SALES FORCE SIZING & PORTFOLIO OPTIMIZATION. David Wood, PhD, Senior Principal Rajnish Kumar, Senior Manager



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Transcription:

SALES FORCE SIZING & PORTFOLIO OPTIMIZATION David Wood, PhD, Senior Principal Rajnish Kumar, Senior Manager

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 2

Natural annual rhythms in sales planning seasons Sales Management / Sales Operations Workload Today s Webinar focuses on this dimension Assumes annual size, alignment, goal processes 3 Slide 3

Today s discussion has the following objectives: 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 4 Slide 4

Sales force sizing typical questions 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? 5 Slide 5

Go-to-market strategy key questions What Customers? How Approach Market? What Work? Customer Universe Role Definitions Direct / indirect / hybrid Inside / outside Hunter / skinner / farmer Activities by Segment Customer Segmentation Targeting / Reach Workload Capacity Go-to-Market Strategy Workload by Segment Sales Force Sizing Staff by Whom? Resourcing Options Tactical Call Plan Resource Deployment Deploy Where? 6 Slide 6

Important Criteria 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? 7 Slide 7

Classic approaches to sales force sizing Same as Last Year Cost of Sales Share of Voice Workload Build-up Affordable Coverage Sales Response 8 Slide 8

Most common approaches internally focused Same as Last Year Sales (in $mn) 50 50 100 Sales Rep (in nos.) 50 200 150 Last Year This Year Next Year Sales (in $mn) Sales Rep (in nos.) 200 Cost of Sales # Sales (in $mn) vs # Sales Rep 100 50 150 75 100 Last Year This Year Next Year 9 Slide 9

Summary & Comparison Criteria Less is good More is good Approach Time Data Complexity Cost Forecast Defensible Implement able L-T Impact Same as Last Year Cost of Sales 10 Slide 10

Summary & Comparison Criteria Approach Time Data Complexity Cost Forecast Defensible Implement able L-T Impact Same as Last Year Cost of Sales Good So-So Bad 11 Slide 11

Geo 1 Geo 2 Geo 3 Geo 4 Geo 5 Geo 6 Geo 7 Geo 8 Geo 9 Share of Voice Example from Insurance (P&C Commercial Lines) Agency presence by P&C carrier in different markets Source: P&C LOB, Axtria Agency Intelligence database 12 Slide 12

Workload Build-up Approach 1 2 Rep Capacity # Days / Year 220 # Calls / Day 6 # Calls / Year 1,320 Assumptions Customer Total # 3 Reach 4 # Calls to Customer Quintile 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 Quintile 5 = largest accounts; Quintile 1 = smallest 63% 29% 6% 1% 0% 5 13 Slide 13

Summary & Comparison Criteria Less is good More is good Approach Time Data Complexity Cost Forecast Defensible Implement able L-T Impact Same as Last Year Cost of Sales Share of Voice Workload Build-up 14 Slide 14

Summary & Comparison Criteria Approach Time Data Complexity Cost Forecast Defensible Implement able L-T Impact Same as Last Year Cost of Sales Share of Voice Workload Build-up Good So-So Bad 15 Slide 15

Sales Force Sizing: Micro-economics 101 What happens when a territory goes vacant? Sales generated from effort this period have a lingering effect into future periods, referred to as carryover What happens when a territory goes vacant? T T + 1 Sales do not drop to $0, due to carryover, brand equity, advertising, etc. 16 Slide 16

Sales Force Sizing: Micro-economics 101 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 Due to Effort (T) Prior Carryover Brand Equity T Sales Due to Effort Carryover (T+1) from T Prior Carryover Brand Equity T+1 T+2 17 Slide 17

Affordable Coverage Approach 1 Rep Capacity Assumptions # Days / Year 220 Sales Forecast 50,000,000 # Calls / Day 6 % Margin 50% # Calls / Year 1,320 % Sales due to Effort 25% $ / Rep $100,000 % Carryover 75% Cost / Call $76 Discount Rate 10% Customer Total # Segment % Revenues in Quintile Segment Prospects % Sales 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% 4 5 Financial Assumptions Customer Total # Estimated $ Sales Per Customer 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 2 3 Quintile 5 = largest accounts; Quintile 1 = smallest 18 Slide 18

Affordable Coverage Approach Customer Estimated L-T Contribution per Customer 6 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 8 7 Customer Maximum Affordable Calls / 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 Refined # Calls / Customer Segment 5 4 3 2 1 A 12 8 4 4 2 B 4 2 C 4 2 D 2 Quintile 5 = largest accounts; Quintile 1 = smallest Customer Refined # Calls Segment 5 4 3 2 1 # Calls # FTEs A 2,400 1,600 800 800 400 6,000 4.5 B 4,000 2,000 - - - 6,000 4.5 C 9,600 4,800-19 - - 14,400 10.9 D 18,000 - - - - 18,000 13.6 Slide 19 9

Summary & Comparison Criteria Less is good More is good Approach Time Data Complexity Cost Forecast Defensible Implement able L-T Impact Same as Last Year Cost of Sales Share of Voice Workload Build-up Affordable Coverage 20

Summary & Comparison 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 21 Slide 21

We re going to take a little side trip into sales force structure considerations What Customers? How Approach Market? What Work? Customer Universe Role Definitions Direct / indirect / hybrid Inside / outside Hunter / skinner / farmer Activities by Segment Customer Segmentation Targeting / Reach Workload Capacity Go-to-Market Strategy Workload by Segment Sales Force Sizing Staff by Whom? Resourcing Options Tactical Call Plan Resource Deployment Deploy Where? 22 Slide 22

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 23

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, highlyexperienced 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 24

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 25

Sales Force Sizing: Micro-economics 102 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 $ Revenues # Sales Reps 26 Slide 26

Assume you have response models showing how call effort turns into sales for each product and customer segment Response Curve Brand A Assume single team with X number of reps Calculate total available calls V2 Calculate the value from each call at possible product combinations. E.g.: o Call A-B provides V1+V2 value o Call A provides V2 value o Call B provides V1 value Response Curve Brand B Assign the set of calls that provides maximum value V1 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. 27

Assume you have response models showing how call effort turns into sales for each product and customer segment Response Curve Brand A Selecting the optimal set of all possible calls across all possible targets and product combinations can be... daunting V2 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. V1 Response Curve Brand B 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 28

Sales response optimization $$ ROI Seeking Revenue Seeking Sales Force Investment 29 Slide 29

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 = 78,000 Optimal PDEs: 1,000K Brand B Targets = 61,000 Optimal PDEs: 400K 40,000 38,000 25,000 Target Overlap 30

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. 31

Summary & Comparison Criteria Less is good More is good Approach Time Data Complexity Cost Forecast Defensible Implement able L-T Impact Same as Last Year Cost of Sales Share of Voice Workload Build-up Affordable Coverage Sales Response 32

Summary & Comparison 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 33 Slide 33

When appropriate? Approach Same as Last Year Best Used When 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 Workload Build-up Affordable Coverage Sales Response Your competitors are brilliant & your products are identical Heuristic to apply within specific segments Starting point to the journey Historical sales + effort data unavailable (i.e., new market) Complex, organizational buying behavior Unable to link sales to historical effort Limited data, time, budget prevents Sales Response Scenarios or sales forecasting is desired CXO requires ROI 34 Slide 34

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 35