, it is important to understand how best to deploy them based on where the business is in terms its natural life-cycle.

In existing business, managers should not only assess how the technology can be used as a sustaining innovation or efficiency play, but whether it creates a significantly different customer value proposition and profit equation. If so, organisations will need to develop an entirely new business, you cannot move back down the cycle.

Machine Learning can be a sustaining innovation and lead to efficiency gains for the likes of Google (seen in their translate and map products). But deployed in a new market with a combination of other technologies, Machine Learning becomes disruptive (driverless cars) — Waymo.

Coping with change. Somethings never change.

This increasing pace of change has required businesses to become more purpose driven. Clayton Christensen uses a framework called, ‘the job to be done’¹⁸. This is the ‘value proposition’ element of the business model.

The value proposition is often consistent. Jeff Bezos, when asked what’s not going to change, says, “people are always going to want more selection, lower prices and faster delivery”.

People can then understand how digital technologies change, enhance or create new value propositions. This after all is the definition of digital disruption; “changes in the competitive environment, resulting from the use of digital technologies by new market entrants or established competitors in ways that undermine the viability of your product/service portfolio or go-to-market approach”.¹⁷

Clayton Christensen adds, “Entrepreneurs start with a passion to solve a problem, but as they scale, the conversation changes. No longer are they using passive data to observe the world, but active data to evaluate their products and performance. Then, as they scale and establish themselves as an incumbent, the conversation turns to efficiency, costs, etc. Firms lose what made them great; they lose that connection to the value they are creating.”¹⁸

Value creation comes from giving consumers something they value relative to the available alternatives, which could be competing companies but also possible substitutes, and in a world of abundance there are increasingly many substitutes.

Simon Sinek’s Golden Circle:

The “how” in large organisations has always been defined as the processes, culture and unspoken truths that exist. However, people often try to change the “what” by deploying the same “how”. Changing this common error is difficult. All businesses need a defined “why”.

The “what” and “how” are malleable. The “why” is a company’s North Star and remains constant.

Companies must:¹⁸

• Understand the job the customer wants to get done
• Understand how the customer chooses a business
• What they can do that others can’t
• How everyone knows what product does the job best (develop a purpose led brand which acts as a ‘shortcut for the brain’)

Changing Context

In systems thinking, understanding the context in which we exist is important. Regardless, it’s clear that the context and narratives being told are beginning to change. We are starting to see a push back against centralisation and ‘the establishment’ as people get left behind. Could tech giants experience the level of regulation and compliance of financial institutions? BBVA estimates that 15 percent of staff are dedicated to compliance and regulatory activity.²³

Another clear societal change is the rise of impact investing, where investors care about sustainability, diversity, and the environment. The US Forum for Sustainable and Responsible Investment estimates that more than a fifth ($8.7trn) of the funds under professional management in America are screened on SRI criteria, up from a ninth in 2012.¹⁹ This completely changes the notion of creating shareholder value.

Businesses are a socio-economic structure, we have moved away from ‘shareholder value’ being about maximising short-term profits at the expense of everything else. Larry Fink recently declared, “to prosper over time, every company must not only deliver financial performance, but also show how it makes a positive contribution to society”²⁴. However, this shift is still in its infancy.

A second and obvious trend is the rise of crypto assets. Much like machine learning, Blockchain is a general-purpose technology akin to the steam engine, electricity, relational databases and the Internet.

These social and technological shifts are giving way to a new paradigm that will co-exist with today’s platform companies (see Chapter 2).

Conclusion

It’s important to understand the changes that are reshaping the world we live in, but equally important is creating organisations that can both thrive and survive in a world of constant transformation.

“Let’s face it face, the universe is messy. It is nonlinear, turbulent and chaotic. It is dynamic. It spends its time in transient behaviour on its way to somewhere else, not in mathematically neat equilibria. It self-organises and evolves. It creates diversity, not uniformity. That’s what makes the world interesting, that’s what makes it beautiful, and that’s what makes it work”. — Donella Meadows²⁰

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