Lecture 9: ICT in Business Decision-Making

Lecture 9: BHMS4472 ICT in Business

• ICT stands for Information, Communication, and Technology
• The lecture focuses on enhancing decision-making using information systems
• Learning objectives include understanding different decision types, information systems support, business intelligence and analytics, and different decision-making constituencies in an organization.

What Are the Different Types of Decisions, and How Does the Decision-Making Process Work?

• Improved decision-making is valuable to businesses, as hundreds of thousands of small decisions impact annual value.
• Decision types:
  • Unstructured: Decision makers use judgments, evaluations, and insights to solve problems.
  • Structured: Repetitive and routine decisions follow established procedures.
  • Semistructured: A portion of the problem involves clear answers from accepted processes.
• Decision-making levels:
  • Senior managers: Make many unstructured decisions.
  • Middle managers: Make structured decisions, sometimes with component unstructured elements.
  • Operational managers and employees: Make mainly structured decisions.

Information Requirements of Key Decision-Making Groups in a Firm

• A hierarchical structure illustrates information needs at different management levels, progressing from unstructured decisions at the senior level to structured decisions at the operational level.
• Senior management: Decisions involve high-level strategic planning, market entry/exit, and budget approvals.
• Middle management: Decisions focus on tactical planning, marketing campaigns, and departmental budgets.
• Operational management: Decisions involve routine tasks, order fulfillment, and re-stocking.

The Decision-Making Process

• The decision-making process comprises four stages:
  • Intelligence: Discovering, identifying, and understanding problems in the organization.
  • Design: Identifying and exploring solutions to the problem.
  • Choice: Choosing the best solution among alternatives.
  • Implementation: Implementing the chosen solution and monitoring its effectiveness.

Managerial Roles

• Information systems can assist in various managerial roles, though not all.
• Classical management models involve five functions: planning, organizing, coordinating, deciding, and controlling.
• Contemporary models show more informal, reactive, and less organized manager behavior compared to the classical models.

Mintzberg's 10 Managerial Roles

• Interpersonal roles include figurehead, leader, and liaison.
• Informational roles include nerve center, disseminator, and spokesperson.
• Decisional roles include entrepreneur, disturbance handler, resource allocator, and negotiator.

Real-World Decision Making

• Three factors hinder IT investment success:
  • Poor information quality: High-quality information is needed for high-quality decisions.
  • Management filters: Managers often use biases and prior conceptions to filter information.
  • Organizational inertia and politics: Organizational structures and politics resist decisions requiring huge changes.

High-Velocity Automated Decision Making

• Computer algorithms define precise steps for structured decisions, eliminating human input.
• Examples include high-speed trading programs, with transactions occurring in nanoseconds.
• Safeguards are crucial for proper operation and regulation.

What is Business Intelligence?

• Business intelligence provides infrastructure for collecting, storing, and analyzing business data.
• It uses databases, data warehouses, data marts, Hadoop, and analytical platforms.
• Business analytics utilize tools and techniques for data analysis, including OLAP, statistics, models, and data mining.
• Business intelligence vendors create and sell BI and analytics tools

The Business Intelligence Environment

• The BI environment consists of six elements:
  • Data from the business environment.
  • Business intelligence infrastructure.
  • Business analytics toolset.
  • Managerial users and methods.
  • Delivery platform (MIS, DSS, ESS).
  • User interface (including data visualization tools).

Business Intelligence and Analytics for Decision Support

• Business intelligence infrastructure collects data, including call centers, online data, mobile devices, and supplier data.
• Analytics tools analyze data, including modeling, data mining, OLAP, and reports.
• Managerial methods include strategy implementation, performance measurement, and forecasting.

Business Intelligence and Analytics Capabilities

• BI aims to provide real-time, accurate information to decision-makers.
• Main functions include production reports, parameterized reports, dashboards/scorecards, ad hoc queries, drill-down, forecasts, and scenarios.

