Overview of Case Study 4

Data mining is an important tool that companies use to find and resolve issues. The case study we’re covering describes how companies Applebee’s, Travelocity, and VistaPrint analyze data and leverage data mining tools in order to help improve their business processes.

Applebee’s use data mining technology not only to purchase supplies, but also to make better decisions on which products to advertise. Travelocity, an online travel site, uses text analytics software by Attensity that extracts important unstructured information from emails, surveys, and call centers that would have took hours or days any other way. Not only does the tool help employees improve customer service, but it allows the unstructured data to be linked with the structured data of Travelocity’s Teradata data warehouse to track trends and forecast events.  VistaPrint is an online retailer that uses data mining to find issues regarding customer registration on their website.  Using a data mining tool called Visual Site to track the process, narrow it down to a specific place, and finally resolve the issue they found the data mining tool helped the company improve new member registration (O’Brien, Marakas).

A good example of a company that uses data mining and the information provided by the analysis is FaceBook.  Data is collected about the user’s friends, likes, comments, etc. In order for these companies to stay competitive they had to change their strategy – they had to learn from their mistakes and from their competitors.  These companies made use of Argyris and Schon’s Organization Learning Model and De Gues’ Law of Learning.

Question 1

What are the business benefits of taking the time and effort required to create and operate data warehouses such as those described in the case? Do you see any disadvantages? Is there any reason that all companies shouldn’t use data warehousing technology?

Answer 1

The business benefits of taking the time and effort to create and operate data warehouses as described in the case was remarkably beneficial. Given there’s a plethora of data just simply sitting in data warehouses not being used provided an opportunity for information technology to be incorporated in order help make improvements to the overall business of the company and its’ bottom line. What makes the implementation of technological tools essential to effectively capture this untapped data is the primary source which is the customers or potential customers themselves. According to the Data-Information-Knowledge-Wisdom (DIKW) Model, this unstructured data can be converted to data that is structural, functional, and beneficial to the overall business. With careful planning, sophisticated technology implementations, and analyses this untapped data has now leveraged companies to make important and real time business decisions based on their different perspectives. From the case, the use of the data varied on the business needs of the company.  For example, Applebee’s utilized the data to make improvements to their procurement and overall customer service, and Travelocity and VistaPrint used customer driven data to make real time improvements to the site.  

With anything there’s an advantage and disadvantage. In regards to the utilization of data warehouses, a potential disadvantage could be the cost effectiveness of resources required to effectively capture the unstructured data. Another possible disadvantage is not seeing an actual return on the investment. At a certain point companies should be able to tell whether or not this data has been useful and beneficial to the overall bottom line of the business.

Personally I don’t believe there’s a single valid reason a company shouldn’t use data warehousing technology. Information is power, and any piece of information that can be leveraged to gain a leg up over the competition is invaluable. This technology now allow companies to make real time, minute by minute decisions, in order to keep up in the super fast paced business world we now live in.

Question 2

Applebee’s noted some of the unexpected insights obtained from analyzing data about “back-of-house” performance. Using your knowledge of how a restaurant works, what other interesting questions would you suggest to the company? Provide several specific examples.

Answer 2

The restaurant business collects a tremendous amount of data enabling better decisions for the business. How are restaurants using the data they have available to driver better results?  There are many questions that I would suggest a restaurant would want to know surrounding, customer profiles, forecasting, client relationship management, menu engineering, and worker productivity. A restaurant depends on proper forecasting to determine the appropriate levels of food, employees, and supplies. How does the restaurant make those important decisions? At most restaurants today you get a buzzer if there is a wait to know when your table is ready. This along with number of tables and nightly revenue enables the restaurant to determine peak demand and wait times and staff accordingly.

    At Applebee’s, they were backing out the cooking time from the time it took from order to payment to see how long the server is spending with a table. What other information could be derived from the order entry system? They would know what foods are ordered together and what up sells the table ordered. The servers could be trained that when quesadilla is ordered then the client might also like a Corona. The menu may even have a picture of a Corona by the quesadilla if they found that type of relationship in the data to encourage the up sell. I would want to know who my best servers were. The data that is obtained from the order entry system would record everything about the server’s tables to inform management about the performance of their employees. This data would help management provide feedback and performance evaluations to its employees. What delights customers and keeps them coming back to the restaurant? This information can be obtained through online customer surveys from a link printed on the bottom of the receipt.

Restaurants today are very technologically driven with buzzers, point of sale machines, and online surveys. They are able to track anything and everything to run statistical analysis looking for relationships and interesting trends that management can use to more effectively and efficiently run the business and drive profits.  

Question 3

Does data mining and developing a data warehouse stifle innovative thinking, causing companies to become too constrained by the data they are already collecting to think about unexplored opportunities?

Answer 3

I couldn’t disagree more.  But I managed a data warehouse for several years, so I have intimate knowledge of the tremendous future benefits that looking at the past can provide.  Also, industries in general are extremely cyclical and if you can learn from your past you will be that much more prepared for the future.  I can understand how people might think that data mining and data warehousing has you focusing on what has occurred and not spending your capital on something that will provide future gains.  But I think that is exactly what you are doing when you invest in data mining and a data warehouse.  You are picking apart the past to find out what worked, what didn’t and what markets you never penetrated.

For example, in the case study VistaPrint created a new four page upload process that they felt should greatly improve the company’s conversion rate in customers completing the process and not losing them during the process.  But during the testing phases the results were the same and it wasn’t until they looked at the data per each page during the upload did they find that the fourth page was causing the majority or drops.  So they modified that page and the new process yielded the results that were originally expected, but those results most likely wouldn’t have been realized if they didn’t mine though all the test data.

Conclusion

Data mining and data warehousing, as stated in class, really is the “next” logical step in using technology to bring your business to the next level.  We have come from just gathering data and processing data, to now understanding the data and figuring out what “we” as a company should do next.  What is the “next” big innovation?

Works Cited

[1] O’Brien, James A., and George M. Marakas. Management Information Systems. Boston: McGraw-Hill Irwin, 2010. 215-16. Print.