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Business Cases and Data Mining for Rules Induction

  • March 01 2002, 1:00am EST

Business rules are fundamental to developing and implementing both processes and systems for effectively managing customer information. They provide the impetus, rationale and platform for change ­ allowing businesses to adapt when rules are violated and to capitalize on opportunities when rules are robust. The process of business rules induction is distinctly different from and necessarily informs the technologies that implement the rules. Business rules are best derived from a combination of a top-down approach or process built upon sound hypotheses or business cases, and a bottom-up or data- driven approach.


The process of business rules induction entails implementing rounds of iteration between business cases and data mining, with the goal being to formulate a methodology to generate rules which will govern the manner in which information systems ultimately manage the business and the customer experience. Business cases provide a framework for applying data mining techniques to derive rules. Imbedding efforts in a "real world" or applied context helps identify and evolve the data and information needs upon which sound infrastructures are built for managing customer relationships.

The creation of business cases requires a thorough understanding of the business and its key drivers. Analysts and business users must work together closely to generate business cases and operationalize the required metrics. The business case approach to rules induction builds upon learnings in iterative fashion, employing a phased project methodology that allows for learnings to shape and influence strategic direction and decision making while providing insights to ongoing platform development.

To effectively employ the business case and data mining approach to rules induction, the following practices are recommended:

Start small and work through the whole process by employing business cases. Because of the scope and complexity of database projects ­ with multiple entities, constituents, data sources, delivery channels and applications to be considered in solutions ­ it is difficult to articulate a strategic vision while integrating the complex dynamics of tactical deployment. A challenge is to keep near-term goals and project management issues clearly in sight, while simultaneously developing the larger vision. The business case approach meets this challenge by:

  • Providing a business context that is both manageable and meaningful;
  • Allowing solutions to be built in an iterative fashion, continually refining processes and incorporating learnings along the way; and
  • Keeping users and key stakeholders engaged and informed.

Employ data mining for rules induction. The need for generating and evolving a set of business rules based on relevant patterns in the data is fundamental to enabling personalized communications and services across channels. Effective solutions require a set of rules that facilitate the automation of processes, are flexible and update as conditions change, and that implement best business practices across systems and channels. Such rules-based solutions are inherently data-driven and must be derived from data mining guided by a set of tenable hypotheses imbedded in the business context.

Leverage current capabilities and knowledge while anticipating and preparing for future requirements. The need to provide meaningful intelligence while larger solutions are in development, and to anticipate user needs in advance, dictates that current efficiencies and knowledge be capitalized and expounded upon. The key is to define a set of standard procedures for generating and evaluating relevant and timely business cases that is consistent, replicable across situations, valid and reliable. For a methodology to be effective, it must: accurately identify data, meta data and rules that are critical the business and to strategic initiatives; and do so in a manner that is consistent across time, functions and situations.

Inform and refine current key projects and initiatives by using them as tutorials or practicals. Continuously educating the user about the benefits of the approach through the use of current projects and strategic initiatives as tutorials will elicit their needs as well keep them engaged and informed. This will also enhance key projects and initiatives through the systematic evaluation of project objectives. A dual purpose is therefore being served of helping to generate business rules and refine processes for ongoing infrastructure development, and providing important information to business users in the interim. It is also important to state the rules themselves in the language of the business user, although rules are operationalized in the language of analysts and developers. Therefore, rules induction requires a continuous dialog between users, analysts and developers ­ business users to generate the business cases for context, analysts for data requirements and computational rules, and developers for implementation through declarative rules.

The business case approach to rules generation focuses on the information needs of the business user in managing customer relations and the cross-functional similarities and differences in those needs. It enables a greater understanding of the current business situation and is intended to stimulate thinking about possible directions to take to maximize opportunities and to avoid pitfalls when planning information solutions. By starting with and evolving applied cases using effective data mining techniques, valuable solutions to information problems can be found which will provide users with critical ongoing information while also providing key insights into ultimate solutions.

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