MIS 874 - Info Technology Mgmt - Chapter 12

Business Analytics

- Tools and techniques for analyzing data. - OLAP, statistics, models, data mining.

Six Elements in the Business Intelligence Environment

1. Data from the business environment. 2. Business intelligence infrastructure. 3. Business analytics toolset. 4. Managerial users and methods. 5. Delivery platform—MIS, DSS, ESS. 6. User interface. (See page 475-477 for additional details.)

The Four Stages of the Decision-making Process

1. Intelligence: Discovering, identifying, and understanding the problems occurring in the organization. 2. Design: Identifying and exploring solutions to the problem. 3. Choice: Choosing among solution alternatives. 4. Implementation: Making chosen alternative work and continuing to monitor how well solution is working.

Two main management strategies for developing BI and BA capabilities

1. One-stop integrated solution: - Hardware firms sell software that run optimally on their hardware. - Makes firm dependent on single vendor—switching costs. 2. Multiple best-of-breed solution: - Greater flexibility and independence. - Potential difficulties in integration. - Must deal with multiple vendors.

Business Intelligence Users

80 percent are casual users relying on production reports. Senior executives: - Use monitoring functionalities. Middle managers and analysts: - Ad-hoc analysis. Operational employees: - Prepackaged reports. - For example: sales forecasts, customer satisfaction, loyalty and attrition, supply chain backlog, employee productivity.

Location Analytics

Ability to gain business insight from the location (geographic) component of data. - Mobile phones. - Sensors, scanning devices. - Map data.

Decision Support Systems

Are information systems at the organization's management level that combine data and sophisticated analytical models or data analysis tools to support semistructured and unstructured decision making. - 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)

Big Data Analytics

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.

Operational Intelligence

Business analytics that delivers insight into data, streaming events and business operations.

Business Intelligence Vendors

Create business intelligence and analytics purchased by firms. The largest five provider of these products are: Oracle, SAP, IBM, Microsoft and SAS.

Big Data

Data sets with volumes so huge that they are beyond the ability of typical relational DBMS to capture, store, and analyze. The data are often unstructured or semi-structured.

Business Intelligence and Analytics Capabilities

Goal is to deliver accurate real-time information to decision makers. Main functionalities of BI systems: 1. Production reports 2. Parameterized reports 3. Dashboards/scorecards 4. Ad hoc query/search/report creation 5. Drill down 6. Forecasts, scenarios, models (See page 477 for overview of main functions)

Key Performance Indicators (KPIs)

How performance on each dimension is measured (financial, business processes, customer, learning and growth). Are the measures proposed by senior management for understanding how well the firm is performing along any given dimension.

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. (In general, structured decision are more prevalent at lower organizational levels, whereas unstructured problems are more common at higher levels of the firm.)

Managers and Decision Making in the Real World

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.

Group Decision Support Systems (GDSS)

Interactive system to facilitate solution of unstructured problems by group. Specialized hardware and software; typically used in conference rooms. - Overhead projectors, display screens, - Software to collect, rank, edit participant ideas and responses, - May require facilitator and staff, Enables increasing meeting size and increasing productivity. Promotes collaborative atmosphere, anonymity. Uses structured methods to organize and evaluate ideas.

Mintzberg's 10 managerial roles

Interpersonal roles: 1. Figurehead, 2. Leader, 3. Liaison, Informational roles: 4. Nerve center, 5. Disseminator, 6. Spokesperson, Decisional roles: 7. Entrepreneur, 8. Disturbance handler, 9. Resource allocator, 10. Negotiator,

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 30 milliseconds. - Responsible for "Flash Crash" of 2010. Require safeguards to ensure proper operation and regulation.

Interpersonal Roles

Managers act as figureheads for the organization when they represent their companies to the outside world and perform symbolic duties, such as giving out employee awards.

Semistructured Decisions

Many decisions have elements of both unstructured and structured, where only part of the problem has a clear-cut answer provided by an accepted procedure.

