1

Key Strategies In Marketing

Developing & Analyzing Strategies in

Uncertain Environments

Marketing Strategy Framework

Customer Analysis

CompetitorAnalysis

Targeting &Positioning

ExternalEnvironment

MarketingMix

CompanyAnalysis

Performance Metrics

ComplementorsAnalysis

3

The Effect of Uncertainty on Decision-making

Perceptions of uncertainty often dominate decision-making Perceptions of risk vary with the individual Perceptions of risk vary with the situation

Managers tend to be risk-averse when decision will be reviewed Managers tend to be risk-averse when things are going well

Perceptions of risk vary with the range of outcomes Managers tend to overweight potential losses

Yet, most managers often assess Uncertainty by “gut feel” 96% of managers alter or reject risk assessments provided to them (March and

Shapira 1987)

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Strategy Under Uncertainty

1) Clear Enough Future Mature markets, low-technology

2) Alternate Futures Discrete events forthcoming from one uncertainty source: technology,

competitive, market

3) Range of Futures High levels of uncertainty from multiple sources

4) True Ambiguity Many sources of uncertainty that interact

Courtney, Kirkland, and Viguerie 1997

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How Firms Should Respond to Uncertainty

1) Shape the Future Big bets -- big risks May come from large or small firms

2) Adapt to the Future No-regrets moves

3) Reserve the right to play Options, no-regrets moves Purpose is to transform big-bets into no-regrets moves

6

How Firms Actually Respond to Uncertainty

1) Head in the Sand

2) Toe in the Water

3) Take the Tiger by the Tail

7

How Firms Actually Respond to Uncertainty

Point estimates of strategy outcomes such as profits, sales, etc.

Sensitivity analysis to account for risk

Full range of outcomes associated with a major strategy

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Systematic Ways to Evaluate Full Range of Outcomes

There are some useful tools to help assess risk Decision trees Sensitivity analysis

However, these can be inaccurate or difficult to use Don’t inspire managerial confidence Don’t capture interactions between multiple variables Often used in an unsystematic way

We need a better way to estimate strategic risk!

La

Shampoo

“For the look and feel of France”

10

La Shampoo -- Financials

Discount Strategy

Price $1.50Variable Cost $ .85CM $ .65

Fixed Costs $10MSales Volume 20M

Net Profit$ 3M

“Brand Building” Strategy

Price $2.25Variable Cost $ .95CM $1.30

Fixed Costs $30MSales Volume 28M

Net Profit$ 6.4M

Which is the better option?

11

La Shampoo -- A closer look at the numbers

Actual value of “Discount” strategy could be affected by: Competitive response Channel acceptance of new positioning Response of loyal customers Response of price sensitive customers

Actual value of “Brand Building” strategy could be affected by: Competitive response Channel acceptance of new positioning Promotional expenses (advertising, sales promotion) Promotional quality

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La ShampooOutcome distribution -- “Discount” Strategy

Frequency Chart

.000

.006

.013

.019

.026

0

12.75

25.5

38.25

51

1,500,000.00 2,250,000.00 3,000,000.00 3,750,000.00 4,500,000.00

2,000 Trials 0 Outliers

Forecast: Net Profit

Most likely Value = $3.0 millionRange of Outcomes = $1.8 million to $4.2 million

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La ShampooOutcome Distribution -- “Brand Building” Strategy

Frequency Chart

.000

.007

.014

.021

.029

0

14.25

28.5

42.75

57

-2,000,000.00 750,000.00 3,500,000.00 6,250,000.00 9,000,000.00

2,000 Trials 0 Outliers

Forecast: Nt Pr

Most likely Value = $6.4 millionRange of Outcomes = -$1.6 million to $9.0 million

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Stage 1

Framing

Stage 2Data

Gathering

Stage 3

Modeling

Stage 4

Implement.

Post-hocAnalysis

Risk Analysis Process

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Putting the Players in the Process

Decision Makers

The Analysts

FramingData

GatheringModeling Implement.

