Post on 25-Mar-2020
SALES FORCE SIZING & PORTFOLIO OPTIMIZATION
David Wood, PhD, Senior PrincipalRajnish Kumar, Senior Manager
Copyright © 2015 Axtria, Inc. All Rights Reserved.
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Today’s Webinar as part of a series
All PMSA Webinars available via http://www.pmsa.net/conferences/webinar
• Promotion Response Modeling 9/16/2015
• SALES FORCE SIZING & PORTFOLIO OPTIMIZATION Today
• Territory Alignments & People Placement 10/14/2015
• Targeting & Call Planning 10/28/2015
• Incentive Compensation 11/11/2015
All Webinars at 12:00 noon Eastern time
Copyright © 2015 Axtria, Inc. All Rights Reserved.
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Natural annual rhythms in sales planning “seasons”
Slide 3
Sales Management / Sales Operations Workload
Assumes annual size, alignment, goal processes
Today’s Webinar focuses on this
dimension
Copyright © 2015 Axtria, Inc. All Rights Reserved.
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Today’s discussion has the following objectives:
Slide 4
Present classic approaches to sales force sizing
o What are the advantages and limitations ?
o When appropriate to use ?
Share illustrative case studies
Answer your questions
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Sales force sizing – typical questions
Slide 5
How many sales people do we need ?
…by type of sales resource ?
What will sales and profits be, given various sales force options ?
How do we allocate reps ? … across product lines ? … geography ?
What is the incremental ROI of additional (or fewer) reps?
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Go-to-market strategy – key questions
Customer Universe
Customer Segmentation
Targeting / Reach
Sales Force Sizing
Activities by Segment
Go-to-Market Strategy
What Customers? What Work?How Approach Market?
Staff by Whom? Deploy Where?
Resourcing Options
Resource Deployment
Workload by Segment
Role Definitions• Direct / indirect / hybrid• Inside / outside• Hunter / skinner / farmer
Workload Capacity
Tactical Call Plan
Slide 6
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Important Criteria
Slide 7
Time: how long does it take to conduct the analysis ?
Data: are the underlying data readily available ? … are the inputs / assumptions
easy to get ?
Complexity: how difficult is the ‘math’ ?
Defensible: can this go to the CFO / CEO ?
Forecast: does it generate estimates of sales and profits ?
Implementable: can outputs be used to deploy, align, guide, and incent the
sales force ?
Cost: how costly is the approach ?
Long term impact: does the organization learn / get better ?
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8
Same as Last Year
Cost of Sales
Share of Voice
Workload Build-up
Affordable Coverage
Sales Response
Classic approaches to sales force sizing
Slide 8
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9
Same as Last Year
Cost of Sales
Most common approaches – internally focused
Slide 9
100
150
200
50 5050
Last Year This Year Next Year
Sales (in $mn) Sales Rep (in nos.)
100
150
200
5075
100
Last Year This Year Next Year
# Sales
(in $mn)
vs# Sales Rep
Sales(in $mn)
Sales Rep(in nos.)
