The Inaccuracy of Forecasting
Predicting the future is difficult. A historical look at forecasting over time suggests that we have continually tried to predict the future ⌠and have continually failed to do so with any accuracy:
The telephone has too many shortcomings to be seriously considered as a means of communication. The device is inherently of no value to us.
Western Union internal memo, 1876
People will tire of talkers. Talking is no substitute for the good acting we had in silent pictures.
Thomas Alva Edison, 1925, on new movies with sound
Predicting the future is difficult.
Every woman is frightened of a mouse.
MGM head Louis B. Mayer in 1926, to a young cartoonist named Walt Disney
I think there is a world market for maybe five computers.
Thomas Watson, IBM Chairman, 1943
The bandâs OK but, if I were you, Iâd get rid of the singer with the tyre-tread lips.
BBC radio producer on rejecting the Rolling Stones at a 1963 audition
How could the experts get it so wrong?
The concept is interesting and well-formed, but in order to earn better than a âCâ, the idea must be feasible.
A business professor at Yale on the FedEx marketing plan, 1966
640k ought to be enough for anybody.
Bill Gates, Microsoft founder, 1981
The Internet will collapse within a year.
Bob Metcalf, founder of 3Com Corporation, in December 1995
We look at these examples today and chuckle â how could the experts get it so wrong? But we have the advantage of hindsight. At the time the comments were made, they surely reflected the current thinking of these individuals and organisations. The simple lesson â that even the experts get it wrong â is a good one to bear in mind as we review in later chapters the role of expert judgement in forecasting.
A more subtle â and just as important â lesson is to reflect upon the pressures that must have existed on the forecaster in industries associated with the individuals who made these statements. If I am a forecaster for Internet equipment and the chairman of 3Com has made a public statement that he believes the Internet will collapse within a year, chances are that I will be affected by this statement in my view of the future. We will discuss the issue of bias in forecasting in each of the subsequent chapters.
Are companies any better at forecasting than individual experts? The results in Table 1.1 suggest that companies also have a mixed record when it comes to forecasting. Table 1.1 presents some new products that have been introduced by large companies and categorises the products as âleadersâ and âlaggardsâ with respect to their relative success in the global markets. These companies all have successful new product launches to their credit, but they also introduced products to the market with limited success. It is reasonable to assume that the planning for the new products included forecasts that presumably justified the product launches. What went wrong? We will explore the answer to this question when we discuss new product forecasting in Chapter 3.
Table 1.1 The success of new product introductions
Company | Leaders | Laggards |
McDonaldâs | Big Mac and fries | Seaweed burgers |
Sony | Walkman | Beta-format VCRs |
Kodak | 35mm photography | Instant photography |
Federal Express | Overnight mail | ZapMail |
Coke | Classic Coke | New Coke |
Forecasting in the Pharmaceutical Industry
What about examples from the pharmaceutical industry? In 1985 there was an article published in Pharmaceutical Executive that examined the linkage between successful new product launches and a companyâs stock price. The authors stated that
Projections of the sales of new drugs, especially of blockbuster drugs, have almost always been too high. Investors have been burned so many times with this game that it is difficult to understand why they continue to play it. 1
In support of this statement have a look at the data in Table 1.2.
Table 1.2 Blockbusters that went bust
| | Peak sales (millions of US dollars) |
Company | Drug name | Estimated | Actual |
|
Merck | Blocarden | 500â1000 | 15 |
A. H. Robbins | Pondamin | 300 | 3 |
Sterling | Amrinone (oral) | 500 | 0 |
SmithKline | Monocid | 100 | 20 |
At the other end of the scale are products that achieved forecasts beyond their initial expectations (...