COMM 391. Learning Objectives. Introduction to Management Information Systems. Case 10.1 Quality Assurance at Daimler AG. Winter 2014 Term 1

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1 COMM 391 Introduction to Management Information Systems BUSINESS INTELLIGENCE AND ANALYTICS Winter 2014 Term 1 Learning Objectives 1. Describe the decision-support framework. 2. Describe business intelligence (BI). 3. Describe the fundamental concepts of data warehouses, data marts, OLAP and data mining. Case 10.1 Quality Assurance at Daimler AG Read the Case 10.1 Quality Assurance at Daimler AG What do we learn from this case? 2014 Y.M. Cheung Y.M. Cheung 4

2 Case 10.1 Quality Assurance at Daimler AG The Problem Dating back to the 1980s, German automaker Daimler AG housed warranty data on its Quality Information System (QUIS), a mainframe-based platform and the diagnostic and warranty data were located in different information silos. The organization was unable to take full advantage of the data and the diagnosis database had reached the limits of its capacity. Case 10.1 Quality Assurance at Daimler AG The IT Solution Over a three-year period, Daimler consolidated its data on a data warehouse, making these data available to users through a shared interface. The new system is called Advanced Quality Analysis (AQUA). AQUA provides support for two strategic goals: (1) to increase customer satisfaction; and (2) to reduce costs Y.M. Cheung Y.M. Cheung 6 Case 10.1 Quality Assurance at Daimler AG The Results AQUA has enabled Daimler to achieve deeper insights into how to optimize its production processes. Defects can be detected more quickly, resolved, and eliminated from future models. AQUA supports Daimler s strategic goals of quality leadership, customer satisfaction and profitability. What we learned from this case. BI enables decision makers to quickly ascertain the status of a business enterprise by examining key information. BI systems provide business intelligence that you can act on in a timely fashion. Users will decide what data should be stored in their data warehouses, how they want to analyze the data (user-driven analysis), and what data they want to see and in which format Y.M. Cheung Y.M. Cheung 8

3 Learning Objective 1 Describe the decision-support framework The Manager s Job and Decision Making Management is a process by which an organization achieves its goals through the use of resources (people, money, materials, and information). Managers have three basic roles (Mintzberg 1973) : Interpersonal Informational Decisional A decision is a choice among two or more alternatives that individuals and groups make. Decision making is a systematic process Y.M. Cheung Y.M. Cheung 10 Decision Making Process Decision Making Process (cont d) Intelligence Phase Managers examine a situation and identify and define the problem or opportunity. Design Phase Decision makers construct a model that simplifies the problem and set criteria for evaluating potential solutions. Choice Phase A solution is selected Y.M. Cheung Y.M. Cheung 12

4 Why Managers Need IT Support? The number of alternatives is constantly increasing. Most decisions must be made under time pressure. Decisions are becoming more complex. Decision makers, as well as the information, can be situated in different locations. An Obvious Question What Information Technologies Are Available to Support Managers? 2014 Y.M. Cheung Y.M. Cheung 14 Decision Support Framework Problem Structure The first dimension deals with the problem structure, where the decision making processes fall along the continuum ranging from highly structured to highly unstructured decisions. Structured Semi-structured Unstructured Example: Inventory Control Example: Evaluating Employees Example: New Services 2014 Y.M. Cheung Y.M. Cheung 16

5 Problem Structure Nature of Decision Structured Deal with routine and repetitive problems for which standard solutions exist. Operational Control Executing specific tasks efficiently and effectively. Semi- Structured Require a combination of standard solution procedures and individual judgement. Management Control Acquiring and using resources efficiently in accomplishing organization goals. Unstructured Deal with complex problems for which there are no cut-and-dried solutions. Strategic Planning The long-range goals and policies for growth and resource allocation Y.M. Cheung Y.M. Cheung 18 For discussion You are registering for classes next term. Apply the decision-making process to your decision about how many and which courses to take. Is your decision structured, semi-structured, or unstructured? For discussion Consider your decision-making process when registering for classes next term. Explain how Information Technology supports (or does not support) each phase of this process Y.M. Cheung Y.M. Cheung 20

6 Learning Objective 2 Describe business intelligence (BI) What is Business Intelligence? Business Intelligence (BI) is a broad category of applications, technologies and processes for gathering, storing, accessing and analyzing data to help business users make better decisions. BI applications enable decision makers to quickly ascertain the status of a business enterprise by examining key information Y.M. Cheung Y.M. Cheung 22 Why Business Intelligence? Data are business assets. Unused data are wasted business resources. The challenge is to make decisions in an environment that is data rich and information poor. The Solution: Business Intelligence Too much data not enough information Business intelligence supports decisionmaking by analysing business information. Provides information about the past Monitors current operations Predicts and forecasts future trends BI systems can assist in better decisions. Source: Y.M. Cheung Y.M. Cheung 24

