PRECONDITIONS FOR DECISION MAKING
IS THERE A PERFORMANCE GAP?
Assumes there are standards to judge
Assumes there is monitoring and feedback
IS THE DECISION MAKER AWARE OF THIS GAP?
Consciousness of the gap
Significance to the organization
DOES THE DECISION MAKER HAVE THE RESOURCES TO ACT?
Knowledge and ability to fix the problem
Budgets, personnel, power
IS THE DECISION MAKER MOTIVATED TO ACT ON THE GAP?
Rewards and risks weighed
Risk-averse or risk-seeker?
TYPES OF DECISIONS
ROUTINE
COMMON PROBLEMS WITH WELL-DEFINED SOLUTIONS
:
Rules, procedures, computer software packages
There is an obvious “best” solution or alternative
ADAPTIVE
A COMBINATION OF MODERATELY UNUSUAL AND ONLY
PARTIALLY-KNOWN PROBLEMS AND ALTERNATIVES
Incremental changes or modifications of past decisions and practices
Selecting from a set of known alternatives, but unsure of the outcomes
INNOVATIVE
UNUSUAL OR AMBIGUOUS PROBLEMS WHICH REQUIRE
UNIQUE OR CREATIVE ALTERNATIVE SOLUTIONS
Emphasizes radical change, innovation, brainstorming
Not sure what the alternatives are, not sure whether any will work
RATIONAL DECISION MAKING MODEL
DEFINE AND DIAGNOSE THE PROBLEMS
SEPARATE SYMPTOMS FROM CAUSES
CLARIFY THE OBJECTIVES TO BE ACHIEVED
IDENTIFY CRITERIA TO BE USED
SEARCH FOR ALTERNATIVE SOLUTIONS
WE MUST HAVE OPTIONS FOR EACH PROBLEM
COMPARE AND EVALUATE ALTERNATIVES
EXPECTED RESULTS, COSTS, POTENTIAL SIDE EFFECTS?
RECOMMENDED SOLUTIONS
JUSTIFY WHY THIS CHOICE…WHY NOT THE OTHERS?
IMPLEMENTATION
STEPS AND PROCEDURES TO FOLLOW TO ENSURE SUCCESS
MONITORING AND CONTROL
ARE THINGS GOING AS EXPECTED? IS FURTHER INTERVENTION NEEDED?
RATIONAL MODEL ASSUMPTIONS
PROBLEM CLARITY
The problem is clear and unambiguous. The decision maker is assumed to
have complete information regarding the decision situation.
KNOWN OPTIONS
The decision maker can identify all the relevant criteria and can list all the
viable alternatives. Furthermore, the decision maker is aware of all the
possible consequences of each alternative.
CLEAR PREFERENCES
The criteria and alternatives can be ranked and weighted to reflect their
importance.
CONSTANT PREFERENCES
The decision criteria are constant and the weights assigned are stable.
NO TIME OR COST CONSTRAINTS
The decision maker can obtain full information about criteria and alternatives
because it is assumed there are no time or cost constraints.
MAXIMUM PAYOFF
The rational decision maker will choose the alternative that yields the highest
perceived value.
BOUNDED RATIONALITY
SIMON (57)
BASED ON A LIMITED PERSPECTIVE
SOME IMPORTANT CRITERIA ARE NOT IDENTIFIED
NOT ALL ALTERNATIVES ARE CONSIDERED
SEQUENTIAL EVALUATION OF ALTERNATIVES
CONSIDER OPTIONS ONE AT A TIME
MAY ONLY COMPARE AND CONTRAST TWO OPTIONS
SATISFICING
IS THE OPTION UNDER CONSIDERATION “OK” or “GOOD ENOUGH?”