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Stage 1: Framing the Decision

Framing is simply the way that individuals think about a decision Example: The proverbial half full (half empty) glass of water One of the most critical factors in decision-making

Proper framing involves developing a common understanding of the decision, its key elements, and the decision-making process

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Stage 1: Framing the Decision

Signs of a poor decision frame Poor quality information is disowned Real decision-maker is not involved or doesn’t understand Manger needed for implementation not included in process New issues raised at conclusion Assumptions challenged after the fact

Managers need a tool to facilitate framing process Influence diagrams

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Two Approaches to Decision-making

Facts &Assumptions

Forecast Modelwith Risk Discount

Traditional Business Case Approach

“What will it take for this strategy to be successful

Cashflow Modelwith Risk Modeling

Influence Diagram

An Inductive Approach

“What should I know to make the best decision?

The Influence Diagram Shows the Relationships of all Uncertainties for a Decision

NPV

RevenuesSales

Volume

Fixed Costs

S,G & A

MarginalCosts

PriceLevel

New ProductDesign

It illustrates the relationships among uncertain quantitiesand shows their influence on the focal decision criterion

Investment

Costs

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Influence Diagrams

Focus on what we need to learn, rather than what we already know

Working back from the decision criterion produces a different type of analysis model than working forward from available facts

Starts with outcome measure Identifies major uncertainties that need to be understood Directs efforts toward resolution of key uncertainties rather than more detailed

analysis of existing data

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What is “Influence”

One factor influences another when it is a major determinant of the possible future outcomes

For example, we know that the volume of next years sales will be “influenced” by our competitor’s pricing strategy as well as our own pricing strategy

CompetitorPricing

ExpectedSales

Our Price

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Building the Diagram

Decisions

Uncertainties

Influence Indicator

Calculation

Outcomes

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An Example: Comparing Two Strategies

InputsSales Forecast 35,000,000Price 1.50Variable Cost 0.75Consumer Promotions 0.15

Revenues 52,500,000Operating Exp. Production Cost 26,250,000 Consumer Promotions 5,250,000

21,000,000

Fixed Expenses Set-up Costs 1,000,000 Advertising 8,500,000 Slotting Allowances 3,500,000Net Profit 8,000,000

Revenues 63,000,000Operating Exp. Production Cost 26,600,000 Consumer Promotions 8,400,000

28,000,000

Fixed Expenses Prod. Develop. Costs 1,500,000 Advertising 13,500,000 Slotting Allowances 5,000,000Net Profit 8,000,000

InputsSales Forecast 28,000,000Price 2.25Variable Cost 0.95Consumer Promotions 0.30

Brand Building Strategy Price Discount Strategy

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LaShampooKey Uncertainties for Brand Building Strategy

Advertising Management approves base plus contingency spending

Channel push Some retailers will require quarterly slotting allowances for shelf space

Sales promotions Coupon redemption depends on quality of advertising

Product development costs Depends on results of consumer research

Competitive response Affects sales volume

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Influence Diagram for Brand Building Strategy

EBIT

Capital

Prod.Develop.

Advertising

SlottingAllowances

Sales Increase

Compet.Response

Adv.Quality

Price

Sales Promotions

ProductQuality

Production Costs

Revenues

OperatingExpenses

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Influence Diagram for Brand Building Strategy

EBIT

Capital

Prod.Develop.

Advertising

SlottingAllowances

Sales Increase

Compet.Response

Adv.Quality

Price

Sales Promotions

ProductQuality

Production Costs

Revenues

OperatingExpenses

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Influence Diagram for Brand Building Strategy

EBIT

Capital

Prod.Develop.

Advertising

SlottingAllowances

Sales Increase

Compet.Response

Adv.Quality

Price

Sales Promotions

ProductQuality

Production Costs

Revenues

OperatingExpenses

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Influence Diagram for Brand Building Strategy

EBIT

Capital

Prod.Develop.

Advertising

SlottingAllowances

Sales Increase

Compet.Response

Adv.Quality

Price

Sales Promotions

ProductQuality

Production Costs

Revenues

OperatingExpenses

MarketCharact.

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Completing the Diagram

The objective is to continue dis-aggregating until we have specific quantities to be estimated

Avoid getting bogged down in minutia The influence diagram is NOT the model

The process of making the diagram is as important as the result Creates a common frame of reference to view the problem Develops consensus at an early stage Can be revised as the analysis team learns more about the decision

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Influence Diagram

Final outcome of stage 1 is a listing of experts to be interviewed

about key uncertainties:

Uncertainty Expert Department

Prod. Development Cost Benny Fitz EngineeringAdvertising Expense Natalie Drest MarketingSlotting Allowances Ima Goober SalesSales Forecast Mary-Kay Mart Market ResearchSales Promotions Exp. Natalie Drest Marketing

Stage 2: Data Gathering

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Expert Interviews

Data gathering involves seeking out the experts identified in Stage 1 and conducting interviews

Traditional approach attempts to pin the expert down to a single number

Focus on what must go right for success Ad Hoc approach to risk assessment

Risk analysis approach attempts to define the full range of values that might occur

Explore the factors that could create extreme outcomes Understand what could go wrong / right

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What if There are Two Experts?

