Efficient Alignment and Allocation of Resources

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Efficient Alignment and Allocation of Resources

• Goal To overview approaches for allocating
  resources across
• Marketing inputs
• Products/business units

Resource Allocation.
Empirical
Practical Methods that you can take and apply
today
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What is the most efficient way to enhance
profitability?

• Marketers posit a basic relationship
• Share of Market (Share of Preference) x
• (Share of Voice) x
• (Share of Distribution)
• Todays central questions if we have weaknesses
  in one of these components, how should we
  allocate resources to best strengthen it? If we
  have strengths, how should we optimally preserve
  and enhance them?

Where do Camfil Farrs strength and weaknesses
lie?
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What underlies these tools a simple theory of
consumer decision making
Psychophysical rule
Integration rule
X(1)
s(X(1))
Choice rule
X(2)
s(X(2))
S
C
Aware?
Available?
X(3)
s(X(3))
.
.
Overall evaluation
X(N)
s(X(N))
Objective product attribute values
Subjective product attribute values
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Basic Assessment

• ProfitUnitSalesMargin-Costs
• Thus our basic assessment in switching from
  situation i to j is to evaluate whether
• US (j)Margin(j) - US(i)Margin(i) gt C(j) - C(i)
• It is the Unit Shares that are uncertain.
• So how do we assess it for various scenarios??

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Optimal resource allocation
In an ideal world, we would allocate resources by
marginal benefit
600
500
400
profit
300
30/30
200
Aeropleat III
100
0
0
1
2
3
4
5
Number of sales reps
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But the world is not ideal

• Response functions are uncertain
• Multiple evaluation criteria
• Risk profiles vary across allocations
• Allocations are "lumpy
• Thus, the goal is to search for useful heuristics

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Common allocation heuristics

• Percentage of sales
• All you can afford
• Match competitors
• Last year based
• What are the limitations of each?
• Could each ever be optimal?
• What does Camfil Farr currently do?

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Use of resource allocation methods
Percentage of
respondents using this
Highest percentages
Allocation method
method
Brazil (73)
Percentage of sales
48
Hong Kong (70)
Executive judgment
USA (64)
33
Denmark (51)
Brazil (46)
Great Britain (46)
All-you-can-afford
Sweden (30)
12
Germany (25)
Great Britain (24)
Matched competitors
Germany (33)
12
Sweden (33)
Great Britain (22)
Canada (24)
Last year based
12
Mexico (21)
Total exceeds 100 percent because respondents
checked all budgeting methods that they used.
SOURCE Nicolaos E. Syndoinos, Charles F. Keown,
and Laurence W. Jacobs, "Transnational
Advertising Practices,"
Journal of Advertising Research, 20 (April-May
1996).
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Case study Sales force sizing and deployment at
Syntex Laboratories

• Company
• Major producer of pharmaceutical products (e.g.,
  Naprosyn, Norinyl)
• Problems
• How large should the sales force be?
• How to allocate sales reps across seven product
  lines?
• - Sequential or Joint Optimization Problem??
• What do firms do in practice??

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Syntex Background

• Had always done All you can afford
• Realized that a principled approach was needed
  especially in the Pharmaceutical industry (After
  R D, sales force is ranked as their most
  critical issue)
• Hired Wharton Professor to guide corporate
  cross-functional team.

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Case study Syntex Labs (cont.)

• Approach "Decision Calculus"
• Assess managers' judgments of market response to
  different levels of sales force activity
• Parameterize "S-shaped" response functions to
  incorporate these judgments
• Use an integer programming approach to perform
  marginal sales force allocations across seven
  product lines
• Perform "what if" scenarios to compare and
  evaluate different sales force configurations

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Assessing response functions

• Ask managers four questions
• What would product sales be with
• Q1 No sales force effort at all?
• Q2 Half the current effort?
• Q3 50 greater sales effort?
• Q4 A saturation level of sales effort?

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Results (consensus from several group
discussions)
Product Response Functions
One-
50
Satura-
No
Calls
Half
Present
More
tion
Naprosyn
47
68
100
126
152
Anaprox
15
48
100
120
135
Norinyl 135
31
63
100
115
125
Norinyl 150
45
70
100
105
110
Lidex
56
80
100
111
120
Synalar
59
76
100
107
111
Nasalide
15
61
100
146
176
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Syntex Labs
Comparison of existing policy with recommended
policies at current levels of number of reps
(1985)
Recommended
Recommended
Present
policy
policy
Allocation to
policy
369 reps
499 reps
Naprosyn
96.8
246.3
246.3
Anaprox
142.4
0.0
129.5
Norinyl 135
52.7
57.5
57.5
Norinyl 150
24.1
28.4
28.4
Lidex
27.3
37.2
37.2
Synalar
29.7
0.0
0.0
Nasalide
56.8
0.0
0.0
Total
429.7
369.4
498.9
Net profit (millions)
218.6
264.3
272.4
Which would you choose?
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Applying Decision Calculus to Air Filtrationthe
ADBUDG advertising planning model

• Q. How does advertising relate to sales?
• Next, we will consider the shape of the
  advertising-sales curve relationship.

