Red Bull Finds Best Route to Optimize Product Assortments
An article in CPG Matters, February 2008
By Al Heller
Makers
of consumer packaged goods often pine for employees who can see the big
picture, their companies’ future role in serving constituents, and the
most productive ways to do just that.
They love when
visionaries exist in many disciplines beyond the boardroom. Now with
software that the meteorological profession uses to visualize weather
patterns from massive data, CPGs could soon be able to discern trends
and patterns in spreadsheet data that would profoundly affect
performance.
“To view data spatially, to be able to
quickly navigate thousands of pages of spreadsheets and zoom in on
opportunities allows even the least analytical salesperson to identify
and make timely decisions on gaps, patterns and trends,” said Rick
Pensa, president, Insight, Information & Consulting Services,
Kennesaw, Ga., a consultancy currently using the tool to help Prism
Distribution, a Red Bull distributor in Canada, build a more efficient
and productive business throughout Alberta, Ontario and Saskatchewan
provinces.
He and another consultant, Sue Nichols of Data
Solutions By Design, Calgary, Alberta, began using the AWhere tool to
help Red Bull do three things: deliver to stores more efficiently,
build route density by covering more stores in and around the
geographic areas it already serves, and optimize product assortment for
each retail door.
To that end, they initially rely on
the tool to show if Red Bull drivers are missing distribution
opportunities and, if so, assign a value to the missed business.
Meanwhile,
the tool shows demographically who Red Bull drinkers are and where they
live, by showing where the highest-indexing stores for the beverage are
located (store volume compared with the store’s trade-area population).
“The tool creates a postal code-sized target for us.
Then we determine which high-potential stores are near the target. And
we optimize assortments at store-level within the grocery, convenience
and on-premise channels to maximize distribution opportunities,”
explained
Pensa.
“With the tool, we can answer the
question, ‘How much is the four-pack worth in this store that Red Bull
isn’t in.’ It forecasts the value of the demand gap, expressed in terms
of case volume,” he said.
While Red Bull sells in singles
and four-packs, in regular and sugar-free, the four-packs are the
growth opportunity in grocery and C-stores, and sugar-free is the
growth leader in on-premise, according to Pensa’s analysis. The
three-year- old distributor seeks better routing and stronger comps in
a growing market for enhanced beverages. By rolling out access to the
tool to its sales managers via the Web, it hopes to secure productive
new shelf space before its
competitors.
Beyond that, growth could come from plotting retail loyalty cardholders around stores to see where demand gaps exist.
The
Red Bull example represents only part of what the tool can do.CPGs can
use the AWhere tool in many ways, noted Pensa, determining for
instance:
• Where a brand’s highest potential consumers live and which stores are in their neighborhoods
• Cluster stores based on metrics and/or indexes describing those stores
• Where the highest rates of out-of-stocks occur, and how important those stores are to a brand’s sales
• Where are new products in distribution
• What is my route density, and where are the stores that aren’t selling my products
• Where are my highest-consuming loyalty card consumers, and which
stores are they living near
• Where do my sales index high or low, and where they can they be described by cluster definitions
To
appreciate the visualization abilities of this
“locationally-intelligent” tool, Pensa said to “take a line on a
spreadsheet which has no connectivity to where it is, say line 1 vs.
line 3,700. By contrast, the tool can compare locations, or clusters of
locations on a map, to show relativity and enable analytics. It shows
patterns, such as ‘my weak stores are here, my strong stores are
there.’ It shows gaps through bar and pie charts on maps that represent
volume, out of stocks or other measures. Users can set criteria to
establish clusters, such as which stores are above a certain ACV or
sales- rate level, and index above a certain target consumer level.
“Since
we can vary the radius of trade areas, we can develop trade areas based
on shopping mission, or on target consumers which may or may not match
a fixed trade area methodology,” Pensa said, describing the tool’s
analytical flexibility.
Functionally, he said the
AWhere tool has the richness of business intelligence and the
analytical dashboard ability of highly sophisticated global information
systems (GIS) tools, yet is easier to use. It is more graphically
robust than Web viewers like Google Maps, Microsoft Virtual Earth and
Yahoo! Maps, and is compatible with Microsoft Office.
Pensa
is one of the first to sense the tool’s application for retail and the
CPG industry, following its success in climatology and agribusiness
forecasting. “We just needed to CPG-ize it,” he said, noting it can
help with many aspects of category management, consumer data analysis,
and trade promotion management.
Al Heller is co-author
of Consumer-Centric Category Management (Nielsen/Wiley, 2006) and
president, Distinct Communications, LLC.
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