Data processing: financial – business practice – management – or co – Automated electrical financial or business practice or... – Discount or incentive
Reexamination Certificate
1998-07-31
2003-06-24
Hafiz, Tariq R. (Department: 2163)
Data processing: financial, business practice, management, or co
Automated electrical financial or business practice or...
Discount or incentive
C705S007380, C705S002000, C705S002000, C705S001100, C705S500000
Reexamination Certificate
active
06584447
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates generally to business performance forecasting, and more particularly to weather adapted, business performance forecasting.
2. Related Art
A. Historical Perspective of Retailing
The retail industry has historically been influenced by the shape of the times. For example, the retail industry is impacted by war and peace, lifestyle changes, demographic shifts, attitude progressions, economic expansion and contraction, tax policies, and currency fluctuations.
The period from 1965 to 1975 was marked by growth and segmentation in the retail industry. New types of stores such as department stores, specialty stores, and discount stores appeared, increasing competition in the retail industry. One result of this growth was a decrease in gross margin (sales price—cost of goods sold). Another result was a shifting of supply sources. Originally, merchandise was supplied exclusively by vendors. However, segmentation and growth resulted in specialty chains and discounters manufacturing merchandise in-house (commonly known as vertical integration).
The period from 1975 to 1980 was marked by disillusionment and complexity in the retail industry. Inflation and women entering the work force in significant numbers resulted in a more sophisticated consumer. Many retailers began to rethink the basics of merchandising in terms of merchandise assortments, store presentations, customer service, and store locations. Other less sophisticated retailers continued on an undisciplined and unstructured policy of store growth.
The period from 1980 to 1990 was marked by recovery and opportunity in the retail industry. An economic boom stimulated consumer confidence and demand. This, coupled with the expansion of the previous period, paved the way for the retail industry to overborrow and overbuild. With their increased size, retailers became increasingly unable to manage and analyze the information flowing into their organizations.
B. Retailing Problems and Opportunities of Today
The problems and opportunities facing the retailer fall into two categories of factors: (1) external factors; and (2) internal (or industry) factors. External factors impacting the retail industry include, for example, adverse or favorable weather, rising labor costs, increasing property costs, increased competition, economics, increasing cost of capital, increasing consumer awareness, increasing distribution costs, changing demographics and zero population growth, decreasing labor pool, and flat to diminishing per capita income.
Internal (or industry) factors affecting the retail industry include, for example, large number of stores (decentralization), homogeneity among retailers, continuous price promotion (equates to decreased gross margin), decreasing customer loyalty, minimal customer service, physical growth limitations, and large quantities of specific retailer store information.
Growth and profitability can only be achieved by maximizing the productivity and profitability of the primary assets of the retail business: merchandise (inventory), people, and retail space. The above external and industry factors have added to a retailer's burdens of maintaining the productivity of these assets.
Of the three primary assets, merchandise productivity is particularly important due to the limiting effect of external and internal factors on people and space productivity (e.g., physical growth limitations and high labor costs). Merchandise productivity can be best achieved by maintaining effective mix of product in a store by product characteristic (merchandise assortments).
To achieve more effective merchandise assortments, a retailer must have a merchandise plan that provides the retailer with the ability to (1) define, source, acquire, and achieve specific target merchandise assortments for each individual store location; (2) achieve an efficient, non-disruptive flow from supply source to store; (3) maintain store assortments which achieve anticipated financial objectives; and (4) communicate effectively across all areas of the business to facilitate coordinated action and reaction.
Such an effective merchandise plan must consider all possible external and industry factors. To obtain this knowledge, a retailer must have responsive and easy access to the data associated with these factors, referred to as external and industry data, respectively. To assimilate and analyze this data, which comes from many sources and in many formats, retailers began utilizing management information systems (MIS). The primary function of the MIS department in the retail industry has been the electronic collection, storage, retrieval, and manipulation of store information. Mainframe-based systems were primarily utilized due to the large amount of store information generated. Store information includes any recordable event, such as purchasing, receiving, allocation, distribution, customer returns, merchandise transfers, merchandise markdowns, promotional markdowns, inventory, store traffic, and labor data. In contrast to the extensive collection and storage of internal data, these systems, did not typically process external data. Rather, this non-industry data was simply gathered and provided to the retailer for personal interpretation.
Since understanding of local and region level dynamics is a requisite for increased retailing productivity, retailers would essentially feed store information at the store level into massive mainframe databases for subsequent analysis to identify basic trends. However, the use of mainframes typically requires the expense of a large MIS department to process data requests. There is also an inherent delay from the time of a data request to the time of the actual execution. This structure prevented MIS systems from becoming cost effective for use by executives in making daily decisions, who are typically not computer specialists and thus rely on data requests to MIS specialists.
FIG. 37
illustrates a block diagram of a conventional MIS system architecture used in the retail industry. Referring to
FIG. 37
, an MIS architecture
3701
captures store information (one form of internal data) and electronically flows this information (data) throughout the organization for managerial planning and control purposes.
At point of sale
3704
, scanners
3708
and electronic registers
3710
record transactions to create POS data
3706
. These transactions include data related to customer purchases, customer returns, merchandise transfers, merchandise markdowns, promotional markdowns, etc. POS data
3706
is one form of store information
3716
. Store information
3716
also includes other store data
3712
. Other store data
3712
includes data related to receiving, allocation, distribution, inventory, store traffic, labor, etc. Other store data
3712
is generally generated by other in-store systems.
Store information
3716
is polled (electronically transferred) from point of sale
3704
by headquarters, typically by modem or leased-line means
3717
. POS
3704
represents one typical location (retail store). However, MIS architecture
3701
can support multiple POS locations
3704
.
A data storage and retrieval facility
3720
receives store information
3716
using computer hardware
3722
and software
3724
. Data storage and retrieval facility
3720
stores store information
3716
. Store information
3716
is retrieved into data analyzer
3727
. Data analyzer
3727
shapes and analyzes store information
3716
under the command of a user to produce data, in the form of reports, for use in the preparation of a managerial plan
3730
.
In the 1970's and 1980's, retrieval of store information
3716
into data analyzer
3727
and the subsequent report generation were manually or electronically generated through a custom request to MIS department personnel. More recently, in response to the need for a rapid executive interface to data for managerial plan preparation, a large industry developed in Executive Information Systems (EIS). Referrin
Brown Tim
Fox Frederic D.
Pearson Douglas R.
Senst Barb Frutchy
Weinstein Syd
Hafiz Tariq R.
Planalytics, Inc.
Robinson-Boyce Akiba
Sterne Kessler Goldstein & Fox P.L.L.C.
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