INFS2036: Business Intelligence - The Difference Between Waterfall and Agile Information System Development Approaches - Business Assignment Help

Assignment Task:

The Case Study Practice Section is designed to give you practice with answering case study questions.  In the exam all case studies and visualisations will be new so don’t expect a Starbucks case study J
 
 
The General Questions Section contains Business Intelligence questions taken from topics covered in the Workshop slides, Practical Discussions and/or tests as well the indicated readings/resources.  Any visualisation you are given to discuss in the exam will be new so don’t expect a Boeing Traffic Flow visualisation as you’ve been given here J
 
 
 
Sample Answers 
 
Case Study Practice Questions  
 
1. What is the Priority? Sample priorities include: • How can Starbucks increase its volume of sales through customer loyalty? • How can Starbucks encourage customers to purchase more frequently? • How can Starbucks use mobile devices to encourage customers into the store more frequently?    
 
2. Name two ways BI can help this organisation achieve this priority. Sample answers: • By coming up with Performance Indicators • By coming up with metrics • By gathering and sharing the data through BI tools among relevant levels of management  
 
3. List two descriptive questions the dashboard should be able to answer. Sample answers: • What were the purchasing habits of Starbucks customers? • How often did customers go to Starbucks? • What products did customers buy in Starbucks? • How much credit did customers add to their loyalty cards? • How often did customers add credit to their loyalty cards? • How successful were the mobile phone offers to get customers in the store? 
 
4. List two diagnostic questions the dashboard should be able to answer. Sample answers: • Why did customers add credit to their loyalty cards? • Why did customers go to the store after receiving a mobile offer? • Why do customer purchasing habits vary? • Why are customers taking up offers in some stores and not others?  
 
5. List two predictive analytics questions the dashboard should be able to answer. Sample answers: • How much credit will customers add to their loyalty cards? • What percentage of customers will take up the loyalty offers? • What percentage of customers will continue with the loyalty program? • How much revenue will be made in loyalty customer sales? 6. List four data items you would need to use in the dashboard.  Sample answers: • Amount spent on coffee • Number of loyalty customers by store • Number of mobile phone offers • Number of free coffees earned • Amount spent by Starbucks on free coffees earned • Credit amount pre-loaded on loyalty card 
 
7. List one internal data item and one external data item you could use for this case study. Sample answers: • Internal: Number of loyalty customers by store • Internal: Number of free coffees earned • Internal: Credit amount pre-loaded on loyalty card 
 
• External: Number of coffee shops in a store’s local area • External: Tourism to a store’s local area • External: Age demographic of local residents/workers 
 
8. Name one data standard that could be used in this BI project.  
 
Sample answers: • A master list of Starbucks stores • How customer purchase information should be stored • Common personal information to collected about each customer (e.g. name, phone number, e-mail address, preferred Starbucks store). 
 
9. Name one example of a data set that could be shared in this case study to better support the Priority of the case study.   Indicate if the data is likely to be internal/external and structured/unstructured. How could you ensure consent? Sample answers: 
 
• Customer coffee preferences shared across different Starbucks stores – Internal, likely to be structured if taken from loyalty card purchases.  To use the data a transparent policy about data usage should be made available to customers so they are aware of data usage and can provide consent. 
 
• Weather data (sunny, rainy, cold, hot etc.) to change recommendations to customers – e.g. hot drinks in cold weather and cold drinks in hot weather – External and unstructured. If the data is taken from publicly available sites (e.g. a weather website) then there is no need for consent.   10. What would you recommend putting in place to ensure there is sufficient consent for sharing the data? 
 Sample answers: • Provide full data privacy information to customers, including how their data would be used and protected.  • Reassure customers their data will not be sold to marketing companies (if this is the case) or if their data will be sold on, to let them know before they  sign up. 
 
11. List a possible performance indicator that could be included in a dashboard for this case study.   
 
Sample answers: • Increase uptake of loyalty membership by 5% in 2019 • Increase customer loyalty spending by $500,000 each quarter in the 2019/2020 financial year • Increased uptake of offers and discounts made to loyalty customers by 25% by end 2019 • Minimum loyalty customer satisfaction rating of 90% by end of 2019 
 
12. List three possible metrics that could be included in a dashboard for this case study. 
 
Sample answers: • The ratio of customers receiving offers on their mobile devices to claiming the offers • The number of loyalty memberships per store • Differences in amount spent across stores • Cost incurred by offering free coffee 

• Ratio of amount spent on coffee to amount spent on free coffee • Quality of coffee  
 
13. What are two things you could do to make this BI Project more successful? 
Sample answers: • Data quality and data availability – identify and profile early • Make sure consent is given for planned data e.g. will customers give their consent for future marketing purposes? • Do Starbucks have the correct analytics people in place to work on the project? • Find out early known constraints and timelines – e.g. budget, specific events in the organisation  • Determine how often the data should be collected • Knowing what systems and data exists already that can be leveraged will deliver results sooner (e.g. existing Starbucks customer data it can use).  14. Give one reason this BI project could fail. 
 
