Location Analytics and Decision Support: Reflections on Recent Advancements

This article discusses the importance of location analytics and decision support in the success of Starbucks stores. It highlights the use of Geographic Information System (GIS) and the Atlas application for site selection and market planning. The article also mentions the impact of neglecting location analytics in the past and the positive returns achieved through proper location analysis.

Information Technology Management

Answer 1
Starbucks prioritizes the selection of appropriate location for their stores. They use the
Geographic Information System (GIS) so that they can open their stores at a proper site and place
the right product in the right place. The company plans their business according to their location.
Starbucks has faced a lot of problems in the past due to their focus on growth acceleration and
negligence of location analytics (Pick, Turetken, Deokar & Sarkar, 2017). The stores had been
just for the sake of creating brand awareness across United States. There was no profit earning
from these store openings. Starbucks has been using GIS since 1990s but they did not have
required expertise to analyse the data collected. Thus there were many flaws in location of stores
during 2007-2008.
Answer 2
The location analytics has helped the managers and decision makers of Starbucks to open their
stores at the best locations. They have opened many new stores during 2011-2012, keeping the
location analytics in mind, which have given them good returns in terms of revenue and sales
(Skibiski, et.al, 2015). Starbucks is using the Atlas which is a store development and market
planning application. This has facilitated their study regarding location and demographics.
The decision makers rely on the real estate staff of Starbucks for the decision regarding opening
a Starbucks store at a particular location. The decision of store location is taken based upon the
data of the Atlas that gives the staff an opportunity to compare various scenarios and finally take
a decision.
The Atlas helps in taking the decision of setting up the Clover Brewing high end system by
providing the required data to Starbucks so that they can analyse the situation. This system

should be installed at a location where the customers are willing to pay more than the average
price to get a cup of exceptionally good and flavored coffee.
Answer 3
In the year 2007-2008 there were many new stores opened across the United States for the
purpose of growth acceleration. The 15,011 stores opened in 2007 earned no profits for the
company and eventually in 2008 around 600 stores had to be closed down. At this time the
management opened new stores just for promotion of their brand. The location analytics were
neglected as the company lacked expertise to handle GIS data.
However, in the year 2011-2012, Starbucks again opened many new stores. This time the new
stores gave exceptionally good returns in terms of per store volume and revenue. The sales-to-
investment ratio was 2:1. This was possible because the location and demographics data
provided by Atlas was analyzed by the real estate staff. Based on the location analytics the final
decision was made about site selection. In this case the management gave due importance to
location and demographic data and used the best technology application named Atlas, a leading
location analytics system and a vendor of GIS.
Answer 4
For opening a new store Starbucks makes an investment of $1 million. Thus it is very important
for them to make a right decision. The losses incurred by one new store will cannibalize the
positive returns from five profitable stores. The location of a store is very crucial as the profits
depend on the store’s proximity to the consumers and also the number of target consumers
available in the location. In fact the success of one store is dependent on the location of other

nearby stores. Product placement to site selection, both depend on a good decision regarding
store location of these determine the profitability of growth of a store.

References
Pick, J. B., Turetken, O., Deokar, A., & Sarkar, A. (2017). Location Analytics and Decision
Support: Reflections on Recent Avancementa, a Research Framework and the Path
Ahead. Decision Support Systems, 99.
Skibiski, G., Pentland, A. S., Jebara, T., Lemke, C., Loecher, M., Rao, G., ... & Mattiello, J.
(2015). U.S. Patent No. 8,959,098. Washington, DC: U.S. Patent and Trademark Office.