The constantly accelerating technological progress is propelling us with full speed into the fourth industrial revolution. The ongoing transformation will fundamentally change the scale as well as the complexity of how future businesses are done. Digital business models play a significant role in this transformational process, changing not only the speed in which commercial transactions are executed, but also strategies and marketing techniques by which customers are approached.
In order to understand the principles of digital businesses, we need to analyze them in several dimensions. First dimension concerns the digital business model from the corporate perspective. It explains the key economic drivers that allow digital businesses to grow fast, from small startups into global market leaders. The second dimension deals with paying customers and freemium users of digital services. Of main interest is how digital companies have changed the customers’ roles as well as the expectations of them. The third dimension covers the aspect of the society. Since digital businesses have penetrated almost every aspect of an individual´s daily life, we also need to consider how the core values of our society must be redefined to meet the new challenges.
Defining Digital Business Models
In digital business models the creation, delivery and capturing of the value proposition are based on digital technology.
The effective application of digital technology allows a unique value proposition to customers, which has the following characteristics:
- Everything: all products are available to the customer at once.
- Immediate: all products are instantly available; there is basically no transaction time or delay in delivery.
- Everywhere: all products or services are available at any geographical place as well as across various end-user technologies.
The near-perfect examples of this principle are video streaming services like Amazon Prime or Netflix: the customer can select to watch from a vast amount of videos, at any time of their convenience, on virtually any device and at any place they like. Obviously, digital technology is a fundamental prerequisite to the everything-immediate-everywhere proposition, making it unique to digital businesses.
In exchange to everything-immediate-everywhere, customers provide an enormous amount of data. These historic and real-time data are diligently analyzed by the delivering companies, allowing them to constantly improve key aspects of their respective business model: the product itself, its delivery to the customer, and the pricing of their service.
Why are Digital Business Models Scalable?
Scalability of a business model is the ratio between the increase of the product volume and the corresponding increase in the volume of required resources. In the case of digital business models, the scalability is only marginally related to additional investments or to fixed costs. This means that the marginal costs (costs required by producing one additional product) are very low for digital business: every new user only requires a minor increase in CPU, memory or bandwidth.
In contrast: the more “physical” a product is, the poorer the scalability. For example, physical goods are not arbitrarily scalable, as every product first needs to be produced at relatively high marginal costs. Furthermore, if there is a bottleneck in the production or delivery process– for instance the limited capacity of a warehouse—the corresponding business is not scalable at all.
Digital businesses rely on global and digital customer channels such as search engines and social media. Due to their high scalability, digital businesses can grow very fast and become in no time global payers. Famous examples include Uber, AirBnB, Netflix, and other such well-known “unicorns”. The potential of exponential growth allows them to endanger the old, established business models – not only for in the B2C but also in B2B sector.
Fast growth and favorable scalability are exactly the characteristics investors are looking for in digital business models, resulting in high volume investment in this sector.
The Dark Side of the Moon
Digital “Pleasure Bubbles”
At first glance, digital businesses have miraculously transformed their customers to cosmopolites. We all enjoy an unlimited access to a vast number of products, services, and information from the whole world – all tailored for us and always available!
Is there a dark side to the digital cosmopolitanism? The trouble comes paradoxically with the increasingly efficient customization. Due to this customization, we may find ourselves inside of a digital ‘pleasure bubble’, where we only see information that is akin to what we have preferred or favored previously. I am sure you notice how efficient the self-learning algorithms in social networks are: some of your contacts’ updates disappear from your news feed, the advertisements show you products compatible to your last purchases, and your search engine makes smarter and smarter suggestions. This creates a feel-good cocoon around us, shielding us from unfamiliar products, possibly ‘disturbing’ opinions or different political convictions. Undoubtedly it is already happening and is not limited to consumer behavior. It may lead to a digital incapacitation of citizens and to a digital “bread and circuses” analogous to that in the ancient Roman Empire. In this way, digital technology leads to the opposite of cosmopolitanism: it reaffirms our biases and gives rise to parochialism, intolerance, polarization, and the closing of public spaces that are crucial to the democratic dialogues in liberal societies.
Whither Are We Abound?
