The decentralized, public Ledger that was created to serve as the foundation for Bitcoin has evolved and proven its viability for other industries. As a result, the Blockchain Technology has got into its Growth phase, and a wide range of organizations and start-ups are exploring how to utilize its numerous benefits for their advantage.
On this week’s post I would like to share with you a great theory that I have read this week about Increasing returns and the new world of business. The theory, that complements Christensen’s Innovation Dilemma, try to describe how today’s business world operates and how the new technology companies such as Uber manage to overcome some of the incumbents in their industries.
One of the major problems that result in large corporations’ failure to grow and develop itself is the lens through which these companies look at their environments. Oftentimes, as mentioned in the Innovator’s Dilemma post, companies believe they would be successful if they will continue to use the same capabilities and serve the same markets as they have done traditionally. However, that is exactly the reason that these companies will eventually fail. To explain this phenomenon and offer a practical solution Theodore Levitt, one of the most influential business thinkers of his time, defined the term Marketing Myopia.
In last week’s post, I’ve written about developing an innovation capability by establishing structures within the organization such as Centers of Excellence and Innovation Labs. On this week, I will refer to developing an innovation capability from a different approach, from within the organization.
As the importance of innovation rise among different industries, executives seek for alternative approaches and structures that will ensure their ability to innovate successfully.
Gladly, there are various proven ways to design an innovative organization that will have the ability to adapt itself and successfully reach its growth goals and objectives. To achieve these, companies should decide whether they would like to work with their existing organizational structures (which will be covered on next week’s post) or create completely new ones (e.g. Centers of Excellence and Innovation labs).
One of the most famous concepts in Innovation is the Innovation S-Curve, the technology life cycle. This framework, which operates alongside the Bass Model, is used to determine performance in regards to time and effort. It assists in determining the level of maturity of the industry / product.
As a result, when evaluating a product or an industry, it is crucial to understand where it is on the S-curve due to the many implications that result out of that such as the possible risks and pitfalls that are associated for certain phases on it.
Every new technology and product experience an adoption life cycle by the market. In an attempt to understand this process better in particular for high tech products and technologies, Geoffrey A. Moore had studied this thoroughly. the outcome of his research is a term that is well known today among every professional who works in the technology field and it is the chasm.
So what is this Chasm and what is its meaning for the business world? How should we as innovation practitioners should address it? For all of these and more I will try to answer in this post.
According to Joe M. Bohlen, George M. Beal and Everret M. Rogers, every new technology is being adopted by the environment in accordance to the innovation adoption life cycle.
How new organization determine what products they should pursue? How can you tell if a product will become successful or not? How markets react to new products?
For all of these questions, innovators have the Bass model.
The goal of the Bass Model invented by Frank M. Bass is to predict how new products and technologies are diffused among the market. As a result, the Bass Model (or curve as it is called often) assists greatly in describing and predicting the possible markets of new consumer durable products.
Usually, the adoption of these new products and technologies look like this: