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Before you blindly accept this writing assignment, please review it all carefully and be willing to follow ALL instructions as I will not pay you if you do not follow the instructions carefully and fully. 

This is a four page writing assignment that must include the following:

This assignment should provide details of how various departments such as Human Resources, Information Technology, Maintenance, Marketing, Operations, Reservations, and Sales at a medium-to-large scale aviation-related enterprise could benefit from the utilization of cloud computing and electronic records management. Distinguishing how the two information systems will benefit your company, proceed by providing the details and examples of applications and solutions offered by retail vendors. Describe the framework for each solution that the internal staff of your company might develop and implement as well as giving an account of the strengths, weaknesses, and cost considerations for those solutions. Finally, identify and describe how a solution can provide a competitive advantage, influence strategy, affect organizational performance and increase operational efficiency. 

As a guideline, I have attached an example document to assist with the formatting.  Double spaced, 12 point times new roman font, 2-3 sources for each subject.  There should be a total of four pages, two pages for cloud computing, and two pages for electronic records. 

Running Head: Big Data Case Study Big Data Case Study (EXAMPLE)

 

Student Name (EXAMPLE)

 

University (EXAMPLE)

 

Instructor (EXAMPLE) 1 Running Head: Big Data Case Study 2 One enterprise that almost every person in America and many more throughout the world

 

are familiar with, is the Starbucks Corporation. For many years, Starbucks has been the leading

 

coffee house worldwide by a long shot. In 2015, they had over 15,000 more stores than their

 

next competitor, McDonald?s McCafe line[Sta16]. As a result of having over 22,000 stores,

 

there were many logistical problems that plagued the corporation. All of these logistical

 

problems arose due to the corporation?s business model that included the idea that it was

 

necessary to open as many U.S. stores as possible. Because they were unable to handle the

 

information technology related logistics associated with this model, Starbucks was on a

 

downward spiral that could only be interrupted by an information technology intervention.

 

When the original CEO Howard Schultz reclaimed the position from standing CEO Jim Donald

 

in 2008, he knew this would be the only way forward. As a result, Chris Bruzzo was named the

 

new chief information officer and was tasked with leveraging technology ?to create innovative

 

ways for Starbucks to connect with our customers and build loyalty programs?[Wai08].

 

Once Bruzzo recognized the issue, he immediately knew that IT could help the

 

corporation?s infrastructure over-development. His first method to begin moving Starbucks in

 

the right direction, was by aggregating and mining data from customer credit and debit cards and

 

to examine their buying patterns. Once this had been done, Starbucks could now determine what

 

employees could do to better serve the customers. Also, this data lead to the development of

 

more sought after products. For example, Starbucks was able to quickly and effectively

 

determine that it?s customers were in search of a more personal experience. They also found that

 

by creating a warm and welcoming experience, customers were more likely to buy more than one

 

drink. It was an assumption at the time that these new changes would not increase sales enough

 

to make up for the over development of infrastructure (number of total stores). Running Head: Big Data Case Study 3 By using big data concepts and data mining, Starbucks was able to completely reverse the

 

effects of having too many stores. Through the specific data mining of customer?s credit card

 

information, they determined that personal experiences and warm and welcoming environments

 

meant more to people than the value of their drinks. Breakthroughs in technology only

 

continued to enable this process. Once it was discovered that internet Wifi Café?s were

 

becoming popular, Starbucks was able to determine that there was a significant percentage of

 

their customer base that bought more than one drink per day and at separate times throughout the

 

day. By getting these customers to stay in the store by offering the free use of internet, they were

 

then able to begin their pre-made and packaged food line. It was determined that customers

 

cared more about the comfort and practicality of having a place to sit, study, read, and drink

 

coffee than they did about having fresh food.

 

Most recently in 2014, Starbucks dropped ?coffee? from their logo and looked to ramp up

 

their food sales. They are looking to double their food sales in the U.S. over the next five years

 

as well as add wine to its menu [Jar14]. All of these changes are a direct reflection of the data

 

mining that has taken place by the corporation. As Bruzzo realized, knowing how to figure out

 

what the customer wanted without the customer even knowing themselves, they were able to

 

exploit their hidden desires.

 

This change in direction has been compared to Steve Jobs return to rescue Apple when it

 

was at its worst. There seems to be a significant attraction to brand that simply cannot be

 

replicated. According to The Market Mogul, Starbucks is still very well known for the pride and

 

care it places in unique brand image and standards [Cur15]. Again, the only way Starbucks was

 

able to turn the proverbial corner with their business model was the heavy use of data mining and

 

a variety of other information systems technologies. Running Head: Big Data Case Study 4 References

 

Curtis, C. (2015, October 1). Starbucks' New Business Model. Retrieved from The Market Mogul

 

Web site: http://themarketmogul.com/starbucks-new-business-model/

 

Jargon, J. (2014, December 4). Starbucks Aims to Double U.S. Food Sales. The Wall Street

 

Journal, p. 12.

 

Statista. (2016, June 30). Restaurants. Retrieved from Statista website:

 

https://www.statista.com/statistics/272900/coffee-house-chains-ranked-by-number-ofstores-worldwide/

 

Wailgum, T. (2008, Jan 25). Feature. Retrieved from CIO Website:

 

http://www.cio.com/article/2437262/strategy/how-it-systems-can-help-starbucks.html

 

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