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HMMC New Products PRODUCTS Professor Andrew ... • While it can be expensive, the rewards can be...
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4/18/2013 1 NEW PRODUCTS Professor Andrew Ainslie Director, UCLA Medical Marketing Program Dean, UCLA MBA Program Agenda • Understanding customers and primary research • Types of new products • The new product lifecycle • Some numbers to bring things together • Case, discussion, wrap‐up
Transcript of HMMC New Products PRODUCTS Professor Andrew ... • While it can be expensive, the rewards can be...
4/18/2013
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NEW PRODUCTS
Professor Andrew Ainslie
Director, UCLA Medical Marketing Program
Dean, UCLA MBA Program
Agenda
• Understanding customers and primary research
• Types of new products
• The new product lifecycle
• Some numbers to bring things together
• Case, discussion, wrap‐up
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Understanding Customers
Customer analysis
What are the customer’s needs and wants?
What are the sources of value for the customer from our product?
How do they make decisions and shop?
What consumer research do we have that informs us about our customers?
Major questions
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Customer analysis
Self‐Expressive Benefits
Emotional Benefits
Functional Benefits
What motivates your customer? What is the product’s primary source of value to him or her?
What does the product say about you?Based on intangible, psychosocial attributes: the “augmented product”
How does the product make you feel?Based on intangible or aesthetic attributes
What needs does the product meet?Tangible attributes: what it does
Customer analysis
Self‐Expressive Benefits
Emotional Benefits
Functional Benefits
What motivates you?
What does Anderson say about you?
“Because I am an Anderson MBA, I am…”
How does Anderson make you feel?
“When I hear Anderson MBA, I think and feel…”
What needs does Anderson meet?
“From Anderson MBA, I get…”
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Customer analysis
Issues in identifying value motives
Manifest motives: Latent motives:
It will demonstratethat I am successful
It will suggest I am wealthy
It will help me lookpowerful
It will be large &comfortable
It will keep me safe
It performs well, is high in quality
Customer analysis
Understanding consumer decisions
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Customer analysis
Decision Modes
Self‐expressive
Utilitarian
Mundane
Customer analysis
Psychological value and the extended self
Can products become an integral part of self‐identity?
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Customer analysis
Sources for research data on customers
Observed Behavior
Stated
Opinion
Primary
(Custom)
•Test markets
•Clickstreams
•Purchase History
•Focus Groups
•Projective Techniques
•Customer Surveys
Secondary
(Standard)
•IRI/AC Nielsen Data
•Census Data
•National surveys
•Previous surveys
Customer analysis
Understanding value through research
Projective techniques
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Customer analysis
Understanding value through research
Projective techniques
Focus groups
Customer analysis
• Surveys can be done in a broad array of ways:– Unstructured, one‐on‐one, phone or in‐person
– Online questions ‐more structured
– Conjoint – highly structured!
• Survey everyone! Administrators, doctors, patients, regulators (if you can find them)
• Consider surveying competitors! And if you don’t, perhaps use a third party to do so as long as they disclose their client.
OLD‐FASHIONED SURVEYS ARE BEST FOR MOST B‐TO‐B SITUATIONS!
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Conjoint
• Conjoint is easily one of the most powerful tools in the marketer’s toolbox.
• While it can be expensive, the rewards can be huge.
• Use it when very close to going to market
Customer analysis
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Product Lifecycle
Product lifecycle
What stage of the lifecycle is our product in?
Do we need to “cross a chasm” to reach a larger target?
How fast will our new product be adopted?
Major questions
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Product lifecycle
Seller’s view– A bundle of tangible and intangible attributesdesigned to provide benefits to the customer
Customer’s view– A bundle of tangible and intangible benefits
We must manage the benefits received and perceived by the customer through the attributes we assemble.
What is a product?
Product lifecycle
Why introduce new products?
