In many industries, products are profitable only during a
limited window of time. We see time-sensitive products, of course, in consumer
electronics, where new models of phones, computers, and home entertainment
products come (and go) frequently. We also see this pattern in fashion markets.
Zara, for instance, introduces new clothing products twice weekly across nearly
2,000 stores – amounting to the introduction (and retirement) of over 10,000
designs a year. Timing is key, as well, in the introduction and short shelf
life of cultural products, such as popular music and films. The market for
video games follows a similar pattern of rapid new-product introduction and
short product lives, including flash-in-the-pan hits like Pokemon Go as well as
the more cadenced, but still time-sensitive, annual replacements of the various
EA Sports games. Innovative pharmaceutical products also compete in a
time-sensitive way, since the first to patent enjoys a profit premium that ends
abruptly with patent expiration. Consequently, drug companies are in a race
against time, first to file the patent, and then to bring the drug to market. Even
some durable products, such as automobiles, are introduced and retired on a
time-sensitive, if cadenced, basis.
Time-sensitive
markets can be identified by the presence of two underlying features. First,
these market place a premium on introducing a product early – or at least on a
reliable schedule where being late is punished. For instance, releasing a new
version of a gaming console like Xbox or Playstation late - after the holiday
season – would be unthinkably costly for Microsoft or Sony. Second, the
products in these markets also have a limited shelf life. A new clothing style
or a new hit song may be wildly popular today, but within weeks (or maybe days)
they will be yesterday’s news.
In such time-sensitive
markets, success depends on a distinct logic: the time-to-market strategy. To
understand this strategy, consider a firm that introduces a successful new
product, “Product 1,” as in the plot below. Initially the product takes off
slowly, and then it catches on, finally reaching a maximum market size. This
“S-shaped” diffusion curve is typical of successful products.
The story
does not end there, however, because this company is facing a market where the
shelf life of a product is limited in time. Consequently, it is preparing to introduce
a second product, “Product 2,” that will compete directly with its own Product
1. Note that if the firm does not introduce Product 2, somebody else will. That
is what is compelling the company to continue with the introduction of another
product even though it will cannibalize its first product, as shown here.
Now
focusing in on Product 1, we can see that there is a limited window of time
during which the firm can make money selling the product. It is interesting to
think about the price that can be charged for Product 1 over the life of the
product. Typically, the price that can be charged will be much higher earlier
in the product’s life, for two reasons. First, the earliest buyers of the newly
introduced product will be those with a greater willingness to pay for the
product. For instance, if Intel comes to market with a new chip that is
extremely valuable to cloud service providers running state-of-the-art server
farms, these eager buyers will be the among the first to buy this new chip and
they have a high willingness to pay. Less enthusiastic buyers will also buy at
some point, but only if the price falls. Second, the price will begin to fall
over time as other competitors come out with a product that is a direct rival
to Product 1. For instance, perhaps AMD will introduce a competitor to Intel’s
new chip. As the price falls, now more and more chips are sold as other buyers
come into the market with lower levels of willingness to pay. Ultimately, once
Product 2 is on the market, the price for Product 1 falls away completely. This
pricing dynamic is pictured below.
At this
point, the logic of a time-to-market strategy is clear. If we introduce Product
1 as shown, our firm will make a great deal of revenue. To see this, look at
both the price and sales volume curves in the plot above. Revenue from Product
1 is found by multiplying these two curves, and total revenue over the life of
the product is just the cumulative revenue over time. However, what if we are
another firm and we release a competitor to Product 1 – but we do so late. A competitor
entering near the end of Product 1’s life may sell at high volumes, but only
for a short time and only during the period when the price of the product is
very low. This firm will have introduced a product that, over its life, will
make very little cumulative revenue. So the earlier a firm enters into this
competition, the more it makes in cumulative revenue. In fact, entering earlier
increases total cumulative revenue at an increasing rate.
By this
logic, it is obvious that we should release Product 1 at the soonest possible
date. However, this may not be profitable. To see this, consider now the costs
of developing Product 1. If we could take all the time we want, we could
carefully research and develop Product 1 and, when it is ready, we will have
run up total costs equal to C1. But by taking our time, we might end
up introducing the product late, and this will hurt our revenue. So instead of
paying C1 over a long period of development, say, 2 years, what if
we accelerate development and pay the same amount but all in one year – or even
in six months?
Well, here is the bad news. It
turns out that compressing development costs into a short period does not give
you the same result. This problem, famously dubbed the “mythical
man month” by Frederick Brooks, occurs for two reasons. First,
compressing the amount spent on development causes many to work simultaneously
and in parallel, which results in coordination diseconomies. Second, there is
the problem sometimes called “gestation,” where development is inherently
sequential and cannot be made to happen all at once. Concretely, gestation
requires time in development because answers obtained at one point in time
decide the questions asked at the next point in time. Doing all this
development at once leaves us asking many questions that we will never need to
know the answer to – and failing to answer questions that we wish we had
researched.
Consequently, to speed
development, it is not enough to concentrate C1 into a more
compressed period of time. Instead, we will have to pay more than C1,
and the more we compress the development process, this additional amount will
continue to escalate until, at some point, we could spend an infinite amount
and not improve our release date any more. So development costs increase at an
increasing rate as time-to-market shortens, as shown below.
As the
figure shows, the time-to-market strategy confronts the firm with a dynamic
cost-benefit comparison. To be profitable, the firm needs to introduce the
product early enough to benefit from higher revenue over a longer time, but not
so early that its development costs skyrocket.
How is a
firm to achieve this balance? The answer comes down to organization. Firms that
are good at the time to market strategy are organized in a way that minimizes
development costs while maximizing the reliability of product introduction. The
key factor to be managed by these firms is uncertainty. These firms typically
design around customer-defined time milestones, track progress toward meeting
those release dates, and hold employees accountable for staying on time. As
uncertainties arise, routines such as phase-review processes are used to update
release dates or revisit go/no-go decisions. And wherever, possible, the firm
contracts with other firms in order to solve “weak link” problems that are
slowing its ability to deliver on time.
Time-based competition is discussed in my book on the Red Queen.
