Chapter 12

• business analytics: the process of developing actionable decisions or recommendations for actions based on insights generated from historical data
• business intelligence: a broad category of application, technologies, and processes for gathering, storing, accessing, and analyzing data to help business users make better decisions
• management: a process by which an organization achieves its goals through the use of resources (people, money, materials, and information)
• basic managerial roles:

  1. interpersonal roles - figurehead, leader, liaison
  2. informational roles- monitor, disseminator, spokesperson, analyzer
  3. decisional roles: entrepreneur, disturbance handler, resource allocator, negotiator
• decision: a choice among two or more alternatives that individuals and groups make
• decision making process:

  1. intelligence phase - managers examine a situation and then identify and define the problem or opportunity
  2. design phase - construct a model for addressing the situation
  3. choice phase- selecting a solution or course of action that seems best suited to resolve the problem
• decision making is difficult because:

  • the number of alternatives is constantly increasing
  • they need to be made under time pressure
  • they are becoming more complex and require a sophisticated analysis
  • bringing all needed information together quickly can be expensive
• problem structure: the way in which the problem is structured, how it is divided into parts
• structured decisions:

  • routine and repetitive problems for which standard solutions exist
  • these decisions are candidates for decision automation
• unstructured decisions:

  • intended to deal with complex problems for which there are no cut and dried solutions
  • no standardized procedure so human intuition and judgement play an important role
• semistructured decisions:

  • only some of the decision process phases are structured
  • require a combination of standard solution procedures and individual judgement
• managerial decisions fall into three categories:

  1. operational control - executing specific tasks efficiently and effectively
  2. management control: acquiring and using resources efficiently in accomplishing organizational goals
  3. strategic planning: long-range goals and policies for growth ans resource allocation
• targets of business analytics:

  • the development of one or a few related analytics applications
  • the development of infrastructure to support enterprise-wide analytics
  • support for organizational transformation
• descriptive analytics: summarizes what has happened in the past and enables decision makers to learn from past behaviours

  • generates information such as total stock in inventory, average dollars spent per cutomer
• online analytical processing (OLAP): involves slicing and dicing the data that are stored in a dimensional format, drilling down the data into greater detail and rolling up the data to greater summarization
• data mining: the process of searching for valuable business information in a large database, data warehouse, or data mart. data mining can perform two basic operations

  1. identifying previously unknown patterns
  2. predicting trends and behaviours
• affinity analysis: a data mining application that discovers co-occurrence relationships among activities performed by specific individuals or groups
• decision support systems: combine models and data to analyze semistructured problems and some unstructured problems that involve extensive user involvement

  • these systems enable business managers and analysts to access data interactively, to manipulate these data, and to conduct appropriate analyses.
• sensitivity analysis examines how sensitive an output is to any change in an input while keeping other inputs constant. it enables the system to adapt to changing conditions and to the varying requirements of different decision making situations
• what-if analysis attempts to predict the impact of changes in the assumptions on the proposed solution
• goal-seeking analysis represents a backward solution approach. it attempts to calculate the value of the inputs necessary to achieve a desired level of output
• predictive analytics: examines recent and historical data to detect patterns and predict future outcomes and trends. it provides estimates about the likelihood of a future outcome
• targeted marketing relies on predictive information
• assumptions about predictive analytics:

  1. there must be at least 30 data points
  2. the relationship between the independent and dependent variables must be linear
  3. data should be normally distributed
• prescriptive analytics: recommending one or more courses of action and identifying the likely outcome of each decision. it does not predict one possible future, it suggests multiple future outcomes based on the decision maker's actions. attempts to quantify the effect of future decisions in order to advise on possible outcomes before the decisions are actually made
• descriptive analytics asks "where are we today?"
• predictive analytics asks "with our current trajectory, where will we be tomorrow?"
• prescriptive analytics asks "where should we be tomorrow?"
• dashboards: provide easy access to timely information and direct access to management reports
• drill down: the ability to go to details, at several levels
• critical success factors: the factors most critical for the success of a business
• key performance indicators: the specific measures of critical success factors
• status access: the latest data available on a key performance indicator
• trend analysis: short, medium and long term trends of key performance indicators, which are projected using forecasting methods
• exception reporting: reports highlight deviations larger than defined thresholds
• geocoding: enables users to generate information for planning, problem solving, and decision making
• geographic information system: a computer-based system for capturing, integrating, manipulating, and displaying data using digitized maps
• stitch fix

  • traditional brick and mortar stores have serious problems understanding customers
  • personal styling service
  • personalization and algorithm are key concepts
  • likelihood that customer will like piece of clothing
  • human stylists finalize the clothing selection
  • challenge managing inventory
  • subscription shopping service
• insight4care

  • physicians collect an enormous amount of data on patients
  • patient dashboards
  • importance of measuring what matters and not measuring everything that can be measured
  • importance of measuring patients who are due or late for cancer screening
• LAPD use of predictive policing

  • analyzes different data sources
  • LAPD deployed to identify and deter people likely to commit crimes
  • chronic offender bulliten
  • explored buying private data
  • civil rights activists are concerned
  • algorithms reinforce systemic biases
  • convictions based on predictive policing are problematicc