Principles of Management_Chapter 7
What makes it hard to be evidence based?
(1) There's too much evidence. (2) There's not enough good evidence. (3) The evidence doesn't quite apply. (4) People are trying to mislead you. (5) You are trying to mislead yourself. (6) The side effects outweigh the cure. (7) Stories are more persuasive, anyway.
Can you name the 10 common decision-making biases?
(1) availability, The Availability Bias: Using Only the Information Available (2) representativeness, The Representativeness Bias: Faulty Generalizing from a Small Sample or a Single Event (3) confirmation, The Confirmation Bias: Seeking Information to Support Your Point of View (4) sunk cost, The Sunk-Cost Bias: Money Already Spent Seems to Justify Continuing (5) anchoring and adjustment, The Anchoring and Adjustment Bias: Being Influenced by an Initial Figure (6) overconfidence, The Overconfidence Bias: Blind to Our Own Blindness (7) hindsight, The Hindsight Bias: The I-Knew-It-All-Along Effect (8) framing, The Framing Bias: Shaping the Way a Problem Is Presented (9) escalation of commitment, The Escalation of Commitment Bias: Feeling Overly Invested in a Decision (10) categorical thinking, The Categorical Thinking Bias: Sorting Information into Buckets
Group Problem-Solving Techniques
(1) brainstorming (2) devil's advocacy (3) the dialectic method (4) post-mortems
Preventing Groupthink
- Allow criticism - Allow other perspectives - Reflect before entering a group discussion
Big Data and How It's Used
- Meeting Customer Needs - Improving Human Resource Management Practices - Enhancing Production Efficiency - Advancing Health and Medicine - Aiding Public Policy - Using Big Data Up and Down the Hierarchy
What are some symptoms of groupthink?
- Sense of invulnerability - Rationalization - Dominant members - Illusion of unanimity and peer pressure - "The wisdom of crowds."
four characteristics of groups
- They are less efficient - Their size affects decision quality - They may be too confident - Knowledge counts
Seven Implementation Principles of Evidence-Based Management
- Treat your organization as an unfinished prototype - No brag, just facts - See yourself and your organization as outsiders do - Evidence-based management is not just for senior executives - Like everything else, you still need to sell it - If all else fails, slow the spread of bad practice - The best diagnostic question: What happens when people fail?
lower managerial level use of big data
- analyze data - project management - safeguard date - present data to middle management
middle managerial level use of big data
- decide what data is necessary - project management - presenting data to executives
upper managerial level use of big data
- making data-driven decisions and strategizing - project management - influencing others to support data-driven decisions
Decision
A choice made from among available alternatives
Groupthink
A cohesive group's blind unwillingness to consider alternatives. This occurs when group members strive for agreement among themselves for the sake of unanimity and avoid accurately assessing the decision situation
Project post-mortem
A review of recent decisions in order to identify possible future improvements Process improvement Boosting team cohesiveness Closure Improving morale
Rational model of decision making
Also called the classical model; the style of decision making that explains how managers should make decisions; it assumes that managers will make logical decisions that are the optimal means of furthering the organization's best interests
Machine learning
An extension of predictive analytics, occurs when systems or algorithms automatically improve themselves based on data patterns, experiences, and observations
Diagnosis
Analyzing the underlying causes
What are some of AI's benefits and drawbacks?
Benefits: - product enhancement - internal process optimization - effective decision making - external process optimization - enhanced worker creativity - new product development - knowledge capture - labor cost reduction - new market development Drawbacks: - AI implementation - Data issues - Cost - Human replacement - dangers it can pose to society
overconfidence bias
Bias in which people's subjective confidence in their decision making is greater than their objective accuracy
Confirmation bias
Biased way of thinking in which people seek information to support their point of view and discount data that do not support it
Predictive analytics
Category of data analysis that makes predictions about future outcomes based on historical data and analytics techniques
Autonomous devices
Collect data from situations to make calculations, define probabilities, and make reason-based decisions according to programmed goals
Problems
Difficulties that inhibit the achievement of goals
Hubris
Extreme and inflated sense of pride, certainty, and confidence
Consensus
General agreement; group solidarity Do's: Use active listening skills. Involve as many members as possible. Seek out the reasons behind arguments. Dig for the facts Don'ts: Avoid log rolling and horse trading ("I'll support your pet project if you'll support mine"). Avoid making an agreement simply to keep relations amicable and not rock the boat. Finally, don't try to achieve consensus by putting questions to a vote; this will only split the group into winners and losers, perhaps creating bad feelings among the latter.
Decision trees
Graph of decisions and their possible consequences, used to create a plan to reach a goal
Ethics officers
Individuals trained in matters of ethics in the workplace, particularly about resolving ethical dilemmas
What are four ethical questions a manager should ask when evaluating a proposed action to make a decision?
Is the proposed action legal? If "yes," does the proposed action maximize shareholder value? If "yes," is the proposed action ethical? If "no," would it be ethical not to take the proposed action?
