Fletcher, Stanley M.

English

Research Papers in Economics

USING TODAY’S INFORMATION:
PLANNING FOR TOMORROW’S VALUES
Chairperson: William Lesser, Associate Professor
Department of Agricultural Economics
Cornell University
Scan Data Research: The Status
by
Stanley M. Fletcher
Associate Professor
Department of Agricultural Economics
Georgia Experiment Station
University of Georgia
Experiment, GA 30212
In the last several years, every major
food industry trade association has had major
programs addressing scanning. The Food Mar-
keting Institute (FMI) has had annual industry-
wide conferences on scanning. The National-
American Wholesale Grocers’ Association
(NAWGA) and the National Grocers’ Association
(NGA) have also had similar conferences.
Thus, one would be hard pressed to find any-
one who does not view scanning and, in parti-
cular, scan data as “having enormous value.
BUT, in the same vein of thought, one would
in all probability not find any well organized
complete scanning research program investigat-
ing the wealth of information contained in
the scan data.
Prior to writing this paper, I had a com-
puterized literature search performed to find
any publications dealing with scarI data re-
search. In this search I excluded any Journaf
of Food Distribution Research publications
since I was already aware of them. To my
amazement, but in support of my earlier state-
ment, only one article was found. The article
was entitled, “New Gold Mines and Minef ields
in Market Research.” The authors discussed
the changes going on in marketing due to
split-cable technology and scanner data and
stressed the need to take full advantage of
the new micro-level experiments possible with
the new technology.
At this point in time, the first question
that should come to the reader’s mind is:
WHY? The answer is not a simple one nor
black and white as to why there is not a
concerted effort on scan data research. The
focus of the paper is on the status of scan
data research. Before delving straight into
this issue, a brief historical perspective on
scanning is presented. Then, an overview of
organized industry scanning research is given.
This is followed by private marketing research
firms and other research groups. Finally, the
general subject of what has been the research
as well as the problems and needs will then
be presented along with the conclusions.
Journal of Food Distribution Research February 87/page 41Scanning
Commercial scanning started in 1974
when Marshh supermarket in Troy, Ohio, in-
stalled one of the first scanners capable of
reading the UPC (Universal Product Code)
symbol. During this period of time, the dis-
cussion concerning scanning was centered
around the feasibility issue. That is, what
volume size retail food store could cost justify
implementing scanning. The savings generated
from scanning were delineated into two areas:
hard savings and soft savings. Hard savings
are those that result from improved speed and
accuracy from the scanner’s ability to identify
a UPC symbol and to retrieve the product
price from a computer file. Soft savings re-
late more to improved management information
and control, and generally accrue over time
“as a result of using scanner-generated infor-
mation that is processed through a computer.
The hard and soft benefit issues were
addressed three years ago by Fletcher et al.
(1984). Capps last year discussed the soft
benefits issue. The industry consensus is that
practically everyone accepts the feasibility of
scanning for the retail food store except for
some low sales volume retailers, On this lat-
ter point, Fletcher et al. (1986) published a
report addressing the feasibility issue for the
smaller retailers. They found, in general,
that if the retailers used the newer scanning
technology that scanning could be justified
economically. BUT, in spite of the information
available to retailers, one still does not see
widespread scanning. In fact, in an Executive
Report on scanning by Progressive Grocer,
the editor states that the retailers are being
divided into the “haves” and “have nets” as
far as scanning competency is concerned.
However, in the last several years the focus
of trade association meetings, seminars and
conferences haa shifted to scanner data and
the use of microcomputers.
Industry Scanning Research
Two major industry scanning research
projects have been undertaken to address the
issues of effectively utilizin scanner data.
The first project was ScanLab L (a trademark
of General Foods Corporation) in 1981. The
purpose of the project was to advance the
level of understanding of the retailer in effec-
tively using scanner data to improve merchan-
dising decisions. The products that the pro-
ject analyzed were detergent, dog food, sham-
poo and hair conditioner. They had matched
store panels where one panel was the control
group and the other was the test group which
utilized the scan data information. The test
stores which used the ScanLab information
had a significant improvement. The ScanLab
software is available through FMI but must be
used on a mainframe or a minicomputer.
