The fuzzy art of decision science
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Keywords: customer decisioning, customer relationship management, fuzzy decisioning, decision support, opportunity prioritisation, campaign planning
The fuzzy art of decision science Richard Turner Received (in revised form): 5 November 2002
Abstract Over the past 20 years there has been massive investment in management information systems, data warehouses, enterprise resource planning systems and analysis technology. However, considering these massive changes, customer decisions are still made using similar techniques. Many customer decisions are made using sequential rules embedded within campaign management, collections, new business and other customer processing systems. But customer decisioning is not just an analytical process based on statistics, since it also requires the input of experts and knowledge about other factors that cannot always be based on past experience — for example, the future actions of competitors or changes in business priorities. However, many organisations have found that sequential rules are often difficult to maintain, since they require specialists who change and manage the code and consequently the systems do not always reflect the many different factors that should be considered in making a decision. This paper addresses the role of customer decision making in organisations and how technology supports this task. It examines whether decisioning technology has moved forward to take advantage of the massive quantities of data and enormous computing power now available, and whether a ‘fuzzy decisioning’ approach would provide better decisions in certain situations. A fuzzy decisioning approach would weight the significant factors in the decisioning process to make a particular outcome more likely. By contrast, a rule-based approach would split groups of customers into different populations based on a logical condition. After reading the paper, readers may also wish to reflect on whether customer decision making is actually a science or an art!
Background
Richard Turner Experian UK Ltd Embankment House Electric Avenue Nottingham NG2 1RQ, UK Tel: +44 (0)115 968 5009 Fax: +44 (0)115 968 5004 E-mail: [email protected]
It was only at the end of the 1970s that the first UK decision support systems were introduced by mail-order companies to make decisions on new customers for account facilities. By the end of the 1980s, most retail banks had taken their first steps in using customer analytics to assist in the automation of operational processes such as pay/no-pay decisions or collections. In the 1990s, many ‘business to consumer’ organisations recruited large teams of analysts to help manage customers more efficiently using statistical models. These models help organisations manage credit risk, retain customers, cross-sell and up-sell new products and services and detect fraudulent behaviours. This enabled banks to
& H E N R Y S T E W A R T P U B L I C AT I O N S 1 4 7 8 - 0 8 4 4 . I n t e r a c t i v e M a r k e t i n g . V O L . 4 N O . 3 . PP 243–256. JANUARY/MARCH 2 0 0 3
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