2015 ITGS HL Paper 3

The 2015 ITGS case study, Asociación de Supermercados Independientes: An investigation into Big Data, is the stimulus material for the research investigation required for May and November 2015 higher level paper 3. All of the work related to the case study should reflect the integrated approach explained on pages 15–17 of the ITGS guide.

Source: http://www.el-nacional.com/reporteya/Instalaran-abastecimiento-supermercados-Foto-Dossier33_NACIMA20140820_0035_6.jpg
Source: http://www.el-nacional.com/reporteya/Instalaran-abastecimiento-supermercados-Foto-Dossier33_NACIMA20140820_0035_6.jpg

Candidates should consider Asociación de Supermercados Independientes: An investigation into Big Data with respect to:
• relevant IT systems in a social context
• both local and global areas of impact
• social and ethical impacts on individuals and societies
• current challenges and solutions
• future developments.

Candidates are expected to research real-life situations similar to Asociación de Supermercados Independientes: An investigation into Big Data and relate their findings to first-hand experiences wherever possible. Information may be collected through a range of activities: secondary and primary research, field trips, guest speakers, personal interviews and email correspondence.

Responses to examination questions must reflect the synthesis of knowledge and experiences that the candidates have gained from their investigations. In some instances, additional information may be provided in examination questions to allow candidates to generate new ideas.

LEARNING GOALS:

New Triangle3.jpg
DEMONSTRATE an understanding of the IT systems presented in the case study and how they work (AO1)
ANALYZE the social/ethical issues relevant to the case study (AO2)
EXPLAIN how the scenarios specified in the case study may be related to other similar global and local situations (AO2)
DEMONSTRATE independent research (use and quote information gathered in the primary and secondary research that goes beyond what was presented in the case study (AO3)
EVALUATE, FORMULATE or JUSTIFY strategic solutions to problems presented in the case study (AO3)

LEARNING RESOURCES:

Required Reading:


KEY TERMS:

  • Electronic Point of Sale (EPOS): technology which enables an efficient recording of the sale of goods or services to the customer.
  • data warehouse: vast collection databases containing many gigabytes of data.
  • data mining: searching collections of data for hidden patterns.
  • database: a collection of information that is organized so that it can easily be accessed, managed, and updated.
  • personal data: data which could identify a user, or lead to social impacts such as identity theft.
  • loyalty/reward card: card used to identify repeat customers, to allow them to accumulate reward points, and to gather data about their shopping habits for marketing purposes.
  • targeted advertising/marketing: Use of data about customers to determine which adverts they are most likely to find useful.
  • deskilling: Reduction in the skill needed to do a job, due to technology
  • Electronic Funds Transfer (EFT): Transfer of money from one account to another using computer systems and networks.
  • barcode: a machine-readable code in the form of numbers and a pattern of parallel lines of varying widths, printed on and identifying a product.
  • barcode scanner: a machine-readable code in the form of numbers and a pattern of parallel lines of varying widths, printed on and identifying a product.


ITGS Textbook Paper 3 Resources
http://www.itgstextbook.com/case-study-2015-investigation-big-data.html
ITGSopedia Paper 3 Resources
http://itgsopedia.wikispaces.com/Case+Study+2015+-+Paper+3



PRIMARY RESOURCES:
Source: http://www.yosoyvenezolano.info/imgs/noticia/supermercado-1398099445.jpeg
Source: http://www.yosoyvenezolano.info/imgs/noticia/supermercado-1398099445.jpeg

IDEAS:
Visit a local supermarket that utilizes loyalty cards. Ask to speak to a store manager. Tell him/her about ITGS and what you are doing to prepare for the paper 3 assessment. Ask if you could ask them a few questions about their loyalty card program. If they are busy see if you can schedule a meeting for the class or ask them if you could email them some questions. Keep in mind that store managers are typically very busy and are responsible for the day to day operations of the store. Communicate that you are simply trying to learn as much about loyalty card programs and data analysis in a real world context so you can prepare for the ITGS assessment regarding data analysis and loyalty card programs in May, etc.

