INFO 3130- Chapter 12 – Flashcards
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Business value of improved decision making
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improving hundreds of thousands of "small" decisions adds up to large annual value for the business
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Types of decisions
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unstructured structured semi-structured
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Unstructured decision
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decision maker must provide judgement, evaluation, and insight to solve problem each decision is novel, important and non-routine, no procedure
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Structured decision
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repetitive and routine, involve definite procedure for handling so they do not have to be treated each time as new
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Semi-structured decision
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only part problem has clear-cut answer provided by accepted procedure
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Senior managers
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make many unstructured decisions
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Middle managers
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make more structured decisions but these may in unstructured components
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Operational managers/ rank-and-file employees
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make more structured decisions common, routine and numerous
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The 4 stages of decision making process
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1. Intelligence 2. Design 3. Choice 4. Implementation
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Intelligence
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discovering, identifying, and understanding the problems occurring in the organization
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Design
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identifying and exploring solutions to problems
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Choice
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choosing among solution alternatives
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Implementation
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making chosen alternative work and continuing to monitor how well solution is working
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Classical model of management: 5 functions
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1. planning 2. organizing 3. coordinating 4. deciding 5. controlling theoretical model, good systematic practice
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More contemporary behavioral models
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actual behavior of managers appears to be less systematic, more informal, less reflective, more reactive, and less well organized in classical model
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Managerial Roles
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expectations of the activities that managers should perform in an organization 3 categories: interpersonal informational decisional
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Interpersonal roles
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managers act as leaders, attempting to motivate, counsel, and support subordinates, act as liaisons between various organizational levels and teams
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Informational roles
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receiving and communicating information to those parties who need it
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Decisional roles
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initiating new kinds of ideas and activities, allocate resources, negotiate conflicts
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three main reasons why investments in information technology do not always produce positive results
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1. Information quality 2. management filters 3. organizational inertia and politics
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Information quality
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high-quality decisions require high-quality information
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Management filters
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managers have selective attention and have variety of biases that reject information that does not conform to prior conceptions
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Organizational inertia and politics
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strong forces within organizations resist making decisions calling for major changes
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High velocity automated decision making
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made possible through computer algorithms precisely defining steps for a highly structured design human taken out of decision (high-speed computer trading programs- 30 milliseconds)- responsible for Flash Crash requires safeguards to ensure proper operation and regulation
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What is an algorithm?
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is a sequence of unambiguous rules and/or instructions for solving a problem used to obtain a required output for any legitimate input(s) in a finite amount of time
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Business Intelligence in the Enterprise
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at the foundation of decision support systems are business intelligence and business analytic infrastructure that supplies the data and the analytic tools for supporting decision making
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Business Intelligence
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infrastructure for collecting, storing, analyzing data produced by business databases, data warehouses, data mart
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Business analytic
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tools and techniques for analyzing data OLAP, statistics, models, data mining
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Business Intelligence vendors
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create business intelligence and analytic purchased by firm leading vendors, SAP, Oracle, IBM, SAS Institute, Mircosoft
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Six elements in the business intelligence environment
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1. Data from the business environment 2. Business intelligence infrastructure 3. Business analytic tool set 4. Managerial users and methods 5. Delivery platform - MIS , DSS, ESS 6. User interface
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Business intelligence and analytic capabilities
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goal is to deliver accurate real-time information to decision makers
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Main functionalities of BI systems
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1.production reports 2. parameterized reports 3. Dashboards/scoreboards 4. Ad hoc query/search/report creation 5. drill down 6. forecasts, scenarios, models
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Business intelligence users
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80% are casual users relying on production reports senior executives- use monitoring functionalities middle managers and analysts- ad hoc analyst operational employees- prepackaged reports (sales forecast)
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Power Users: Producers
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IT developer Super users Business analysts Analytical modelers
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Causal Users: Consumers
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Customers Suppliers Operational employees senior managers managers staff business analyst
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Production reports
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most widely used output of BI suites common predefined, prepackaged reports: sales, service/call center, marketing, procurement and support, supply chain, financials, and human resources
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sales
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forecast sales; sales team performance
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service/call center
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customer sanctification; service cost
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marketing
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campaign effectiveness, loyalty and attrition
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procurement and support
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supplier performance
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supply chain
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backlog, fulfillment status
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financials
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general ledger, cash flow
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human resources
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employee productivity, compensation
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Predictive analytic
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used variety of data, techniques 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 score, predicting response to direct marketing campaign)
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Big Data Analytics
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massive datasets collected from social media, online and in-store customer data help create real-time, personalized shopping experience for major online retailers hunch.com- used by eBay: customized recommendations, database includes purchases data, social networks, taste graphs map users w/o product affinities
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Additional BI applications
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data visualization and visual analytics tools- help users see patterns and relationships that would be difficult to see in text lists: rich graphs, charts, dashboards, and maps geographic information systems (GSG)- ties location-related data to maps ex. for helping local govt. calculate response times to disasters
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Two main management strategies for developing BI and BA capabilities
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1. One-stop integrated solution 2. Multiple best-of-breed solution
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One-stop integrated solution
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hardware firm sells software that run optimally on their hardware makes firm dependent on single vendor- switching costs
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Multiple best-of-breed solution
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greater flexibility and independence potential difficulties in integration must deal with multiple vendors
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Operational and middle managers
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monitor day to day business performance make fairly structured decisions use MIS for routine production reports and exception reports
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"Super users" and business analysts use DSS for
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more sophisticated analysis and custom reports semi-structured decisions
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Decision support system
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use mathematical or analytical models allowed varies types of analysis: "what-if" analysis sensitivity analysis backward sensitivity analysis (goal seeking) multidimensional analysis / OLAP (pivot tables)
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Pivot table
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examines customer regional distribution and advertising source
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Decision-support for senior management
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help executives focus on important performance information
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Balanced scorecard methods
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measures outcomes of 4 dimensions: 1. Financial 2. Business processes 3. Customers 4. Learning and growth
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Financial elements
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cash flow return on investments return on capital employed financial results return on equity
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Business processes elements
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number of activities process execution time accident ratios resource efficiency equipment downtime
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Customer elements
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delivery performance quality performance customer loyalty customer satisfactions customer retention
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Learning and growth elements
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investment rate illness rate internal promotions % employee turnover gender ratio
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Business performance management (BPM)
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translates firms strategies into operational targets producers (differentiation, low-cost producer, scope operation) KPIs developed to measure progress toward targets
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Data for ESS
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internal data from enterprise applications external data such as financial market databases drill-down capabilities
