Test Prep Flashcards
Digital Transformation
Digital Technology creates Disruptive Digital Forces which demands Digital Transformation.
Digital transformation is inevitable for firms.
Nature of Big Data
- Volume:Large-capacity data storage is not only the problem of data integration but also a critical challenge for analysis.
- Velocity: Data’s patency, availability, and liquidity become critical; velocity indicates the speed of data changes as well as the need for timely data access and processing.
- Variety: Firms have more new data for analysis, such as social media, mobile data, various databases that store hierarchical data, text records, e-mail, metering data, video, images, audio, stock ticker data, and financial transactions.
Role of IT in organizations
Support ->
Enhance Effectiveness & Efficeny ->
Value Creation
Data Information - Knowledge Pyramid
(Bottom up) -
Data -> Information -> Knowledge
Organization and Information Systems
A growing interdependence between a firm’s information systems and its business capabilities and operations: Changes in strategy, rules, and business processes increasingly require changes in hardware, software, databases, and telecommunications; often, what an organization can do depends on what its information systems will permit it to do.
Uses of Information Technology by Firms
• Cost reduction through technology-enabled automation.
• Improve firm competitiveness; e.g., IT as a strategic driver. Empowerment: Customers, suppliers, and internal employees.
• IT-enabled self-service practices and models.
• Operations excellence by increasing organization effectiveness and
efficiency; e.g., decision making, communications and coordination.
• Accelerate information velocity and make the organization more
agile, adaptive, and competitive.
• Effective customer relationship management for customer intimacy
• Effective supply chain integration for supplier intimacy.
• Enable new product development, service design, and business models.
IT Empowers
Supplers - Firm - Customers
Identifying Valuable Customers: RFM Analysis
Recency
Frequency
Monetary
Valuable customers” are more important to a firm !
Identifying Valuable Customer: Clustering Analysis in N-Dimensional Space
Growth Potential Making Referrals Revenue Contributions Purchase Frequency Profit Margin
Customer Life Cycle
Acquire, Enhance, Retain
Supply Chain: Bullwhip Effect
- Small changes in actual demand create much grater problems for upstream partners. • Lack of trust and information sharing among channel partners !!
- Stockpiling translates to huge costs because firms manage inventories “just-in-case.” • Manufacturers cannot plan production efficiently and effectively.
Data and Firm Performance
Data (Information) Visibility
Data (Information) Accessibility
Data (Information) Analytics Capability
Information Velocity
Data quality:
The totality of features and characteristics of data that bears on their ability to satisfy the given business purposes.
Total Data Quality Management
Define
Measure
Analyze
Improve
Data Governance
- Data governance establishes a formal structure and processes by which an organization manages all important issues surrounding data, including data quality as measured by accuracy, completeness, consistency, security, availability.
- In addition to data quality management, data governance also defines data ownership, data access rights, data sharing mechanisms and data audits, across different departments and business units, which are critical to the entire organization.
- Central to effective data governance are formal structure, commitment, technology, processes, and accountability.
Data-Centric Information Value Chain
- Increasing Visibility
- Mirroring Capability
- Create Value
Key Challenges in IT Management
- A young technology (discipline).
- Rapid technological advancements and changes. • Deep penetrations in all aspect of organizations. • Widening business-technology gap.
- Increasing specialization and sub-specialization. • Shifting focuses, disruptive technology.
Key Challenges in IT Management
- A young technology (discipline).
- Rapid technological advancements and changes. • Deep penetrations in all aspect of organizations. • Widening business-technology gap.
- Increasing specialization and sub-specialization. • Shifting focuses, disruptive technology.
Business Intelligence
(BI) refers to use of technology and statistical techniques to gather, analyze large amounts of data to support business decision making; i.e., discovering important patterns and phenomena for interpretation and business actions.
Data mining:
A common technological/computational approach to extract business intelligence from vast amounts of (high-quality) data.
Data mining: A process that extracts previously unknown, interesting, valid, and actionable data patterns (knowledge) from a large set of data.
Web mining:
Discovery and analysis of useful patterns and information from the Web (e.g., Web resources, Web structures, clickstream data); firms can use Web mining to better understand customer behaviors, evaluate the effectiveness of a website, or manage marketing campaigns.
Data Mining: General Process
Selection -> Preprocessing -> Transformation -> Data Mining -> Interpretation/Evaluation