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Sales increases associated with target GRP
increases established product weight tests
80
60
40
Covariate adjusted volume sales effect ()
20
0
-20
-40
0.0
25
50
75
100
125
150
175
200
225
250
Total plan target GRP change
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Sales increases associated with target GRP
increases established product weight tests
80
60
A
A
40
A
A
A
A
Covariate adjusted volume sales effect ()
A
A
A
A
20
A
A
A
A
A
A
A
A
A
A
A
A
A
0
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
B
-20
-40
0.0
25
50
75
100
125
150
175
200
225
250
Total plan target GRP change
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Implication

• Advertising effectiveness is a function of your
  current situation.
• Advertising effectiveness is a function of your
  competitors situation.

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Applying Decision Calculus to Air Flitrationthe
ADBUDG advertising planning model

• Q. How does advertising relate to sales?
• Given this, maybe we need a more formal approach
  to assessment.

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Assessing advertising response functions

• Answer three questions
• What would awareness be with
• Q1 No advertising at all for one period?
• Q2 50 greater advertising?
• Q3 A saturation level of advertising?
• Let us use the ad-budget model to help us make
  these decisions.

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Allocating resources across business units

• The problem Firms have finite cash resources to
  support multiple business units. How to best use
  these resources?
• Popular approach
• BCG/GE portfolio models

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What determines the health of a business unit?

• Business strength within industry
• BCG Relative market share
• Strength of industry
• BCG Industry growth rate
• The basic principle
• A healthy portfolio has a balanced mix of
  products that fund future, high-share,
  high-profit products

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Industry attractiveness The GE/McKinsey view
Industry
attractiveness
Weighted
Criteria

weight
Rating
criteria
score
1
Size
.15
4
.60
Growth
.12
3
.36
Pricing
.05
3
.15
Market diversity
.05
2
.10
Competitive structure
.05
3
.15
Industry profitability
.20
3
.60
Technical role
.05
4
.20
Inflation vulnerability
.05
2
.10
Cyclicality
.05
2
.10
Customer fnancials
.10
5
.50
Energy impact
.08
4
.32
Social
GO
4
--
Environmental
GO
4
--
Legal
GO
4
--
Human
.05
4
.20
1.00
3.38
SOURCE Adapted from C. W. Hofer and D. Schendel
(1978), Strategy Formulation Analytical
Concepts, St. Paul, MN West, pp. 73, 76.
,
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Business strength The GE/McKinsey view
Business
strength
Weighted
Determinant
determinants
weight
Rating
score
5
Market share
.10
.50
4
Breadth of product line
.05
.20
4
Sales distribution effectiveness
.20
.80
4
Advertising and promotion
.05
.20
effectiveness
5
Facilities location and newness
.05
.25
4
Experience curve effects
.15
.60
4
Raw materials cost
.05
.20
4
Relative product quality
.15
.60
4
RD advantages/position
.05
.20
5
Cash throw-off
.10
.50
5
General image
.05
25
1.00
4.30
SOURCE Adapted from C. W. Hofer and D. Schendel
(1978), Strategy Formulation Analytical
Concepts, St. Paul, MN West, pp. 73, 76.
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A healthy portfolio?
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A sick portfolio?
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What does Camfil Farrs portfolio of products
look like?
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Critiques of BCG/GE portfolio approach

• Questions about share profitability link
• Overstatement of experience effects
• Overstatement of market power effects

• Overemphasis on high growth
• Assumption about finite cash flow
• Overlooks covariation among products
• Ambiguous definitions
• Attractiveness and business strength
• Markets (geographic? customer segments?)
• Products (SBU's, product lines, brands, SKU's?)

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Quote of the Week

• . a prominent consulting firms growth-share
  matrix has caused more harm and damage to the
  United States industry than any other model in
  the history of mankind.
• Professor Jerry Wind (Lauder Professor, Professor
  of Marketing The Wharton School)

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Summary

• Be Careful when using Ad Hoc approaches.
• Quantitative approaches to allocating resources
  do exist
• Direct experimentation (best)
• Historical Data if available and relevant (next
  best)
• Delphi method (can be quite effective)
• Use these approaches to assess response curves.
  From these you can properly allocate your
  resources.
• Use these approaches as a guide to include in
  your
• decision making toolbox.