7 How BI can Provide Answers? Scope of Business Intelligence Three specific BI targets that represent different levels of change: Development of one or a few related BI applications. o E.g. campaign management in marketing Development of infrastructure to support enterprise-wide BI. Where the business has been? Where it is now? Where it will be in the near future? o E.g. enterprise data warehouse Support for organizational transformation o E.g. support for new business model 2014 Y.M. Cheung Y.M. Cheung 26 Strategic, Operational and Tactical BI The three forms of BI must work towards a common goal. Strategic, Operational and Tactical BI (cont d) 2014 Y.M. Cheung Y.M. Cheung 28

8 BI s Operational Value Time needed to make transactional data ready for analysis. What is Business Intelligence? Learn from the Leaders Time it takes a human to comprehend the analysis and take appropriate action. Time from which data is made available and analysis of it is completed. (Source: Please click this link to watch the video! 2014 Y.M. Cheung Y.M. Cheung 30 Enterprise BI Platforms and Tools Learning Objective 3 Source: Forrester Describe the fundamental concepts of data warehouses, data marts, OLAP and data mining. (Source: Y.M. Cheung Y.M. Cheung 32

9 What is a Data Warehouse? A Typical Data Warehouse Data warehouse a logical collection of information gathered from many different operational databases that supports business analysis activities and decision-making tasks. The primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository for decision-making purposes. A repository of historical data that are organized by subject, e.g. by customer, product, vendor, etc. External Sources Operational Databases e.g. interest rate, stock prices, crude oil price, competitors product price Extract Transform Data Warehouse e.g., At P&G, each of product divisions (beauty, baby care, snacks and beverage) may have a DB in each of sales offices throughout the world Serve Analysis Query/ Reporting Data Mining 2014 Y.M. Cheung Y.M. Cheung 34 ETL Extract/Transform/Load Extraction, Transformation, and Loading (ETL) a process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse. What is a Data Mart? Data mart contains a subset of data warehouse information extracted to be analyzed for specific business units. A low-cost, scaled-down version of a data warehouse. Can be implemented more quickly than data warehouses Y.M. Cheung Y.M. Cheung 36

10 Databases, Data Warehouses, Data Marts in an Organization An Obvious Question Would it be possible that certain valuable information is indeed in the data but we cannot easily discover the information? 2014 Y.M. Cheung Y.M. Cheung 38 What is OLAP? Online Analytical Processing (OLAP) or Multidimensional Analysis slices & dices data stored in a dimensional format drills down in the data to greater detail aggregates the data What is a Multidimensional Database? A multidimensional database (MDB) is a type of database that is optimized for data warehouse and online analytical processing (OLAP) applications. Multidimensional databases are frequently created using input from existing relational databases Y.M. Cheung Y.M. Cheung 40

11 Relational Databases Two dimensional. Multidimensional Databases Three dimensional matrix or data cube. Databases 2014 Y.M. Cheung Y.M. Cheung 42 What is Data Mining? Data mining the process of searching and analyzing data to extract valuable information not offered by the raw data alone. Drilling Down increasing levels of detail. Drilling Up increasing summarization. Perform two basic operations: Predicting trends and behaviors. Identifying previously unknown patterns. Examples of Data Mining Application Retailing and sales predicting sales, preventing theft and fraud Banking forecasting levels of bad loans and fraudulent credit card use, predicting credit card spending by new customers Insurance forecasting claim amounts and medical coverage costs Marketing classifying customer demographics that can be used to predict which customers will respond to a mailing or buy a particular product Y.M. Cheung Y.M. Cheung 44

12 Decision Support Systems What are BI Dashboards? Decision Support Systems (DSS) combine models and data in an attempt to analyze semistructured and some unstructured problems with extensive user involvement. Models are simplified representations, or abstractions, of reality. DSS enable business managers and analysts to access data interactively, to manipulate these data, and to conduct appropriate analyses, e.g. sensitivity analysis, what-if analysis, goal-seeking analysis. SAP Business One Sales Monitoring Dashboard A dashboard shows not only BI analysis results, but also when business performance variables reach critical threshold levels. Evolved from EIS Y.M. Cheung Y.M. Cheung 46 Bloomberg Terminals Conclusion Bloomberg Charts Bloomberg provides a subscription service that sells financial data, software to analyze these data, trading tools, and news. All of this information is accessible through a colour-coded Bloomberg keyboard that displays the desired information on a computer screen. Business Intelligence (BI) leverages the information stored in data warehouses for strategic advantage and more effective business practice. Data warehouses (and data marts) contain summarized, analytical information sourced from transactional relational databases. Raw transactional data from different operational relational databases are extracted, transformed and loaded (ETL) into data warehouses. Data mining is the process of searching for valuable business information in a large data warehouse or data mart Y.M. Cheung Y.M. Cheung 48