Sales Organization Structure and Salesforce Deployment

Learning Objectives Define the concepts of specialization, centralization, span of control versus management levels, and line versus staff positions. Describe the ways salesforces might be specialized. Evaluate the advantages and disadvantages of sales organization structures. Name the important considerations in organizing strategic account management programs. Explain how to determine the appropriate sales organization structure for a given selling situation.

Learning Objectives Discuss salesforce deployment. Explain three analytical approaches for determining allocation of selling effort. Describe three methods for calculating sales force size. Explain the importance of sales territories and list the steps in the territory design process. Discuss the important “people” considerations in salesforce deployment.

Sales Organization Concepts The degree to which individuals perform some of the required tasks to the exclusion of others. Individuals can become experts on certain tasks, leading to better performance for the entire organization. Specialization The degree two which important decisions and tasks performed at higher levels in the management hierarchy. Centralized structures place authority and responsibility at higher management levels. Centralization 3

Sales Force Specialization Continuum All selling activities and all products to all customers Generalists Certain selling activities for certain products for certain customers Specialists Some specialization of selling activities, products, and/or customers 2

Centralization

Span of Control vs. Management Levels Flat Sales Organization Span of Control Management Levels National Sales Manager District Sales Manager

Span of Control vs. Management Levels Tall Sales Organization National Sales Manager Span of Control Management Levels District Sales Manager Regional Sales Manager

Line vs. Staff Positions National Sales Manager Regional Sales Managers District Sales Managers Sales Training Manager Salespeople Staff Position Line Position 4

Selling Situation Contingencies 1. Should the salesforce be specialized? 2. If the salesforce should be specialized, what type of specialization is most appropriate?

Selling-Situation Factors and Organizational Structure Environmental Characteristics Task Performance Objective Specialization High Environmental Uncertainty Nonroutine Adaptiveness Centralization Low Environmental Uncertainty Repetitive Effectiveness 5

Customer and Product Determinants of Sales Force Specialization 5

Geographic Sales Organization

Product Sales Organization

Market Sales Organization

Functional Sales Organization

Identifying Strategic Accounts Large Small Complexity of Account Size of Account Account Simple Complex Strategic Regular

Strategic Accounts Options

Comparison of Sales Organization Structures Organizational Structure Advantages Disadvantages Geographic Low Cost No geographic duplication No customer duplication Fewer management levels Limited specialization Lack of management control over product or customer emphasis Product Salespeople become experts in product attributes & applications Management control over selling effort High cost Geographic duplication Customer duplication 7

Comparison of Sales Organization Structures Organizational Structure Advantages Disadvantages Market Salespeople develop better understanding of unique customer needs Management control over selling allocated to different markets High cost Geographic duplication Functional Efficiency in performing selling activities Customer duplication Need for coordination 7

Salesforce Deployment How much selling effort is needed to cover accounts and prospects adequately so that sales and profit objectives will be achieved? 1. 2. How many salespeople are required to provide the desired amount of selling effort?

Hybrid Sales Organization Structure

Salesforce Deployment Salesforce deployment decisions can be viewed as providing answers to three interrelated questions. 3

Interrelatedness of Salesforce Deployment Decisions How much selling effort is needed to cover accounts and prospects adequately so that sales and profit objectives will be achieved? How many salespeople are required to provide the desired amount of selling effort? How should territories be designed to ensure proper coverage of accounts and to provide each salesperson with a reasonable opportunity for success? Allocation of Selling Effort Salesforce Size Territory Design 4

Interrelatedness of Salesforce Deployment Decisions Allocation of Selling Effort Salesforce Size Territory Design 2,000 accounts x 25 sales calls/account = 50,000 sales calls required to cover accounts 50,000 sales calls required ÷ 1,250 sales calls/ salesperson = 40 salespeople needed 40 territories needed to provide each salesperson with opportunity for success and to ensure proper coverage of accounts (e.g. 50 accounts per territory) 4

Analytical Approaches to Allocation of Selling Effort

Single Factor Models Easy to develop and use; low analytical rigor Accounts classified into categories based on one factor, such as market potential All accounts in the same category are assigned the same number of sales calls 5

Single Factor Model Example Market Potential Categories Average Sales Calls to an Account Last Year an Account Next Year A 25 32 B 23 24 C 20 16 D 8 6

Portfolio Models Account Opportunity - an account’s need for and ability to purchase the firm’s products Competitive Position - the strength of the relationship between the firm and an account 6

Portfolio Model Segments and Strategies 6

Decision Models 1. Simple Basic Concept - to allocate sales calls to accounts that promise the highest sales return from the sales calls Optimal number of calls in terms of sales or profit maximization 2. 6

Sales Force Size: Key Considerations Sales Productivity Ration of Outputs to Inputs Sales Growth as a Result of Adding Salespeople is Curvilinear Diminishing Marginal Returns Salesforce Turnover Usually Very Costly Should be Anticipated and Managed Organizational Strategy Growth Targets Selling Costs Market Share 15

Sales and Cost Relationship

Salesforce Size Decisions

Analytical Tools: Breakdown Approach Uses sales forecast to determine salesforce size Easy to use and understand Conceptually weak - assumes sales drives the need for salespeople Best suited in stable selling environments Salesforce size = Forecasted sales / Average sales per salesperson 16

Analytical Tools: Workload Approach Estimation of selling effort needed is used to determine salesforce size Estimating selling effort needed may be simple or complex Conceptually sound Number of salespeople = Total selling effort needed Average selling effort per salesperson 16

