The Nature and Measurement of
Marketing Productivity in Consumer
Durables Industries: A Firm Level
Analysis
HAWKINS, DELL I, ROGER J. BEST AND
CHARLES M. LILLIS (1987), “THE NATURE
AND MEASUREMENT OF MARKETING
PRODUCTIVITY IN CONSUMER DURABLES
INDUSTRIES: A FIRM LEVEL ANALYSIS,”
JOURNAL OF THE ACADEMY OF MARKETING
SCIENCE, 15 (4), 1-8.
Authors
 Del I. Hawkins
Professor of Marketing

Various marketing Journals and Textbooks
 Roger J. Best

Associate Professor of Marketing

Journals and Textbooks
 Charles M. Lillis

Vice President of Strategic Marketing for US WEST
Inc.

Various Journals

Marketing executive

Purpose of the Article
 Develop a managerially relevant concept of
marketing productivity
 Construct an operational measurement of
marketing productivity-a validity issue
 Establish environment specific benchmarks
with which to compare the marketing
productivity of various businesses
Model Development
 How the authors develop the model step by step is
a good learning exercise (this is one of the reason I
have included this article in the reading list)
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Define the variables first
Explain conceptualization and limitation of variables
Identify their relevance in the area
Operationalize the variables-validity
Testing the model with credible data
Explain limitations
 Model has no meaning in isolation, relative to
what is the question
The Nature of Marketing Productivity
 Concept of Productivity: Output/Input
 Marketing productivity = marketing output
divided by marketing input
 Marketing Output = (Relative market share) x
(Relative Price)
 Marketing input= (Marketing Expenditures)
/(Sales)
 Percentage or ratio measures, not in absolute
dollars
Marketing Productivity
 Marketing Productivity Formula:
Relative Market Share x Relative Price
Marketing Expenditures/Sales
» Marketing Productivity Score (MPS) – In
isolation it has no meaning !
» Marketing Productivity Index (MPI)
PIMS Database
(now Marketing Science Institute)
 Sources of data: firms pay a fee to join
PIMS
 Self reported data, multiplied by an
unknown constant when supplied to PIMS
 Questionnaire is provided by PIMS
 Operational Definitions of Variables (ses
Table 1)
Variables Influencing Marketing Productivity
Variables
Influence
Relative Product Breadth (RPB)
+
Number of Competitors (NC)
-
Relative Product Quality (RPQ)
+
Relative Customer Size Range (RCSR)
+
Served Market Growth (SMG)
+
Number of Immediate Customer (NIC)
-
Importance of Auxiliary Services to End User
(IASE)
-
Frequency of Product Changes (FPC)
-
Purchase Amount Immediate Customers (PAIC)
+
Customization (C)
+
Construction of the Model
Firms
Correlation
Model
• Durables and Nondurables
• 135 Firms
• Correlation between Y and X1,….,X10
• Correlation between X1,….,X10
• Regression Equation Y= X1+………+X10
Correlation Analysis
Model Evaluation
 R² is significant
 Model is reasonably stable
 Durables, nondurables, split-half…..all
supports the model
 Supports the overall structure of the model
developed for the durables industries
 Variables that were collinear were removed
before implementing the model
Critique of the Article
 Positive Contribution:
 First of its kind
 Reasonable model
 Credible database
 Coming from industry
 Questionable Issues
 Limitation in variable definition
 Variability in the dataset
 Collinearity
 Future direction
Discussion Questions
 What is marketing productivity? What problems
do we face in measuring productivity? How can
we overcome them?
 What are the drawbacks/limitations of the
Hawkins et al.’s (1987) marketing productivity
score/index? Can we apply the index to measure
productivity in other industries? How?
 Write a critique of the article.