| How many times have you and your company, | | | | revising prices on a quarterly basis may produce the |
| debated and fought over the potential outcomes of | | | | same disruption and disorientation as would revisions |
| a particular pricing strategy, only to have seemingly | | | | on a monthly or weekly basis. You could then focus |
| random, unpredictable factors rear their ugly heads? | | | | planning on other factors such as brand investment, |
| How many analytical tools have you used: game | | | | efficient use of resources and so on. The idea is that |
| theory, forecasting, market research, decision-tree | | | | you should expect ranges of control parameter |
| analyses,... only to realize that none of these was able | | | | values where the system behavior is relatively |
| to help predict much beyond the next quarter or less. | | | | consistent; but you should also note parameter |
| Welcome to our wonderful world of chaos! | | | | ranges where small adjustments produce drastic |
| So what is happening? Just as in the movie, Jurassic | | | | changes in response. If you were an IC manufacturer |
| Park, industries evolve in a very dynamic way given | | | | with facilities to improve efficiencies more quickly |
| complex interactions. As in nature, very small | | | | than your competitors, you may want to introduce |
| disturbances can lead to significantly different | | | | small but frequent, price changes to disrupt the |
| outcomes- a reflection of a chaotic system. | | | | market and drive competitors out that cannot follow |
| Briefly, chaos theory considers nonlinear systems. In | | | | the efficiencies and maintain margins. |
| a linear system, if I do A then I know that B will | | | | PREDICTABILITY |
| happen and C will happen as a result of this. But, | | | | HOW DOES chaos theory explain, reduce or increase |
| according to chaos theory, a number of variables will | | | | predictability? |
| change what happens between A and B and then | | | | In the near-term chaos can be used to uncover |
| between B and C. Again, as in Jurassic Park, a | | | | patterns and sub patterns that are not apparent and |
| butterfly may flap its wings and its rains in Central | | | | this information can be used to project the behavior |
| Park. | | | | of an industry that has irregular dynamics. Chaos |
| There are a few points to be aware of when | | | | analysts have been able to tease out competitors |
| thinking about the impact of chaos on pricing: | | | | pricing activities by using techniques that allow them |
| There are deterministic relationships between the | | | | to find information embedded within a mass of |
| participants in a chaotic system but only patterned | | | | background noise ( the economy, stock market |
| outcomes and not predictable, outcomes result. In | | | | fluctuations, commodity prices, etc) over the short |
| the business world, outcomes reflect very complex | | | | term. In addition, using chaos theory, pricing |
| underlying relationships that include the interaction of | | | | decision-makers have been able to estimate how long |
| several potentially chaotic systems; crop prices for | | | | the projections may be useful. |
| example, are influenced by the interaction of | | | | Over the longer term, while the paths of individual |
| economic and weather systems. While, chaos theory | | | | chaotic trajectories cannot be predicted accurately |
| provides guidance on crop price cycle patterns, it | | | | for very long, knowledge of the system attractors |
| says that it's basically impossible to predict exactly | | | | provides useful information about the long-term |
| the size of the fluctuations or their timing. | | | | trends in system/industry behavior. In chaos theory, |
| Chaos theory, however, does say that prices will | | | | the 'strange attractor' plays an organizing role, as the |
| vary between particular boundaries. | | | | order or pattern at the heart of what appears to be |
| In chaotic systems, small disturbances multiply over | | | | chaos. For example, if you're packing to go to |
| time because of nonlinear relationships and the | | | | Minneapolis in January, you'll pack very differently |
| dynamic, repetitive nature of chaotic systems. As a | | | | than if you were going to Miami, without any current |
| result, such systems are extremely sensitive to initial | | | | weather information. So, in Minneapolis the basic |
| conditions. For example, Dell's mail order strategy | | | | attractor is such that the temperatures trend to a |
| forced other companies to reduce their prices and | | | | point that will be below freezing. You would have |
| reexamine their traditional high-cost sales and service | | | | made your packing decisions based on some |
| channels. | | | | knowledge of the system trends. One major |
| While you might think that by obtaining better models | | | | producer of surfactants in Europe, knowing that |
| and a more accurate specification of starting | | | | market dynamics were such that an industry |
| conditions, better forecasts would result. Chaos | | | | attractor was leading to rapid price declines, used |
| theory suggests that the payoff from developing | | | | that knowledge to offer 10% discounts upfront for |
| more accurate models may be small. Oil companies | | | | the signing of one-year contracts. At the end of the |
| recognize this and have developed pricing models | | | | year, other competitors were facing 50% lower |
| that take into account the numerous factors that | | | | prices. |
| could influence prices at the pump- making ongoing | | | | CONTROLLING CHAOS |
| adjustments to prices. | | | | Chaos theory helps first, by recognizing that an |
| In contrast to game theoretic models that predict | | | | attractor can help understand and manipulate the |
