1. Disco SA: Problems Didn’t know customer
Needed to understand behavior of loyal customers
Retail Analytics
Reliant on OLTP systems and IT ppl to solve/prepare information
More employees needed more access to data to try to figure out anomalies/patterns
‘full-service’ gas station

2. Disco SA: Solution
Used data warehouse to centrally store data  data mining used to find unknown patterns to bridge analysis gap
Descriptive Data Mining = finds patterns in data to explain/describe behavior
Segmenting = putting customers into distinct groups
Clustering = describes customer in segment
Few specific dimensions determine cluster
Predictive Data Mining = finds patterns that are used to ID trends
Finding characteristics of customers who are likely to buy particular product
Decision Tree = visual & interactive model used to break data into groups

3. Cascade Designs: Problem
Diverse collection of loosely integrated standalone applications  ‘legacy systems’
Developed and supported by a few internal IT people
‘full-service’ gas station
System complexity limited its efficiency and growth for company

4. Cascade Designs: Solution & Benefits
ERP (Enterprise Resources Planning ) System
Real-time INFO
Individual Responsibility
Better control/management of inventories/procedures
Better product decisions (effective choices)
Ex: carabineers
Discovery of 20/80 customers

5. Identifying BI Opportunities
1. Do Homework
WHERE : BI will be used/needed
Functional Areas = dept. of buiness (FIN, OPS, HR)
Business Units = line of business that crosses funtions
Cross-functional and business-unit applications have bigger payoff potential  protecting competitive advantage
WHO : will use BI and benefit from information
BI at Higher Level = need for summarized data that supports analysis of trends/patterns w/in and across functional areas
BI at Lower Level = need detailed data that is operational in nature and specific to functional area

6. BI Opportunities 1. Doing Homework (cont.)
WHAT : information (measures/dimensions)
Measures = KSF for functional areas /business units
Base Measures = measures captured at transaction level
Calculated Measures = computation of base measures
Dimensions = ‘by,by,by’ = data you need for analysis
Level of Detail = summarization can be derived from detail
Ex: target  POS down to hour instead of minute was sufficient for good results

7. BI Opportunities 2. Sharing & Collecting Ideas
Brainstorming Teams = specify measures & dimensions
Why ?’s  What ?’s  answers define SO
Answering what you NEED out of system to perform successful analysis
BI blueprint = measure and dimension analysis (p.127)

8. BI Opportunities
Evaluating Alternatives= synthesis of BI blueprint to list of BI opportunity areas
Group requirements by Opportunity Areas
Opportunity Areas = logical grouping of measure requirements w/ consistent data of dimensions
Consistent set of requirements/data that can be used by many groups of users
Grade Opps by Importance
Actionability = empowerment of employees to be able to ‘act’ on data
Materiality = can you save/make $$ with info
Tactical vs. Strategic
Strategic = LT = ‘process view’
Tactical = ST = ‘functional view’

9. BI Opportunities Evaluating Alternatives (cont.)
Grade Opps by Difficulty
Cross-Functionality of Design
Functional Opps = easy = functional view
Used in one functional area
Cross-Functionality = Hard = ‘process view’
Existence & Accessibility of Data
Complexity of Calculation =

10. II I III IV BI Opportunities Evaluating Alternatives (cont)
Rank Opps = BI Scorecard
Level of Effort--low II I
III IV
I = high priority/easy = GO FOR IT
II = low & med priority, easy to do = CONFIDENT, maybe more homework
III = low priority/hard = case by case & maybe pilot test
IV = high priority/hard = pilot test
Business Priority-----high

11. Case Summary
Audi = used BI to help improve efficiency of assembly line/operations
CompUSA = used BI to help improve day-to-day store management and operations
Cascade Design = used BI to help product/inventory management & to maintain stable workforce
DiscoSA = used BI to enhance service to keep customers loyal
CAN YOU IDENTIFY PROBLEM EACH COMPANY ENCOUNTERED, SOLUTION THAT WAS IMPLEMENTED, & BENEFITS THAT CAME FROM EACH SOLUTION