Scalability also means that digital businesses will continuously seek to build closer relations to permeate all aspects of their customers’ daily lives, by improving the quality of the ‘docking station’ attached to the information bubble of the consumers. The key is to enhance the precision with which the consumer behaviors are understood and predicted. Two directions emerge as the most important ones:
1. Individual Psychological Level: psychometric consumer analytics
Customers of digital businesses produce a vast amount of data, all of which are instantaneously being analyzed. Beside the ‘click & like’ analytics, new trends are upcoming: sophisticated semantic analysis based on artificial intelligence (AI) algorithms as well as the use of psychometric models, such as ‘The Big Five (personality traits)’ (also known as the OCEAN model). Analytics companies prey on our waste use of social media, hereby coming to not only know us but be able to predict and manipulate us. We will then be not only provided with products we may want, but also addressed in the way most receptive to us possible. These new digital business models create individualized information, products, and services.
An impressive and disturbing example of the combinations of big data and psychometrics is Cambridge Analytica (CA). This company uses ‘data modeling and psychographic profiling to grow audiences, identify key influencers, and connect with people in ways that move them to action’. An outstanding analysis of its method as well as the role it played in the 2016 US presidential election can be found in: Das Magazin N°48-3 Dezember 2016 Article under the title: ‘Ich habe nur gezeigt, dass es die Bombe gibt’ (‘I Just Showed That the Bomb Does Exist’), link: https://www.dasmagazin.ch/2016/12/03/ich-habe-nur-gezeigt-dass-es-die-bombe-gibt/
2. Technological Level: Near Future Predictive Services
The upcoming loT trend is expected to generate an unprecedented amount of data, coupled with our enhanced technical capacity to analyze and store these data. Consequently, the predictive analysis will become available on a large scale. This means we may expect a fundamental shift from on-time-instant services to short-term predictive services. Some of the predictive services already in place are:
- PRECOBS: Near Repeat Prediction Method already used by the German police in several towns to forecast the commitment of ’near repeat crimes’, mainly applied to burglary prevention. For additional details see: www.ifmpt.de
- Autopilot crash prediction: Tesla autopilot seems to have predicted a crash and initiated and emergency break before the actual crash happened. For the video of this incident see here.
Near-future prediction will be based not only on deterministic calculations, but increasingly on artificial intelligence (AI). AI has a real potential to become a key disruptive technology of the future. Current AI-examples are numerous, beside prominent IBM’s WATSON and Google’s AlphaGo, there is even one curious oddity:
- AI as a member of the Board of Directors: in 2014 the Hong Kong based VC firm Deep Knowledge Ventures appointed an AI algorithm, called VITAL (Validating Investment Tool for Advancing Life Sciences), as a member of the Board of Directors. The key task of VITAL is to find and analyze information, the significance of which not obvious to humans. You can find more here.
Advantages and Disadvantages of Digital Business Models
Digital business models are unique in their value proposition and have a very attractive growth profile for entrepreneurs and investors alike. In addition, digital businesses change customers’ expectations on delivering value: ‘I want it all & I want it now’ has become a digital reality. At the same time, the customers are more than ready to pay for the everything-immediate-everywhere experience, with money but first of all with our data.
In summary, there is a trade-off between advantages and disadvantages of digital business models, from the corporates’, customers’, as well as societies’ point of view. The corporates are those who benefit the most from the current arrangement, enjoying the following advantages:
- unique value proposition based on everything-immediate-everywhere products and services
- high scalability with low marginal costs
- global reach and high growth rates based on digital customer channels such as social media and search engines
- investors’ darling: good chances to be well-funded by investors
However, the advantages to these corporates are accompanied by hefty personal and social costs, if they are left to develop unregulated, which includes, for instance:
- market monopoly: fast growth often leads to a ´winner takes it all market situation’. Example: we need only one Amazon instead of thousands of local shops or even other digital store fronts
- ‘pleasure bubble’: customers are manipulated by way of psychometric-based analytics. Example: your social media feed continuously nudges you to affirm your political bias
- users become the products. Example: freemium offerings of search engines or social media in exchange for data. In that case the true customers are the companies paying for the advertisement. Even when the users are indeed paying customers, the companies can still profit from analyzing or trading their data.