|
Business Tip 8
Creating Virtual Data Sources to Grow Your Bottom Line
The Basics
What it means and why you need to
know
Although syndicated data (e.g., ACNielsen and IRI) are still
a standard component of sales analysis and category management,
more manufacturers are seeking to raise the data analysis
bar by combining two completely different data sources. For
example, consumer goods suppliers try to compare actual sales
in a certain market against the retailer shelf-set to determine
if the 'right' assortment is in place-a process called validation.
This is often a time-intensive process because it requires
that the analyst manually check facings in a Plan-O-Gram spreadsheet
against sales data from a syndicated supplier. Here is the
problem:
While both types of data share products, time periods, and
measures, the challenge is relating shelf set data to geographical
(market) data. The solution is to turn these two separate
three-dimensional data sources into a single four-dimensional
virtual data source by using On-Line Analytical Processing
(OLAP) technology.
In Action
OLAP databases solve complex data
integration issues
The goal is to systematically compare retailer-specific Plan-O-Grams
with syndicated sales data to perform the following analyses:
- Identify top selling items in the market that are not
in the shelf set
- Identify items in the shelf set that do not represent
the needs of the market
- Identify products that sell in the market but are not
present in the Plan-O-Gram
Using On-Line Analytical Processing (OLAP) technology, it
is possible to create virtual data sources that combine dissimilar
data types for specific business uses. In turn, building an
OLAP database (called a cube) enables a user to apply multiple
Plan-O-Grams in a given market to determine the best fitting
standard shelf set.
How do virtual data sources work?
Instead of actually combining the data in a "real"
database containing actual data points, an OLAP environment
sets up virtual dimensions (in a single merged data cube) that
deliver results only when queried. In this way, unique data
combinations can be created on the fly, such as "Dollars
per Facing," or a comparison between a Plan-O-Gram and
a given retailer's sales results.
Through this kind of virtual data source, a manufacturer
can apply a consistent Plan-O-Gram validation methodology
to all its products and retailers on a regular basis.
The Deliverables
By adding a fourth dimensionals have been created, XP3
also has built-in calculation functions that would be able
to show the percent change (growth) between comparison time
periods, or across several different promotions.
- Improved efficiency: eliminating time-consuming, manual
work
- Effectiveness: bringing insights to light that were previously
impossible to attain.
XP3 is a data management application developed by Interactive
Edge that builds multidimensional databases and loads disparate
data into Microsoft Analysis Services, an OLAP application.
Using XP3's ability to harness the power of Microsoft Analysis
Services, a manufacturer can quickly and easily do all the
'heavy lifting' needed to truly integrate Plan-O-Gram data
with Syndicated Sales data. Moreover, because XP3's presentation
tools allow PowerPoint to connect directly to data in Microsoft
Analysis Services, scorecards and validation tools (such as
'Top 10 Items Not in the Shelf-set') can be developed much
faster and more accurately than if attempted manually.
The data, products and accounts depicted in this example are fictitious. Any resemblance to actual data, products or accounts is purely coincidental.
|
jjj
