1. Sales Organization Structure and Sales Force Deployment Module Four

2. Sales Organization Concepts Specialization 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. Centralization 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.

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

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

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

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

7. Organizational Structure Environmental Characteristics Task Performance Objective Specialization High Envir. uncertainty NonroutineAdaptiveness Centralization Low Envir. Uncertainty RepetitiveEffectiveness Selling-Situation Factors and Organizational Structure Selling Situation Contingencies

8. Customer and Product Determinants of Sales Force Specialization Simple Product Offering Complex Range of Products Customer Needs Different Customer Needs Similar Market- Driven Specialization Product/Market- Driven Specialization Geography- Driven Specialization Product- Selling Situation Contingencies

9. Geographic Sales Organization National Sales Manager Zone Sales Managers (4) District Sales Managers (20) Salespeople (100) District Sales Managers (20) Eastern Region Sales Manager Western Region Sales Manager Sales Training Manager

10. Product Sales Organization National Sales Manager Office Equipment Sales Manager Office Supplies Sales Manager District Sales Managers (10) Salespeople (100) District Sales Managers (10)

11. Market Sales Organization National Sales Manager Zone Sales Managers (4) District Sales Managers (25) Salespeople (150) District Sales Managers (5) Commercial Accounts Sales Manager Government Accounts Sales Manager Sales Training Manager Salespeople (50)

12. Functional Sales Organization National Sales Manager Field Sales Manager Telemarketing Sales Manager Regional Sales Managers (4) Salespeople (160) Salespeople (40) District Sales Managers (2) District Sales Managers (16)

13. LargeSmall Complexity of Account Size of Account LargeAccountSimpleComplexMajorAccount RegularAccountComplexAccount Sales Organization Structures: Identifying Major Accounts

14. Develop Major Account Salesforce Assign Major Accounts to Sales Managers Assign Major Accounts to Salespeople along with Other Accounts Sales Organization Structures: Major Accounts Options

15. Comparison of Sales Organization Structures OrganizationalStructureAdvantagesDisadvantages Geographic Low Cost No geographic duplication No geographic duplication No customer duplication No customer duplication Fewer management levels Fewer management levels Limited specialization Lack of management Lack of management control over product or control over product or customer emphasis customer emphasis Product Salespeople become experts in product attr. & applications in product attr. & applications Management control over Management control over selling effort selling effort High cost Geographic duplication Geographic duplication Customer duplication Customer duplication

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

17. Hybrid Sales Organization Structure National Sales Manager Major Accounts Sales Manager Regular Accounts Sales Manager Office Equipment Sales Manager Office Supplies Sales Manager Field Sales ManagerTelemarketing Sales Manager Commercial Accounts Sales Manager Government Accounts Sales Manager Western Eastern

18. Salesforce Deployment 1.How much selling effort is needed to cover accounts and prospects adequately so that sales and profit objectives will be achieved? 2.How many salespeople are required to provide the desired amount of selling effort? 3.How should territories be designed to ensure proper coverage of accounts and to provide each salesperson with a reasonable opportunity for success? Sales Force deployment decisions can be viewed as providing answers to three interrelated questions.

19. Interrelatedness of Sales Force 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 and salespeople assigned to territories to ensure proper coverage of accounts and to provide each salesperson with a reasonable opportunity for success? Allocation of Selling Effort Allocation of Selling Effort Sales Force Size Size TerritoryDesignTerritoryDesign

20. So How Many Sale People Do I Need? The budget way: The budget way: Revenue Divided by Quota Revenue Divided by Quota The Workload way: How many unit sales do I needHow many unit sales do I need How many sales calls need to make that many salesHow many sales calls need to make that many sales How many sales calls can a sales person makeHow many sales calls can a sales person make Total sales people to make that many calls.Total sales people to make that many calls.

21. Example Goal is $12,000,000 and average sale is $10,000 means you need 1200 sales to make goal.Goal is $12,000,000 and average sale is $10,000 means you need 1200 sales to make goal. Look at last years team batting average, if it was 30%:Look at last years team batting average, if it was 30%: Batting Average = # Orders__ Total # Calls Total # Calls Total # of calls = 1200 divided by 0.30 = 4000 calls

22. Example continued If a sale person can make an average of 3 calls per day and is in the field 100 days per year they can make 300 sales calls in the year. If you need to have 4000 sales calls made, # of sales people = 4000 divided by 300 = 13.3 sales people

23. Single Factor Models Models Easy to Develop and Use Difficult to Develop and Use LowAnalyticalRigor HighAnalyticalRigor PortfolioModelsPortfolioModels DecisionModelsDecisionModels Allocation of Selling Effort: Analytical Approaches to Allocation of Selling Effort