Offensive
Achieve share or profit goalsOpening wedge into customer
segment or channel
Defensive
Preempt attackPrevent loss
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Product lifecycle
Types of new products
Survey conducted by Booz, Allen & Hamilton Newness to the Market
Low High
Newnessto
theFirm
High
Low
New product lines/established markets
20%
New to the worldproducts
10%
Improvements toexisting products
26%
Cost reductions
11%
Additions to existingproduct lines
26%
Repositioning 7%
Product lifecycle
A cautionary note…
“An estimated 86% of products introduced last year failed to reach their business objectives . . .”
Wall Street Journal
“Only 56% of new products introduced are still on the market 5 years after launch.”
Business Week
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Product lifecycle
New product development process
IdeaGeneration
IdeaScreening
ProductDesign
MarketTesting
Market Introduction
35%Rejected
40%Rejected
50%Rejected
Product lifecycle
Accidental inventions
What inventions did these lead to?
Raytheon “cooking” radar
Upjohn clinical trials
3M “clean” splashes
G. D. Searle “page turner”
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Simply Spending More on R&D May Not Work
• Booz, Allen study looked at six years of data for 1,000 publicly traded companies
• R&D spending (top 10%, mid 80%, bottom 10%)
• Six years financial results
• Mid 80% spenders did as well as top 10% spenders (bottom 10% did worse)
• Study found that better oversight and culture were most important in predicting financial results
• “It is the culture, the skills and the process more than the absolute amount of money available.” – Barry Jaruzelski, Booz, Allen
Source: WSJ, October 11, 2005, pp. 2,13
DIFFUSION AND LIFECYCLE
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Product lifecycle
Do we need to “cross a chasm” to reach a larger target?
Effects of lifecycle on company, competition, and customers
Effects of lifecycle on segmentation, targeting and positioning
How fast will our new product be adopted?
The Bass Diffusion Model
ACCORD
Major questions
Product lifecycle Expert forecasts: the “J curve”
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Product lifecycle
Introduction Growth Maturity Decline
Sales
Profits
The Product Lifecycle
Product lifecycle
The Product Lifecycle: company goals
Introduction Growth Maturity Decline
Create awarenessand trial
Maximize share,grow market
Maximize profit,fill product lines
Harvest,delete
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Product lifecycle
The Product Lifecycle: competitor behavior
Single Many FewCompetitor Competitors Competitors
Basic Product Product
Product Proliferation Simplification
Awareness Preference Order taking
Introduction Growth / Maturity Decline
Product lifecycle
The Product Lifecycle: customer behavior
2 1/2%Innovators
13 1/2%Early
adopters
34%Early
majority
34%Late
majority
16%Laggards
Time of adoption of innovations
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Product lifecycle
Crossing the chasmIs there a chasm between the early
adopters and the early majority?
– Different motivations for purchase• Early adopters are visionaries, willing to take risks with untested products to gain competitive advantage; willing to help publicize innovation
• Early majority are pragmatists who want to be sure product works before adopting; only buy from category leader
– Require different positionings and strategies• Key approach: target a single early majority member, make them happy, and use that customer as a “beachhead” to attract others
*Geoffrey A. Moore, Crossing the Chasm, Harper Business, 1991.