SELECTION OF THE FIRST TOLERABLE OPTION
JUDGMENTAL HEURISTICS AND BIASES
OVERCONFIDENCE – “I’m 70% sure”…more like 50/50
ANCHORS -- Get stuck on some initial info…$15-$50 mill…”Primacy Effect”
CONFIRMATION – Bias that remembers only data that supports your predisposition
AVAILABILITY– Information that is readily available and vivid, we don’t dig deeper
ESCALATION OF COMMITMENT – More investment in a bad decision
DECISION MAKING
UNDER CONDITIONS OF:
CERTAINTY
RISK
UNCERTAINTY
AMBIGUITY
LEADS TO SOLUTIONS THAT ARE:
OPTIMIZED
SATISFICED
FOUR DECISION MAKING CONDITIONS
CERTAINTY
DECISION MAKERS KNOW WHICH OBJECTIVES THEY WANT TO ACHIEVE
ALTERNATIVES ARE CLEARLY DEFINED
KNOWLEDGE OF OUTCOMES IS COMPLETE
ALL INFORMATION NEEDED IS FULLY AVAILABLE
RISK
DECISION MAKERS KNOW WHICH OBJECTIVES THEY WANT TO ACHIEVE
ALTERNATIVES ARE CLEAR
LIKELIHOOD OF OUTCOMES IS SUBJECT TO CHANCE
GOOD INFORMATION IS AVAILABLE
UNCERTAINTY
DECISION MAKERS KNOW WHICH OBJECTIVES THEY WANT TO ACHIEVE
ALTERNATIVES ARE INCOMPLETE
LIKELIHOOD OF OUTCOMES IS NOT UNDERSTOOD
INFORMATION IS INCOMPLETE
AMBIGUITY
OBJECTIVES TO BE ACHIEVED ARE NOT CLEAR
ALTERNATIVES ARE DIFFICULT TO DEFINE
INFORMATION ABOUT OUTCOMES IS UNAVAILABLE
DECISION STYLES
THOMPSON & TUDEN (59)
CLEAR PREFERENCES
REGARDING OUTCOMES
YES, Known
NO Agreement
with Certainty
Not Known
---------------------------------------------------YES, We Know
What To Do
CLEAR UNDERSTANDING
COMPUTATIONAL
COMPROMISE
OF CAUSE / EFFECT
--------------------------------------RELATIONSHIPS
JUDGMENTAL
BLUE-SKY
(Inspirational)
NO, We Don’t
Know What to Do
----------------------------------------------------
DO YOU KNOW WHAT OUTCOMES YOU WANT AND WHAT TO DO
TO GET THEM?
THREE “RATIONAL”
DECISION PROCESSES
COMPENSATORY, CONJUNCTIVE, DISJUNCTIVE
COMPENSATORY PROCESS (CLASSICAL)
ALL IMPORTANT CRITERIA ARE CLEARLY IDENTIFIED
CRITERIA ARE WEIGHTED ACCORDING TO IMPORTANCE
ALL ALTERNATIVES CAN BE MATHEMATICALLY MODELED
EXPECTED VALUE IS CALCULATED FOR EACH OPTION
THE “BEST” EXPECTED VALUE IS THE OPTIMAL CHOICE
USE OF EXPECTED VALUES ALWAYS LEADS TO THE OPTIMAL SOLUTION
VERY HIGH PERFORMANCE ON ONE CRITERION CAN OFFSET
WEAKNESSES IN ANOTHER
ARE YOU CONFIDENT THE WEIGHTS AND VALUES ARE CORRECT?
COMPENSATORY DECISION PROCESS
CLASSICAL / ECONOMIC APPROACH
ORIGINAL GRID
CAR A
CAR B
CAR C
CAR D
Price
MPG Room Power Style
.40
.20
.10
.10
.20
----------------------------9,000 50
.4
.4
.6
12,000 35
.6
.7
.9
14,000 28
.7
.9
.7
10,500 32
.7
.7
.4
EXPECTED
VALUE
CONVERTED GRID (so all #’s are standardized)
CAR A
CAR B
CAR C
CAR D
.889
.667
.571
.762
Ideal =
$8,000
1.00
.70
.56
.64
.4
.6
.7
.7
50mpg 1.0
.4
.7
.9
.7
.6
.9
.7
.4
1.0
1.0
.7556**
.7168
.6404
.6528
CONJUNCTIVE PROCESS
OR ”MULTIPLE HURDLES” APPROACH
ALL IMPORTANT CRITERIA ARE CLEARLY IDENTIFIED
CRITERIA CAN BE RANKED OR ORDERED IN IMPORTANCE
CUTOFF LIMITS ARE SET FOR EACH CRITERION
ALTERNATIVES ARE COMPARED TO THE CUTOFF LIMITS
ONLY ALTERNATIVES WITHIN ALL CUTOFF LIMITS SURVIVE
NOT AN OPTIMIZING PROCESS---NO SOLUTION GUARANTEED
THE PROCESS MAY NARROW DOWN THE OPTIONS, BUT DOESN’T
GUARANTEE A “BEST” SOLUTION WILL BE FOUND.
