Breakthrough Ideas (continued)
Foresight Into Qualcomm’s Potential Faces Residual Uncertainty
Rule The World investing strives to winnow uncertainty in a rapidly changing world--changing because of accelerating advances in knowledge, technology, globalization, and connectivity--to sift the grain of uncertain times to sieve its rare and precious kernels of opportunity. The search is for companies with unusually strong and sustainable competitive positions that strategically shape large opportunities for unusual profit.
Thus, the investor desires foresight, the prescience gained by looking forward through the present into a probable future, a foreknowledge based on the best possible analysis that enables selecting the right company before the market has discounted a precious insight into a stock’s probable future. Foresight uses all the information that can be known as distinguished from what cannot be known. I would add that this information should be advantaged, possessing a high ratio of power to simplicity.
Only the foolish are undaunted by uncertainty, but only the coward turns from it. The brave investor embraces uncertainty to perceive whether its face is one of promise or peril. By crafting a strategy for understanding advantaged information, and by securing the best available information, and by analyzing it with awareness of what is knowable from which specific significant events, strategic understanding transforms commonplace uncertainty into an investing advantage. Mix theoretical topsight and the best available information, then season with astute analysis and you can create insight that reduces the residual uncertainties until foresight emerges. Disciplined foresight requires venturing prudently by matching investment size to foresight gained.
Can we learn to identify the key events and seek out the momentous moments when dynamic movement down a strategic path crosses the threshold of significance, giving birth to opportunity? If, and only if, we can identify the steppingstone events, can we monitor strategic movement along a dynamic path, watching as it unfolds, waiting until it becomes just probable enough to invest with confidence. Despite any lingering, but inevitable, residuals of unknowable uncertainty, if we can correctly anticipate the conditions required for its generation, then we can see intelligently reduced uncertainty born anew as emergent opportunity. The theory of dynamic paths and 20/20 foresight into the idea of residual uncertainty are required to be able to recognize the normally unseen face of opportunity.
20/20 Foresight. In "20/20 Foresight: Crafting Strategy in an Uncertain World," Hugh Courtney (2001) described the key conceptual distinctions from the McKinsey Strategic Theory Initiative’s (STI) study of strategy for making decisions under conditions of high uncertainty.
In a rapidly changing business landscape, the McKinsey group discovered that the traditional tried-and-true approach of building a fact-based business case, which makes point-forecasts of value drivers to ascertain their net present value, failed. Failed, because their forecasters and decision-makers had unwittingly ignored uncertainties. Failed, because companies were seduced by the power of the DCF model and its resulting requirements to forecast what they could not know.
Uncertainty typically pulls a binary response. “We must ignore uncertainty and make the our business case point-forecasts as usual,” or “Thing are so uncertain that we must abandon all rigor for intuition.”
The McKinsey Group believed that when forecasters dared see uncertainty, their hands had held the wrong tools; when forecasters acted blindly by ignoring uncertainty, they failed to use the right tools that could reduce uncertainty further. Without foresight into uncertainty itself, you can neither see risk nor grasp opportunity in uncertain times.
Four Levels of Residual Uncertainty.
In between the white of “uncertainty does not exist” and the black of “uncertainty blocks all analytical rigor,” Courtney offers the paradoxical certainty that uncertainty is not binary because residual uncertainty can be partitioned into only four levels. Residual uncertainty is the uncertainty left over after the best possible analysis of the problem at hand. Adopting STI’s framework of four levels of residual uncertainty leaves behind the trap of all-or-nothing actions.
Decision makers achieve 20/20 foresight when they accurately identify the specific level of residual uncertainty they face and then act accordingly.
To make any strategic decision under uncertainty, you must follow a four-step process: (a) Define the strategic issue and its level of residual uncertainty; (b) Frame possible solutions; (c) Analyze possible solutions and make strategy choices; and, (d) Monitor and update strategy choices over time.
