Hypotheses
Over the course of 2 one-day workshops, all 12 foresight files were presented to the members of the group, who were able to comment on them and add to them. Working from the material in the files, hypotheses on how the macro-variables might evolve were built collectively, distinguishing between:
- Trend-based hypotheses: which relate to dynamics already under way.
- Contrasting hypotheses: which take up uncertainties, controversies and the seeds of change.
- Disruptive hypotheses: which relate to disruptions.
Trend-based hypothesis: The platformisation of industry
The internet giants (Google, Amazon, etc.) make the technology available. At the same time, an M2M standard shared by industry, and not specific to players such as Bosch, Dassault Systèmes or GE, manages to emerge.
The convergence between disruptive technologies (AI, distributed computing, IoT, etc.) promoted by internet leaders and manufacturers fosters the creation of new business models. Manufacturers take ownership of these technologies and reconfigure their production processes, becoming players in technological innovation. At the same time, a cultural shift takes place through the sharing of resources and information between manufacturers.
Manufacturers accept the pooling of resources: sharing of the workforce, M2M, the introduction of a labelling standard for all players in industry (Global Transport Label). Small industrial players also get involved in a context of the sector catching up overall.
However, the risks linked to data security give rise to social and political concerns regarding employment law, competition and the regulation of platforms. Moreover, manufacturers refuse to share "sensitive" information with their competitors, their customers and their suppliers.
Contrasting hypothesis: Platformisation of industry carried out by non-industrial players
Several players, notably start-ups, outpace the traditional players in industry. New platforms offer new business models for industry by mobilising and concentrating new technologies (IoT, AI, etc.).
Development of the human cloud (M-Turk, Taskrabbit, etc.) and of robotisation (Automation Anywhere: a start-up offering generalised robotisation). All functions are "uberized", for example HR: 365 Talents (assessment and internal mobility), maintenance (Pipler, the start-up Mobility Work, a social network for maintenance), marketing (Kantar Marketplaces), asset management (Swissborg); information systems (Skaffolder), sales, research (open innovation), etc.
These start-ups are financed by institutional investors, internet giants, incubators and investment platforms. Investors themselves create new models by detecting opportunities and looking for players able to develop them (start-up studios). An innovation dynamic is sustained by the mix of large companies with substantial financial resources and the start-up ecosystem.
Disruptive hypothesis: Collapse of the platform model
The platform model proves insufficiently profitable, causing the main players to disappear: invalidation of the Uber model and of Chinese-origin platforms (Alibaba, etc.) that fail to develop. Moreover, competition between platforms exerts significant pressure on margins, reducing their profitability. States decide to introduce drastic regulatory policies, for example the drafting of an antitrust law that affects players such as Amazon, which breaks up into several entities, and the drafting of social standards for the benefit of Uber workers. In addition, consumers rebel against the platform model and its hegemony.