Possible questions for store manager:
  1. Explain how your loyalty card program works.
  2. What information do customers have to provide to obtain a loyalty card?
  3. What benefits does the loyalty card program provide for the customers?
  4. What benefits does the loyalty card program provide for your store?
  5. Is the information in your customer database sold to other companies?
  6. Can customers access their profile and history of purchases online?
  7. As the store manager how do you use the data at hand to aid with store operations?
  8. Have you participated in or led any data related training?
  9. What processes does your distribution center use to ensure that the volume of stock being held in storage both in the distribution centre and in the individual stores is as low as possible?
  10. How has this changed since the time you have started with the company?
  11. Is there a person that works with the data on a full time basis that you could put us in contact with to get more information regarding data analysis including clustering, pattern analysis, forecasting, hypothesis testing and targeted marketing?

Possible topics for Data Analyst(s) include: Analysis, Business intelligence software, Clustering/pattern analysis, Data analysis/data analytics, Data extrapolation, Data mining, Data querying, Data visualization, Data warehouse, ETL (Extract, Transform, Load) process, and Forecasting and /or hypothesis testing.

Possible questions for Data Analyst(s):
  1. When, during data analysis, do you become confident enough in a pattern to use it for practical purposes?
  2. When you form a hypothesis about the data, do you test it? If so, is that testing on a small scale (i.e. a few customers at a single store)?
  3. Is there a dedicated staff that performs data analysis tasks?

Possible topics for Marketing include: Behavioural marketing, Targeted advertising, and/or Targeted marketing.
Possible questions for Marketing:
  1. How often does a customer have to purchase an item before he is targeted with ads for that item or similar items?
  2. How do you determine how frequently to advertise to a customer?
  3. Did you learn this "the hard way?"
  4. How much does targeted advertising/marketing contribute to the sales and profits generated for the business?

SECONDARY RESOURCES:
Facebook Group: 2015 ITGSopedia Case Study
ITGSopedia Wiki: Case Study 2015 - Paper 3
ITGS Textbook Case Study 2015 Asociación de Supermercados Independientes - An investigation into Big Data
Insert link to Diigo tagged articles here.
Use the ITGS global tag 7.15_case_study_2015

Insert links to other ITGS specific Wikis (other classes) here

A webpage from another ITGS class

Add additional secondary resources here.

RESEARCH QUESTIONS:
  • What are potential problem(s) in this case?
      • Efficiency In Stock Management
        • Goods are not available on the system
        • JIT
        • Incompatible data formats
        • Access to real-time display
        • Unable to create reports for individual stores
        • Send data to local suppliers on trends, which needs ETL
        • Economics of scale
        Privacy Of Customers
        • loyalty card contains all information on customers
        • no mention of uses of customer data
        • Anonymityof customers
        • using of data for Advertising
        • Target marketing
        • predict their buying trends
        Communication
        • SQL training needed
        • Data visualisation (GUI?/spreadsheet?)
        • Training needed for the system (digital immigrant)
        • Language barrier between Mexicans and international suppliers
        Security Of Data
        • No mention of what this data is used for
        • Security of ETL process and security of servers used for the main database
        Reliability And Integrity
        • JIT prediction
        • Human error
        • Data mining is used
        • Forecasting may be accurate
        • ETL is essential for the stores to run
        • relying on 1 system

  • Who are the stakeholders?
    • Insert response here

  • What are the goals of the stakeholders?
    • Insert response here

  • What are the obstacles that prevent them from achieving their goals?
    • Insert response here

  • How does the problem affect the stakeholders both in the long run and the short run?
    • Insert response here

  • What social/ethical issues arise from this analysis
    • Positive social
      • Customers reap rewards such as discounts, charitable donations, and free items by using loyalty cards
      • The information collected allows stores to send customers special coupons and advertisements for items based on their buying habits (targeted marketing)
      • ASI stores use purchase data to manage stock inventory and maximize profits by offering competitive pricing
    • Negative social
      • Targeted marketing can become excessive if ASI stores bombard customers with unwanted materials
      • It can be difficult to maintain the privacy and anonymity of customer data in store databases
    • Negative ethical
      • ASI collects customers’ personal data and purchase data without them being aware of it
      • Customers don’t know what their information is being used for

  • Definitions of ALL related ITGS Key Terms
    • See above

  • How do the technologies work?
    • When a customer at an ASI store makes a purchase, the cashier scans the barcode of his loyalty card along with the purchased items. By doing this, information about the items is put into the store’s database, and connected to the customer’s profile. This data is collected and used both to reward the customer and to allow the ASI store to manage its stock of the items that the customer bought. Data analysts examine data from all the loyalty cards and items scanned, and use data mining techniques to reveal patterns that guide ASI administrative decisions.