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10
Summary & Comparison
Slide 10
Criteria
Approach Time Data Complexity Cost Forecast DefensibleImplement
ableL-T Impact
Same as Last Year
Cost of Sales
Less is good More is good
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11
Summary & Comparison
Criteria
Approach Time Data Complexity Cost Forecast DefensibleImplement
ableL-T Impact
Same as Last Year
Cost of Sales
Slide 11
Good So-So Bad
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Share of Voice – Example from Insurance (P&C Commercial Lines)
Slide 12
Agency presence by P&C carrier in
different markets
Ge
o 1
Ge
o 2
Ge
o 3
Ge
o 4
Ge
o 5
Ge
o 6
Ge
o 7
Ge
o 8
Ge
o 9
Source: P&C LOB, Axtria Agency Intelligence database
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Workload Build-up Approach
Slide 13
Assumptions
# Days / Year 220
# Calls / Day 6
# Calls / Year 1,320
Customer Total #
Segment Prospects % # 5 4 3 2 1 # Calls # FTEs
A 1,000 80% 800 24 12 12 4 8,320 6.3
B 5,000 60% 3,000 12 8 4 14,400 10.9
C 12,000 60% 7,200 12 4 23,040 17.5
D 45,000 40% 18,000 4 2 21,600 16.4
Totals 63,000 46% 29,000 42,720 19,680 4,320 640 0 67,360 51.0
63% 29% 6% 1% 0%
# Calls to Customer QuintileReach
Rep Capacity1
2
3 4
5Quintile 5 = largest accounts; Quintile 1 = smallest
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14
Summary & Comparison
Slide 14
Criteria
Approach Time Data Complexity Cost Forecast DefensibleImplement
ableL-T Impact
Same as Last Year
Cost of Sales
Share of Voice
Workload Build-up
Less is good More is good
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15
Summary & Comparison
Slide 15
Criteria
Approach Time Data Complexity Cost Forecast DefensibleImplement
ableL-T Impact
Same as Last Year
Cost of Sales
Share of Voice
Workload Build-up
Good So-So Bad
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16
Sales Force Sizing: Micro-economics 101
Slide 16
What happens when a territory goes
vacant ?
T T + 1
Sales do not drop to $0, due to “carryover”, brand equity, advertising, etc.
What happens when a territory goes vacant ?
Sales generated from effort this period have a lingering effect into future periods, referred to as “carryover”
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Are all sales ‘attributable’ to sales force effort in the same time period ?
No. Sales due to sales force effort vary by industry, market, product, marketing spend, etc.
Sales Force Sizing: Micro-economics 101
Slide 17
T
Brand Equity
PriorCarryover
Sales Due to
Effort (T)
T+1
BrandEquity
PriorCarryover
Sales Due to Effort
(T+1)
T+2 …
Carryover from T
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Affordable Coverage Approach
Slide 18
Assumptions
# Days / Year 220 50,000,000
# Calls / Day 6 50%
# Calls / Year 1,320 25%
$ / Rep $100,000 75%
Cost / Call $76 10%
Customer Total #
Segment Prospects 5 4 3 2 1
A 1,000 20% 60% 20% 10% 7% 3% 100%
B 5,000 15% 60% 20% 10% 7% 3% 100%
C 12,000 20% 60% 20% 10% 7% 3% 100%
D 45,000 45% 60% 20% 10% 7% 3% 100%
Totals 63,000 100%
Customer Total #
Segment Prospects 5 4 3 2 1
A 1,000 6,000$ 2,000$ 1,000$ 700$ 300$
B 5,000 900$ 300$ 150$ 105$ 45$
C 12,000 500$ 167$ 83$ 58$ 25$
D 45,000 300$ 100$ 50$ 35$ 15$
Financial Assumptions
Sales Forecast
% Margin
% Sales due to Effort
% Carryover
Discount Rate
Rep Capacity
% Revenues in Quintile
Estimated $ Sales Per Customer
Segment
% Sales
1
2
3
4
5
Quintile 5 = largest accounts; Quintile 1 = smallest
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Affordable Coverage Approach
Slide 19
6 Customer
Segment 5 4 3 2 1
A 1,610$ 537$ 268$ 188$ 81$
B 242$ 81$ 40$ 28$ 12$
C 134$ 45$ 22$ 16$ 7$
D 81$ 27$ 13$ 9$ 4$
Customer
Segment 5 4 3 2 1
A 21.3 7.1 3.5 2.5 1.1
B 3.2 1.1 0.5 0.4 0.2
C 1.8 0.6 0.3 0.2 0.1
D 1.1 0.4 0.2 0.1 0.1
Customer
Segment 5 4 3 2 1
A 12 8 4 4 2
B 4 2
C 4 2
D 2
Customer
Segment 5 4 3 2 1 # Calls # FTEsA 2,400 1,600 800 800 400 6,000 4.5
B 4,000 2,000 - - - 6,000 4.5
C 9,600 4,800 - - - 14,400 10.9
D 18,000 - - - - 18,000 13.6
44,400 33.6
Refined # Calls
Maximum Affordable Calls / Customer
Refined # Calls / Customer
Estimated L-T Contribution per Customer
7
8
9
Quintile 5 = largest accounts;Quintile 1 = smallest
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20
Summary & Comparison
Criteria
Approach Time Data Complexity Cost Forecast DefensibleImplement
ableL-T Impact
Same as Last Year
Cost of Sales
Share of Voice
Workload Build-up
Affordable Coverage
Less is good More is good
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21
Summary & Comparison
Slide 21
Criteria
Approach Time Data Complexity Cost Forecast Defensible Implement L-T Impact
Same as Last Year
Cost of Sales
Share of Voice
Workload Build-up
Affordable Coverage
Good So-So Bad
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Customer Universe
Customer Segmentation
Targeting / Reach
Sales Force Sizing
Activities by Segment
Go-to-Market Strategy
What Customers? What Work?How Approach Market?
