Are there some fundamental laws for digitisation?

As we have learned in through the development of other sciences, fundamental laws emerge which help us make sense of evolution. Digitisation many would argue is still in it’s infancy, but there may be sufficient examples to start to identify some candidate fundamental laws. In the HBR Paper “New Patterns for Innovation”, we identified the 5 atomic business model patterns that result from applying digitisation. They continue to serve well in developing the innovation strategy within a business. However, are there more fundamental laws at play here?

The first candidate law seems to be that data has gravity. Technopedia has a good summary as does this McGrory’s blog. So the amount of data you have is important, and how you use this continually attract new data and increase the gravitational effect. The risk of course is that having too little data, will result in the data being subsumed by a larger pull of data. The effort required to ensure that this data remains distinct, relevant, and current can be determined.

The second candidate law is what can be digitised, will be digitised. Digitisation increase the understanding of the thing being digitised. It guides the improvement and optimisation. In some cases digitisation replaces the physical object. Think of the bus ticket. 40 years ago you would see conductors on the bus taking a passengers money in return for a printed paper ticket. Digitisation led to the creation of ticket machines that provided machine readable cards, then to contact-less travel cards and now apps on phones.

This leads us nicely to the third and final candidate law – what ever is digitised, tends to become free. The wired article Free! Why $0.00 is the future business model provides a compelling case. In his book “The Curve”, Nicholas Lovell explains how to make money when everything is going free. Daniel Pink in “A Whole Mind” discusses the 3 A’s of Automation, Abundance and Aisa that is driving the need for whole mind thinking. The underlying narrative is how individuals need to find ways to remain valuable when digitisation in the form of automation is driving out costs.

As a Digital Leader, these three laws can help guide you in the development of your strategies and plans to:

  1. Use digitisation to disrupt established industries
  2. Identify the risks of digitisation and develop mitigating plans
  3. Transform your business to remain relevant and valuable.

What are the generic data platform business models?

Over the last 3 months, there has been a common set of questions about the design of the underlying business model for a data platform. If you have a data set that you think is valuable, how should you “sell” it?

  1. Data as a product.
    This is the simplest model and in essence you sell all or part of that data for a defined value. This is a one off payment as for a product and the purchaser has unrestricted use of that data. This is typically useful for static data e..g clinical trials, survey results, insights from analytics.
  2. Subscription model
    The purchaser is able to access defined portions of the data, through an API. Restrictions are often applied on quality of data, frequency of access, usage etc.
  3. Analysis or Model as a Service
    Here the data provider will create a model where the purchaser is able to add their own data to create unique insights. As an example, retail sales data gathers for areas of a city can be provided as a model to allow real estate companies assess the value of developing a shopping mall at a particular location.
  4. Insight as a Service
    Consultants or experts are made available by the data platform provider to provide insights or answers to specific questions required by the purchaser. This is essentially a consulting service, where the consultants are data scientists that have access to unique data stores and analysis tools. Benchmarking services are a good example here.

These seem to be the four generic models I have come across so far. What other models have you come across?

Having data is an ideal starting place for the Digitial Economy..

The digital economy is not possible without any data, but you can still play a significant part by having access to data. However, you need “big data” to start to find the interesting patterns and the insights that are going to make a real difference. So IBM’s announcement to acquire the’s digital business should be no surprise.

Weather can often allow new levels of automated optimization that previously unimaginable. We can all image the retailing examples, however the manufactures being able to tune assembly lines based on weather create fascinating opportunities.

I look forward to seeing these new uses emerge in the near future.

Here are a few of the articles in the press that I found interesting background.

Is Blockchain the next digital economy platform?

As we see the exponential rise in the use of blockchain technologies, many are asking is this the next digital economy platform. So before we can answer this question we need a structure for the types of digital economy platforms. The 5 New Patterns for Innovation provides a framework exploring the potential value.

Pattern Role of Blockchain Value to be captured
Product Augmentation Capture history of product design, manufacture and usage Product enhancement, offer services to enhance product experience
Codify Services Capture audit trail of usage Limited value – possibly simplify billing
Interconnect Industries Be the trusted platform to share data across the industries Optimisation of the interactions by removing friction
Trade Data Capture audit trail of how insights were derived Could create
Digitise Assets Capture audit trail of usage Limited value..

In essence the blockchain has most value in creating an open trusted ledger for interactions that span multiple organisation boundaries. The analysis published in the “4 Trillion Dollar Challenge” provides a view of the industries where there is potential value from the blockchain technologies. This leads me to believe that blockchain is likely to disrupt many if not all interactions across multiple organisations and so is likely to be a s very significant platform in the digital economy in the future.