First, identify the key variables that matter in crafting your strategy. For instance, Courtney mentions customer demand, drivers of capital and operating costs, technology performance, competitor behavior, and the like. As an investor, you might identify competitive advantages, proprietary open architecture, network externalities, strong value chain, competitor behavior, position in the technology life cycle, business design, architectural control, and the like.
Second, establish a time frame to evaluate your chosen strategy against measures of success.
Third, ask yourself not just what do I know now, but instead, after determining the level of residual uncertainty and making the best possible analysis of the best possible current information, continue by asking what more can I come to know and understand about these key variables and the unfolding events that decisively disclose what is most essential and imperative to know both now and over my selected time frame.
Fourth, continue to monitor the stepping-stone events that lead the milestone criteria you have selected for, say, strategic architectural control.
According to Courtney, to develop 20/20 foresight, your answers must always identify one of only four general forms that define the level of residual uncertainty:
Level 1. A clear single view of the future
Level 2. A limited set of possible future outcomes, one of which will occur
Level 3. A range of possible future outcomes
Level 4. A limitless range of possible future outcomes
Level 1 residual uncertainty occurs only in stable, information-rich environments. You can develop a single clear view of the future when the future path of every key value driver is known well enough to measure or estimate because change is slow and well defined and information is available.
Often, this includes conditions such as retail competitions among established brands with established market share positions in which customers are well known or “owned” and competitors follow expectable strategies.
This well-trod ground permits point-forecasts and the usual NPV tools used in the business case strategic process. You don’t know absolutely everything with certainty, but you can have reasonable confidence in your analysis of how this future will unfold because it is clear enough that it will be an extension of the past into a stable, orderly, and predictable future.
Courtney identified three sources of Level 1 uncertainty: (a) returns on “common” investments in mature stable markets; (b) customer and competitor reactions to strategies to reposition well-established brands; and (c) returns on “uncommon” investments in mature stable markets.
However, the dynamic, non-linear and surprising business landscapes of high tech investing don’t dwell in this traditional world of static, linear, and predictable businesses-as-usual. Instead, most of the residual uncertainty that can be analyzed to produce advantaged information resides at residual uncertainty Levels 2 or 3.
Future outcomes of Level 4 uncertainties are both unknown and unknowable because it is not possible to identify the relevant variables that will shape and define the uncertain future.
There is a limitless range of potential outcomes in markets because either the market is just beginning to form or has experienced a major discontinuity engendered by a radical turn in technology, economics, or social forces. Discontinuities are uncommon.
In time, Level 4 uncertainties decay, breaking down as the field of forces self-organizes and patterns emerge. An unknowable uncertainty becomes bounded as drivers become recognizable and we can infer a range of possible outcomes because we know some of what cannot happen and a range of expected possible outcomes, accepting Level 3 residual uncertainties as the best available now.
Level 2 uncertainty deals with a limited set of alternative futures, one of which will occur.
This set of possible future alternatives can be precisely categorized as mutually exclusive and collectively exhaustive (MECE).
Three sources of Level 2 Uncertainty are: (a) potential regulatory, legislative, or judicial changes, (b) unpredictable competitor moves and countermoves, and (c) all-or-nothing industry standard competitions.
Courtney cited Qualcomm as an example of Level 2 uncertainty as it tried to establish CDMA as the 3G standard.
Level 3 uncertainty concerns a range of possible future outcomes, where it is possible only to identify or define a representative set of possible outcomes.
Three sources of Level 3 uncertainty are: (a) customer demand for new products or services, (b) the relative performance of and customer preference for new competing technologies, business models, or processes, and (c) unstable macroeconomic conditions.
What is required is systematic rigor under conditions of uncertainty. We must use specific tools that can help reduce that uncertainty by separating the unknown from the unknowable when using the best available advantaged information.
Courtney went on to discuss the circumstances and conditions that favor strategies that: (a) shape or adapt, (b) commit now or later, and (c) focus or diversify strategies.
Next, he extended the traditional toolkit by adding specific supplements that are most relevant to the level of and conditions producing high uncertainty.
Courtney concluded by discussing the alternative processes that companies should use to monitor and update their strategies over time. |
