Dunkin' Donuts Uses Business Intelligence In War Against Starbucks

Date

Apr 18, 2007

Northeastern coffee connoisseurs fall into two camps: those that prefer Starbucks' dark, rich blend or those that go for the milder, quaffable brew that comes in those retro Dunkin' Donuts orange-and-pink cups. While Dunkin' Donuts may be old school, it's using modern technology to try and outsmart Starbucks for the best franchise operators and locations. The coffee war is playing out in such areas as Boston, New York, and other Northeast locales, where the bulk of Dunkin' Donut's 5,000 U.S. franchises are located, and where Starbucks is determinedly pushing in.

Now the battle is going global under the direction of a private equity group that bought Dunkin' Donuts last year and plans for 15,000 franchises worldwide. Its nemesis is Starbucks, which has 12,000 stores worldwide, including 8,800 in the U.S., and plans to add another 2,400 globally this year. What ends up on the corner of your block -- dark and rich, or mild and quaffable -- could be determined by who gets there first.

To help it win this race, Dunkin' Donuts is using a new system that helps it more quickly close deals with "customers," who in the franchising world are the people who apply to run a franchise, pay the franchise fee after the approval process, and then pay royalties. Salespeople and managers use the system to manage information about these customers, including the stage of each potential deal and how financing is going for them. This is particularly important in the competition against Starbucks, which doesn't franchise, so its growth isn't stalled by difficulty finding suitable and willing franchise operators and getting them signed up quickly.

Dunkin' Donuts managers use a dashboard-type software application to identify any problem areas so they can keep deals on track. The can get a geographic view of regions where deals are stalling, and then drill down into a specific account to determine what's slowing down the process. They can identify potential deals in locales that are too close in proximity. They also can identify high-performing areas, and gather best practices from those regions' salespeople to share with other areas. Key metrics they're watching include the average cycle time for getting a franchise deal done, the size of deals, and average cycle time by what type of deal gets done.

External Source - InformationWeek