Mgt Ch 3

Front 1

Benchmarking (pg 104-105)

Back 1

– generating alternatives. Organizational members trying to solve a problem go to visit other organizations thought to have successfully solved the problem or a similar one. During their visit problem solvers generate ideas that might work in their organization. Benchmarking seems to be most effective when managers visit organizations that specialize in the particular problem area regardless of the industry.

Front 2

Black or White fallacy (pg 96)

Back 2

people generally tend to framework problems into “either-or” terms. Which means are choices are clear and limited to two when in reality there may be many other choices.

Front 3

Availability bias

Back 3

clouds our judgement because things more readily available to us are likely to be interpreted as more frequent or important. For example most people think homicide compared to suicides cause more death in a year but its actually the opposite with a ratio of suicide deaths 2:1 of homicide deaths. This is because there are more stories in the news about homicide. We often choose solutions we’ve heard about.

Front 4

Self –serving bias

Back 4

attributing successes to internal causes and personal failures to external causes. Example you Ace a test and attribute that success to being smart, studied hard, good study strategy but when you fail you blame the tricky words, dumb professor sniffling of students because of cold. This helps us maintain a a comfortable postitive image about ourselves that is often built on false information.

Front 5

Pareto graphing or 80/20 rule

Back 5

helps identify the most critical components of a problem. 80% of the value to be gained is likely to be accomplished by solving 20% of the problem. Some things are just more important to others. If you could fix the one or two major problem areas, youd be likely to eradicate over ¾ of the problem. Using this principle can help you quickly isolate where youd like to spend your problem solving efforts.

Front 6

Bounded rationality

Back 6

Limiting decision making to simplified solutions that do not represent the full complexity of the problem. Leads to SATISFICING or determining the most acceptable soulution to a problem rather than an optimal one.

Front 7

Problem solving framework - PADIL (pg 91, 97, 98)-

Back 7

Problems, alternatives, decide, implement, learn. There are several ways in which people solve the wrong problem precisely: Picking the wrong stakeholders, framing the problem too narrowly, failurte to think systematically, failure to find the facts. Stakeholder is literally anyone who has a stake/involvement in the problem or solution

Front 8

Trial and Error (pg 89)-

Back 8

calibration process that avoids biases and make better decisions for tomorrow.

Front 9

Confidence estimates(89)-

Back 9

a way to avoid bias by estimating confidence beliefs held by ourselves and others. Do not rely on single point estimates, its good to get a range of confidence estimatesl

Front 10

Escalation of Commitment -

Back 10

The phenomenon where people increase their investment in a decision despite new evidence suggesting that the decision was probably wrong. Such investment may include money (known informally as "throwing good money after bad"), time, or other resources. Why we do this = 1. We don’t want to admit that our solution was a wrong one so we stay the course. 2. We don’t want to appear inconsistent or irrational, so we continue to hope for the best even though data simply don’t justify such a response. 3 organizations, not continuing could be seen as giving up rather than fighting onward and nobody likes a quitter.

Front 11

Overconfidence bias –

Back 11

leads us to believe that we possess some unique trait or ability that allows us to defy odds, whereas others simply don’t have such a trait or ability. Surveys resulted in 80 percent of students believed they were in the top 30 percent of safe drivers. We greatly overestimate the true probability of success.

Front 12

Confirmation Bias –

Back 12

represents peoples tendancy to collect evidence that supports rather than negates our intuition before deciding. When students found a rule that seemed to work they were done searching. In solving problems one of the most insidious traps is gathering data that seek to confirm our ideas and exclude data that might disconfirm them.

Front 13

Anchoring and Adjusting

Back 13

research shows we often provide estimates based on the initial starting estimate. Even when people are told the intitial estimate is random, their adjusted estimates remain close to the intial estimate or ANCHOR. Different starting points lead to different end results. PG 86.

Front 14

Hasty Generalization fallacy – representitive bias

Back 14

– people often draw wrong general conclusions from specific cases because they do not realize their specific example is not necessarily true in all or even most cases. Example one guy argues about motorcycle helmet laws complaining that after 25 years of riding with no helmet he has had no accidents. This may be true but doesn’t mean that it is safe to wear no helmet.

Front 15

“Gamblers Fallacy”(pg 84)- representitive bias

Back 15

people truly believe that each coin flip or pull of the slot machine is somehow connected to previous actions. The coin, the slot machine have no memory.

Front 16

Fundamental Attribution error

Back 16

process of attributing causes to events – explaining why things occurred. Over attributing behavior to internal(personality, ethniticty, gender, etc) rather than external (weather, lighting, traffic, etc) causes.

Front 17

Ladder of inference(pg 82,83)

Back 17

– Inference is drawing a conclusion about something we don’t know based on things we do know. Bottom of ladder = we observe or experience what people say and do. This info is objective in the sense that the behavior doesn’t change from person to person. For example you would ALL observe that someone is late 45 minutes if it happened. TOO LONG READ PAGE 82 – 83