24. Allocation of Selling Effort: Single Factor Models Easy to develop and use/low analytical rigorEasy to develop and use/low analytical rigor Accounts classified into categories based on one factor, such as market potentialAccounts classified into categories based on one factor, such as market potential All accounts in the same category are assigned the same number of sales callsAll accounts in the same category are assigned the same number of sales calls Effort allocation decisions are based on the analysis of only one factor and differences among accounts in the same category are not considered in assigning sales call coverageEffort allocation decisions are based on the analysis of only one factor and differences among accounts in the same category are not considered in assigning sales call coverage

25. Allocation of Selling Effort: Single Factor Model Example Market Potential Categories A B C D Average Sales Calls to an Account Last Year 25 23 20 16 Average Sales Calls to an Account Next Year 32 24 16 8

26. Allocation of Selling Effort: Portfolio Models Account Opportunity - an account’s need for and ability to purchase the firm’s productsAccount 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 accountCompetitive Position - the strength of the relationship between the firm and an account

27. Allocation of Selling Effort: Portfolio Model Segments and Strategies Competitive Position Segment 1 Segment 2 Segment 4 Segment 3 StrongWeak Low High Account Opportunity

28. Allocation of Selling Effort: Decision Models Simple Basic Concept - to allocate sales calls to accounts that promise the highest sales return from the sales callsSimple 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 maximizationOptimal number of calls in terms of sales or profit maximization

29. Determining Minimum Account Size Break-even sales volume = Cost per call X Number of calls Sales cost as a percentage of sales

30. Example Cost per call = $300Cost per call = $300 Number of calls to close = 3.5 (average)Number of calls to close = 3.5 (average) Sales cost as a percentage of sales = 4%Sales cost as a percentage of sales = 4% Break-even sales volume = Cost per call X Number of calls Sales cost as a percentage of sales $300 X 3.5.04 = $26,250

31. Sales Force Size: Key Considerations Sales Productivity - the ratio of sales generated to selling effort usedSales Productivity - the ratio of sales generated to selling effort used –In early stages, the addition of salespeople increases sales considerably more than the selling costs. As salespeople continue to be added, sales increases tend to decline until a point is reached when the costs to add a salesperson are more than the revenues that salesperson can generate. Salesforce TurnoverSalesforce Turnover –Is very costly –Should be anticipated

32. Sales Force Size: Analytical Tools Salesforce size = Forecasted sales / Average sales per person The Breakdown Approach is used to determine the number of salespeople needed to generate a forecasted level of sales. This approach is easy to develop. However, it is weak conceptually. The concept underlying the calculations is that sales determine the number of salespeople needed—putting “the cart before the horse.”

33. Sales Force Size: Analytical Tools The Workload Approach determines how much selling effort is needed to adequately cover the firm’s market. Then the number of salespeople required to provide this amount of selling effort is calculated. This approach relatively simple to develop and is sound conceptually. Number of salespeople = Total selling effort needed Average selling effort per salesperson

34. Sales Force Size: Analytical Tools The Incremental Approach is the most rigorous for calculating salesforce size. Its basic concept is to compare the marginal profits and marginal costs associated with each incremental salesperson. The major advantage of this approach is that it quantifies the important relationships between salesforce size, sales, and costs. However, the incremental method is difficult to develop, and it cannot be used for new sales forces where historical data and accurate judgments are not possible.

35. 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.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 ConsiderationsTerritory Considerations –Trading areas –Present effort –Recommended effort

36. Territory Design Procedure FinalizeTerritoryDesignFinalizeTerritoryDesign AssessTerritoryWorkloadAssessTerritoryWorkload Form Initial Territories Analyze Planning and Control Unit OpportunityAnalyze Planning and Control Unit Opportunity Select Planning and Control Unit Select Planning and Control Unit

37. Estimating Potentials and Forecasting Sales THIS TOPIC TO BE COMPLETED AFTER Module 5

38. Market Potential – Maximum demand in a time period based on the number of potential users and the purchase rate. Industry Forecast – Total predicted sales for competitive arena. Company Potential – Company portion of industry potential (forecast) Company Forecast – Predicted sales for the competitive arena.

