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102 SCHEDULES AND TIME COMPRESSION

But how much has been written that actually quantifies the benefits of shorter
development cycles? Well, marketing consultant Geoffrey Moore [Crossing the
Chasm (HarperBusiness, 1991) and Inside the Tornado (HarperBusiness, 1995)]
has some interesting figures to offer on this.

He says when a new product is created for a new market, the first one
getting to market is most likely to garner at least 50 percent of the total
market. The remaining 50 percent is all that will remain for all the other
players. No wonder that there is so much pressure on new developments (and,
perhaps why some developers are willing to skimp on quality rather than
chance delays).

Hey! There’s more yet. If the first vendor to the market garners 50 percent
of possible sales, while #2 picks up, say, 20 percent, that is not the probable ra-
tio for income. That is because #1 sets the price, which, without competition
allows maximizing profits and return on investment. By the time the other ven-
dors join the battle, profit margins will drop (but only after #1 has made its
killing). Moore figures that #1 will garner at least 70 percent of the profits pie,
in this model.

Now I ask you—is that enough motivation to drive schedule compression and
management?

Every day that can be squeezed out of the schedule improves the developer’s
chances of grabbing the lion’s share of the market. The new product developer
must not only invest effort in creating fast-track schedules, but must also continu-
ally tweak the schedule looking for ways to optimize (shorten) the time cycles.
The payoff, for getting there first, is monumental.

Schedule and Cost—Effect on Profit

Here’s another bit of data to support our case on the deleterious effect of sched-
ule delays. As project managers and project owners, we tend to worry, equally,
about schedule delays and cost overruns. But, according to an oft-quoted study by
McKinsey and Company, one of these is more equal than the other.

That study looks at the effect of schedule delays and cost overruns on the ex-
pected profit, over a 5-year period. The resultant data indicates that cost overruns
in the neighborhood of 50 percent eventually reduced the profit by about 3 to 4
percent. On the other hand, they found that a schedule delay of 6 months often
resulted in a loss of a third of the expected profit, over five years.

Certainly, in view of Geoffrey Moore’s marketing models, this should not be
surprising. Furthermore, the effect of schedule delays on cash flow and return on
investment, as noted in the following paragraphs, provides additional support for
these findings.