Chapter 12: Enhancing Decision Making

Question 1

Business value of improved DM

Answer 1

Improving hundreds of thousands of “small” decisions adds up to large annual value for the
business

Question 2

Types of decisions

Answer 2

• Unstructured: Decision maker must provide judgment, evaluation, and insight to solve problem
• Structured: Repetitive and routine; involve definite procedure for handling so they do not have to be treated each time as new
• Semistructured: Only part of problem has clear-cut answer provided by accepted procedure

Question 3

Decisions on different management levels

Answer 3

• Senior managers: many unstructured decisions
  –> Should we enter a new market?
• Middle managers: more structured decisions but these may include unstructured components
  –> Why is order fulfillment report showing decline in Minneapolis?
• Operational managers, rank & file employees: more structured decisions
  –> Does customer meet criteria for credit?

Question 4

Four stages of the DM process

Answer 4

1. Intelligence: Discovering, identifying & understanding the problems occurring in the organization
2. Design: Identifying & exploring solutions to the problem
3. Choice: Choosing among solution alternatives
4. Implementation: Making the chosen alternative work & continuing to monitor how well solution is working

Question 5

How are DM & IS interrelated?

Answer 5

• IS can only assist in some of the roles played by managers
• Classical model of management: Planning, organizing, coordinating, deciding & controlling
• More contemporary behavioral models: Actual behavior of managers appears to be less systematic, more informal, less reflective, more
  reactive & less well organized than in classical model

Question 6

Mintzberg’s 10 managerial roles

Answer 6

Interpersonal roles:
1. Figurehead
2. Leader
3. Liaison
- Informational roles:
4. Nerve center
5. Disseminator
6. Spokesperson
- Decisional roles:
7. Entrepreneur
8. Disturbance handler
9. Resource allocator
10. Negotiator

Question 7

What prevents investments in IT from having a positive effect?

Answer 7

• Poor information quality
• Management filters: selective attention & variety of biases that reject information that does not
  conform to prior conceptions
• Organizational inertia & politics: Strong forces within organizations resist making decisions calling for major change

Question 8

What is high-velocity automated DM?

Answer 8

• Made possible through computer algorithms precisely defining steps for a highly structured decision (humans taken out of decision)
• Safeguards required
• example: High-speed computer trading programs that execut trades in 30 ms (“Flash Crash” 2010)

Question 9

How are business intelligence & business analytics connected?

Answer 9

• Business intelligence & analytics require a strong database foundation, a set of analytic tools & an involved management team that can ask intelligent questions & analyze data
• BI: Infrastructure for collecting, storing, analyzing data produced by business (databases, data warehouses, data marts)
• BA: Tools & techniques for analyzing data (OLAP, statistics, models, data mining)
• Business intelligence vendors BI & BA purchased by firms

Question 10

Six elements in the business intelligence environment

Answer 10

• Data from the business environment
• Business intelligence infrastructure
• Business analytics toolset
• Managerial users & methods
• Delivery platform: MIS, DSS, ESS
• User interface (sata visualization tools)

Question 11

Main analytic functionalities of BI systems & goal

Answer 11

• Production reports
• Parameterized reports
• Dashboards/scorecards
• Ad hoc query/search/report creation
• Drilldown
• Forecasts, scenarios, models
  –> Goal: deliver accurate real-time information to decision makers
  –> most widely used output: production reports (predefined & prepackaged)

Question 12

Types of business analytics

Answer 12

• predictive analytics
• big data analytics
• operational intelligence & analytics
• location analytics

Question 13

Define predictive analytics

Answer 13

• use a variety of data & techniques to predict future trends & behavior patterns (Statistical analysis, data mining, historical data, assumptions)
• incorporated into numerous BI applications for sales, marketing, finance, fraud detection, health care (credit scoring, predicting responses to direct marketing campaigns)

Question 14

Define big data analytics

Answer 14

• Big data: Massive datasets collected from social media, online and in-store customer data etc.
• Help create real-time, personalized shopping experiences for major online retailers
• Smart cities: public records, sensors (location data from smartphones), ability to evaluate effect of one service change on system

Question 15

Define operational intelligence & analytics

Answer 15

• operational intelligence: Business activity monitoring
• collection & use of data generated by sensors
• IoT: creating huge streams of data from web activities, sensors & other monitoring devices
• software for operational intelligence & analytics enable companies to analyze their big data

Question 16

Define location analytics

Answer 16

• ability to gain business insight from the location (geographic) component of data (mobile phones, sensors, scanning devices, map data)
• map data based on geographic information systems (GIS), which ties location-related data to maps (e.g. calculate response times to disasters)

Question 17

Define two types of BI users

Answer 17

• power users/ producers (20% of employees): IT developers, super users, business analysts, analytical modelers
• casual users/ consumers (80% of employees): customers/ suppliers, operational employees, (senior) managers, staff

Question 18

Decision support systems (DSS)

Answer 18

DSS give support for semistructured decisions through the use mathematical or analytical models to conduct different types of analysis:
- “What-if” analysis
- Sensitivity analysis
- Backward sensitivity analysis
- Multidimensional analysis / OLAP
–> For example: pivot tables

Question 19

Executive support system (ESS) & balanced scorecard method

Answer 19

• decision support for senior management, helping to focus on important performance information
• Balanced scorecard method operationalizes strategic objectives on 4 dimensions: Financial, BPs, customer, learning & growth
• KPIs measure each dimension
• data for ESS: internal data from enterprise applications, external data such as financial market databases, drill-down capabilities (moving from a more general view of the data to a more specific one)

Question 20

Business performance management (BPM)

Answer 20

• decision support for senior management
• translating firm’s strategies (e.g., differentiation, low-cost producer, scope of operation) into operational targets –> KPI development

Question 21

Group decision support systems (GDSS)

Answer 21

• interactive system to facilitate solution of unstructured problems by group
• uses specialized tools such as virtual collaboration rooms and software to collect, rank, edit participant ideas & responses
  Functions:
• enables increasing meeting size & increasing productivity
• promotes collaborative atmosphere, anonymity
• uses structured methods to organize and evaluate ideas
  Examples:
• Cisco’s Collaboration Meeting Rooms Hybrid (CMR)
• Skype for Business