Use quantitative data when it is available; be very careful to use the
same units, to use a consistent scale, and to present
the
time lines consistently. A trap to avoid it assuming time is always
linear. Check the data by seasons as well.
Use graphics to present data to your team, where the axes scales clearly
display the units. Our eyes, the world's best computer, quickly spot the
direction and shifts in magnitude over time.
If you have good sources of quantitative information, show as much
historical data as you can. The rule of thumb is at least three
to five years of
history. No one I've worked with will guarantee the accuracy of forecast
more than two years into the future. Accept that. Beyond two years,
you
will be guessing.
For example, consider the demand and capacity drivers impacting the
aviation industry. The blue line is total passenger enplanements and
the green line
is total foreign travel enplanements, each with a linear extrapolation.
The bars are added capacity for planned runways. One new runway can
handle
about 7.8 million passengers a year.
Current construction suggest future shortages as runway construction
fails to satisfy demand, particularly domestic travel. As delays increase,
it creates years of opportunity
for firms providing alternate transportation or optimizing the current
national airspace system.
As I prepared this example, I noted that most of the runway construction
was not at the airports that support international travelers.
