The Future Really Is Now

Forecaster Paul Saffo explains how to recognize it when you see it.

Silicon Valley is littered with the corpses of companies who mistook a clear view for a short distance, says Paul Saffo in this months Harvard Business Review. Even when you see a change coming, its difficult to estimate how quickly it will arrive, Saffo says, but understanding forecasting can help you turn uncertainty into opportunity. Saffo (, a veteran forecaster who explores the impact of long-term technological change on society, shared some of the tricks of the trade with Kathleen Melymuka.

What is forecasting, and how does it differ from predicting? Predicting is about certainty, and forecasting is about appreciating uncertainty. Forecasting gives a context for decision-makers to act in the face of uncertainty. In the business world, uncertainty is our friend, because uncertainty is opportunity.

Paul Saffo

Paul SaffoWhy should a CIO care about forecasting? Forecasting is more important than ever for CIOs today because the CIO job function is central to enabling the corporate strategy, and the underlying tools that CIOs use are changing at the rate of Moores Law. CIOs live in the eye of the hurricane.

What is the role of intuition in forecasting? When youre making a decision, its very, very rare that you can have 100% of the information. If you wait until you do, that opportunity will have passed. So any strategic decision is going to require action before all the information is available, and it will require an intuitive leap. Its folly to rely on blind intuition, but forecasting makes your intuition informed intuition.

What is the cone of uncertainty, and how do you use it in forecasting? Its a way of thinking about what lies ahead. Youve seen it on the weather map: They draw a cone showing all the places a storm could go. Its also the cone of possibility: the space that encompasses all the possible outcomes that could unfold from some present moment. I think its a good visual aid. It forces me to make sure Ive accounted for all possible outcomes. Thats the essential step in forecasting.

What are wild cards, and why are they so difficult to read? A wild card is a trend or event that has either a very low probability less than 15% or a likelihood of occurring that you simply cannot quantify. Right now, an interesting wild card in IT is quantum computing: How quickly does it arrive? Its coming eventually, but is it a decade or two off? What if it happens in the next two to three years? It would completely negate all the advantages of public-key cryptography. There would be no secrets. The impact would be huge.

Tell me about S curves. Humans are linear thinkers, but almost everything interesting in life is nonlinear and follows an S-shaped pattern. Television, PCs, use of the Internet all had S-shaped adoption curves. CIOs have been surfing the mother of all S curves: Moores Law. The key question is, where on the S curve are we?

What are the common mistakes in forecasting S curves? The most common is to assume its a hockey stick [shape]. But things do not go up forever. Eventually theres a leveling off, and then the curve starts going downward. Knowing when the S curve is topping out is essential because you have to jump to another platform, and usually what will replace the old order is inferior when it first comes out. You have to make a tough choice about how long to hang on to legacy and when to jump, without being too early or too late.

What are some other mistakes with S curves? Everybody obsesses on the inflection point because thats how to make money. But if you want to understand the inflection point, pay attention to the long, flat line to the left of it. One of the secrets in my business is that everything changes slower than people imagine. Change only seems fast because people overlook the antecedents. Most ideas take 20 years to become overnight successes. The Internet was almost 20 years old in 1988 when Al Gore invented it. If something has been tried a million times and its never caught on, and its about 20 years old and everybodys dismissed it, pay close attention: It may surprise you.

How do you spot an emerging S curve? Look for little hints of things in the zeitgeist that dont quite fit that seem odd but might be whispering about the future. When you see them stringing together, you realize theyre beginning to form that flat part of the S curve. An example: the Roomba, the little vacuum robot. People are very attached to it. I had friends who were as excited about the Roomba as they were with the original 128K Mac. Also, iRobot [the maker] says that two-thirds of Roomba owners give them names, and one-third admit to having taken them on vacation with them. This is about something much deeper than clean floors.

What do you see coming next? Theres a wave building on the horizon because of sensors. Sensors are putting eyes, ears and sensory organization on computers and asking them to observe and manipulate the physical world on our behalf. And the poster child for sensors pretty clearly is going to be robots. Just as people were surprised and astonished by the PC in the 80s and the World Wide Web in the 90s, in a couple years maybe as soon as five years, but probably longer people will be amazed by arrival of the ubiquitous robot. So Id say to CIOs: Look at sensors really closely. In 10 years, most of your information wont be generated by people; it will come from sensors.

Six Rules for Effective Forecasting

1. Define a cone of uncertainty.2. Look for the S curve.3. Embrace the things that don't fit.4. Hold strong opinions weakly.5. Look back twice as far as you look forward.6. Know when not to make a forecast.

What are the right ways and the wrong ways to use the past to forecast the future? Mark Twain is credited with the observation though he didnt say it that history doesnt repeat itself but sometimes it rhymes. The shape of S curves is remarkably similar over time: 20 years to an overnight success. There are deep underlying currents that are the same because the biggest thing that never changes is human nature. Theres always the same resistance to change. So the rearview mirror is the most important forecast tool you have. But you have to look back twice as far as youre looking forward so you will capture the hints of the cycle that is unfolding. All CIOs should be historians of IT.

What would they learn? I think theyd learn that the information revolution is over. Information was a word that made sense in an age when we didnt have much information. But when it goes deep and becomes ubiquitous, it ceases to be information and it becomes media. Heres whats going on: If you look back to the 1950s, with the advent of TV, that was a mass-media revolution. Were going through it again with the Web, the Internet, information appliances, podcasts; but this is a personal media revolution. Google is a personal media company, not an information company. Blogging is a personal medium. Mass media is over; personal media is everything, and its fundamentally affecting the IT landscape. Thats why executives in traditional mass-media companies are going through all sorts of uncertainty.

Copyright © 2007 IDG Communications, Inc.

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