Decision Making: Types, Requirements & Process

Types of Decisions

• Decision-making is categorized into unstructured, structured, and semi-structured types.
• Unstructured decisions require judgment, evaluation, and insight from the decision-maker to solve the problem
• Structured decisions are repetitive and routine, handled with definite procedures, ensuring they don't need to be treated as new each time.
• Semi-structured decisions have only a partially clear-cut answer, provided by the accepted procedure.

Information Requirements by Management Group

• Senior Management deals with unstructured decisions like market entry/exit and long-term goals.
• Middle Management handles semi-structured decisions such as marketing plans and website design.
• Operational Management focuses on structured decisions like overtime eligibility and inventory restocking.

The Decision-Making Process

• Intelligence involves discovering and understanding organizational problems.
• Design focuses on identifying and exploring solutions to the problem.
• Choice involves selecting among the possible solutions.
• Implementation centers on making the chosen solution work and monitoring its effectiveness.

Managerial Roles

• The classical model of management involves planning, organizing, coordinating, deciding, and controlling.
• Contemporary behavioral models suggest managers are less systematic, more informal, reflective, reactive, and less organized.

Mintzberg's Managerial Roles

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

Real-World Decision Making Challenges

• IT investments don't always guarantee positive outcomes.
• High-quality decisions require high-quality information.
• Management filters, influenced by selective attention and biases, can reject information not aligned with prior beliefs.
• Organizational inertia and politics can create strong resistance to decisions that call for significant change.

High-Velocity Automated Decision Making

• Computer algorithms precisely define steps for structured decisions.
• This removes humans from the immediate decision-making loop.
• Safeguards are necessary to ensure proper operation and regulation.
• High-speed computer trading programs are examples.

Business Intelligence (BI)

• Business intelligence involves infrastructure for collecting, storing, and analyzing business data, including databases, data warehouses, data marts, Hadoop, and analytic platforms.
• Business analytics provides the tools and techniques, such as OLAP, statistics, models, and data mining, for analyzing data.
• Business intelligence vendors create analytics purchased by firms.

The Business Intelligence Environment

• The six elements include: data from the business environment, BI infrastructure, business analytics toolset, managerial users and methods, delivery platform (MIS, DSS, ESS), and user interface.
• Data visualization tools are key.

BI and Analytics for Decision Support

• Raw data comes from databases, data warehouses, data marts, and analytic platforms.
• Data is analyzed using models, data mining, OLAP, and reporting tools.
• Business strategy is supported via performance management, balanced scorecards, and forecasts.

BI & Analytics Capabilities

• Production reports are standard, pre-defined reports.
• Parameterized reports allow customization with user-defined parameters.
• Dashboards/scorecards provide visual summaries of key performance indicators.
• Ad hoc query/search tools enable users to create custom reports on demand.
• Drill-down capabilities allow users to explore data in more detail.
• Forecasts, scenarios, and models support predictive analysis.

Examples of Business Intelligence Production Reports

• Sales analyzes forecast sales, team performance, cross-selling, and sales cycle times.
• Service/call centers focus on customer satisfaction, costs, resolution rates, and churn rates.
• Marketing measures campaign effectiveness, loyalty, attrition, and market basket analysis.
• Procurement and support tracks direct/indirect spending, off-contract purchases, and supplier performance.
• The supply chain considers backlog, fulfillment status, order cycle time, and bill of materials analysis.
• Financial analysis includes general ledger, accounts receivable/payable, cash flow, and profitability.
• Production reports for human resources include productivity, compensation, workforce demographics, and retention.

Predictive Analytics Overview

• Predictive analytics uses various data and techniques to predict future trends and behavior patterns through:
  • Statistical analysis
  • Data mining
  • Historical data
  • Assumptions
• Predictive analytics is incorporated in various BI applications
  • Used in credit scoring
  • Used in predicting responses to direct marketing campaigns

Big Data Analytics

• Big data includes massive datasets collected from social media, online activity, and customer data.
• This analysis helps create real-time, personalized shopping experiences for online retailers.
• Applications include smart cities.

Operational Intelligence

• Operational intelligence is about business activity monitoring.
• It involves the collection and use of data from sensors and the Internet of Things (IoT), which generates huge streams of data.
• Specialized software enables companies to analyze this big data for operational insights.

Location Analytics and GIS

• Combines location analytics with GIS to gain business insights from geographic data.
• Utilizes mobile phones, sensors, scanning devices, and map data.
• It helps calculate response times to disasters.

Business Intelligence Users

• Power Users / Producers: 20% of employees, including IT developers, super users, business analysts, and analytical modelers who create production reports, parameterized reports, dashboards, ad hoc queries, forecasts and statistical models.
• Casual Users / Consumers: 80% are customers, suppliers, operational employees, senior managers, or staff who are the recipients.

Decisional Support for Operational and Middle Management

• Managers are charged with monitoring key aspects of the business where decisions are fairly structured.
• Middle managers typically use Management Information Systems (MIS) to creates exception reports.

Support for Semi-Structured Decisions

• Decision-support systems support semi-structured decisions through use of mathematical or analytical models.
• This involves different types of analysis to allow for "what-if", sensitivity, backward sensitivity, and multidimensional analysis / OLAP.

Executive Support Systems (ESS)

• ESS helps executives focus on important performance information using both internal data from enterprise applications and external data like financial market databases.
• The balanced scorecard method measures outcomes on four dimensions: financial, business process, customer, and learning/growth.
• Key Performance Indicators measure each dimension.

Business Performance Management (BPM)

• BPM translates the firm's strategies into operational targets and KPIs.
• Measures progress toward targets.