THE BASS MODEL
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Product lifecycle
Modeling the product lifecycle
Innovators:
not influenced by others in the timing of their
initial product purchase
Imitators:
influenced by number of previous buyers in the timing of their initial product purchase
Potential adopters classified into two groups
Implication: The importance of innovators to product sales will be high at first but will diminish with time
Product lifecycle
The Bass Diffusion Model
)]()[()( TYmTPTS
Sales (new adoptions) at time T, S(T), is given by
where
adopters potential ofnumber total
adopters ofnumber cumulative)(
imitation oft coefficien
innovation oft coefficien
m
TY
q
p
• P(T) is the probability of adoption
at time T, given not yet adopted
• [m‐Y(T)] gives the number of
potential adopters left in the market
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Product lifecycle
Modeling the product lifecycle
The coefficient of innovation (p)– High: Shifts the adoption curve to the left
– Low: Shifts the adoption curve right
– Ranges from near 0 to 0.30; average is 0.03
Consumer durables tend to have higher innovation rates than industrial durables
The coefficient of imitation (q)– High: Creates a more spiked curve
– Low: Flattens the curve
– Ranges from 0.3 to 0.9; average is 0.4
Industrial durables tend to have higher imitation rates than consumer durables
Coefficients of Innovation and Imitation control the shape of the curve
Product lifecycle
Examples of values of pand q
Cluster product p q
initial price in
real $1 Electric Toothbrush 0.083 0.22 108
Fire ExtinguisherHair SetterSlow CookerStyling DryerTrash CompactorTurntable
2 Calculator 0.0249 0.27 140Digital Watch
3 Can Opener 0.0232 0.32 151Cass.Tape DeckCurling IronElectric BlanketHeating PadKnife SharpenerLawn MowerWaffle Iron
4 B&W TV 0.0141 0.48 623BlenderDeep FryerElec. Clothes Dryer Food ProcessorMicrowave OvenRoom A/C
5 Color TV 0.002 0.54 2109RefrigeratorVCR
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Product lifecycle
Working with the Bass Model
m 100p 0.03q 0.4
time Adopters CumAdopters1 3 32 4.074 7.0743 5.417214 12.49121414 6.997627 19.488841595 8.691612 28.18045326 10.25022 38.430669117 11.31168 49.742351378 11.50746 61.249815299 10.65627 71.90608746
10 8.923311 80.8293981611 6.773311 87.6027090512 4.716064 92.3187728713 3.066923 95.3856955414 1.898984 97.2846792315 1.138096 98.4227752916 0.668256 99.09103137
99.09103
qpm
Bass Diffusion Model
0
2
4
6
8
10
12
14
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
0
20
40
60
80
100
120
Adopters
Cumulative Adopters
Product lifecycle
Example #1: power lawnmower diffusion
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Product lifecycle
Example #2: clothes drier diffusion
Product lifecycle
Applying the Bass Model
• The Bass model tracks adoption.
• This is easy for durables (e.g. Blu‐ray players) in the early years, as purchase = adoption.
• One caveat: beware of replacement sales in later years; model can be adjusted for this
• For consumables and package goods where repeat purchase is critical, the Bass Model may help predict first‐time trial, but would need to be extended to capture repurchase rates, etc.
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Product lifecycle
Forecasting with the Bass Model
Wait until you have early sales data and use regression,
OR work by analogy:
• Select similar products for which a fairly complete diffusion history is available
• Obtain the diffusion model parameters for innovation and imitation for these products
• Estimate market potential m for the new innovation through management judgment or survey research
• Conduct scenario analysis
Product lifecycle
Forecasting with the Bass ModelDirecTV Forecast vs. Actual
0
2
4
6
8
10
12
94-95 95-96 96-97 97-98 98-99
Mil
lio
ns
of
Ho
me
s
Actual
Predicted
Frank M. Bass, Kent Gordon, Teresa L. Ferguson, and Mary Lou Githens, “DirecTV: Forecasting Diffusion of a New Technology Prior to Product Launch,” Interfaces,31:3, Part 2 of 2, May‐June 2001 (pp. S82‐S93).
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ACCORD
Product lifecycle
Other factors influencing diffusion
Characteristics of Innovation (Roger’s ACCORD):
• Relative Advantage
• Compatibility with current behaviors
• Complexity in communicating the benefits
• Observability of the product’s benefits
• Riskiness (What if the product fails to work?)
• Divisibility (Sometimes called trialability)
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Product lifecycle
ACCORD Example
Product lifecycle
ACCORD Example
• Relative Advantage?
– Not much of an advantage over regular butter. May go on more easily, but might have different texture and taste. Not useful for cooking.
• Compatibility with current behaviors?
– Very similar to current behavior
• Complexity in communicating the benefits?
– Not complex; easy to explain
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Product lifecycle
ACCORD Example
• Observability of benefits?
– Immediate observability in use
• Riskiness (What if the product fails to work?)
– Might not taste good. Waste of money if not useful. Does it make you look silly?
• Divisibility (trialability)?
