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Transcript of Part Six: Measurement, Analysis, and Knowledge Management Copyright © 2009 Pearson Education, Inc....
Part Six: Measurement, Analysis, and Knowledge Management
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-1
Sales Management: Shaping Future Sales Leaders
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-2Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.
Turning Customer Information into Sales Knowledge
Chapter 13
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-3Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.
Learning Objectives
Identify the major elements of customer data integration
Explain how documented, accessible customer information benefits a firm’s various functional groups
Create sales forecasts using the various types of forecasting methods prominently implemented in sales settings
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-4
Forecasting Demand
Overestimating Leads to investing in manufacturing and distribution
assets the firm won’t need Example: Caterpillar construction equipment
Underestimating If manufacturing isn’t making enough of the product to
meet demand, door is open for competitors to launch “copycat” products and steal market share
Example: IBM Thinkpad laptop computers
Sales Management: Shaping Future Sales Leaders
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-5Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.
Knowledge Generated by the Sales Force
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-6
Customer Data Integration (CDI) Process
Customer knowledge competence: ability to gather, analyze, and utilize customer knowledge effectively at the organizational level
Customer data integration (CDI): technical process of gathering data and making it useful and available
Customer Data Integration Process
Acquire the DataSales dataMarket researchService data
Make the Data UsableFormat, clean, and merge data
Make the Data AvailableVia data marts, analytical software
Use the DataCreate forecastsBuild sales plansCreate pricingCreate marketing plans
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-7
Sales-Generated Knowledge: Manufacturing & Product Development
Manufacturing may rely on orders, subsequently manufacture product (furniture) May stockpile products until they’re sold Forecasts important either way
Reps know what their customers are asking for, provide R&D with recommendations for new products or different features Reps are often the first
to run across competitors’ new products
Can provide insight into what customers are willing to pay for
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-8
Sales-Generated Knowledge: Finance/Accounting & Marketing
Credit policies affect reps Loose policies = more sales, more
bad debts Tight policies = fewer sales, fewer
bad debts Reps can provide info so credit
policies are competitive Competition pricing, market
conditions, etc.
Reps contribute information before and after marketing campaigns Info before can help design good campaign
Info during helps determine if campaign is working Key term: any increase in sales due to a campaign is called lift
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-9
Sales-Generated Knowledge:Sales Management & Human Resources
Info about ease of selling product can lead to decisions Training What products are emphasized Push for price cuts, product enhancements How many reps to hire
Rep info can impact hiring plans Ensure enough employees at the right time Bad sales may = hiring more reps to improve sales, or
perhaps hiring freeze, possibly downsizing
Sales Management: Shaping Future Sales Leaders
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-10Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.
Sales Forecasting
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-11
Estimates Used in Sales Forecasting
SalesForecast / Quota
Based on estimate of market and sales potential, create sales forecast of either revenue or units the firm expects to sell
Allocate revenue or units to individual reps as sales quotas
SalesPotential
Maximum market share the company can reasonably expect to achieve
Typically represented as a percentage of a market’s total sales
MarketPotential
Total, industry-wide sales expected for a product category for a period of time
What can reasonably be sold by all companies in a market
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Market Potential, Sales Potential, Sales Forecast, and Sample Sales Quota
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-13
Estimating Market Potential
Derived demand: demand for a product is created by (or derived from) demand for a product further down the supply chain Can cause wide swings in demand for a product
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Factors Affecting Demand
Elasticity
Inelastic demand: there are few or no substitutes and people have to have it, no matter the price
Demand does not change if price changes
Laws & Regulations
Can increase costs associated with products and impose tariffs and trade restrictions on them
Social Factors
General fashions and trends within a society
Example: laptop colors Example: avoiding products from
country with reputation for failing to monitor quality
Demographic Trends
Example: generational differences Example: low birth rate = smaller
market for baby-related products
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Ethics in Sales Management
Sales forecasts have a cascading effect
Forecasts influence forecasts of suppliers
Forecasts influence stock price
Scandals: booking false sales to increase stock price Mattel (tentative orders as confirmed sales) Enron (forecasts of continued growth) Anonymous company (place fake orders, then cancel)
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How External Factors Can Affect Market Potential
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The Forecasting Process
Economic factors Technological
factors Government &
legal factors Social &
demographic factors
ExternalCustomer & distributor surveysMarket research conducted by other firmsGovernment-generated info related to economyExperts’ opinions
Look at the Marketplace
Estimate the Market Potential for the Industry
Look at Sales Potential: Gather Internal and External Info
InternalInfo generated by quantitative methods using sales dataSales mgrs’ estimate for their teamReps’ estimates of their salesExecutives’ opinionsFirm’s plans
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-18
The Forecasting Process
ExternalCustomer & distributor surveysMarket research conducted by other firmsGovernment-generated info related to economyExperts’ opinions
Look at Sales Potential: Gather Internal and External Info
InternalInfo generated by quantitative methods using sales dataSales mgrs’ estimate for their teamReps’ estimates of their salesExecutives’ opinionsFirm’s plans
Company-Wide Sales Forecast
Set Quotas for the Period
Forecast Sales
By product By territory By customer
type By time
period
For individual territories
For regions
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-19
Is Forecasting Easy?
70% of sales organizations have CRM systems
60% of sales leaders want to improve forecasting processes
50% have difficulty adjusting to market changes
49% have difficulty identifying best sales practices and sharing those
Problem isn’t availability of data – but of understanding!
