Consumer packaged goods are small, non-durable items that are generally bought at the grocery store. These might include soda, breakfast cereal and laundry detergent. Like most retailers and manufacturers of consumers’ goods of any type, the consumer packaged goods industry is beginning to use micro-marketing techniques (Buxton 1993). Through using a sophisticated combination of databases and manipulation techniques, product marketing programmes can be developed at the retail chain level. In the US, almost all grocery stores use check-out scanners. These scanners read a bar-code on each product and automatically provide the price of the product. This is convenient for stores because they can change the price of the product (such as for a sale) without having to re-tag each item. Not only is this convenient for stores, but because of this process, a very rich database of what brand’s products are purchased at what stores is generated. These data are aggregated into approximately 50 “scanner markets” that cover various portions of the US. By combing these data with the demographics that tend to drive product demand, such as age and income, a buying power index (BPI) can be modelled for stores. The BPI indicates how much of various products could be sold at that store. By knowing a store’s BPI, the retailer can improve the product mix (micro-marketing) to “push through more product” – to use the industry jargon.
Among fast-food chain restaurants such as McDonald’s and Burger King, the most visible and vocal users of GIS are at Arby’s. Among a variety of applications used at Arby’s is one that uses drive time to establish the likely trade area for an existing or potential store (Freeling 1993). In the fast-food business, customers are likely to be attracted more to the convenience of the product than to its gourmet appeal. It is, therefore, important to look at a trade area from the perspective of drive-time accessibility. Like many retailers, Arby’s personnel know how long someone will drive to access their product. In addition, they are familiar with the demographic characteristics of their typical customers. By analysing the demographics of a trade area established by using drive times, the likely sales performance for a store can be modelled. Arby’s is careful not to “cannibalize” an existing store when developing a new store. Cannibalizing means taking customers from one of their existing stores. Cannibalization should be avoided since a new store should increase overall business, not spread it around. By the same token, they are very eager to take away their competitors’ customers, and so they carefully analyse their competitors’ existing locations in comparison with their own.
Levi Strauss & Company (LS&Co) is a good example of a product retailer that has begun to use geographical technology to customize “product mix”, or the combination of products available in specific stores (Allen 1993). LS&Co is one of the world’s largest clothing manufacturers, and sells many product lines in addition to Levi’s jeans. Unfortunately, the company’s sales had been lagging significantly primarily as a result of mergers, acquisitions, price wars and significant retailers such as GAP chain creating their own product lines instead of selling LS&Co’s products. Continue reading GIS FOR RETAIL AND PRODUCT MIX – GIS for Business and Service Planning
It is highly likely that the insurance industry will soon face similar regulations to those already faced by the banking industry (Mertz 1993a). The reporting is likely to be at the zipcode (postcode) level. However, since this is in the future, this section on insurance will focus on current applications: risk assessment and avoidance. In the US, natural disaster after natural disaster has occurred over the last four years, bringing the total insurance industry’s bill to $34 billion (Mertz 1993b). Because of this, the industry has begun seriously to consider how it underwrites policies. The Oakland fire, Hurricane Andrew and the floods and other catastrophes of the summer of 1003 each pointed out the need for greater underwriting care. Insurance companies are beginning to realize that they must either refuse to insure properties that are at great risk from natural disasters, or justify larger premiums for doing so, or clearly identify precise areas in which property damage may be partially reimbursed from other sources. For example, the cross-hatched areas in the figure are wind-pools: insurers who write property-damage policies in these areas may be partially reimbursed by a state fund. Continue reading GIS FOR INSURANCE – GIS for Business and Service Planning
Perhaps the most important use of GIS in the banking industry is regulatory compliance (Tavakoli A. 1993). The Community Reinvestment Act (CRA) and the Home Mortage Disclosure Act (HMDA) are both laws which were passed in order to ensure that the banking industry does not practise “red-lining”. Red-lining is the illegal practice of geographically discriminating against groups (primarily minorities) by refusing to meet the credit needs of customers. For example, if a bank has a branch in an area and accepts deposits from customers within that area but refuses to lend money to those customers, that is considered red-lining. Red-lining reporting is done at the census tract level, making it an ideal application for business geographics. Banks use GIS to analyse whether they are guilty of red-lining, and if not, to help prove to regulators that they are not. Theoretically, if they do find that they are guilty of red-lining, they can use GIS to market to specific groups of customers in order to increase their lending activities within an area: I say “theoretically” because I have not heard of a bank that has admitted to using GIS this way since to do so would also be to red-line in a different way, which would also be against the law. Continue reading GIS for BANKING – GIS for Business and Service Planning
GEOGRAPHY AS THE BASIS OF GIS
In the rush to create bigger and better technical solutions, many in the GIS industry tend to forget that the discipline known as “geography” is the basis of GIS. GIS provides nothing more than the opportunity to manipulate and analyse geographical phenomena using automated systems. In fact, Michael Goodchild, director of the US National Center for Geographic Information Analysis (NCGIA) quite “recently” suggested (Goodchild 1992) that the acronym GIS should be understood to stand for “geographic information science”. This new definition would place more emphasis on analysis of “geographic information” and less on “system”.
The automobile industry is a sector that has long recognized the importance of geographical planning and analysis. All the main auto manufacturers distribute their products to the market via a network of franchise dealers. These dealers are independent businesses but are allocated an exclusive geographical territory to which the manufacturer agrees not to assign any other dealer, subject to the existing dealer meeting certain performance criteria. Clearly most manufacturers aim to maximize their market share and profitability in their market. From analysis of the voluminous amounts of registration data it is clear that there is a very strong relationship between market share and dealer location. In other words the more dealers the manufacturer appoints. The greater the likely market share. However, this is traded off against the fact that as market share increases there are diminishing returns and the sales of each dealer reduce, thus affecting individual dealer profitability and, possibly, the scope for retail price discounting. As a consequence, manufacturers are trying to find a balance between maximizing market share whilst at the same time ensuring that each individual dealership is a profitable business in its own right.
Achieving this balance requires a thorough understanding of existing market performance and the ability to examine alternative scenarios through an intelligent GIS approach. Continue reading Case Study – GIS IN THE AUTOMOBILE INDUSTRY – GIS for Business and Service Planning