The second scanning project was the
Pillsbury Scan Share Group which started in
the fall of 1982. The objective of this group
was to further the applications of scanner
data for merchandising decisions. They deline-
ated scanning data applications into three
general categories: tracking, analysis and
experimentation. This group also found signi-
ficant benefits from utilizing scan data in
merchandising dec~ions. However, three key
lessons were learned if the benefits are to be
achieved: 1) A close working relationship
must exist between the user of the information
and the data processor. 2) An investment
must be made in software development and
database development, 3) A company must
prioritize its scan applications.
Other Research Groups
In recognizing the potential benefits
from scanning, several private firms have
entered the scanner data market. Some of
the firms are Information Resources, Inc. Ad
Tel (Test Marketing Group), NPD, A. C.
Nielsen, Safeway’s Scanner Marketing Research
Services, ScanAmerica and SAMI. This list of
firms is not all encompassing. The major
focus of the private firms in utilizing scanner
data has been to track advertising’ effects.
Recently, they have been tying the split-cable
technology with the scanner data. Besides
these private firms, there are other groups
investigating and utilizing scanner data. The
individual retail food companies have been
some of the leaders. They have done the
work either by themselves, with a consultant
or with a researcher from an academic institu-
tion. However, this type of work has been
February 87/page 42 Journal of “Food Distribution Researchbasically “proprietary.” Besides the retail
food companies, academic institutions have
started research programs into the uses of
scanner data. Some of the institutions are
the University of Chicago, Cornell University,
University of Southern California, University
of Illinois, Texas A&M University and the
University of Georgia.
Research Thrusts
Some of the research thrusts have already
been addressed in the industry scanning re-
search section. This research was of an in-
dividual store or chain need. Methods to
utilize scanner data in order to address other
needs of the retail food store operator are in
the areas of shelf allocation, automatic reor-
dering, price sensitivity, product mix, trade
area analysis, etc. Once again, this work is
generally of “proprietary” nature.
Another area of research thrust has been
measuring the advertising effect on product
movement. Information Resources, Inc. (IRI)
has been one of the industry leaders in this
area of marketing research. They have inte-
grated the technologies of split-cable TV,
UPC scanner and computers. Using these
technologies, one can direct specific advertis-
ing toward a particular segment of the popula-
tion and then measure product movement as
well as obtain sociodemographic information
on the purchasing households. The advertising
work has also been proprietary.
One of the first scanner data research
projects was done by Jourdan. Her work won
her the FDRS Applebaum Award. Her study
was to estimate own-price and cross-price
elasticities of demand for a group of related
beef cuts using scanner data. Her results
were mixed since she did not have any house-
hold information in her model.
Two years ago MacNeary of IRI (1985b)
presented a meat study using scanner data at
FMI’s 2nd Annual Industry Wide Scanning
Conference. He divided IRI’s scanner panel
households into light and heavy beef buyers.
Thus, he was able to examine purchasing
dynamics. MacNeary did not find any differ-
ential impact on the two household groups
from promotions. Thus, he concluded that it
seems that one should not look to buyer-group
segments as a focus of promotional programs
but rather one should emphasize product areas.
With the increased use of scanner data
for merchandising decisions, the accuracy of
the data is paramount. If the data is errone-
ous, the results will be inaccurate which could
lead to inappropriate decisions. Thus, Lesser
and Smith did a study on the accuracy with
which scanning data actually reflect disappear-
ances. In their conclusions they found that,
basically, scanning data provide a quite accur-
ate measure of aggregate item sales over a
multi-week period. However, for individual
items for a particular store for a one-week
period, they felt that one should exercise
caution.
A recent major research thrust has been
with the National Dairy Promotion Board.
They have been charged to evaluate the effect
of advertising on sales of dairy products.
One component of their research program has
been to utilize split-cable scanner data in
evaluating advertising effect on sales of fluid
milk, cheese and butter. A. D. Little was
given the contract for the analysis. Initially,
the researchers used analysis of variance pro-
cedures to compare the test ‘and control
household panels. Later on, they did an econ-
ometric analysis. However, in their report
they state that the results are inconclusive.
