One of the things we cannot avoid in strategic thinking is making predictions.  While predictions, being assumptions, inevitably carry the risk of error, there are things we can do to make better predictions.  When you can match an understanding of future trends with a clear vision, your plans are much more likely to be successful.

Making better predictions with curvesIn any complex system built around process flows and limits, we can graph changes over time.  It’s common to refer to a simple XY graph over time as a curve, and the behavior of curves is a very important part of understanding how these systems will change.  If we want to predict automobile sales, new technology adoption, population trends or even the stock market, some simple ideas about the shape of these curves can lead to much better predictions about the future.

Common curve shapes

There are three common curve shapes we encounter.  While I won’t go into the math, it’s important to remember these shapes can be combined to yield other, different shapes.  The three basic types are stable, oscillating and geometric.  The stable curve is just what it sounds like – basically a straight line.  It can have a flat slope – growing arithmetically over time – but it doesn’t do the kinds of ups and downs we often see in graphs of the economy or the stock market.  It’s fairly easy to make better predictions with a stable curve because the slope clearly indicates the rate of change.

Oscillating curves

The second curve shape, oscillating, is very common in complex systems.  This is because complex systems change behavior as limits are approached.  As an example, consider a population of squirrels on an island.  When food is plentiful, the population soars, but when the population reaches a certain point, there is not enough food, and starvation results.  This leads to a crash in population, and the cycle can start all over again.  When you see a graph with consistent undulations, like a sine wave, you are likely seeing a depiction of an oscillating curve.  If you are forecasting around an oscillating curve shape, you can make better predictions by knowing the causes of the cycles you see in the curve.

Geometric curves

The third curve shape is geometric, and it’s common when looking at short term changes, but uncommon over the long term.  This is because the geometric curve represents something that is growing at a geometric rate, where each succeeding time period has a higher rate of growth (or decline).  The reason these are rare over long periods of time is that limits often arise that cause the curve to peak out.  Interestingly, the curve after the peak may either become stable and flat, or decline precipitously.  When there is a repeated cycle of geometric growth followed by geometric decline, we get an oscillating curve.  This means that if you following a geometric curve long enough, you’re likely to see it become and oscillating curve or it will plateau, looking a lot like a simple step up or down.

Example of curve shapes in analysing change in an industry

The reason we want to understand these shapes is that curves can be fairly predictable.  Here’s an example:  in 2000, air travel was becoming less expensive and more pervasive.  The price competition in the industry combined with the ease of online booking was driving a steady increase in passenger miles.  This was not a geometric growth, but it was a positive time for volume in the industry.  Some heavily travelled routes, like New York to Boston, were seeing hourly flight departures that suggested the whole industry was beginning to resemble commuter bussing.  On 9/11 in 2001, terrorist attacks cause a dramatic downward step in that curve which lasted months.  As the industry recovered, restrictions, higher costs and economic pressure shifted the entire curve downward, but it did resume its upward trend – at a slower pace.  If you were a supplier to that industry, or simply invested in airline stocks, understanding this behavior could lead you to some astute observations about the future of the industry.

This kind of prediction is exactly the kind of thing we need to do in our strategic thinking.  While no one can predict the kind of disaster that leads to a step down, it was useful to note that the effect of the attacks was a sharp step down followed by lower stable growth.  An important question for your business is what the curves you see will do in the next few years.  Do you anticipate a dramatic step up, a flat upward trend, or an oscillating curve that may slope upward?  One of the most important ways to make these predictions well is to understand the real world factors that lead to these different shapes.  If you can accurately assess the dynamics of your environment, it’s possible to do an excellent job of thinking strategically about where your organization should go.

If you are considering new directions for your organization, now is an excellent time to bring new strategic thinking into your strategic planning process.  Our online seminar is a great way to learn more about strategic thinking and how to beat or avoid your competition.

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