| equilibrium outcomes, chaotic systems do not reach a | | | | industry or system since the attractor gives form |
| stable equilibrium. They never pass through the same | | | | and structure to behavior that we might otherwise |
| state more than once. The implication is that | | | | dismiss as random. Second, if you can find an |
| industries do not settle down and any apparent | | | | attractor for an industry (system), then any |
| stability for example, in pricing, is likely to be | | | | disturbances to the current state will still render its |
| short-lived. | | | | particular evolution unpredictable (think of a swinging |
| A chaotic system constantly changes based on the | | | | tire). But any, transient behavior eventually dies out, |
| feedback that results from the actions of players in | | | | and the global system behavior trends are |
| the system | | | | unchanged. Third, there is some hope of predicting |
| Chaotic behavior can take place on an attractor, in | | | | basins of attraction, so that in initiating pricing moves, |
| which case, a large set of initial conditions will lead to | | | | you can set up initial conditions so that the systems |
| convergence towards a particular pattern of behavior. | | | | evolves under its own dynamics towards the trends |
| USING CHAOS THEORY IN PRICING STRATEGY | | | | of the attractor that you want. For example, if you |
| Use Of Feedback | | | | were the lowest cost producer in a price sensitive |
| The results of chaos theory help us know what | | | | market with a large number of aggressive |
| transitions to expect when we add feedback to a | | | | competitors, by taking a small decrease in price you |
| system and suggest ways to adjust feedback. | | | | would likely initiate a price war. The attractor, |
| For example, suppose that you observe a change in | | | | industry movement towards the lowest price, would |
| your competitor's behavior based on how often you | | | | ultimately favor you, as the lowest cost producer. |
| change your prices. Normally, your competitor may | | | | KEY LEARNINGS |
| not change prices when you make no price changes; | | | | By thinking about your industry as a chaotic system, |
| but, if you have adjusted your prices, the competitor | | | | you need to be aware of the extent to which |
| responds by changing prices on some key products. | | | | uncertainties can disrupt the industry and dramatic |
| Should you double your rate of price changes to | | | | change can occur unexpectedly- so flexibility and |
| twice a year, your competitor may then change | | | | adaptiveness in pricing are necessary |
| prices on all products. You have cut the time | | | | As a result, you need to identify the key metrics |
| difference between significant events in half and | | | | that will provide you with sufficiently fast feedback |
| observe a transition in the system. While it is not | | | | so that the chaos does not get to the extreme |
| clear exactly how you can predict the next transition | | | | boundaries that chaotic systems can reach. |
| in competitive behavior by decreasing the time | | | | By testing and understanding the dynamics of a |
| between price changes, you should at least be alert | | | | chaotic system, you can mitigate the potential |
| that the next transition in this system could occur | | | | downside of a chaotic industry. |
| only if we increase the frequency of price changes | | | | Most importantly, Chaos can be controlled. Chaos |
| by a small amount. Such an understanding of the | | | | theory demonstrates that a chaotic system, |
| chaotic dynamics should help you understand and | | | | previously thought of as random, can be influenced |
| control your own response, selected from a flexible | | | | so that it becomes stable. Small changes can make |
| range of options, given the likely transitions tested | | | | big differences. There are three techniques for doing |
| when the system control parameters were tested. | | | | this, described above. |
| Another key use of feedback being introduced into a | | | | Regular periodic disturbances can be introduced into |
| system so as to create chaos is the relative timing | | | | the system so that the system responds in a |
| of an incursion on a competitive decision cycle (it | | | | manner that will see it evolve into the longer term |
| may even be more important than the magnitude of | | | | trends that you may want based on an attractor |
| the incursion). Many successful strategies hinge on | | | | describing the longer-term recurrent behavior that |
| "getting inside the decision cycle" of the competitor. | | | | you want in an industry. |
| The idea is to take some pricing action and then | | | | Real-time measurements of the system output to |
| move with such agility as to make a subsequent | | | | determine how far to adjust the selected control |
| move before the competitor has time to orient, | | | | parameter ( think of keeping a yardstick balanced on |
| observe, decide and act (OODA, to use a military | | | | the palm of your hand; by moving your hand a bit, |
| term) in response to your first pricing move. Chaos | | | | you keep the yardstick balanced). While this requires |
| theory offers an important new insight into this basic | | | | a constant feedback loop, a stable output is reached |
| strategy: we should expect ranges of different | | | | intentionally, and not in a "hit and miss manner". |
| responses depending on how tightly we approach the | | | | Extensive calculations can be developed to |
| duration of the OODA loop. That is, to outpace the | | | | approximate the dynamics of the system's attractor. |
| competitor that may operate on a semi-annual basis, | | | | |