Staff by Whom? Deploy Where?
Resourcing Options
Resource Deployment
Workload by Segment
Role Definitions• Direct / indirect / hybrid• Inside / outside• Hunter / skinner / farmer
Workload Capacity
Tactical Call Plan
Slide 22
We’re going to take a little side trip into sales force “structure” considerations
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Approaches to sales force structure
1. Highly dependent on your specific situation, mandates, product portfolio, etc.
2. Very general considerations:
– Consider targets you want to reach and roles required to sell to those targets
– “Standard” office-based physician practices (retail prescribing) usually only requires a “standard” rep
• May be able to make secondary details in a single call (more on this later)
• Probably only need to reach the prescribing physician, other office contacts less important
– Products with an “account selling model” (typically, any product that is dispensed in the office (vaccines, infused products, etc.) will require a more complicated selling process
• Contacts and selling to other office staff (nurses, office manager, billing coordinator) may be equally, or more, important than selling to the physician(s)
• Sale may depend on more than clinical efficacy (price, convenience, company support) and may require a more complete skill set than a “standard” office-rep
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Approaches to sales force structure
2. Very general considerations (continued):
– Hospital-based products typically require even more complex selling roles
• Physicians, formulary committee, medical director, possibly CFO (depending on product characteristics)
• Higher skill, higher cost reps are commonly used
• Note that the physician targets themselves frequently will have office-based practices outside the hospital, and may be easier to reach in that setting. You may want to plan on multiple reps (hospital, and office-based) both reaching these targets in different settings.
– IDNs / Major Health Systems almost always require a highly-skilled, highly-experienced rep.
• Significant interaction with non-medical personnel
• Need ability to present a total picture of product advantages (clinical, financial, company service etc.) to a wide variety of targets
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Approaches to sales force structure
2. Very general considerations (continued)
– Generally, giving reps fewer products to sell (as few as one) will increase product focus and make it easier to incentivize reps.
• Product effectiveness per call is likely to be high, and target selection is easy
– However, it’s also highly inefficient
• Most reps (in most situations) can deliver at least one additional “secondary” detail in call
• Giving the rep only one product to sell wastes that opportunity, and, arguably, ignores up to 1/3 the total capacity of the sales force
– Giving the reps multiple products to sell improves overall efficiency, but makes target selection, call allocation, and incentive creation a bit more complex
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26
Additional investment yields diminishing returns
Ideally, we would like to add sales reps until the very last one covers their costs
… where marginal revenue equals marginal cost
Sales Force Sizing: Micro-economics 102
Slide 26
$ Revenues
# Sales Reps
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Assume you have response models showing how call effort turns into sales for each product and customer segment
Response Curve – Brand A
Response Curve – Brand B
V1
V2
Assume single team with X number of reps
Calculate total available calls
Calculate the “value” from each call at possible product combinations. E.g.:o Call A-B provides V1+V2 valueo Call A provides V2 valueo Call B provides V1 value
Assign the set of calls that provides maximum value
Add up across all calls to arrive at scenario values from X reps
Now do the same for varying numbers of reps and compare the projected revenue and profits.
