The discussions at the Academy of Management annual meeting symposium – “A Multi-Disciplinary Perspective on Platform Ecosystems Research” made a strong case for platforms as a primary model to understand business models. Industry Platforms and Ecosystem Innovation also makes a strong case for the central role of platforms in evolution of a firm.
At the firm level using the 5 patterns described in “The New Patterns of Innovation” provide a simple way to identify innovation ideas and explore opportunities for growth. Considering these ideas as candidate platforms allows the full market potential of the idea to be explored. In addition, the challenges in creating the ecosystem of complementors, design of the digital platform, impacts to the current organisation and financial case can be created.
Adding the structure of Component Business Modelling can provide an analytical framework to substantiate the financial case and develop the change programme.
These tools all seem to point to the digital platform as being the primary value creation tool for established business and there is clear need for unpacking this idea into a practical toolbox for managers.
As I reflect on the emerging 3 laws of digitisation, I have been asked many times if there is an overall “business case” for the shift in labour or GDP. The way I think about this is to start with some very simple high level metrics.
Global GDP is 75 Trillion approximately. (World Bank)
The high-level industry breakdown extrapolating the UK data:
Digitisation in the form of the pattern 1 : augmented product pattern will allow the manufacturing industries to grow into the service industries and capture some of this GDP. If they are wildly successful, they could increase the GDP by 20% over a 20 year period and grow to 28% and take share from the service industries. This represents a $3.5tr shift in GDP as a direct result of the augmented product pattern.
For the service industries digitisation will lead to pattern 5: codify services. If we consider the service industries as consisting of three broad groups – creative, routine and personal. Creative includes graphic designers, engineers etc. Personal includes hair dressers, local retailers etc. Routine includes those with a significant element of routine work that is highly likely to be digitised using combinations of Cognitive technologies such as AI or Machine Learning. If we make the assumption that these represent an even distribution of the service industries i.e. 25% each of the 75% GDP. The impact on the 25% of the routine service industry is the question we need to explore further to understand the business case.
If the manufacturing industries are successful in their augmented industry pattern, we can see the routine service industry being reduced by 5%. The remaining 20% will be subject to further digitisation. A working assumption could be that 50% of this will be displaced in the 20-50 year period and open a new industry for services digitisation. If we assumed creating the platform for digitisation will be the key to success, and there will be an exponential adoption, we could argue 25% of the transformation will happen in the first 20 years and so a further reduction of 5% is possible.
The conclusion is that the digitisation industries have the opportunity to represent 10% of the global GDP over a 20 year period. Which based on current GDP value is $7.5tr.