SALES FORCE SIZING & PORTFOLIO OPTIMIZATION · SALES FORCE SIZING & PORTFOLIO OPTIMIZATION ... Approach Time Data Complexity Cost Forecast Defensible Implement L-T Impact Same as

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

http://www.pmsa.net/conferences/webinar


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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


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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


5

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?


6

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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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


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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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


11


Criteria


ableL-T Impact

Same as Last Year

Cost of Sales

Slide 11

Good So-So Bad


12

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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Slide 14

Criteria


ableL-T Impact

Same as Last Year

Cost of Sales

Share of Voice

Workload Build-up



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Slide 15

Criteria


ableL-T Impact

Same as Last Year

Cost of Sales

Share of Voice

Workload Build-up

Good So-So Bad


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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.


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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Criteria


ableL-T Impact

Same as Last Year

Cost of Sales

Share of Voice

Workload Build-up

Affordable Coverage



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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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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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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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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


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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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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Criteria


ableL-T Impact

Same as Last Year

Cost of Sales

Share of Voice

Workload Build-up

Affordable Coverage

Sales Response



33


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: [email protected] [email protected]

Contact No.: +1 908 892 2194 +1 908 240 9420

mailto:[email protected]

mailto:[email protected]

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SALES FORCE SIZING & PORTFOLIO OPTIMIZATION · SALES FORCE SIZING & PORTFOLIO OPTIMIZATION ... Approach Time Data Complexity Cost Forecast Defensible Implement L-T Impact Same as