– Easy to purchase a single unit for trial
Product lifecycle
ACCORD Example
• Relative Advantage?
• Compatibility?
• Complexity?
• Observability of benefits?
• Riskiness?
• Divisibility (trialability)?
Conclusion:Lack of advantage and risk may slow adoption
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Product lifecycle
Applying ACCORD
If several of the characteristics are negative, adoption may be slower than average
Make adjustments to Bass Model parameters accordingly
Identification of negative characteristics provides guidance for changes to the marketing mix
For example, high financial risk may suggestthe need for 30‐day free returns or other guarantees
Low divisibility may suggest that consumers need a better way to trial the product
Product lifecycle
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KEY CALCULATIONS FOR NEW PRODUCT EVALUATION
Calculations
• Breakeven
• Market size
• Diffusion
• Bringing them together
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Numbers review
Breakeven analysis
$
total revenue
Break-Even Point
total cost
Unit Volume
fixed cost
Profit
Revenue = Price * Quantity
Total cost = Fixed cost + (Var. cost * Quantity)
Numbers review
• Profit = (Quantity * Contrib. Margin) ‐ Fixed Costs
• At what quantity do we breakeven (i.e., exactly cover our costs)?
Set Profit = 0 and solve for Quantity
BEV = Fixed Cost / Contrib. Margin
• Can also calculate Breakeven Price
Set Profit = 0 and solve for Price
BE Price = (Fixed Cost / Quantity) + Variable Cost
Breakeven analysis
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Numbers review
• Costs are $150/watch, and $10M/year to run plant
• What is breakeven volume if you sell watches at $250 each?
• What is breakeven price if you sell 10,000 watches per year?
Breakeven example: Watch manufacturer
Numbers review
• Costs are $150/watch, and $10M/year to run plant
• What is breakeven volume if you sell watches at $250 each?
• What is breakeven price if you sell 10,000 watches per year?
Breakeven example: Watch manufacturer
BEV = FC / CM
= $10M / ($250 ‐ $150) = 100,000
BEP = (FC / Q) + VC
= ($10M/ 10K) + $150 = $1,150
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Numbers review
• Let’s test some alternate scenarios for BEV
• What if we can reduce our fixed costs by 10%?
• What if we reduce variable cost by 10%?
• What if we increase price by 10%?
Breakeven example: Watch manufacturer
BEV = FC / CM = $9M / ($250 ‐ $150) = 90,000
BEV = FC / CM = $10M / ($250 ‐ $135) = 86,957
BEV = FC / CM = $10M / ($275 ‐ $150) = 80,000
Breakeven
• What’s the unit in quantity?
• Can we incorporate CLV?
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Numbers review
• A friend’s restaurant isn’t breaking a profit. Without major menu changes, what can we recommend?
• What are the drivers for cost and revenue?
• How do we calculate a breakeven?
Breakeven example: Restaurant
Fixed Costs? Variable Costs?
Revenue?
BEV = FC / CM
= Expected Value per table
Market Size
Total market
Segmentation
Your mktshare
Dif‐fusion
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Bringing it together
• Find out your breakeven quantity
• Estimate the size of the market
• Which segment are you going after?
• Estimate your market share
• Remember that diffusion takes a long time!
• Use different scenarios. What works?
Numbers review
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Appendix: Estimating the Bass ModelSales at time t equal the probability of adoption timesthe number of potential adopters who haven’t done so already
2
2
( ) ( ). ( )
( ). ( )
( )[ ( )] . ( )
( ) ( ) ( )
. ( ) . ( )
S t P t m Y t
Y tp q m Y t
m
Y tp m Y t q m Y t
m
sales to innovators sales to imitators
qpm q p Y t Y t
m
a bY t cY t
Estimating the Bass Model (cont’d)
Use Regression:
Where:
Peak:
2( ) . ( ) . ( )S t a bY t cY t
0 1 2
2
( ) ...
4
2
tY t S S S S
aa pm p
mb q p q mc
q b b acc m
m c
*
2*
ln( )
,4t
qp m p q
t Sp q q
