If you want to persuade a decision maker, your first requirement is to capture and hold her attention. You can scarcely influence one who is not at least drawn into your arguments. Obviously, even when drawn in, the decision maker may not confer your recommendations, but you have no chance if she is abstracted. Practice audience capture by taking a single argument and examining how you might present it in a compelling way.
For example, yesterday we all watched the century event of the Indianapolis 500. It finished with flair as rookie J.R. Hildebrand stuck the wall only a few hundred yards from the finish allowing Briton Dan Weldon to whiz past him for the trophy and the several millions dollars that accompany it.
Weldon started in the number six position with a qualifying speed of 226.4 mph, only one mph behind the pole starter and two mph better than the number 24 starter. That is a small variation and emphasizes the athletic/team skills required to win the race, not to mention a peck on the cheek from that two-timing mistress, Lady Luck.
I plotted the top qualifying speed for the entire 100
years of the Indy expecting to scientifically curve-fit the data and predict the speed for the 150th Indy event. Surprisingly, I found that the pole position qualifying speed has not changed appreciably since about 1991. In other words, within statistical bounds the fastest qualifying speed has remained in the same small range for 20 years. Now, pundits will say this is the fault of the track, the Indy specifications, and so forth. Nevertheless, it points out how the race has transitioned from dominant speed to coordinated team skills.
I plotted the average lap speed for the winner each year. That was even more surprising since you can fit the data with a reasonable straight line and impressive correlation coefficient starting almost forty years ago, way back around 1970. In looking at the data, you might even make a case that the slope is slightly negative. In other words, the average lap speed might be decreasing instead of increasing. Again, the pundits will hand-wave the yellow flags, varying weather, pit affairs, and so forth.
Regardless, the compelling observation is that speed is not the primary factor in the Indianapolis 500 and has not been for decades. All cars that enter are capable of and exercise almost the same top speeds, the same average lap times, and the same pit efficiencies. Track and weather conditions are the same for all entrants in any given race. Speed is not the essential element.
So, if it is not speed, what is it? Probably a combination of athleticism, team ability, team coordination, split-second decision making, strategy improvisation, equipment optimization, and, of course, random events that take the moniker ‘luck.’ This convoluted complexity makes modeling the speed a tad more difficult. So, what about my prediction for the top speed 50 years from how? Can it be done based on past events?
I liken it to the NBA finals coming up this week. You can posit all the statistics you like, you can make all the predictions you want, but the winner will be determined by who has the highest score at the end of the game. Thus, the Indianapolis 500. The only way to predict the winner is observe who crosses the finish line first and that likely will keep up coming back year after year.