But, further work is being done using the
split-cable scanner data. The Meat Board is
also following a course similar to that of the
Dairy Group.
Problems and Needs
One obvious criterion for performing
scan data research is that the items that one
desires to examine must have UPC symbols.
Another criterion is that one must decide
which items to examine first. In a store with
a minimum of 10,000-15,000 UPC items, one
would be immediately doomed to failure if
some setting of priorities were not done.
However, even with this many items UPC-
coded, there are some critical products and
categories that do not have UPC codes. For
example, random weight items (e.g., cheese
Journal of Food Distribution Research February 87/page 43and produce) do not have UPC codes. While
meat has UPC codes, such codes are not in
widespread use. Thus, many retailers have
developed their own price look-up number for
scanning these non-UPC-coded items since
they constitute a significant proportion of the
store sales.
As previously mentioned in the Lesser
and Smith study, data accuracy is critical. If
the data is not accurate, the research is mean-
ingless. Along the same lines is the question
of the accuracy of split-cable scanner data.
Some items may not be purchased at a scan-
ning store. For example, if a household pur-
chases milk at a convenience store all milk
purchases in that household may not be col-
lected by scanning equipment. Also, if a con-
sumer forgets the household ID card when
shopping, none of those particular purchases
will be recorded.
Even though there are some problems
with split-cable scanner data, let’s examine
the flip side to this. What have been the
data sets used to do consumer research? The
major ones are the National Household Food
Consumption Survey by the USDA, Consumer
Expenditure Survey by the Bureau of Labor
and MRCA survey data. All these databases
are based on diary surveys which consumers
fill out after making purchases. The question
that comes to mind is: Just how accurate is
this type of data? Based on a study by
MacNeary (1985a), the answer is not reassur-
ing. He found that household information
based on recall was significantly different
from the observed behavior. Furthermore, he
found that one’s memory seems to be associ-
ated with frequency of consumption rather
than with frequency of purchasing.
Given these potential problems, are there
any alternatives? One possible alternative is
to use ScanAmerica’s approach. A fully port-
able wand resembling a large laundry marker
scans the UPC symbol of items purchased by
a household independent of source of purchase.
Each household has a wand. Periodically, the
information stored in the wand is downloaded
to a central comcmter. One obvious drawback
to this approach is that price information
not being recorded. Another alternative is
February 87/page 44
is
to
have a procedure that could read scanner and
non-scanner tape receipts.
Assuming that data problems could be
corrected, financial considerations have to be
taken into account. The cost of doing a com-
prehensive research project is prohibitive to a
research institution without outside financial
support. For example, the National Dairy
Promotion Board spent over $1 million for one
year’s worth of split-cable scanner data of
dairy purchases for only a couple of markets.
Furthermore, the data was in raw form which
must be transformed into a usable data set.
This latter step takes an enormous amount of
time, manpower and money.
Conclusions
Retail food store operators see the use
of scanning data as a means to stay competi-
tive and improve the bottom line. For exam-
ple, the widespread interest and use of a DPP
model illustrates the concern about competi-
tiveness and the bottom line, Integrating
scanner data with the DPP model will enhance
an operator’s position. In addition to the
retail food store operator, commodity associa-
tions want to know how their product is per-
forming in the market and whether advertising
is helping them. The bottom line is that they
want information which scanner data can pro-
vide. Food market projections done at the
Georgia Experiment Station, University of
Georgia, are sensitive to parameter estimates.
Incorrect projections could lead to inaccurate
policy implications. All of this points to the
fact that the need for scanner data is tre-
mendous. Researchers need the data available
to them, but a concerted effort is required.
This year a new regional research project
(NEC-65) has been approved. Use of scanner
data is a key component in the project. How-
ever, for this project to be effective, the
cooperation of trade associations, industry
and government is needed. In the meantime,
one potential method of aiding scanner data
research is for the USDA and the National
Dairy Promotion Board to make the dairy scan-
ning database available- -within appropriate
guidelines--to research institutions.
Journal of Food Distribution ResearchReferences
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Journal of Food Distribution Research February 87/page 45

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