Examples of Business Intelligence Predefined Production Reports

• Various business areas, including sales, service, marketing, procurement, supply chain, financials, and human resources, use reports to provide insights.
• Specific areas, like sales, offer forecasting, cross-selling, sales cycle time, and customer satisfaction insights.

Predictive Analytics

• Predictive analytics uses various data sources and techniques to predict future patterns and trends.
• Includes statistical analysis, data mining, and historical data integration, and incorporated in applications for sales, marketing, finance, fraud detection, and healthcare (including credit scoring)
• Used to predict responses to direct marketing campaigns.

Big Data Analytics

• Big data involves massive datasets collected from diverse sources, like social media, online stores, and in-store interactions.
• Enables real-time, personalized shopping experiences for major online retail stores.
• Applications include the use of location data and public records for smart cities for data monitoring.

Operational Intelligence and Analytics

• Operational intelligence focuses on monitoring business activity and utilizes sensor data.
• The Internet of Things (IoT) enables devices to collect vast streams of data, and software tools enable businesses to analyze it.

Interactive Session: Organizations: Predictive Maintenance in the Oil and Gas Industry

• The interactive session discusses the importance of predictive maintenance in the oil and gas industry, problems it solves, IoT and Big Data analytics role, BP and Royal Dutch Shell's predictive maintenance applications, and other industry examples.

Location Analytics and Geographic Information Systems

• Location analytics uses location data for business insights.
• Mobile phones, sensors, and scanning devices collect location data and provide insights to local governments.
• Geographic Information Systems (GIS) ties location data to maps, helping calculate response times to disasters.

Interactive Session: Management: GIS Helps Land O'Lakes Manage Assets Strategically

• This interactive session details the importance of geographic location data for Land O'Lakes, categories of geographic information utilized, the improvement of operations and decision-making through GIS, and example decisions enhanced by GIS use.

Decisional Support for Operational and Middle Management

• Operational and middle management are responsible for monitoring business activities and using well-structured decision-support systems.
• Management Information Systems (MIS) are crucial for reporting and analysis and play an increasingly important role in online reporting.
• Exception reports highlight deviations from normal patterns.

Business Intelligence Users

• BI users are categorized into power users (20% of employees, including IT developers), super users, business analysts, and analytical modelers. Casual users (80%) include customers, operational employees, and so on.
• Users access and utilize various capabilities, like production reports, parameterized reports, dashboards/scorecards, ad hoc queries, and forecasts.

Support for Semi-structured Decisions

• Decision support systems (DSS) help in semi-structured decision making using analytical models.
• DSS allows "what-if" analysis and sensitivity analysis, backward sensitivity analysis, multidimensional analysis, and OLAP are all included in the toolkit. – Pivot tables are a common tool.

Sensitivity Analysis

• A decision-making technique analyzing change in variables, like the impact of varying a price on profit margins.
• Relevant variables (like total fixed costs, unit variable costs, average sale price, contribution margin, and break-even point) are used to construct a table, which displays the results of these changes.

A Pivot Table That Examines Customer Regional Distribution and Advertising Source

• Pivot tables allow complex statistical analysis of spreadsheet data to answer business questions. Data is categorized and analyzed, allowing summarization of trends or patterns that would otherwise be hard to discern in a more large format spread sheet.

Decision Support for Senior Management: Balanced Scorecard and Enterprise Performance Management Methods

• Executive support systems (ESS) focus senior management on crucial performance information.
• A balanced scorecard analyzes performance from four perspectives: financial, business processes, customer, and learning and growth.
• Key performance indicators (KPIs) measure these dimensions.
• A balanced scorecard framework demonstrates links between strategy and metrics and performance targets.

The Balanced Scorecard Framework

• Links corporate strategy with performance measurement and targets.
• Includes financial, customer, internal business processes, and learning/growth dimensions.

Decision Support for Senior Management (BPM)

• Business performance management (BPM) translates firm strategies into operational targets and uses KPIs to track progress.
• Data sources include internal enterprise applications and external financial databases.
• Drill-down capabilities provide deeper analysis.