Intuition
Making a choice without the use of conscious thought or logical inference
Sham participation
Occurs when powerless, but useful individuals are selected by leaders to rubber stamp decisions and work hard to implement them
Bounded rationality
One type of nonrational decision making; the ability of decision makers to be rational is limited by numerous constraints complexity, time, money, and other resources, and their cognitive capacity, values, skills, habits, and unconscious reflexes, imperfect information, information overload, different priorities, conflicting goals.
Satisficing model
One type of nonrational decision-making model; managers seek alternatives until they find one that is satisfactory, not optimal
Data analytics
Process of examining data sets in order to draw conclusions about the information they contain
What are the steps in rational decision making?
Stage 1 is identifying the problem or opportunity. A problem is a difficulty that inhibits the achievement of goals. An opportunity is a situation that presents possibilities for exceeding existing goals. This is a matter of diagnosis—analyzing the underlying causes. Stage 2 is thinking up alternative solutions. Stage 3 is evaluating the alternatives and selecting a solution. Alternatives should be evaluated according to cost, quality, ethics, feasibility, and effectiveness. Stage 4 is implementing and evaluating the solution chosen. Plan carefully, Be sensitive to those affected. Evaluate: Not working? -> Give it more time, Change it slightly, Try another alternative, Start over
Big data
Stores of data so vast that conventional database management systems cannot handle them
Heuristics
Strategies that simplify the process of making decisions
Decision-making styles
Styles that reflect the combination of how an individual perceives and responds to information
electronic brainstorming
Technique in which members of a group come together over a computer network to generate ideas and alternatives
Brainstorming
Technique used to help groups generate multiple ideas and alternatives for solving problems; individuals in a group meet and review a problem to be solved, then silently generate ideas, which are collected and later analyzed
Categorical thinking bias
Tendency of decision makers to classify people or information based on observed or inferred characteristics
Artificial intelligence (AI)
The ability of a computer system to perform tasks that normally require human intelligence
Goal displacement
The primary goal is subsumed to a secondary goal
Decision making
The process of identifying and choosing alternative courses of action
problems with the rational model
The rational model is prescriptive, describing how managers ought to make decisions. It doesn't describe how managers actually make decisions. - Complete information, no uncertainty - Logical, unemotional analysis - Best decision for the organization
framing bias
The tendency of decision makers to be influenced by the way a situation or problem is presented to them
Hindsight bias
The tendency of people to view events as being more predictable than they really are
Representative bias
The tendency to generalize from a small sample or a single event
Anchoring and adjustment bias
The tendency to make decisions based on an initial figure
Availability bias
The use of information readily available from memory to make judgments
Sunk-cost bias
Way of thinking in which managers add up all the money already spent on a project and conclude it is too costly to simply abandon it; also called the sunk-cost fallacy
What Is Your Decision-Making Style?
What is your dominant decision-making style? What are the pros and cons of your style? What might you say to a recruiter during a job interview to demonstrate your awareness regarding your decision-making style?
escalation of commitment bias
When decision makers increase their commitment to a project despite negative information about it
Robotic process automation (RPA)
When robots act like a human inputing and extracting information
The Dialectic Method
attempted to identify a truth, called thesis, by exploring opposite positions, called antitheses.
Describe the four general decision-making styles.
directive (action-oriented decision makers who focus on facts) analytical (careful decision makers who like lots of information and alternative choices) conceptual (decision makers who rely on intuition and have a long-term perspective) behavioral (the most people-oriented decision makers).
Minority dissent
dissent that occurs when a minority in a group publicly opposes the beliefs, attitudes, ideas, procedures, or policies assumed by the majority of the group
Nonrational models of decision making
explain how managers make decisions; they assume that decision making is nearly always uncertain and risky, making it difficult for managers to make optimal decisions
What are two models of nonrational decision making?
explain how managers make decisions; they assume that decision making is nearly always uncertain and risky, making it difficult for managers to make optimal decisions. The nonrational models are descriptive rather than prescriptive: They describe how managers actually make decisions rather than how they should. 1. Bounded Rationality, Hubris, and the Satisficing Model: "Satisfactory Is Good Enough" 2. The Intuition Model: "It Just Feels Right"
What is big data?
includes not only data in corporate databases, but also web-browsing data trails, social network communications, sensor data, and surveillance data.
What are the advantages and disadvantages of group decision making?
possible advantages: (1) a greater pool of knowledge, (2) different perspectives, (3) intellectual stimulation, (4) better understanding of the reasoning behind the decision, and (5) deeper commitment to the decision. disadvantages: (1) a few people may dominate or intimidate; (2) it will produce groupthink, when group members strive for agreement among themselves for the sake of unanimity and so avoid accurately assessing the decision situation; (3) satisficing; and (4) goal displacement, when the primary goal is subsumed to a secondary goal.
opportunities
situations that present possibilities for exceeding existing goals
What types of AI exist?
supports three important business needs: automating business processes: automation of digital and physical tasks, achieved through robotic process automation (RPA) analyzing data: detect patterns in vast volumes of data and interpret their meaning, Predictive analytics, Machine learning engaging customers and employees.
Devil's Advocacy
uncover and air all possible objections to the person's canonization