Page 156 - DCAP208_Management Support Systems

Unit 9: Data Mining

Notes
Although Jaeger has only had the system since June, it already expects a return on investment
in its first financial year. Hearn says, “Data mining is widely accepted as having one of the
fastest returns on investment of any technology. We are still in the early days in terms of
assessing the benefits, but we are almost double-counting our results to check they are
right.”

One of the earliest discoveries was that theft by employees was only a small part of total
losses at Jaeger.
“We have not gone out en masse and started arresting staff members for fraud, but we
have identified considerable numbers of erroneous transactions. That is not to say that
they are all fraud,” explains Hearn.

Data mining is helping the clothing retailer to manage its stock, thereby reducing the
need for markdowns when items go out of season and reducing the number of items that
go missing altogether.
In a recession that has already claimed the scalps of established retailers such as Woolworths
and MFI, any initiative that helps a retailer conserve cash will receive management support.

“Data mining is even more important now in terms of being able to understand margin
erosion. Shrinkage is the last free margin on the table. We have got to keep the stock
current,” says Hearn.
At the start of the data mining project, Jaeger forecast that it would make a return on
investment within six to nine months of the project going live. That target will be met.
Jaeger now expects both a significant improvement in margins and a substantial benefit to
its net profits.

“The sheer opportunities to improve margin - it’s not just about fraud, it’s about putting
the wrong stock in the wrong place at the wrong time. As a result, the decision to go with
data mining was very quick. I had no resistance from Jaeger,” Hearn says.
In Jaeger’s case, the difficulty with implementing its data mining application did not come
from the management it came from the complexity of setting up data feeds between
Jaeger’s existing store applications and its new centralised system. The company decided
to buy a data mining application in the summer of 2007.

“It was nearly a year,” says Hearn. “It was nothing to do with IDM, but to do with Jaeger.
Our data was very complicated because we have had so much in-house development of
our systems. For instance, at just one meeting, we had to review at line level the data we
used in over 800 fields.”
Jaeger’s data mining project will make a positive contribution to profits at the most
important part of the business cycle. As the recession worsens in 2009, retailers will need
to develop similar projects that produce rapid returns on investment those that make
sustained improvements to net profits year after year will stand the best chance of winning
management approval. As money strains lead more customers and employees to steal
from retailers, applications that can reduce theft will become increasingly important.
How Data Mining Gathers Information?
A data mining application becomes more powerful if it uses a greater number of feeds
from the retailer’s other systems. LossManager was built in the Microsoft Development
Environment and was written in C++ so it can be used to accept feeds from as many
different systems as possible.

Contd....

LOVELY PROFESSIONAL UNIVERSITY 149