39. Forecasting Relationships

40. Estimating Potentials Buying Power Index MethodBuying Power Index Method –Sales & Marketing Magazine NAICS and Industry Census DataNAICS and Industry Census Data –North American Industry Classification System Published budgets or annual reportsPublished budgets or annual reports

41. 1999 Effective1999 Total Buying IncomeRetail Sales Total Population Percentage Percentage Percentage Buying Amount of United Amount of United Amount of United Power ($000,000) States ($000,000) States (000) States Index Total United States $4,621,491 100.0% $2,852429 100.0% 273,537 100.0% 100.0 Atlanta Metro 70,4651.524% 43,703 1.532% 3,807 1.391% 0.1.498 Table 7-1 Data Used to Calculate Buying Power Index What portion of the total market potential is in the given market area. http://www.salesandmarketing.com http://www.census.gov/epcd/www/naics.html

42. Qualitative Sales Forecasting Sales Force CompositeSales Force Composite Jury of Executive OpinionJury of Executive Opinion Leading IndicatorsLeading Indicators –Housing Starts –Interest Rates –Consumer Confidence Index –Stock Market Indicators

43. Quantitative Forecast Adjust for SeasonAdjust for Season Naïve ForecastsNaïve Forecasts Trend ForecastsTrend Forecasts Percentage ErrorPercentage Error Mean Absolute Percentage Error (MAPE)Mean Absolute Percentage Error (MAPE) Moving AveragesMoving Averages Exponential SmoothingExponential Smoothing Linear RegressionLinear Regression Turning PointsTurning Points

44. Calculating a Seasonal Index from Historical Sales Data Four-year Quarterly Seasonal Quarter 1 2 3 4 Average Index 149575373 58.0 0.73 2779885100 90.0 1.13 390899298 92.3 1.16 479628878 76.8 0.97 Four-year sales of 1268/16 = 79.25 average quarterly sales Year Seasonal Index for quarter 4 is 76.8/79.25 =.969

45. Naïve Forecasts This period’s forecast is the same as last period’s sales.

46. Trend Forecast Quarter 1 2 3 4 Sales 10 20 25 25 Rate of Change Forecast 30 30 % Rate of Change Forecast 40 31.25 Rate of Change % Rate of Change S3= S2 + (S2-S1) S3 = [(S2-S1)/S1 X S2]+S2

47. Percentage Forecast Error = Forecast -- Actual Actual MAPE = ∑ (forecast – actual) / actual n X 100% Mean Absolute Percentage Error Calculate % Error for each period and then take average

48. Calculate MAPE Quarter 1 2 3 4 Actual Sales 49 77 90 79 Forecast 60.2 72.1 % ErrorF3 = (60.2-90)/90 =33% % ErrorF4 = (72.1- 79)/79 = 9% MAPE = (33% + 9%)/2 = 21%

49. Moving Average= S1+S2+S3… n Forecast (S) = α X Current sales + (1-α) X Last Forecast Exponential Smoothing Linear Regression Y = mx + b

50. Forecasting with Moving Averages 123456 Actual sales497790795798 Seasonally adjusted sales676878817887 Two-period moving average forecast seasonally corrected67.57379.579.5 Three-period moving average forecast seasonally corrected717579 Two-period Moving AverageThree-period Moving Average F 3 = ( S 1 + S 2 )/2F 4 = ( S 1 + S 2 + S 3 )/3 = ( 67 + 68 ) /2 = ( 67 + 68 + 78 ) /3 = 67.5 = 71 Time Periods

51. Forecasting with Exponential Smoothing Alpha is always between 0 and 1.Alpha is always between 0 and 1. Calculate alpha to fit previous actual sales.Calculate alpha to fit previous actual sales. An alpha of 1 is equivalent to a naïve forecast.An alpha of 1 is equivalent to a naïve forecast.

52. Exponential Smoothing Quarter 1 2 3 4 Actual Sales 49 77 90 79 Smooth Forecast 60.2 72.1 If alpha =.4 SF3 =.4 X S2 + (1-.4) X S1 = 30.8 +.6X 49 30.8 + 29.4 S3 = 60.2 SF4 =.4 X 90 + (1-.4) X SF3 = 36 +.6 X 60.2 = 36 + 36.1 = 72.1

53. Figure 7-3: Fitting a Trend Regression to Seasonally Adjusted Sales Data 0 1 2 3 4 5 6 50 60 70 80 90 63.9 3.6 Y = 63.9 + 3.5 X Sales Time Period Linear Regression

54. Turning Points By definition breaks the mathematical model.By definition breaks the mathematical model. Turning points are best predicted by Qualitative Methods.Turning points are best predicted by Qualitative Methods.

55. How to determine the best method Download the spreadsheet Download the spreadsheet

56. Rate of Change % Rate of Change S3= S2 + (S2-S1) S3 = [(S2-S1)/S1 X S2]+S2 Moving Average= S1+S2+S3… n Forecast (S) = α X Current sales + (1-α) X Last Forecast Exponential Smoothing MAPE = ∑ (forecast – actual) / actual n X 100% Mean Absolute Percentage Error