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Sometimes, modeling the demand for a new product
or service needs to account for phases of the product life cycle:
Introduction, Growth, and Maturity. Advertising, deployment constraints,
consumer acceptance, competition, and technological changes all
have an impact. The Introduction Phase is often characterized by
slower growth due to advertising, distribution, and training efforts
being initially started up. It is also impacted by the amount of
pent-up demand already existing in the market. The Growth Phase
reflects the highest rate of consumer acceptance where the product
is being purchased at its most rapid pace. The Maturity Phase implies
the market's saturation level for the product has been reached and
most potential buyers have already purchased. These phases of the
product life cycle can generate an S-shaped market diffusion over
time. The following discussion demonstrates a relatively simple
way to incorporate market research and a set of standardized assumptions
into the forecasting process for new products.
Output from S-curve models represent LONG TERM outlooks based
upon rational insight or market research. Other methods such as
Time Series models will often produce more accurate forecasts
in the SHORT TERM. However, when long term projections are necessary
and historical data is limited, these approaches provide an analytically
sound framework with which to quantify market assumptions and
product diffusion over the extended planning horizon.
When a truly new product is introduced, there exists a lack
of historical data. Standard time series and regression models
are impossible to use under these conditions. As a result, the
forecast process is typically ad-hoc and distorted by lack of
consistency across individuals generating the forecasts. Penetration
levels may vary across geographic regions simply because the primary
assumptions have not been adequately identified and standardized.
For the same reasons, diffusion rates may lack consistency through
embedded assumptions of pent- up demand, advertising, and deployment.
The advantage of the following approach is that the forecaster
is conditioned to quantify primary market assumptions in a standardize
way. This is accomplished by answering three basic questions:
- What is the Maximum Level of Penetration
?
- What is the Inflection Point or Half
Life of the Product ?
- What is the Delay Factor ( reflecting
the time spent in Introduction) ?
The Maximum Level of Penetration: is the long-run saturation
level of your product or service. This kind of information can
usually be obtained from intent to purchase surveys or primary
market research. It is simply the maximum number of units the
market will bear for your company's product. The graph to the
right depicts how different saturation values change the shape
of the S-curve.
The Inflection Point (Half-Life) of Product: represents
that point in time where the product is selling at its fastest
rate. After this point, the rate begins to diminish and forms
the second half of the S-curve. Because of the mathematics of
the forecast equation, this point in time will always occur when
sales reaches exactly one-half of the long-run penetration level
of the product. The lower the inflection point, the quicker the
product is projected to reach half of its sales potential.
The Delay Factor: is the most subjective assumption of
the process. Its value impacts the first part of the S-curve -
describing how long the product is expected to remain in the Introductory
phase of the product life cycle. This factor usually will fall
between zero and one, depending on how soon the product is expected
to reach its half-life. A factor close to zero implies that there
is a substantial amount of pent-up demand in the market. In other
words, as soon as the product is introduced, immediate sales are
to be expected. If all other factors remain constant, increasing
the delay factor could imply reduced advertising budgets or increased
deployment problems. For products with a life cycle inflection
of thirty months, a normal looking S-shaped curve might have a
delay factor between around .1.
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