Digital Business Model: 3 Characteristics & Future Developments
Status Quo: The ‘Everything-Immediate-Everywhere’ Society
Digital businesses have transformed us into self-centered consumers in an everything-immediate-everywhere society.
We, the customer expect:
- Everything: a large variety of products in high quality at low prices, with excellent service
- Immediate: instant response and transaction time; on-demand services
- Everywhere: all services should be available across various end-user technologies, anytime, anywhere. Again the key word is on-demand.
As a result, lean digital startup business models have good chances to be highly scalable. Some of them have even turned out to be disruptive (= substituting a present business model or creating a whole new market).This may endanger the old, established business models – not only for the B2C but also for the B2B sector.
Example: imagine a FinTech startup specialized in providing company loans, with which you could track down every step of your loan processing, just as you can track down the delivery of the last book you ordered by Amazon. This would be fantastic and could shake the established lending institutions. Why? Well, the company’s loan is probably of vital importance for your business. So you would certainly turn to this new institution with you loan request in order to know where you stand. In this hypothetical example, just a simple increase of transparency of the otherwise unchanged business model – by no means a disruption – could easily lead to the ‘fall of giants’ in the banking sector.
What is the impact of the digital business model on us, the consumers?
At first glance we are miraculously transformed to cosmopolites, obtaining services from all over the globe, having an unlimited access to a vast number of products, services, and information from the whole world– all tailored for us and always available!
So we are now all open-minded cosmopolites and discerning, and consumers!
Well, yes and no! The trouble comes with the increasingly efficient customization. Due to this customization we find ourselves inside of a ‘pleasure bubble’, where we only see information we have preferred or favored previously. I’m 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. This is undoubtedly already happening and is not limited to consumer behavior. On the dark side this may lead to a digital incapacitation of the citizens and to a digital “bread and circuses” analogous to the ancient Roman Empire. However, the social impact of this trend is not the topic here.
QUO VADIS: Key Trends in the Future of Digital Business Models
One of the key issues is going to be the quality of the ‘docking station’ attached to the information bubble of the consumers. The precision in which the consumers are understood and predicted will be the key. Two directions could become fundamental:
1. Individual psychological level: Platform-based psychometric consumer analytics
Digital platforms fundamentally differ from the value chains of the ‘old economy’. Previously, the producer may select or establish his own distribution channel for his product or service. Now, in case of markets based on digital platforms, like app-stores from Google or Apple, no alternative ways of distribution are possible for product developer. The digital platform owner determines the standard and owns the entire market segment – he sets the rules and owns the game.
At the same time, the digital platforms are increasing the quality of the consumer understanding. Beside the ‘klick & like’ analytics, new trend are upcoming: sophisticated semantic analysis based on artificial intelligence (AI) algorithms as well as the use of psychometric models, such as ‘The Big Five’. These 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 will become literally individualized.
An impressive and disturbing example of the combinations of big data and psychometrics are the activities of 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
Based on the huge amount of expected data from the upcoming Internet of Things (IoT, or in Germany called Industrie 4.0) trend and the capability to store and process these data, 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: http://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: https://www.youtube.com/watch?v=om3z1yLQtwo.
Near future prediction will be based not only on deterministic calculations, but will increasingly rely on artificial intelligence (AI) with its cognitive processes. AI has a real potential to become a key disruptive technology of the future. Current AI-examples are numerous: beside 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.
I do believe that the future of the digital business models will be strongly influenced, maybe even dominated, by the following developments:
- Individual level: Consumer analytics strongly enhanced by psychometric methods
- Technological level: shift from instant to (near future) predictive technologies based on AI and cognitive technologies analyzing big data
In consequence we may observe the following socio-economical shifts:
- Shift from market economy towards platform economy; competition for the ownership of platforms
- Companies obtaining more power over the consumers, while the consumers will be placed in an illusionary ‘pleasure bubble’ of independence and choice