  • How the technologies are part of the problem and/or the solution?
    • The technology contributes to the problems of customer privacy and the security of personal customer data. Because data about all of a store’s customers is kept in a single database, it can be difficult to ensure the security of the information should a data breach occur. Additionally, since ASI does not inform customers when data is being collected, large amounts of potentially private information is being accessed by database administrators.
    • The ASI dashboard website is a part of the technology that contributes to the problems mentioned above. Because customers can access their ASI profiles online via a computer or smartphone, some privacy and anonymity concerns are somewhat alleviated. Customers can see some of the data that they have shared with ASI, as well as track the status of the rewards they receive via their reward cards.
  • What are the available solutions?
    • Insert response here
  • What creative solutions can we generate?
    • Insert response here
  • What are the criteria to choose a solution(s)?
    • Insert response here
  • What are the advantages of the solution(s), for which stakeholders?
    • Insert response here
  • What are the disadvantages of the solution(s), for which stakeholders?
    • Insert response here
  • Are there ways to mitigate the disadvantages?
    • Insert response here
  • What additional effects are generated by the solution(s)?
    • Insert response here
  • Taking into account the social and ethical issues which arise, which is/are the best solution(s)?
    • Insert response here

POSSIBLE PAPER 3 IB ASSESSMENT QUESTIONS:
  • IDENTIFY up to 3 valid uses for how the data could be used to enhance the business.
  • DEFINE the term _.

GUIDED LEARNING ACTIVITIES:
A-Critically read the case study. Print a copy of the case study.
B-Highlight information in the case study as it relates to the four parts of the ITGS triangle. Use Green for stakeholders, Blue for Social/Ethical Significance, Orange for IT Systems, and Yellow for Application to Specified Scenarios. Do not perform a full triangle analysis yet, simply start to organize what goes where, etc. Meet with a group of 3 other students to COMPARE and CONTRAST your findings.
C-Create a new Wiki via Wikispaces to collect and analyze your findings regarding the HL Paper 3 Case Study together as a class. This will provide a place for you to review relevant sources and information before the exam in May. Include the following:
  • IDENTIFY all ITGS key terms used in the article and at the end of the article and define them on the class Wiki in a section or page named KEY TERMS. Include definitions, explanations and diagrams relating to the terminology along with the properly cited sources.
  • FORMULATE research questions for inquiry into the case study (questions you will need to answer through research). Questions should be added as secondary research progresses on the class Wiki in a section or page named RESEARCH QUESTIONS. Design and develop new questions as research progresses.
  • IDENTIFY possible Primary Resources (examples: Stock management / ordering systems, Loyalty card systems, Check out systems, Systems designed to analyze big data collected from customers and from store operations) in a section or page named PRIMARY SOURCES.
  • IDENTIFY secondary resources (examples: websites, .pdf files, videos, printed magazines and books, ebooks). Reliable and relevant sources must be used in a section or page named SECONDARY RESOURCES.
  • COMPARE and CONTRAST findings from primary sources with findings from secondary resources. Create a section or page on the Wiki for this. Choose an appropriate name.
  • Predict possible questions that could appear on Paper 3 using ITGS Command terms under a heading titled POSSIBLE PAPER 3 IB ASSESSMENT QUESTIONS.
  • IDENTIFY a set of tags and use Diigo throughout the year to tag useful information related to the case study. Utilize the ITGSopedia Global Tagging System page and the 2015 ITGS Case Study Facebook Group to aid in your research. Place links to these resources on the Wiki under the heading LEARNING RESOURCES.
  • ANNOTATE the case study as a class with Diigo based on your original highlighted copy. Post the link to the annotated copy to the Wiki under the REQUIRED READING heading.

Resources utilized in the development of this Wikipage:

http://blogs.osc-ib.com/2014/08/ib-teacher-blogs/dp_itgs/itgs-case-study-2015-how-to-get-started/
Add additional sources here via EasyBib
Contributors: Chris Grzegorczyk, Sudesna Paul, Jacob Peters, Michael Broughton, and Rafia Haq.