The genesis of the novel and new is, by its very nature, highly uncertain and hence unpredictable. You can make reasonable guesses by looking at components that are commoditizing and how they may be used to create other things but this is more about narrowing down a potential wide field to what is more likely. For example, today with ubiquitous and well-defined components for computer infrastructure, data capture through devices, voice recognition and complex search capabilities, predictive algorithms and ... then you could guess that “intelligent agents” will arise. In fact this is already happening with tools such as Google Now or MindMeld
In general genesis is extremely hard to predict. It’s like being able to predict the rise of television when Westinghouse introduced utility provision of electricity. The odds are not in your favour.
Solution to the Genesis Problem
Other than normal means of experimentation with fail quick, the only effective way of solving this problem is to get others to create the novel and new for you. The approach of using an ecosystem under an ILC model is specifically focused on this.
Many products provide for numerous needs of consumers. Such products often have complex value chains with many high level visible components. Competing products also often differentiate with novel and new components. In some cases one product will simply be beaten by a better product (i.e. iPhone vs Blackberry). In some cases, the substitution of one product with another (e.g. cable vs hydraulic excavators) occurs because of changes in the value chain such as a new component or characteristic becoming important. This is extremely hard to predict and the competitor often develops in underserved markets first. Unfortunately the change is also compounded by inertia caused by pre-existing business models that sell one form of the product to established customers (e.g. cable excavators). The market is seen to move in an “unpredictable” or “unexpected” manner with existing vendors that are suffering from inertia likely to be “disrupted”. This is a classic case of the Innovator’s Dilemma.
Solution to Substitution
Protecting yourself against such “unexpected” market change is extremely difficult. Given some new characteristic or a change in the value chain then the opponent can often establish themselves in other underserved markets before attacking the main market. Being able to see that hydraulic will replace cable excavators requires incredible foresight. The best option is access to information (as per the ecosystem model) combined with a willingness to understand that existing models can be replaced. Often a method of buying up smaller companies that are growing and which could provide alternative approaches is relatively sound but the innovator’s dilemma is an extremely hard nut to crack.
Unlike the creation of the novel and new (genesis) or the substitution of one value chain with another, the evolution of any activity, practice or data is highly predictable. For example, the shift from genesis to custom built to products (and rental services) to commodity (and utility services) is a well-trodden path.
The process of evolution is governed by competition between all actors (consumers and suppliers) however the timing depends upon the actions of individual actors. Hence whilst evolution (the “what”) is predictable, “when” it will occur is not.
An example of this is cloud computing and the shift towards utility services. This was a highly predictable change in terms of “what” which was first described in 1966 in Douglas Parkhill’s book the challenge of the computer utility. The precise “when” however depended upon individual actors and hence was not predictable.
The difference between changes that result from the interaction of all actors (e.g. the “what” of evolution) vs. changes that result from individual actors (e.g. the “when” of evolution) is essential in understanding many broad economic effects. For example, whilst Cloud Computing was an inevitable consequence of evolution, the question of centralization vs decentralization very much depends upon the game play between the individual actors in the market.
Solution to Evolution
The issues caused by evolution, such as disruption of past business models and inertia to change can be prepared for well in advance due to its highly predictable nature. However, the “when” of action needs to be resolved by looking for weak signals such as consumer dissatisfaction with the cost associated with an activity. Changes such as cloud computing are often associated with the Innovator’s dilemma however given this class of change is neither “unexpected” nor “unpredictable” there exist little reason why any corporation should be disrupted by such a change other than through executive failure.
Economic Cycles (Predictable)
Since evolution is predictable, the corresponding economic phases of peace, war and wonder are also predictable. This means the style of competition and types of approaches needed for each phase can also be prepared for e.g:-
- The “war” phase is all about operational efficiency, volume operations and provision of good enough components.
- The “wonder” phase is all about experimentation, the rush to become established and rapid rates of genesis. Though “what” is created is unpredictable, the “when” is predictable i.e. during this phase, novel and new creations will appear which will dominate our society over time.
- The “peace” phase is all about maintenance of profitability and the status quo.
Solution to Economic Cycle
The solution is simply to understand the style of competition, type of leadership and the methods that are appropriate change with evolution of any activity, data or practice.
Mapping is a useful technique in visualizing the environment onto which the above rules can be applied. In Boyd’s OODA loop (observe, orient, decide, act) then mapping is focused on the first step of observation and hence increasing situational awareness. Without this any action or strategy is akin to shooting in the dark. In such environments, companies are reduced to simply observing what others are doing. Symptoms of this include many decisions being based upon backward causality i.e. if successful Company A does X then by doing X we will become successful. Copying, use of hype-cycles, analyst reports on the market become rife.
Assuming the reader has an understanding of mapping, then I find the following table useful when dealing with prediction: -
Post 25 on Management and Strategy series.
Next post in series ... Falsifiability and Secondary Predictions
Previous post in series ... On Structure
Beginning of the Management and Strategy series ... There must be some way out of here