Ray Kurzweil, author of several books and well known futurist, has stated that we typically underestimate what will happen far out and overestimate the close in. Richard Foster, the author of Creative Destruction has stated “[People] deal with the complexity of the future by adopting a skeptics bias in the face of good prospects - and an optimists bias about poor prospects”. Both of these statements reflect an underlying difficulty people have in dealing with time.

If one considers innovation as the means of changing the future behaviors and experiences of people in meaningful (and valuable) ways, then innovation deals explicitly with the issue of time and the future. Learning about the future requires knowledge of what can plausibly happen and how to influence potential outcomes. This is also the purpose of strategy in an organization. Strategy is the organization’s method of implementing the influences that will shape the desired, plausible future.

Strategy is therefore intimately tied to time horizons and time horizons are intimately tied to knowledge of the future. Strategy for one time horizon can be viewed as tactics for a longer time horizon. This recursive, or fractal, view of time horizons and strategy is a useful framework for considering how to discover and develop new knowledge and how and when to create knowledge and strategy and how and when to implement it. It is also a useful framework for how to integrate innovation and strategy – two critical aspects of any organizations growth and success.

The Knowledge Maturity Surface

The diagram below shows a relationship between knowledge (amount of knowledge and how ‘mature’ or ‘truthful’ it is), uncertainty (how much is not known and how variable the known knowledge is) and time. What it illustrates is what is intuitively obvious. The more time spent learning about the future, the more knowledge is acquired and the more certain it becomes.

The relationship between the amount of knowledge, certainty and time is not linear since knowledge builds on previous knowledge, but the ‘knowledge maturity surface’ gives a general idea of the decision and action space that is inherent to the front-end of the innovation process and the strategy creation process. Both of these activities occur in the region of little knowledge, maximum uncertainty and a short time horizon to decision. It should be noted that the knowledge-maturity surface can have many forms, not all of them positive. There are cases, some would say they are common, where more time increases uncertainty and decreases knowledge maturity. This is the case when your knowledge discovery tools become corrupted by human cognitive biases as Richard Foster has so aptly noted in the quote mentioned above.

One of the things that this model illustrates is the distinction between the time horizon to decide and the time horizon to act. Decision time horizons are typically very short – matters of weeks or months. The decisions made, however, are decisions about actions that will take place in years or, in some cases, decades.

Deciding and Acting

To learn about the future you need to be very clear about i) the time horizon for your decision process and ii) the time horizon for the actions you will undertake. This relationship between these determines the level of knowledge and uncertainty that is possible in the time allocated. This is shown in the following table.

		Time Horizon for Action
		Near	Mid	Far
Time Horizon for Decision	Rapid
	Paced
	Measured

Rapid decisions taken for actions with a long time horizon have the most inherent risk (the red cell in the table above). In these cases, a robust strategy of option creation is appropriate. The yellow cells are situations with lower, but still significant risk. The green cells represent those case where, given a reliable knowledge discovery process, the decision time frame matches the action time horizon. But note the key assumption in the previous sentence. A reliable and accurate knowledge discovery process, one that is not corrupted by cognitive bias, is necessary to achieve any type of meaningful decision-action framework.

Now look at the knowledge discovery process that underpins the decision-action framework. Knowledge discovery can be characterized by the pace of discovery (rapid, paced, or measured), and by the level of knowledge maturity (nascent, emergent or adaptive).

		Knowledge Acquisition
		Rapid	Paced	Measured
Knowledge Maturity	Nascent
	Emergent
	Adaptive

The knowledge maturity level represents the ability of the acquired knowledge to enable understanding and insight. It represents the depth, the truth and the integration (analysis and synthesis with other knowledge) of the knowledge being discovered or acquired. Nascent knowledge is just that, initial ideas or notions about what may be true, what may matter and what causes what. Expressed knowledge is when a clear causal system can at least be hypothesized and articulated. Adaptive knowledge comes when this causal knowledge system creates understanding and can be used to create plausible futures, the reasons for them and how they can be adapted in the ways desired.

It takes a while for knowledge to mature – to be mulled through, thought about, validated and related to other knowledge items. This maturing process cannot happen overnight (and indeed in some cases doesn’t happen at all). It is therefore important to realize that the rapid knowledge acquisition and decision making typical of the front-end has inherent risks that come from the nature of knowledge and the human mind itself. These risks must also be mitigated with a strong option-based approach.

An Option Framework

This perspective on knowledge maturity and time horizons points to the need for tools to change the beginning of the uncertainty and knowledge curves to drive increases in knowledge and decreases in uncertainty at the early stages of discovery, and to increase the pace of this process to reduce risk. This, in turn, relates to the need to create options to deal with both the uncertainty and knowledge dimensions. An effective action framework is one that can be applied to different time horizons (levels of strategy/tactics) and different elapsed times (different levels of maturity) for both decision making and the action. A process that recognizes the nature of time horizons and knowledge maturity, and provides the tools and methods to influence the pace and manage the risks, is critical to success in the front-end.