Production Reports

Most widely used output of BI suites. These are predefined reports based on industry-specific requirements (see Table 12.4). Common predefined, prepackaged reports - Sales: Forecast sales; sales team performance. - Service/call center: Customer satisfaction; service cost. - Marketing: Campaign effectiveness; loyalty and attrition. - Procurement and support: Supplier performance. - Supply chain: Backlog; fulfillment status. - Financials: General ledger; cash flow. - Human resources: Employee productivity; compensation.

Multidimensional Data Analysis and OLAP

One of the key business intelligence technologies. Manage "super users" and analysts employ to identify and understand patterns in business information that may be useful for semistructured decision making.

Operational Intelligence and Analytics

Operational intelligence: Business activity monitoring. Collection and use of data generated by sensors. Internet of Things: - Creating huge streams of data from Web activities, sensors, and other monitoring devices. Software for operational intelligence and analytics enable companies to analyze their Big Data.

Key Decision Making Groups

Senior managers: Make many unstructured decisions. For example: Should we enter a new market? Middle managers: Make more structured decisions but these may include unstructured components. For example: Why is order fulfillment report showing decline in Minneapolis? Operational managers, rank and file employees: Make more structured decisions. For example: Does customer meet criteria for credit?

Pivot Table

Spreadsheet tool for reorganizing and summarizing two or more dimensions of data in a tabular format.

Data Visualization

Technology for helping users see patterns and relationships in large amounts of data by presenting the data in graphical form.

Drill-Down

The ability to move from summary data to lower and lower levels of detail.

Real World Decision Making

Three main reasons why investments in information technology 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.

Classical Model of Management

Traditional description of management that focused on its formal functions of planning, organizing, coordinating, deciding, and controlling.

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.

What If Analysis

Working forward from known or assumed conditions, allows the user to vary certain values to test results to predict outcomes if changes occur in those values.

Managerial Roles

are expectations of the activities that managers should perform in an organization. Mintzberg found that these managerial roles fell into three categories: interpersonal, informational, and decisional.

Structured Decisions

are repetitive and routine, and they involve a definite procedure for handling them so that they do not have to be treated each time as if they were new.

Unstructured Decisions

are those in which the decision maker must provide judgment, evaluation, and insight to solve the problem. Each of these decisions is novel, important, and non-routine, and there is no well-understood or agreed-on procedure for making them.

Executive Support Systems (ESS)

decision support for senior management. Help executives focus on important performance information. Balanced scorecard method: Measures outcomes on four dimensions. 1. Financial, 2. Business process, 3. Customer, 4. Learning and growth, Key performance indicators (KPIs) measure each dimension

Backward Analysis

helps decision makers with goal seeking: if I want to sell 1 million product units next year, how much must I reduce the price of the product?

Balanced Scorecard

is a framework for operationalzing a firm's strategic plan by focusing on measurable outcomes on four dimensions of firm performance: financial, business process, customer, and learn and growth.

Business Intelligence

is a term used by hardware and software vendors and information technology consultants to describe the infrastructure for warehousing, integrating, reporting, and analyzing data that come from the business environment, including big data. - Infrastructure for collecting, storing, analyzing data produced by business. - Databases, data warehouses, data marts.

Information Roles

managers act as the nerve centers of their organizations, receiving the most concrete, up-to-date information and redistributing it to those who need to be aware of it. Managers are therefore information disseminators and spokespersons for their organizations.

Decisional Roles

managers make decisions. they act as entrepreneurs by initiating new kinds of activities; they handle disturbances arising in the organization, they allocate resources to staff members who need them; and they negotiate conflicts and mediate between conflicting groups.

Sensitivity Analysis

models ask what if questions repeatdely to predict a range of outomces when one or more variables are changed multiple times.

Geographic Information Systems (GIS)

provides tools to help decision makers visualize problems that benefit from mapping. - Ties location-related data to maps. - Example: For helping local governments calculate response times to disasters.

Behavioral Models

state that the actual behavior of managers appears to be less systematic, more informal, less reflective, more reactive, and less well organized than the classical model would have us believe.

Predictive Analytics

use statistical analysis, data mining techniques, historical data, and assumptions about future conditions 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.