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Assume you have response models showing how call effort turns into sales for each product and customer segment
Response Curve – Brand A
Response Curve – Brand B
V1
V2
Selecting the optimal set of all possible calls across all possible targets and product combinations can be . . . daunting
Even a middle-sized problem (3 or 4 products, 2 sales forces, 100,000 possible targets) presents literally millions of possible decisions to be optimized.
Two major strategies: Linear programming solutions: a bit
complex to set up, and slightly limited in how fully they can capture “reality” . . . but very robust solutions that are always optimal for the inputs.
“Greedy” algorithms: select the “next best thing to do” at ever step. These are conceptually simpler, and more flexible in what they can represent . . . but they have known risks and can deliver up a significantly sub-optimal solution under certain conditions . . . so be careful
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29
Sales response optimization
Slide 29
Sales Force Investment
$$
ROI Seeking
Revenue Seeking
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Product & Target Overlap
One thing to consider as you develop a portfolio model: The sum of optimal calls for any two products does not equal the total calls required for your sales force to make
Brand A Targets = 78,000Optimal PDEs: 1,000K
Brand B Targets = 61,000Optimal PDEs: 400K
Target Overlap
40,00038,000
25,000
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Product & Target Overlap
The “ideal” situation is to have two (or even more) products that share a high degree of target overlap (i.e., a target for one product is likely to be a target for the others.
BUT . . . too much overlap is a problem, too . . . you may want to deliver multiple primary details to the target to meet all products needs. If the count of total desired primaries (across multiple products) exceeds the maximum number of calls a rep can make, you have to either:
– Accept that you can’t make all the calls (product presentations) that you want
– Divide the products among multiple reps (multiple sales forces with varying product portfolios) calling on the same doctor
• Multiple reps can almost always achieve a higher overall call rate to a specific target (but two reps won’t necessarily double the total calls)
• Multiple reps may also distract / confuse the doctor and undermine other aspects of the company’s strategy. This is not a decision to make lightly.
• Generally, it’s best if the multiple reps calling on the same doctor can be differentiated in some way . . .by their lead product, by their role in serving that office, etc.
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32
Summary & Comparison
Criteria
Approach Time Data Complexity Cost Forecast DefensibleImplement
ableL-T Impact
Same as Last Year
Cost of Sales
Share of Voice
Workload Build-up
Affordable Coverage
Sales Response
Less is good More is good
Copyright © 2015 Axtria, Inc. All Rights Reserved.
33
Summary & Comparison
Slide 33
Criteria
Approach Time Data Complexity Cost Forecast Defensible Implement L-T Impact
Same as Last Year
Cost of Sales
Share of Voice
Workload Build-up
Affordable Coverage
Sales Response
Good So-So Bad
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When appropriate ?
Slide 34
Approach Best Used When…
Same as Last Year• Recently conducted robust analysis• Markets are relatively stable• Costs must be ruthlessly controlled
Cost of Sales • Best use is as a heuristic to diagnose over/under investment
Share of Voice• Your competitors are brilliant & your products are identical• Heuristic to apply within specific segments
Workload Build-up
• Starting point to the ‘journey’• Historical sales + effort data unavailable (i.e., new market)
Affordable Coverage• Complex, organizational buying behavior• Unable to link sales to historical effort• Limited data, time, budget prevents Sales Response
Sales Response• Scenarios or sales forecasting is desired• CXO requires ROI
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THANK YOU
Presenter: David Wood Rajnish Kumar
Email: david.wood@axtria.com Rajnish.Kumar@axtria.com
Contact No.: +1 908 892 2194 +1 908 240 9420