Business Intelligence and Decision Making PDF
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Summary
This document provides an overview of business intelligence and the decision-making process. It covers different types of decisions, the stages involved in the decision-making process, and the different roles of managers in organizations. The document also explores how information technology can support business intelligence and decision-making.
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1 What Are the Different Types of Decisions, and How Does the Decision-Making Process Work? (1 of 2) Business value of improved decision making – Improving hundreds of thousands of “small” decisions adds up to large annual value for the business Types of decisions – Unstructured:...
1 What Are the Different Types of Decisions, and How Does the Decision-Making Process Work? (1 of 2) Business value of improved decision making – Improving hundreds of thousands of “small” decisions adds up to large annual value for the business Types of decisions – Unstructured: Decision maker must provide judgment, evaluation, and insight to solve problem – Structured: Repetitive and routine; involve definite procedure for handling so they do not have to be treated each time as new – Semistructured: Only part of problem has clear-cut answer provided by accepted procedure Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved 2 What Are the Different Types of Decisions, and How Does the Decision-Making Process Work? (2 of 2) Senior managers – Make many unstructured decisions Middle managers – Make more structured decisions but these may include unstructured components Operational managers and rank and file employees – Make more structured decisions Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved 3 Figure 12.1 Information Requirements of Key Decision-Making Groups in a Firm Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved 4 The Decision-Making Process Intelligence – Discovering, identifying, and understanding the problems occurring in the organization Design – Identifying and exploring solutions to the problem Choice – Choosing among solution alternatives Implementation – Making chosen alternative work and continuing to monitor how well solution is working Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved 5 Figure 12.2 Stages in Decision Making Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved Managerial Roles 6 Information systems can only assist in some of the roles played by managers Classical model of management: five functions – Planning, organizing, coordinating, deciding, and controlling More contemporary behavioral models – Actual behavior of managers appears to be less systematic, more informal, less reflective, more reactive, and less well organized than in classical model Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved Real-World Decision Making 7 Three main reasons why investments in IT do not always produce positive results – Information quality High-quality decisions require high-quality information – Management filters Managers have selective attention and have variety of biases that reject information that does not conform to prior conceptions – Organizational inertia and politics Strong forces within organizations resist making decisions calling for major change Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved 8 High-Velocity Automated Decision Making Made possible through computer algorithms precisely defining steps for a highly structured decision – Humans taken out of decision For example: High-speed computer trading programs – Trades executed in nanoseconds Require safeguards to ensure proper operation and regulation Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved What is Business Intelligence? 9 Business intelligence – Infrastructure for collecting, storing, analyzing data produced by business – Databases, data warehouses, data marts, Hadoop, analytic platforms Business analytics – Tools and techniques for analyzing data – OLAP, statistics, models, data mining Business intelligence vendors – Create business intelligence and analytics purchased by firms Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved The Business Intelligence Environment 10 Six elements in the business intelligence environment – Data from the business environment – Business intelligence infrastructure – Business analytics toolset – Managerial users and methods – Delivery platform—MIS, DSS, ESS – User interface Data visualization tools Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved Figure 12.3 Business Intelligence and 11 Analytics for Decision Support Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved 12 Business Intelligence and Analytics Capabilities Goal is to deliver accurate real-time information to decision makers Main analytic functionalities of BI systems – Production reports – Parameterized reports – Dashboards/scorecards – Ad hoc query/search/report creation – Drill down – Forecasts, scenarios, models Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved 13 Table 12.4 Examples of Business Intelligence Predefined Production Reports Business Functional Area Production Reports Sales Forecast sales; sales team performance; cross-selling; sales cycle times Service/call center Customer satisfaction; service cost; resolution rates; churn rates Marketing Campaign effectiveness; loyalty and attrition; market basket analysis Procurement and support Direct and indirect spending; off-contract purchases; supplier performance Supply chain Backlog; fulfillment status; order cycle time; bill of materials analysis Financials General ledger; accounts receivable and payable; cash flow; profitability Human resources Employee productivity; compensation; workforce demographics; retention Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved Predictive Analytics 14 Uses variety of data, techniques to predict future trends and behavior patterns – Statistical analysis – Data mining – Historical data – Assumptions Incorporated into numerous BI applications for sales, marketing, finance, fraud detection, health care – Credit scoring – Predicting responses to direct marketing campaigns Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved Big Data Analytics 15 Big data: Massive datasets collected from social media, online and in-store customer data, and so on Help create real-time, personalized shopping experiences for major online retailers Smart cities – Public