MGS4020_03.ppt/Feb 19, 2013/Page 1 Georgia State University - Confidential MGS 4020 Business...

MGS4020_03.ppt/Feb 19, 2013/Georgia State University - Confidential

MGS 4020

Business Intelligence

Ch 2 – Decision & Decision MakersCh 4 – Modeling Decision Processes

Feb 19, 2013


Agenda

Direct Marketing

Decisions and Decision Makers

Decision Tree


Example of a Decision-Making Process

Stimulus

DecisionMaker

ProblemDefinition

AlternativeSelection

Implement

Opportunities,Feedback,

Threats External Pressures and

Personal Values

Bias, Risks, Costs, and

Assumptions

Frame of Reference

Reframing, Strategy, Creativity

Acceptance, Evaluation, and

Control


Decision Making Process Basics

• Stimulus – External forces that the Decision Maker must evaluate to determine if he or she perceives a problem

• A problem is defined simply as the perception of a difference between the current state of affairs and a desired state.

• Decision Maker – Evaluates the stimulus to determine if he or she perceives a problem


Decision Making Process Basics

• Problem Definition – Decision Maker must define or frame the problem before an alternative solutions can be searched

• Alternative Selection – Evaluating the alternative solution to determine the best decision

• Implementation – Putting the solution into production

• Creating Consensus

• Negotiation

• Strategizing

• Politicking

• Intense Planning


Classification of Decision Makers& Decision Style

Classification of Decision Makers• Individual Decision Maker• Multiple Decision Maker• Group Decision Maker• Team Decision Maker• Organizational Decision Maker• Meta-Organizational Decision Maker

Decision Style• Problem Context• Perceptions of the Decision Maker• Personal Values


Decision Style Classification

Value Orientation

Co

gn

itiv

e C

om

ple

xity

StructureNeed for Structure

ComplexityTolerance for

Ambiguity

Logical Task/Technical

Relational People/Social

Analytical Conceptual

Directive Behavioral

Analytical

Directive

Conceptual

Behavioral


Decision Forces

A Decision Maker must balance various forces and constraints that act on a problem context in formulating a decision.

• Personal / Emotional ForcesFeelings, Health, Security, Rewards, etc.Personal and Emotional forces can reinforce or debilitate a decision makers ability to make a sound decision

• Economic / External ForcesSocietal Values, Competitive Pressures, Consumer Demands, New Technology, etc.The ultimate decision is often adjusted to account for these external forces.

• Organizational ForcesOrganizational Culture, Polices and Procedures, Resources Allocation, etc.What is the Risk Tolerance of the Organization?Is it a Conformity or Innovative Culture?

• Contextual and Emergent ForcesTime Requirements, Motivation to reach a decision, Skills Inventory etc.


Why are decision so hard?

Factors that determine the relative difficulty of a decision

• Structure

A Structured Problem vs. An Unstructured Problem

• Cognitive Limitations

Miller’s study of cognitive limitations resulted in the “7 slots” theory

• Uncertainty

Must rely on Subjective Probability

• Alternatives and multiple objectives

The more alternative solutions to choose from, the more difficult the

decision


Simon’s Model of Problem Solving

Intelligence Design Choice

ImplementationOutcomeReality

OfSituation Success

Failure

Model Validation Solution Testing


Rational Decision Making

Optimal Solution vs. Acceptable Solution

• Most economic theory built on the concept of individuals always seeking

the optimal solution

• Impractical because it is cost prohibitive to search, analyze and compare

every possible alternative to determine which is optimal.

• Simon suggested that we tend to “simplify reality” by searching for

solutions that meet our preconceived notion of an acceptable solution

given the problem context.


The Process of Choice

• While quantitative models can be used to compare and evaluate the alternatives, the Decision Maker is always faced with some uncertainty and must make a judgmental decision.

• “If you choose not to decide, you still have made a choice.”

Cognitive Processes

• The need for a DSS comes from the limits of the Decision Makers

cognitive abilities.

