Case in Point: Large Auto Manufacturer
-- DaimlerChrysler Corporation (USA)
An auto manufacturer spends billions of dollars promoting vehicles
to consumers every year. But marketing teams at a typical manufacturer
have very little information with which to make decisions around
the products to build, how to distribute them and how to promote
them. In fact, without the proper link to sales and consumer behavior
data, promotional decisions can often be made to liquidate inventory
because the wrong vehicles were manufactured in the first place.
This is a situation that can clearly be changed if data assets
are put to work properly and if the data is used to predict future
demand and determine how much of each vehicle to be manufactured
and when to apply incentives appropriately to optimize sales.
DaimlerChrysler is one of the world's leading automotive companies.
Its passenger car brands include Maybach, Mercedes-Benz, Chrysler,
Jeep®, Dodge and smart. Commercial vehicle brands include
Mercedes-Benz, Freightliner, Sterling, Western Star and Setra.
It offers financial and other automotive services through DaimlerChrysler
Services.
DaimlerChrylser marketing team approached the ISS to assist building
an enterprise system In working with DaimlerChrysler Corporation,
ISS has built an enterprise system to capture consumer behavior
data from multiple data sources and predict sales models and regions.
For the first time in the auto industry in the U.S., a large manufacturer
is able to harness data from multiple sources to make accurate
predictions of future sales broken down by detailed geographic
region and vehicle model configuration.
The data sources feeding information into this business intelligence
market forecasting system include:
- Web site behavioral data for longer term market demand forecasts
- Hand raiser data from web, call centers, and dealers.
- Inventory and production planning data by individual vehicle
model
- Vehicle configuration behavior from on-line configurators for
medium-term forecasting.
- Detailed sales data across the nation
- Dealer performance data
- Other data sources from customer loyalty and warranty databases
- Data describing competitor sales and customer shopping behavior
for competitive vehicle models
By harnessing
information from multiple channels of interactions, not only is
DaimlerChrysler able to derive accurate sales predictions, but
more importantly integrate the results into operational business
units from manufacturing to production planning to incentives
management. In addition, the ISS data marts deliver score cards
on various aspects of the business to report both on historical
performance as well as predicted future performance, all in one
integrated complete view of the customer.
A
particular innovation in this case is the intelligent fusion of
the on-line and web systems data with the traditional sales reporting
data to obtain a powerful predictive source of information.
Every day,
thousands of customers go to the site and configure automobiles
as they do research toward making the purchase decision. By itself,
information about car configurations is interesting. Coupled with
detailed market research and sales data it is an extremely powerful
tool that can be used to make much more precise manufacturing,
distribution and promotion decisions that have the potential to
add billions of dollars to the bottom line.
The situation
at DaimlerChrysler is not uncommon. It is certainly the case for
other auto manufacturers and in many other, equally compelling
industries including pharmaceuticals, healthcare, telecommunications
and packaged goods. The application of data warehousing, data
mining and business consulting holds the solution to allowing
such companies to benefit from data assets that are kept in stores,
which today serve little purpose more than being expensive data
tombs.