Sample answers: • Only see the questions once the project is finished/already in implementation  • Data could be unreliable (e.g. collected or processed incorrectly) • Reliance on people’s availability to participate (do customers want to join the loyalty program?) • Find out early known constraints and timelines – such as budget allocated to the customer loyalty program 
 
15. List two potential issues with data quality arising from this process. 
Sample answers: • The legalities of customer data collection • Is there enough data? • Is it complete data? • Can the data sets be successfully joined? 
 
16. Name two stakeholders in this project. 
Sample answers: • Employees of Starbucks (they convert customers to loyalty members by encouraging sign-up) • Shareholders of Starbucks • Suppliers to Starbucks (e.g. they will need to deliver coffee and food supplies to meet changing demands based on loyalty member success) • CEO 

• Board 
 
17. Name two end users of this project. 
Sample answers (nontechnical decision makers tend to be end users): • Store managers at Starbucks • Local area managers  • Head of Sales (locally, regionally, etc) • Customers of Starbucks – they make decisions to purchase/not purchase 
 
18. Discuss how the four phases of Business Performance apply to the case study.  (We discussed this in the Week 7 prac. J ) 
 
Sample answers: 
 
1. Strategise – e.g. setting the goal for this project (e.g. How can Starbucks increase its volume of sales through customer loyalty?). 
 
2. Plan – e.g. setting a target to have a 100% success rate in uptake of loyalty membership by all repeat customers. 
 
3. Monitor/Analyse – e.g. metrics and performance indicators e.g. a metric could be the number of loyalty memberships per store and a performance indicator could be the success of loyalty membership. 
 
4. Act/Adjust – e.g. comparing customer loyalty uptake across stores and encourage uptake at those stores that are less successful in converting customers to membership. 
 
19. Explain the difference between Business Intelligence and Business Analytics in the context of this case study.  Sample answers: 
 
Business Intelligence provides organisational capacity to make reports and dashboards to multiple groups of users.   
  
E.g. Starbucks managers could receive daily reports of customer loyalty sign-up, discounted offers claimed, amounts spent by loyalty customers, etc. 
 
Business Analytics uses specialised technical tools and methods for advanced data analysis and predictive modelling over the large and complex data. 
 
E.g. To produce the daily reports and dashboard data analysts could analyse the data using pivot tables, charts, regression analysis for prediction and other analytical tools such as market basket analysis to encourage association rule spending. 
  
 
20. Write an elementary-level question at the operational level of decision making relating to the case study.  
 
Sample answers: • How many sandwiches/baguettes/wraps to prepare each day? • Does the promotional posters match merchandise display in store? • Are food items being kept at the required temperature?   
 
 
 
21. Write an overall-level question at the strategic level of decision making relating to the case study. 
 
Sample answers: • Is the store profitable in the long run? • Can IoT be introduced to better understand the business environment? • Which leading brands could Starbucks partner with for merchandise collectors? (eg. Disney) 
 
 
22. Explain the difference between waterfall and agile information system development approaches in the context of this case study.  
 
Sample answers: 
 
An agile information system development model approach could be used to predict purchases and offers customers would likely be interested in.  .  Each stage (Define, Analyse and Build) would be conducted repeatedly to refine the definition, improve the analysis and build a stronger predictive model. 
 
A waterfall system development model approach could be used to predict purchases and offers customers would likely be interested in. Each stage (Define, Analyse and Build) would be conducted once only – so the problem definition would be defined, data collected would be analysed and then the predictive model would be built. 
 
 
23. Using the performance indicator identified in Question 11 create an impact diagram that uses your chosen KPI for this case study.  
 
Break this diagram down into two more levels and at each level, give two Performance Indicators that would make up the Key Performance Indicator.  
 
For this question assume all but one of the Performance Indicators are performing above target, with one performing below target, however you do not need to use colour coding in your answer, just the appropriate shape (circle, diamond, square). 

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