[SOUND] Hi,
welcome back.
Today, we will talk about the process of demand estimation.
Despite the fact that this type of process is more associated with market research
than competitive intelligence, sometimes, access to information is not possible.
Often, there is simply not enough information to allow to use of classic
market research tools.
In these cases, competitive intelligence can be a useful tool as a complement.
This is particularly true in emerging markets.
Countries such as the United States have a much greater wealth of data and
information which facilitates this kind of analysis.
There are several methods of estimating future demand.
Some of them are based on past demand, and includes
methods extrapolation, also called naive extrapolation,
with the proper correction for seasonal and cyclical effects.
Unemployment of sugar cane pickers is cyclical because they
are hired at the beginning of the harvest and fired at the end of it.
The problem with methods that use extrapolation from the past is that they
do not necessarily consider and analyze what factors triggered the demand.
With this, any rupture introduces serious errors in the demand estimation process.
This is what happened to the demand for cameras in the US.
Until 1998, the growth was constant and strongly related to population growth.
The introduction of digital cameras has led to the demand for
analog cameras to go to zero in eight years.
For this exercise, we will focus on two basic approaches, top down and bottom up.
Top down analysis is based on the analysis
of the economatic variables that define the demand of a given product or services.
The method analyzes historical demand data of the total market, and
compares it to several historical series of economatic
indexes to identify the correlations between two or more variables.
When you find the correlations, the next step is to find information sources for
the most relevant variables and
then apply the formula that correlate to the demand you need to calculate.
For example, studies of demand for
passenger air transport services have a very strong correlation with GDP growth.
With GDP growth estimations from several sources,
one can easily calculate the total demand for passenger air transport.
On the other hand,
aircraft sales estimates are also governed by a number of other variables.
Number of aircraft to be retired in the same time period.
Passengers' preference, typically,
passengers prefer jet aircraft to turbo prop aircraft.
How airlines will serve the demand.
For example, if you take a pair of cities in which the demand for
air transport is 5,000 passengers per day.
It can be satisfied with 10 daily flights with a 500-passenger aircraft or
50 daily flights with 100-passenger aircraft.
The airline's decision is important because in the first case,
the airline will need an A380 aircraft, produced by Airbus.
In the second case, it can choose between a CRJ1000 and
an E195, produced by Bombardier and Embraer, respectively.
The bottom up analysis is based on research
with the airlines that make up the market.
Aircraft manufacturers talk to as many companies as possible to understand their
future buying intentions.
In addition to talk to companies, aircraft manufacturers always analyze
the operations of each of the most important companies through an analysis
which is very much like the four corner analysis and value chain analysis.
They study the comparative environment in which the current airlines operate and
the effect of the most important market issues.
Typically, data analysis is done jointly by the marketing and sales areas.
Considering that in many customers, the planners are optimistic, and
they imagine that they will be able to take market share from their competitors.
The sum of the values obtained by the bottom up analysis
is often greater than the numbers obtained by the top down analysis.
In the end, the results from both analyses are confronted, and
the process of number harmonizations takes place.
This discussion is important and generates insights about the market and
the variables that most influence the performance of the industry.
Thank you for watching.
I'll see you in our next video.
[SOUND]
