Deployment, Allocation & Evaluation
Decisions are all Interrelated
 Deployment Decisions
 How large should my sales force be?
 How should I structure my territories? Do I need to realign?
 Allocation Decisions
 How much emphasis should each product or segment receive?
 How often should my reps call on each account and prospect?
 Evaluation Decisions
 What sales volume should I expect from each salesperson?
ALL OF THESE DECISIONS DEPEND ON
“SALES RESPONSE FUNCTIONS”
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Topics we’ll cover today
Sales Response Functions
Syntex Case
Other issues in sales force structure &
organization
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What is a sales response function?
Sales (territory) = f(effort of the sales
rep)
Sales (group/organization)= f(effort of the
group/organization)
Example
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Typical Sales Response Functions
Account
0
1
2
3
4
5
6
A
B
C
D
E
F
G
H
20
10
0
0
0
200
0
0
200
30
5
100
5
220
10
50
205
50
40
250
10
230
20
110
208
68
45
300
15
240
30
150
213
80
50
340
20
245
30
180
217
90
55
375
25
250
40
200
220
95
55
400
25
260
45
215
Present Hours Allocated
Total Hours Allocated: 5+1+2+3+1+5+2+1=20
Salesof Present Allocation: 912
5
4
Criteria for Planning Across
Accounts
Effort Required & Payoffs for Each Account
Potential of Each Account (A,B,C accounts)
Number of calls/time required for each account
Sales Response Curves for each account
Competition for each account
Efficiency
Routing
Planned versus Unplanned Calls
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Estimating Sales Response Functions
 Regression (econometrics)
need lots of observations
historical data, restricted range- firms don’t experiment
limited ability to extrapolate outside the range of data
hard to handle non-linearities
 Experimentation
let’s see what happens when we don’t call at all on our large
accounts
 Subjective Estimates (judgment)
somebody’s estimates are treated as data and fit to a model
Examples: CALLPLAN and Syntex
 Blitzing
blanket an area for a short time frame to assess the
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responsiveness of the territory
How do we get subjective estimates?
Ask individual/group for estimates of response
at various effort levels.
Syntex: No effort, 50% of current effort,
current effort, 150% of current effort and
saturation level of effort
Fit a curve through the estimates (using
appropriate software)
KEY ASSUMPTION: Judgement will provide a
relatively accurate view of the world
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Using the Sales Response Function for
Deployment & Allocation Decision
Making
Sales Force Size (Incremental Method)
A salesperson should be added as long as
the incremental profit produced by the
addition exceeds the incremental costs
(Syntex)
Allocating resources across accounts
(CALLPLAN) or...
or products (Syntex)..
or segments (Syntex)..
or....
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Syntex
Size of the Sales Force and Allocation of
the Reps across Products/Segments
Inputs to the Model (Exhibits 4 and 5)
# of Reps/Product= 430 x (# of presentations for
product/total # of presentations)
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Syntex- Immediate Realizations
 Optimal size of sales force was considerably larger
than expected (550 vs. 740)
 Existing resources should immediately be redeployed
to support the major product
 A significant bottom line opportunity cost resulting
from the constraint of selling time
 Sales and marketing shared some explicit, intuitive
understanding of how our products and markets
behaved. This recognition of a shared common
belief promoted a sense of partnership, mutual
respect and cohesiveness between two disparate
groups
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Syntex- Immediate Actions
Decided to increase sales force to 700 as
quickly as possible
This was somewhat below the model
maximum of 740 (“cautious skepticism”)
Could only add 100 reps/year due to
hiring/training constraints
All necessary resources would be
mobilized to achieve this objective
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Syntex- Longer Term Ramifications
Collective recognition of Naprosyn’s
importance, both currently and for the
foreseeable future
this recognition aided in improving resource
volume and allocation decisions
Altered people’s understanding of where
the opportunities lay
must divorce organization from the
company’s history and prepare for the future
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Syntex- Why were these actions
agreed to so quickly?
The model output had the appearance of
a scientific approach
It coincided with the managers’ intuitive
judgements
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Syntex- How Accurate were the
Original Estimates?
Use base 1984 strategic plan forecast
Adjust for 3 unforecastable events;
market withdrawal of competitive product,
new dosage form of birth control pills,
pipeline filling for new form
Multiply by Delphi estimated response
function at the actual level of sales effort
applied during fiscal 1983; 1984
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Syntex- The Model Forecasts vs.
The Base Plan
Product
Naprosyn
“Base” FY
Base +
‘84 Forecast Adjustment
$175.00
$175.00
Actual FY
Model +
Model FY
‘84
Adjustment ‘84 Forecast
$204.00
$203.00
$203.00
Anaprox
26.00
35.30
28.00
27.60
18.30
Nurinyl
15.20
20.70
20.40
20.70
15.20
Norinyl
38.80
37.30
39.00
38.80
38.30
Synalar
33.80
36.20
34.90
33.80
31.40
Lydex
14.00
14.00
13.10
12.00
12.00
7.30
7.30
11.90
5.20
5.20
325.80
351.30
341.30
Nasalide
Total
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Syntex- Model Forecast vs. Base
Plan and Results
Model mean absolute deviation $1.51 million
Base plan absolute deviation $6.44 million
Sales $25.5 million higher than plan in directions
predicted by model
Model response functions were conservative on
average
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Advantages of the “Incremental/
Sales Response” Approach
Sales Force Size/Allocation Decisions
 Managers gain insight while coming to consensus on sales response
curves
 Focuses on profitability rather than efficiency
 Can highlight opportunities which may be clouded by firm’s
historical approach to allocation of resources
Call Planning Decisions
 Sales Rep thinks about the territory
 S/he is better prepared for each call
 Improves weekly and long-range planning
 Spend time where it will pay off most
 Frees up time for selling
 Better communication between salesperson and supervisor
 Subordinate to salesperson’s judgment (more likely to be used)
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Sales Force Structure & Organization
 Generalist vs. specialized force(s)
 Partitioning across:
 geography
 products
 customer segments
 type of selling task
 technology application
 combinations of above
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Single/Generalist Sales Force
 Advantages
 economies of scale in administration and calling
 sometimes better access to the customer
 can serve more needs of the customer
 avoid confusing the customer
 one person is accountable to the customer
 Disadvantages
 human tendency to focus: cherry picking
 one blockbuster product gets all the attention
 difficult to develop expertise on all products
 Tends to be best where effort is the principal determinant of sales.
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Specialized Sales Forces
 Advantages
 task focus- new product launch
 product focus- high tech, complex products, customized
products/services
 coherent role for sales person
 Disadvantages
 internal communications problematic
no big picture
 becomes awkward quickly
 Tends to be best where skill is the principal determinant of sales.
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Dividing the Sales Force
 Divide by geography when:
 customer needs are similar
 product line is narrow or easy to understand
 selling tasks require similar skills
 Divide by customer type when:
 customer needs are diverse
 product line is narrow or easy to understand
 selling tasks require similar skills
 Divide by task or product when:
 customer needs are similar
 product line is broad or complex
 selling tasks require diverse skills
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Next time:
Now that we know how many people and how
they should be divided.. Where exactly do they
go?
Guest speaker from Z-S Associates
Territory Design
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