IN FACT, IT IS POSSIBLE THAT ALL ALTERNATIVES MAY BE ELIMINATED
BY THE CUTOFF LIMITS, LEAVING US WITH NO RECOMMENDATION.
EXCEPTIONAL STRENGTH ON ONE CRITERION CANNOT MAKE UP FOR A
WEAKNESS OR LACK ON ANOTHER CRITERION.
ALL THE MINIMUMS ON ALL THE CRITERIA MUST BE MET.
CONJUNCTIVE DECISION PROCESS
MULTIPLE HURDLES APPROACH
Rank =
Original Grid
CAR A
CAR B
CAR C
CAR D
CUTOFFS
Price
MPG
Style Power Room
1
2
3
4
5
----------------------------9,000 50
.6
.4
.4
12,000 35
.9
.7
.6
14,000 28
.7
.9
.7
10,500 32
.4
.7
.7
Max
13,000
Min
30
Min
.6
Min
.6
Min
.6
OK
OK
---OK
OK
OK
FAIL
OK
--OK
FAIL
----
PASSED ALL
CUTOFFS
RUNNING THE HURDLES
CAR A
CAR B
CAR C
CAR D
OK
OK
FAIL
OK
YES**
DISJUNCTIVE PROCESS
OR “BEHAVIORAL”
WE HAVE SOME CRITERIA, BUT THE LIST SEEMS INCOMPLETE
UNABLE TO EITHER WEIGHT OR RANK CRITERIA BY IMPORTANCE
WE CAN PERCEIVE OUTSTANDING ATTRIBUTES FOR EACH OPTION
WE LIST THE “STRENGTHS” & “WEAKNESSES” OF EACH OPTION
WE PICK OUR CHOICE BASED ON A REVIEW OF THESE S/W LISTS
THE DECISION PROCESS IS UNSYSTEMATIC, INCONSISTENT
AN ALTERNATIVE WITH A “BAD” ATTRIBUTE IS FREQUENTLY REJECTED
FINAL CHOICES ARE USUALLY MADE USING A SINGLE CRITERION WHICH
THE DECISION MAKER HAS DECIDED TO FOCUS UPON.
THESE DECISIONS ARE MUCH MORE SUBJECTIVE THAN THEY APPEAR,
AND ARE DIFFICULT TO DEFEND IF CHALLENGED.
DISJUNCTIVE DECISION PROCESS
BEHAVIORAL, STRENGTHS/WEAKNESSES APPROACH
Original Grid
CAR A
CAR B
CAR C
CAR D
Price
Style
Power MPG ????
----------------------------Good
Bad
Good
Good
Bad
Good
Bad
Eliminate the alternatives with “Bad” evaluations, and see what is left.
Thus, we buy Car B because I liked the color and my wife liked the
interior!
NOT RATIONAL OR SYSTEMATIC, BUT WE THINK WE WERE “LOGICAL” IN
WHAT WE DID BEFORE SELECTING THE CAR.
ENVIRONMENTAL SCENARIOS
WHAT ARE YOUR ASSUMPTIONS ABOUT THE ENVIRONMENT?
POSSIBLE STATES OF NATURE (Scenarios)
MUTUALLY EXCLUSIVE
THINGS WE DON’T CONTROL
POSSIBLE ACTIONS WE CAN TAKE (Alternatives)
ALTERNATIVES OR OPTIONS
THESE ARE THE CHOICES WE CAN MAKE (WE CONTROL THESE)
EXPECTED OUTCOMES FOR EACH POSSIBLE ACTION
REVENUES, COSTS, PROFITS
UNITS PRODUCED, HOURS WORKED, ETC.
LIKELIHOOD OF EACH OUTCOME
CERTAINTY
RISK or PROBABILITY
TOTAL UNCERTAINTY
PAYOFF TABLES
SINGLE-PHASE PROBLEMS
RECURRING, REPETITIVE DECISIONS
CAN ILLUSTRATE THE CLASSICAL DECISION PROCESS
DECISION TREES
MULTI-PHASE PROBLEMS
NEAR-UNIQUE, ONE-TIME-ONLY DECISIONS
A PAYOFF TABLE ILLUSTRATION
UNDER TOTAL UNCERTAINTY
EXPECTED PROFITS $ / ACRE
STATES OF NATURE / ENVIRONMENTAL SCENARIOS
ALTERNATIVE CROPS
CORN
POTATOES
HAY/GRASS
1.
2.
3.
4.