records – Sensors, location data from smartphones – Ability to evaluate effect of one service change on system Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved 16 Location Analytics and Geographic Information Systems Location analytics – Ability to gain business insight from the location (geographic) component of data Mobile phones Sensors, scanning devices Map data Geographic information systems (GIS) – Ties location-related data to maps – Example: For helping local governments calculate response times to disasters Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved Decisional Support for Operational and 17 Middle Management Charged with monitoring key aspects of business Most decisions fairly structured Middle managers typically use MIS – Increasingly online; can be queried interactively – Exception reports Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved 18 Figure 12.4 Business Intelligence Users Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved Support for Semi-structured Decisions 19 Decision-support systems – Support for semi-structured decisions Use mathematical or analytical models Allow varied types of analysis – “What-if” analysis – Sensitivity analysis – Backward sensitivity analysis – Multidimensional analysis / OLAP For example: pivot tables Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved Figure 12.5 Sensitivity Analysis 20 Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved 21 Figure 12.6 A Pivot Table That Examines Customer Regional Distribution and Advertising Source Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved Decision Support for Senior Management: Balanced 22 Scorecard and Enterprise Performance Management Methods (1 of 2) ESS: decision support for senior management – Help executives focus on important performance information Balanced scorecard method – Measures outcomes on four dimensions Financial Business process Customer Learning and growth – Key performance indicators (KPIs) measure each dimension Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved 23 Figure 12.7 The Balanced Scorecard Framework Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved Decision Support for Senior Management: Balanced 24 Scorecard and Enterprise Performance Management Methods (2 of 2) Business performance management (BPM) – Translates firm’s strategies (e.g., differentiation, low-cost producer, scope of operation) into operational targets – KPIs developed to measure progress toward targets Data for ESS – Internal data from enterprise applications – External data such as financial market databases – Drill-down capabilities Copyright © 2022, 2020, 2018 Pearson Education, Inc. All Rights Reserved Dashboards Dashboard: an interface between BI tools and the user – Resembles a car dashboard – Contains visual images to quickly represent specific business metrics of interest to management – Helps management monitor revenue and sales, monitor inventory levels, and pinpoint trends and changes over time 25 What is the Role of Knowledge Management Systems in Business? Knowledge management systems among fastest growing areas of software investment Information economy: production and distribution of information and knowledge a major source of wealth and prosperity Substantial part of a firm’s stock market value is related to intangible assets: knowledge, brands, reputations, and unique business processes Well-executed knowledge-based projects can produce extraordinary ROI Important Dimensions of Knowledge (1 of 2) Data, information, knowledge, and wisdom Tacit knowledge and explicit knowledge Important dimensions of knowledge – Knowledge is a firm asset – Knowledge has different forms – Knowledge has a location – Knowledge is situational Important Dimensions of Knowledge (2 of 2) Knowledge-based core competencies – Key organizational assets Knowing how to do things effectively and efficiently in ways others cannot duplicate is a prime source of profit and competitive advantage – Example: Having a unique build-to-order production system Organizational learning – Process in which organizations gain experience through collection of data, measurement, trial and error, and feedback The Knowledge Management Value Chain (1 of 3) Knowledge management – Set of business processes developed in an organization to create, store, transfer, and apply knowledge Knowledge management value chain – Each stage adds value to raw data and information as they are transformed into usable knowledge Knowledge acquisition Knowledge storage Knowledge dissemination Knowledge application The Knowledge Management Value Chain (2 of 3) Knowledge acquisition – Documenting tacit and explicit knowledge Storing documents, reports, presentations, best practices Unstructured documents (e.g., e-mails) Developing online expert networks – Creating knowledge – Tracking data from TPS and external sources Knowledge storage – Databases – Document management systems – Role of management The Knowledge Management Value Chain (3 of 3) Knowledge dissemination – Portals, wikis – E-mail, instant messaging – Search engines, collaboration tools – A deluge of information Training programs, informal networks, and shared management experience help managers focus attention on important information. Knowledge application – New business practices – New products and services – New markets Figure 11.1 The Knowledge Management Value Chain Building Organizational and Management Capital: Collaboration, Communities of Practice, and Office Environments Developing new organizational roles and responsibilities for the acquisition of knowledge Chief knowledge officer executives; dedicated staff / knowledge managers Communities of practice (COPs) – Informal social networks of professionals and employees – Activities include education, online newsletters, sharing knowledge – Reduce learning curves of new employees Types of Knowledge Management Systems Enterprise-wide knowledge management systems – General-purpose firm-wide efforts to collect, store, distribute, and apply digital content and knowledge Knowledge work systems (KWS) – Specialized systems built for engineers, scientists, other knowledge workers charged with discovering and creating new knowledge Intelligent techniques – Diverse group of techniques, such as data mining, expert systems, machine learning, used for various goals: discovering knowledge, distilling knowledge, discovering optimal solutions Figure 11.2 Major Types of Knowledge Management Systems