- Cognitive Limitations- Perception- Judgment


Agenda

Direct Marketing


Decision Tree


Decision Tree

Buy Stock

Do Not Buy Stock

Price goes up

Price goes down

Gain

Loss

Loss/gain nothing


Decision Tree

Buy Stock

Leave money in savings

Return > 4 %

Return < 4 %

Reach Objective - 40%

Miss Objective - 60%

Return > 4 %

Return < 4 %

Reach Objective - 70%

Miss Objective - 30%


Decision Tree – Activation Test

SkyMiles Enrollment

Message A

Returned within xx days

Message B


Did not return within xx days

Message C


If Vc xx, send

Message D

Graduate to “SOW”


If Vc < xx, no more

messages


If Vc xx, send

Message D

If Vc < xx, no more

messages


Decision Tree - Activation Test

ChannelsEnrollmentMessage E/F

flied within xx days

Message G

flied within xx days

Did not fly within xx days

Message H


If Vc xx, send

Message J



If Vc < xx, no more

messages


If Vc xx, send

Message J

If Vc < xx, no more

messages


Decision Tree - Retention / SOW Test

HURDLE

SkyMiles w/ x flies last year, fly x+y

this yearMessages R*


Non-SkyMiles w/ x lx days

since last tripMessage P**


If Vc xx, send

Message Q

Next promotion

(responsive)


If Vc < xx, no more messages (non-responsive)

Next promotion

(responsive)

If Vc xx, send

Message S




Decision Tree - Reactivation Test

RATE OF trip

SkyMiles w/ xx days since last tripMessages L,M,N,O*


Non- SkyMiles w/ xx days

since last tripMessage P**


If Vc xx, send

Message Q

Next promotion

(responsive)



Next promotion

(responsive)

If Vc xx, send

Message Q




Probability

The Three Requirements of Probabilities:

1. All Probabilities must lie with the range of 0 to 1.

2. The sum of the individual probabilities equal to the probability of their union

3. The total probability of a complete set of outcomes must be equal to 1.


Decomposing Complex Probabilities

Severe Winter70%

Sales > 25,000 units

Sales <= 25,000 units

80%

20%

Sales > 25,000 units

Sales <= 25,000 units

50%

50%

Moderate Winter30%

Probability [ Sales > 25,000 units ] = ( .70 X .80 ) + ( .30 X .50 )= .56 + .15 .= .71 .


Agenda

Direct Marketing


Decision Tree


Direct Marketing Campaign Platform

ACQUIRE

RETAIN

REACTIVATE

“FIRE”

STORE DIFFERENT CHANNELS

A C T I V A T I O N P R O M O T I O NA C T I V A T I O N P R O M O T I O N

E-mail Address

Vehicles:

• Statements

• Newsletters

• Inserts

• Direct mail

• Personalized kits

• E-mail

• Telephone

Vc Cost to reactivateIf:

Vc < Cost to reactivateIf:

Ugly Postcard???

TestArea

• POS

• Partners

• Advertising

Vehicles:

• Direct Mail

• E-mail

• Statements

Triggered Promotions

highest value

customers

lowest value

customersdowngrade

trigger *

(for example)Days since last purchase = X

X = 30 days for PTNM

X = 60 days for GOLD

X = 120 days for CLUB

Direct Marketing Campaign Platform

PURCHASED

NO PURCHASE

PURCHASE

* < 1 purchase in last 12 mo

If : Time since inactive = X, and

Point balance > X


Communication “Variables”

Vehicles

= E-mail

= Kits

= Statement

= Telephone

= Direct Mail (USPS)

Message / Offer (incentive)

• Hurdle (SOW)

› trip x get y

• Next trip (Re-Activation)

› Rate of trip triggers

• Points (double/flat?)

• Miles (front & back-end)

•Other

Creative Execution

• Can test several executions tailored to clusters/segments

Timing/Frequency

• Monthly (statements)

• Repeat/Follow-up Mailings


“Measuring Effectiveness: Lift/Gains Chart

Percent of population targeted

Percent of potentialresponders captured

100

1000

90

45

45

Targeting

Random mailing


Example Direct Mail Optimization

• Using multivariate model we are able to maximize profit while minimizing costs

• In comparison to methodology used last year model savings = $XXX

– Savings attributable to reduced mailing to achieve last years result (variable cost savings).

