Sales Organization Structure and Salesforce Deployment
Chapter 4: Sales Organization Structure and Salesforce Deployment
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Sales Management: Analysis and Decision Making
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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.
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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.
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Sales Organization Concepts
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Specialization
Centralization
The degree to which individuals perform some of the required tasks to the exclusion of others.
The degree two which important decisions and tasks performed at higher levels in the management hierarchy.
Individuals can become experts on certain tasks, leading to better performance for the entire organization.
Centralized structures place authority and responsibility at higher management levels.
Sales Force Specialization Continuum
Some specialization
of selling activities,
products, and/or
customers
All selling activities
and all products to
all customers
Generalists
Certain selling activities for certain products for certain customers
Specialists
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Flat Sales Organization
Span of Control
Management Levels
National Sales Manager
District Sales Manager
District Sales Manager
District Sales Manager
District Sales Manager
District Sales Manager
Span of Control vs. Management Levels
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Tall Sales Organization
National Sales Manager
Span of Control
Management Levels
District Sales Manager
District Sales Manager
District Sales Manager
District Sales Manager
District Sales Manager
District Sales Manager
Regional Sales Manager
Regional Sales Manager
Span of Control vs. Management Levels
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National Sales Manager
Regional Sales Managers
District Sales Managers
Sales Training Manager
Sales Training Manager
Salespeople
Staff Position
Line Position
Line vs. Staff Positions
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Selling-Situation Factors and Organizational Structure
Organizational Structure Environmental Characteristics Task Performance Performance Objective
Specialization High Environmental Uncertainty Nonroutine Adaptiveness
Centralization Low Environmental Uncertainty Repetitive Effectiveness
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Customer and Product Determinants of Sales Force Specialization
Customer Needs Different
Customer Needs Similar
Simple Product Offering
Complex Range of Products
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Geographic Sales Organization
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Product Sales Organization
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Market Sales Organization
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Functional Sales Organization
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Large
Small
Complexity of Account
Size of Account
Large
Account
Simple
Complex
Strategic
Account
Regular
Account
Complex
Account
Identifying Strategic Accounts
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Strategic Accounts Options
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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
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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 Geographic duplication Customer duplication Need for coordination
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Hybrid Sales Organization Structure
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Salesforce Deployment
Salesforce deployment decisions can be viewed as providing answers to three interrelated questions.
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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
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Interrelatedness of Salesforce Deployment Decisions
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)
Allocation of
Selling Effort
Salesforce
Size
Territory
Design
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Analytical Approaches to Allocation of Selling Effort
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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
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Single Factor Model Example
Market Potential Categories Average Sales Calls to an Account Last Year Average Sales Calls to an Account Next Year
A 25 32
B 23 24
C 20 16
D 16 8
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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
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Portfolio Model Segments and Strategies
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Decision Models
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
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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
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Salesforce Size Decisions
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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 sales person
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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
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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
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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
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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%
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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
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Territory Design Procedure
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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
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“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.
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Developing Forecasts
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Why Forecast?
Determining Sales Force Size
Designing Territories
Establishing Sales Quotas and Selling Budgets
Determining Sales Compensation Levels
Evaluating Salesperson Performance
Evaluating Prospective Accounts
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Types of Forecasts
Market Potential
Sales Potential
Market Potential
Sales Potential
Industry Level
Firm Level
Best Possible Results
Expected Results for Given Strategy
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Top-Down vs. Bottom-Up Forecasting
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Bottom – Up
Top – Down
Forecast made at the “front-line” level and then aggregated up the levels of the organization
Forecast made at the business unit level then broken down by zone, region, district, territory, and account forecast.
Top-Down Approach
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Bottom-Up Approach
Company Sales Forecast
Combined into district, region, and zone forecasts
Combined into territory forecasts
Salespersons’ forecasts of accounts
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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
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Moving Averages Forecast Example
Year Actual Sales Two-Year Four-Year
2002 $8,400,000
2003 $8,820,000
2004 $8,644,000 $8,610,000
2005 $8,212,000 $8,732,000
2006 $8,622,000 $8,428,000 $8,520,000
2007 $9,484,000 $8,418,000 $8,574,000
2008 $9,674,000 $9,054,000 $8,740,000
2009 $10,060,000 $9,579,000 $8,998,000
2010 ? $9,868,000 $9,460,000
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Exponential Smoothing Forecast Example
Year Actual Sales α = 0.2 α = 0.5 α = 0.8
2002 $8,400,000
2003 $8,820,000 $8,400,000 $8,400,000 $8,400,000
2004 $8,644,000 $8,484,000 $861,000 $8,736,000
2005 $8,212,000 $8,516,000 $8,627,000 $8,662,000
2006 $8,622,000 $8,455,000 $8,420,000 $8,302,000
2007 $9,484,000 $8,488,000 $8,521,000 $8,558,000
2008 $9,674,000 $8,687,000 $9,003,000 $9,299,000
2009 $10,060,000 $8,884,000 $9,339,000 $9,599,000
2010 ? $9,119,000 $9,700,000 $9,968,000
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Moving Averages Forecast Example
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Actual Sales 2002 2003 2004 2005 2006 2007 2008 2009 2010 8400000 8820000 8644000 8212000 8622000 9484000 9674000 10060000 Two-Year 2002 2003 2004 2005 2006 2007 2008 2009 2010 8610000 8732000 8428000 8417000 9053000 9579000 9867000 Four-Year 2002 2003 2004 2005 2006 2007 2008 2009 2010 8989500 8574500 8740500 8998000 9460000 Exp. Smoothing 2002 2003 2004 2005 2006 2007 2008 2009 2010 8400000 8736000 8662000 8302000 8558000 9299000 9599000 9968000
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.
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Even Allocation vs. Breakdown Methods
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Company Sales Forecast = $1,000,000
Region A Portion= .33
Forecast = $333,333
Region B Portion = .33
Forecast = $333,333
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
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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
Chapter 4: Sales Organization Structure and Salesforce Deployment
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Sales Management: Analysis and Decision Making