Business Decision Making Process

Decision Making

• Managers make strategic, tactical, or operational decisions every day
• Strategic decisions are high-level and deal with the organization's overall direction and future goals
• Tactical decisions focus on achieving the strategic goals and objectives, typically made by middle-level management
• Operational decisions concern the day-to-day running of the organization, made by operations managers

Decision Making Process

• Identifying and defining the problem is crucial
• Criteria for evaluating alternative solutions must be established
• A set of alternative solutions need to be determined and evaluated
• Selection of the best alternative is the final step

Common Approaches to Decision Making

• Tradition, intuition, rules of thumb, and using the relevant data are common methods

Business Analytics Defined

• The significant challenge in decision making is overcoming uncertainty and the vast number of alternatives
• Business analytics aims to transform data into insights for making better decisions
• It promotes data-driven or fact-based decision making, which is perceived as more objective

Benefits of Business Analytics for Decision Making

• Generates insights from data
• Improves forecasting accuracy for planning purposes
• Quantifies risk more effectively
• Provides better alternatives through analysis and optimization

Categorization of Analytical Methods

• Descriptive Analytics describes what has happened in the past, using techniques like data queries, reports, and descriptive statistics
  • Data mining is a crucial part of descriptive analytics, using techniques like cluster analysis and sentiment analysis to understand patterns and relationships in large datasets
• Predictive Analytics uses models based on past data to predict the future and understand the impact of variables
  • Common techniques include linear regression, time series analysis, and simulation
• Prescriptive Analytics indicates the best course of action to take, guiding decision-makers
  • Optimization models determine the best decision within constraints
    • Examples include portfolio models in finance, supply network design models in operations, and price-markdown models in retail
  • Simulation Optimization combines probability, statistics, and optimization techniques to find good decisions in complex and uncertain situations
  • Decision Analysis helps develop optimal strategies faced with various decision alternatives and uncertain future events

Big Data

• Big data refers to datasets too large or complex for standard data-processing techniques and typical software
• IBM defines big data using the 4Vs: Volume, Velocity, Variety, and Veracity

Business Analytics in Practice

• Financial Analytics uses models to forecast financial performance, assess investment risks, construct financial instruments, and optimize investment portfolios, often employing simulation
• Human Resource Analytics, a newer field, aims to ensure the organization has the right mix of skills, recruits top talent, retains employees, and achieves diversity goals
• Marketing Analytics uses data from scanner data and social media to understand consumer behavior for better advertising, pricing, demand forecasting, product management, and customer satisfaction and loyalty
• Healthcare Analytics employs descriptive, predictive, and prescriptive analytics to improve patient, staff, and facility scheduling, patient flow, purchasing, and inventory control
• Supply-Chain Analytics focuses on efficient delivery of goods, utilizing analytics for optimized sorting, vehicle and staff scheduling, vehicle routing, inventory and processing control, and supply chain resilience
• Web Analytics analyzes online activity like website and social media visits, using descriptive and advanced analytics to configure websites, position ads, and utilize social networks for product and service promotion