Frequently the decision-makers will appoint two experts Often competing factions will want their expert to have input How would you handle this?

Expert #1

Expert #2

25 50 75 100

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Conducting the Interview

1) Qualify the expert

2) Search for bias (expert or motivational)

3) Define quantity precisely (determine units)

4) Have expert explain factors behind extreme optimistic/pessimistic outcomes

5) Explore likelihood of outcomes (5/50/95 values) Most likely value Symmetry Uniformity

6) Have expert review big picture and make adjustments

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Objectives of the Interview

Identify the appropriate distribution of possible outcomes A few distributions will cover most scenarios Identify any bias Identify drivers of extreme values

Major distributions include Normal / Lognormal Triangular Uniform

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The Normal Distribution

Normal distribution with parameters:10% - tile 9,000.0090% - tile 11,000.00

Selected range is from -Infinity to +InfinityMean value in simulation was 9,983.26 7,659.09 8,829.54 10,000.00 11,170.46 12,340.91

A4

Normal distribution is most common Not bounded on high or low sides Must be symmetric Not appropriate for some values that must always be positive

e.g., unit sales

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The Log-Normal Distribution

Lognormal distribution overcomes some limitations of normal Distribution is always positive Can be skewed

Lognormal distribution with parameters:5% - tile 9,00095% - tile 11,000

Selected range is from 0 to +InfinityMean value in simulation was 9,963 8,286 9,201 10,117 11,032 11,948

B4

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The Triangular Distribution

Triangular distribution is powerful, and easy to use Covers most situations Can be skewed

Triangular distribution with parameters:Minimum 9,000Likeliest 10,000Maximum 11,000

Selected range is from 9,000 to 11,000Mean value in simulation was 9,995

9,000 9,500 10,000 10,500 11,000

C4

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The Triangular Distribution

Triangular distribution is powerful, and easy to use Covers most situations Can be skewed

Triangular distribution with parameters:Minimum 9,000Likeliest 10,747Maximum 11,000

Selected range is from 9,000 to 11,000Mean value in simulation was 10,242

9,000 9,500 10,000 10,500 11,000

C4

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The Uniform Distribution

The uniform is also simple and intuitive Useful when there is not a “most likely” value

Uniform distribution with parameters:Minimum 9,000Maximum 11,000

Mean value in simulation was 9,998 9,000 9,500 10,000 10,500 11,000

D4

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The Custom Distribution

The custom distribution is a variant of the uniform Useful when there is a contingent factor affecting the decision

9,000 10,500 12,000 13,500 15,000

D4

DistributionUncertainty Units Function Assumptions

Prod. Dev. Costs $ Triangular 0% - $1.0M50% - $1.5M100% - $2.3M

Advertising Exp. $ Uniform 0% - $12M100% - $15M

Slotting Allowances $ Triangular 5% - $2M50% - $5M95% - $8M

Sales Forecast Units Triangular 0% - 23M

50% - 28M100% - 30M

Cons. Promotions $ / unit Normal 5% - .2050% - .3095% - .40

Production Costs $ / unit Uniform 0% - 0.900% - 1.05

LaShampoo: Assessing Key Variables

Stage 3: Modeling the Strategy

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Monte Carlo Simulation

A process that creates an artificial model of the “real” world by modeling the distribution of important and related variables and then sampling from these distributions many times to estimate the impact on an outcome variable

Conceptually simple Computationally intensive Commercial packages only recently available

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The Monte Carlo Principle

Revenues

Costs

Profits

0.12 0.21 0.30 0.39 0.48

Consumer Promotions

0.12 0.21 0.30 0.39 0.48

Consumer Promotions

0.12 0.21 0.30 0.39 0.48

Consumer Promotions

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LaShampoo: Brand Building Model