Source: Jim Dickie, “Analyzing the Sales Process,” CRM Magazine, Oct. 2007, p. 10
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Forecasting Methods: Time Series Techniques, Trend Analysis
Group of statistical methods used to examine sales patterns over time
Trend analysis (naïve forecast): determining the rate sales have grown in the past and using that to estimate future sales Can be useful when changes in a market are few and not
very dramatic
Adjustments Moving average: rate of change for past few periods is
averaged Exponential smoothing: type of moving average that puts
more emphasis on the most recent period.
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Example of Trend Forecasts and Adjustments
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Forecasting Methods: Time Series Techniques, Correlational Analysis
Correlational analysis: form of trend analysis, forecasts are based on trends of other variables Leading indicator: variable that happens before sales
of the company’s product (housing starts) Regression analysis: includes a number of variables;
influence of each variable is estimated and weighted, and effects are summed to provide a single estimate of sales
Consumer spending correlates: variables that predict how much consumers will spend overall (Consumer Confidence Index)
Business spending correlates: variables useful to business in correlational analysis (NAICS)
Survey of Buying Power Estimates
Population by city
Retail sales By city Type of store Type of product
Effective buying income (spending money)
Annual projections and 5-year trends
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Available from Nielsen Business Media, through Sales & Marketing Management
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Other Forecasting Models
Response models: sophisticated statistical models that examine how customers respond to sales and marketing strategies
Market test: response model that’s especially useful when firms are trying to figure out how well a new product or service is likely to be accepted Company launches in a limited market to learn how the
market will react to the product, demand is extrapolated to full market
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Other Forecasting Techniques
Judgment techniques: involve judgments by someone of the actual forecast
Executive opinion: best-guess estimates of a company’s executives
Expert opinion: similar to executive opinion except that expert is usually outside of the company
Customer (and channel) surveys: ask customers (or distributors and retailers) how much they plan to spend
Sales force composite: ask members of sales force what they think they can sell
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-26
Self-Assessment Library
Go to http://www.prenhall.com/sal/ Access code came with your book
Click the following Assessments
I. What About Me?A. Personality Insights
5. How Well Do I Handle Ambiguity?
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-27
Limitations of Forecasting
Length ofHorizon
The longer the forecasting horizon is, the less accurate the forecast is likely to be
RapidChange
Don’t place too much emphasis on one forecast or one method
Likelihood of an accurate forecast is diminished, particularly if conditions are changing rapidly
DataQuality
“How many do you hope to sell?” vs. “How many will you sell?”
Customer data integration is important
Time andCost
Window of opportunity The longer it takes to get a forecast, the less time
you have to act on info before the forecasting period has passed and conditions change again
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-28
Guidelines for Forecasting
Use multiple methods1
Pick the right method for your business2
Use as much info as you can3
Plan for multiple scenarios4
Track your progress and adjust the forecast5
Discussion Question (#6)
For the following products and services, what factor(s) would you use to estimate market potential?a) Campbell’s Soup
b) Fossil watches
c) Pontiac sports cars
d) Bose Wave radios
e) Viagra
f) Calvin Klein men’s suits
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.4-29
Discussion Question (#7)
You just took over as the chief sales officer of Lombardi Trophy Co., a company you’ve worked at for almost 20 years
You know the firm’s sales forecasts are inaccurate because the company has annually added 20% to the quotas assigned to the firm’s salespeople, which collectively they have always met or exceeded
But you need an accurate forecast for various purposes, including budgeting
How would you change the situation so you get accurate forecasts?
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Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-31
Sales Manager’s Workshop
Your boss, regional VP, sends email
Revenue is down 10% this month, which is a poor way to start the quarter
I’d like a forecast from each of you (sales managers)
We’ll discuss Friday on conference call
Using Aplicor data set, create three different forecasts using different methods
Combine them into one brief PowerPoint presentation
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-32Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.
Caselet 13.1: Englander Container
Mfgs cardboard shipping boxes for moving and shipping companies
Also sells direct to companies that ship their own products (Procter & Gamble)
Sales figures are provided in textbook
Secured contract to provide containers for US government, can bid on special packaging for military
Currently has $100 million in 4 bids on military contracts to be decided in Q1 next year
Expect to bid on $300 million more decided later in year
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-33Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.
Caselet 13.1 (continued): Questions
1. Use two different trend analysis methods and determine how much the company will sell next year. How confident are you that this is an accurate
forecast? What additional information or methods would you
like to incorporate in your forecast?
2. Assume that the company is manufacturing at 90 percent of its capacity in order to meet its current sales levels. If it wins every U.S. government contract it’s bid on,
what impact will that have?
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-34Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.
Caselet 13.2: Freud Testing Services
Psychological profile testing for new B2B sales hires
Claims tests are accurate 90% of time
Sells through 22 independent distributors, retail tests for $95/person Sales / distributor range from $10,000 to $100,000 Average sales / distributor ~$22,000 Total sales ~$4 million annually
Owner wants to grow business another $1 million in 2 years
How? Adapting tests for retail salespeople? Different languages / different countries? Additional distributors?
Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.13-35Copyright © 2009 Pearson Education, Inc. Publishing as Prentice Hall.
Caselet 13.2 (continued): Questions
1. George Shannon, FTS owner, has called you and asked how to determine potential of each market
2. In a perfect world, how would you answer George?
3. Assuming George had no cash to spend, how would your answer change?
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