Analytical Tools: Incremental Approach Uses Marginal Profit Contribution and Marginal Costs to Determine Salesforce Size Quantifies Important Relationships Between Salesforce Size, Sales, and Costs, Most Rigorous Method and Difficult to Develop Not appropriate for New Salesforces # of Salespeople Marginal Contribution Marginal Cost 100 101 102 103 $85,000 $80,000 $75,000 $70,000 $75,000 $75,000 $75,000 $75,000 16

Salesforce Size: Other Considerations Turnover Salesforce Size Calculations Should Incorporate Turnover Rates Example: Desired Size is 100; Annual Turnover is 20%; Recruiting, Selecting, and Training Should be Based on Salesforce Size of 120. Outsourcing the Salesforce Need salesforce quickly and/or for short period Flexible Contractual arrangements vary

Calculating Turnover For any given time frame (e.g., month quarter, year), divide the number of salespeople leaving their jobs (e.g., terminated, quit, promoted) by the total number of salespeople employed at the mid-point of the time frame. Example: Time Frame – 1 Year Separations – 50 Salespeople # of Salespeople at Mid-Point – 200 Salesforce Turnover = 25%

Designing Territories Territories consist of whatever specific accounts are assigned to a specific salesperson. The territory can be viewed as the work unit for a salesperson. Territory Considerations Trading areas Present effort Recommended effort 19

Territory Design Procedure 20

Territory Design: Using Technology Software Optimizes Territory Design Using Multiple User-Defined Criteria Compare Multiple Methods Quickly and Easily Examples Sales Territory Configurator Tactician TerrAlign Alignstar

“People” Considerations Analytical models don’t account for “people” considerations Individual differences in buyers and accounts Salesperson intuition Sales managers should temper the analytical results with people considerations before making final deployment decisions.

Appendix 4 Developing Forecasts

Why Forecast? Determining Sales Force Size Designing Territories Establishing Sales Quotas and Selling Budgets Determining Sales Compensation Levels Evaluating Salesperson Performance Evaluating Prospective Accounts

Expected Results for Given Strategy Types of Forecasts Market Potential Sales Potential Market Forecast Sales Forecast Industry Level Firm Level Best Possible Results Expected Results for Given Strategy

Top-Down vs. Bottom-Up Forecasting Forecast made at the “front-line” level and then aggregated up the levels of the organization Bottom – Up Forecast made at the business unit level then broken down by zone, region, district, territory, and account forecast. Top – Down

Top-Down Approach

Bottom-Up Approach Company Sales Forecast Combined into district, region, and zone forecasts Combined into territory forecasts Salespersons’ forecasts of accounts

Company Forecasting Methods Moving Averages Uses historical averages to forecast future sales Averages are calculated using a predetermined number of previous periods (e.g., two-year moving average; four-year moving average) Exponential Smoothing Weighted moving average Usually most recent period is weighted heavier Decomposition Methods Breakdown historical sales data into four components (trend, cycle, seasonal, erratic) Evaluate the components and then reincorporate to create forecast

Moving Averages Forecast Example Year Actual Sales Two-Year Four-Year 2008 $8,400,000 2009 $8,820,000 2010 $8,644,000 $8,610,000 2011 $8,212,000 $8,732,000 2012 $8,622,000 $8,428,000 $8,520,000 2013 $9,484,000 $8,418,000 $8,574,000 2014 $9,674,000 $9,054,000 $8,740,000 2015 $10,060,000 $9,579,000 $8,998,000 2016 ? $9,868,000 $9,460,000

Exponential Smoothing Forecast Example Year Actual Sales α = 0.2 α = 0.5 α = 0.8 2008 $8,400,000 2009 $8,820,000 2010 $8,644,000 $8,484,000 $861,000 $8,736,000 2011 $8,212,000 $8,516,000 $8,627,000 $8,662,000 2012 $8,622,000 $8,455,000 $8,420,000 $8,302,000 2013 $9,484,000 $8,488,000 $8,521,000 $8,558,000 2014 $9,674,000 $8,687,000 $9,003,000 $9,299,000 2015 $10,060,000 $8,884,000 $9,339,000 $9,599,000 2016 ? $9,119,000 $9,700,000 $9,968,000

Moving Averages Forecast Example

Breakdown Methods Use factors influencing sales at the region, district, and territory levels to adjust forecasts made at the business unit level (top-down method). Buying Power Index (BPI) is often used to adjust forecasts. Factors should be continuously evaluated.

Even Allocation vs. Breakdown Methods Company Sales Forecast = $1,000,000 Region A Portion= .33 Forecast = $333,333 Region B Portion = .33 Region C Portion = .34 Forecast = $333,334 Company Sales Forecast = $1,000,000 Region A Breakdown Factor = .20 Forecast = $200,000 Region B Breakdown Factor = .30 Forecast = $300,000 Region C Breakdown Factor = .50 Forecast = $500,000

Bottom-Up Approach Methods Survey buyer intentions Survey buyers purchasing intentions Aggregate Jury of executive opinion Executives or other experts estimate sales at the account level Estimates are averaged or otherwise agreed upon to generate forecast Delphi (A form of jury of executive opinion) “jury” is anonymous and estimates are redistributed for revision “jury” review and revise estimates until consensus is reached Sales force composite Salespeople create forecasts for the accounts and territories Forecasts are aggregated

Forecasting with Regression Analysis Statistical technique using predictor variables (factors) to forecast sales May be complex Requires collection of predictor variable data Analysis may be linear or logarithmic