Revenues 63,000,000Operating Exp. Production Cost 26,600,000 Consumer Promotions 8,400,000

28,000,000

Fixed Expenses Prod. Develop. Costs 1,500,000 Advertising 13,500,000 Slotting Allowances 5,000,000Net Profit 8,000,000

InputsSales Forecast 28,000,000Price 2.25Variable Cost 0.95Consumer Promotions 0.30

EBIT

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Stage 3: Primary Outcome

Frequency Chart

Mean = 6,195,928.000

.008

.015

.023

.030

0

7.5

15

22.5

30

-2,500,000 1,875,000 6,250,000 10,625,000 15,000,000

1,000 Trials 1 Outlier

Forecast: Net Profit

The primary outcome of the modeling stage is a probability distribution of the focal variable

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Supplementary Analyses

The modeling approach allows the analyst to probe the data to answer important questions regarding the key drivers of the final outcome

Supplementary Analyses include: Probability analysis Quantitative sensitivity analysis Analysis of key drivers Qualitative sensitivity analysis

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Probability Analysis

The goal of probability analysis is to provide insights into the downside risk and upside potential of a strategy

Probability analysis allows the analysts to answer strategic questions such as:

What is the probability that this strategy will be profitable? What is the probability that this strategy will achieve its target level of profits? What is the probability that the strategy will exceed expectations?

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LaShampoo: Brand Building Strategy

What is the probability that LaShampoo will achieve its target profitability of $8,000,000?

Frequency Chart

Certainty is 26.50% from 8,000,000 to +Infinity

Mean = 6,195,928.000

.008

.015

.023

.030

0

7.5

15

22.5

30

-2,500,000 1,875,000 6,250,000 10,625,000 15,000,000

1,000 Trials 1 Outlier

Forecast: Net Profit

Approx.25%

Approx.25%

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LaShampoo: Brand Building Strategy

What is the probability that the brand building strategy will lose money?

Approx.2%

Approx.2%

Frequency Chart

Certainty is 98.40% from 8,333 to +Infinity

Mean = 6,195,928.000

.008

.015

.023

.030

0

7.5

15

22.5

30

-2,500,000 1,875,000 6,250,000 10,625,000 15,000,000

1,000 Trials 1 Outlier

Forecast: Net Profit

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Quantitative Sensitivity Analysis

The purpose of quantitative sensitivity analysis is to identify the critical variables that drive strategy outcomes

Essential part of analysis Provides insights into sources of downside risk Enables decision team to direct attention where it will do the most good

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LaShampoo: Brand Building Strategy

Target Forecast: Net Profit

Consumer Promotions -.49

Sales Forecast .47

Variable Cost -.44

Slotting Allowances -.41

Advertising -.31

Prod. Develop. Costs -.09

-1 -0.5 0 0.5 1

Measured by Rank Correlation

Sensitivity Chart

Consumer PromotionsSales ForecastProduction CostSlotting AllowancesAdvertisingProduct Dev. Costs

-.49.47-.44-.41-.31-.09

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Tornado Diagram

Net Profit

0.22

24,870,829

3,341,641

0.92

12,300,000

1,254,951

0.38

28,816,784

6,658,359

1.04

14,700,000

1,977,510

2,000,000 4,000,000 6,000,000 8,000,000 10,000,000

ConsumerPromotions

Sales Forecast

SlottingAllowances

Variable Cost

Advertising

Prod. Develop.Costs

Downside

Upside

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Qualitative Analysis

The qualitative analysis is intended to yield insights into the key variables identified by the quantitative analysis

Relies on the expert interviews

Purpose is to identify specific actions that could be undertaken to manage downside risk or improve upside potential

Stage 4: Decision / Implementation

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Making the Decision

The analysis is not the only factor to be considered in the decision. Other factors include:

Strategic considerations Risk environment

Individual tolerance Size of project Financial stability of division, company

Social / political environment

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Implementation

Implementing a decision means translating the outcomes of the analysis made in our pseudo-world into concrete actions in the real world

Good decisions can still be derailed by poor implementation

Implementation will be broader than the analysis New issues will emerge But key issues should have already been resolved

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Developing Strategies in Uncertain Environments

We have talked about a new approach to evaluating strategies Its powerful Its flexible Its thorough

At this point, you should be able to go out and do your own analyses

Be cautious, however, this type of modeling can be subtle Stick to the basics