• Other benefits - Customer Behavior, Planning Tool

CUMULATIVE ROI PREDICTED

0%

50%

100%

150%

200%

250%

300%

350%

400%

450%

40 37 34 31 28 25 22 19 16 13 10 7 4 1

Deciles

Hurdle 2000 Ranked List Q1 Last Year Mailed 798,313

Cost & Revenue assumptions Registered 92,523

FIXED COST 185,000$ (Last Year) % Last YearVC 0.41$ (Last Year) Planned Mail 691,951 -13.32%

Cost/Register 5.25$ (Last Year) Plan_Regis. 132,639 43.36%

Revenue/Register 23.79$ (Last Year) Equal Last Years Registration

Mailing 407,029

Multivariate Logistic Regression PREDICTIONS $ Savings 161,746$ PREDICTED PREDICTED Cumulative Cumulative Cumulative Cumulative Cumulative Cumulative Cumulative

Segments CUSTOMERS REGISTRATION RR % COST/REG REVENUE/REG PROFIT/REG ROI Predict RR % Registered Mailed

40 40,703 13,844 34.01% 14.58$ 18.54$ 3.97$ 27.2% 34.0% 13,844 40,703 39 40,703 12,282 30.17% 8.37$ 18.54$ 10.18$ 121.6% 32.1% 26,126 81,406 38 40,704 10,669 26.21% 6.40$ 18.54$ 12.14$ 189.8% 30.1% 36,795 122,110 37 40,700 9,674 23.77% 5.43$ 18.54$ 13.11$ 241.6% 28.5% 46,470 162,810 36 40,707 8,963 22.02% 4.86$ 18.54$ 13.69$ 282.0% 27.2% 55,433 203,517 35 40,702 8,383 20.60% 4.48$ 18.54$ 14.06$ 313.9% 26.1% 63,816 244,219 34 40,703 7,894 19.40% 4.22$ 18.54$ 14.32$ 339.2% 25.2% 71,710 284,922 33 40,705 7,472 18.36% 4.04$ 18.54$ 14.51$ 359.4% 24.3% 79,183 325,627 32 40,702 7,097 17.44% 3.90$ 18.54$ 14.65$ 375.6% 23.6% 86,279 366,329 31 40,700 6,755 16.60% 3.80$ 18.54$ 14.75$ 388.4% 22.9% 93,035 407,029

30 40,708 6,446 15.83% 3.72$ 18.54$ 14.82$ 398.5% 22.2% 99,480 447,737

29 40,703 6,154 15.12% 3.66$ 18.54$ 14.88$ 406.3% 21.6% 105,635 488,440 28 40,696 5,880 14.45% 3.62$ 18.54$ 14.92$ 412.2% 21.1% 111,514 529,136 27 40,711 5,627 13.82% 3.59$ 18.54$ 14.95$ 416.5% 20.6% 117,141 569,847 26 40,701 5,386 13.23% 3.57$ 18.54$ 14.97$ 419.5% 20.1% 122,527 610,548 25 40,702 5,162 12.68% 3.56$ 18.54$ 14.99$ 421.3% 19.6% 127,689 651,250 24 40,701 4,950 12.16% 3.55$ 18.54$ 14.99$ 422.2% 19.2% 132,639 691,951 23 40,707 4,749 11.67% 3.55$ 18.54$ 14.99$ 422.2% 18.8% 137,388 732,658 22 40,699 4,557 11.20% 3.56$ 18.54$ 14.99$ 421.6% 18.4% 141,945 773,357 21 40,709 4,373 10.74% 3.56$ 18.54$ 14.98$ 420.3% 18.0% 146,318 814,066 20 40,697 4,194 10.30% 3.58$ 18.54$ 14.97$ 418.5% 17.6% 150,512 854,763

.. .. .. .. .. .. .. .. .. .. ..5 40,695 2,393 5.88% 4.00$ 18.54$ 14.54$ 363.7% 13.5% 197,711 1,465,309 4 40,706 2,300 5.65% 4.04$ 18.54$ 14.51$ 359.3% 13.3% 200,012 1,506,015 3 40,709 2,196 5.39% 4.08$ 18.54$ 14.47$ 354.9% 13.1% 202,207 1,546,724 2 40,707 2,048 5.03% 4.12$ 18.54$ 14.43$ 350.3% 12.9% 204,255 1,587,431 1 40,705 1,509 3.71% 4.17$ 18.54$ 14.37$ 344.7% 12.6% 205,764 1,628,136

Totals 1,628,136 205,764 12.64% 4.17$ 18.54$ 14.37$ 344.7% 12.6% 205,764 1,628,136

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