Six Rules for Effective Forecasting. By: Saffo, Paul, Harvard Business Review, 00178012, Jul/Aug2007, Vol. 85, Issue 7/8
I liked this article because I am advocating this philosophy to share investors/traders and also to analysts. (KVSSNRao)
The goal of forecasting is not to predict the future but to tell you what you need to know to take meaningful action in the present
PEOPLE AT COCKTAIL PARTIES are always asking me for stock tips, and then they want to know how my predictions have turned out. Their requests reveal the common but fundamentally erroneous perception that forecasters make predictions.
Forecasting looks at how hidden currents in the present signal possible changes in direction for companies, societies, or the world at large. Thus, the primary goal of forecasting is to identify the full range of possibilities, not a limited set of illusory certainties. Whether a specific forecast actually turns out to be accurate is only part of the picture. Above all, the forecaster's task is to map uncertainty, for in a world where our actions in the present influence the future, uncertainty is opportunity.
Unlike a prediction, a forecast must have a logic to it. The forecaster must be able to articulate and defend that logic. Moreover, the consumer of the forecast must understand enough of the forecast process and logic to make an independent assessment of its quality -- and to properly account for the opportunities and risks it presents. The wise consumer of a forecast is not a trusting bystander but a participant and, above all, a critic.
As a decision maker, you ultimately have to rely on your intuition and judgment. There's no getting around that in a world of uncertainty. But effective forecasting provides essential context that informs your intuition. It broadens your understanding by revealing overlooked possibilities and exposing unexamined assumptions regarding hoped-for outcomes. At the same time, it narrows the decision space within which you must exercise your intuition.
Change rarely unfolds in a straight line. The most important developments typically follow the S-curve shape of a power law: Change starts slowly and incrementally, putters along quietly, and then suddenly explodes, eventually tapering off and even dropping back down.
The art of forecasting is to identify an S-curve pattern as it begins to emerge, well ahead of the inflection point. The tricky part of S curves is that they inevitably invite us to focus on the inflection point, that dramatic moment of takeoff when fortunes are made and revolutions launched. But the wise forecaster will look to the left of the curve in hopes of identifying the inflection point's inevitable precursors.
The entire portion of the S curve to the left of the inflection point is paved with indicators -- subtle pointers that when aggregated become powerful hints of things to come. The best way for forecasters to spot an emerging S curve is to become attuned to things that don't fit, things people can't classify or will even reject. Because of our dislike of uncertainty and our preoccupation with the present, we tend to ignore indicators that don't fit into familiar boxes. But by definition anything that is truly new won't fit into a category that already exists.
In forecasting, as in navigation, lots of interlocking weak information is vastly more trustworthy than a point or two of strong information. The problem is that traditional research habits are based on collecting strong information. And once researchers have gone through the long process of developing a beautiful hypothesis, they have a tendency to ignore any evidence that contradicts their conclusion. This inevitable resistance to contradictory information is responsible in no small part for the nonlinear process of paradigm shifts identified by Thomas Kuhn in his classic The Structure of Scientific Revolutions. Once a theory gains wide acceptance, there follows a long stable period in which the theory remains accepted wisdom. All the while, however, contradictory evidence is quietly building that eventually results in a sudden shift.
Good forecasting is the reverse: It is a process of strong opinions, weakly held. If you must forecast, then forecast often -- and be the first one to prove yourself wrong.
So when you look back for parallels, always look back at least twice as far as you are looking forward. Search for similar patterns, keeping in mind that history -- especially recent history -- rarely repeats itself directly. And don't be afraid to keep looking further back if the double interval is not enough to trigger your forecaster's informed intuition.
The hardest part of looking back is to know when history doesn't fit. The temptation is to use history (as the old analogy goes) the way a drunk uses a lamppost, for support rather than illumination. That's the single worst mistake a forecaster can make, and examples, unfortunately, abound.
Paul Saffo (firstname.lastname@example.org) is a forecaster based in Silicon Valley, in California.