NORMAL
WET
DRY
VIOLENT
-------------------------------$ 900
450
-800
250
-------------------------------800
-300
400
500
-------------------------------300
500
0
100
--------------------------------
MAXI-MAX (Optimist)
*Corn 900, Potato 800, Hay 500
MAXI-MIN (Pessimist)
Corn -800, Potato -300, *Hay 0
MINI-MAX (Regret)
Regrets..Corn 1200, Potato 800, *Hay 600
AVERAGE (Rational) Ex Value…Corn 200, *Potato 350, Hay 225
BUILDING A REGRET MATRIX
EXPECTED PROFITS $ / ACRE
STATES OF NATURE / ENVIRONMENTAL SCENARIOS
ORIGINAL MATRIX
ALTERNATIVE CROPS
CORN
POTATOES
HAY/GRASS
NORMAL
WET
DRY
VIOLENT
-------------------------------$ 900
450
-800
250
800
-300
400
500
300
500
0
100
--------------------------------
REGRET MATRIX
CORN
POTATOES
HAY/GRASS
0
50
1200
250
100
800
0
0
600
0
400
400
-----------------------------------MINIMIZE THE MAXIMUM REGRETS
Corn = 1200, Potatoes = 800, Hay = 600**
A PAYOFF TABLE ILLUSTRATION
UNDER RISK (ASSIGNED PROBABILITY)
EXPECTED PROFITS $ / ACRE
PROBABILITIES COME FROM “GOOD” GUESSES. CALCULATE THE EXPECTED VALUES
INDIAN JOE’S ESTIMATES = Normal 30%, Wet 25%, Dry 20%, Violent 25%
STATES OF NATURE / ENVIRONMENTAL SCENARIOS
ALTERNATIVE CROPS
WEIGHTS
CORN
POTATOES
HAY/GRASS
NORMAL
WET
DRY
VIOLENT EXPECTED
.30
.25
.20
.25
VALUES
=======================
$ 900
450
-800
250
$ 285
-------------------------------800
-300
400
500
370**
-------------------------------300
500
0
100
240
= = = = = = = = = = = = = = = = = = = = = = = == =
You should PLANT POTATOES EVERY YEAR. In any one year you’ll either make 800,
lose 300, make 400, or make 500 …but over the years, you’ll average $370 of profits.
A PAYOFF TABLE ILLUSTRATION
UNDER RISK (FACTUAL PROBABILITY)
EXPECTED PROFITS $ / ACRE
PROBABILITY INFORMATION COMES FROM RELIABLE (FACTUAL) SOURCES
WEATHER BUREAU HISTORY = Normal 35%, Wet 30%, Dry 15%, Violent 20%
STATES OF NATURE / ENVIRONMENTAL SCENARIOS
ALTERNATIVE CROPS
NORMAL
WET
DRY
VIOLENT EXPECTED
.35
.30
.15
.20
VALUES
=======================
CORN
$ 900
450
-800
250
$ 380**
-------------------------------POTATOES
800
-300
400
500
350
-------------------------------HAY/GRASS
300
500
0
100
275
=======================
You should PLANT CORN EVERY YEAR. In any one year you’ll either make 900,
make 450, lose 800 or make 250 …but over the years, you’ll average $380 of
profits.
WEIGHTS
A PAYOFF TABLE ILLUSTRATION
UNDER RISK (WHAT IS THE VALUE OF PERFECT INFORMATION?)
WE KNOW ONLY GOD CONTROLS THE WEATHER, BUT IF WE HAD PERFECT
PREDICTION EACH YEAR, WE’D KNOW EXACTLY WHAT THE WEATHER
WOULD BE AND WHAT WE SHOULD PLANT. WE’D HAVE NORMAL
CONDITIONS 35% OF THE TIME, AND DURING THOSE TIMES, WE’D PLANT
CORN. 30% OF THE TIME IT WOULD BE WET AND WE’D PLANT HAY, ETC.
STATES OF NATURE / ENVIRONMENTAL SCENARIOS
ALTERNATIVE CROPS
NORMAL
WET
DRY
VIOLENT EXPECTED
.35
.30
.15
.20
VALUES
=======================
CORN
$ 900
450
-800
250
$ 380**
POTATOES
800
-300
400
500
350
HAY/GRASS
300
500
0
100
275
=======================
Expected Profits given Perfect Information (EPPI) = $625.
Expected Value of Perfect Information (EVPI) = EPPI – EV = $625 –380 = $ 245
Therefore, you can increase your profits by up to $245 if you have a perfect
weather forecast each spring.
WEIGHTS