Sales organization structure and sales force deployment

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

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