Constraint-based versus rules-based logic in web product configurators
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¶ … Logic-Based Configurator on the Web, authored by McGuiness, Isbel, Parker, Patel-Schneider, Resnick and Welty (1998). The authors are researchers at AT&T Bell Labs, MIT, and Vassar College, and together the authors posit that a more constraint-based approach to defining online configuration logic through an abbreviated set of constraint linkages that comprise collectively an engine make more sense than having a vast library of rules that guide the definition of a given product under consideration by a customer using web-enabled tools. The authors, while not specifically discussing the variations in rules-based vs. constraint-based configuration logic, point towards the growth of the latter mainly as a result of the need for simplification of complex configuration as is evidenced by the authors' research at AT&T Bell Labs experimenting with telecommunications products configuration logic. In product configuration arena the development and execution of telecommunications configurations are orders of magnitude more complex than many other products' configuration logic, trucks and buses included. The only complexity that approaches telecommunications is the definition of aircraft assemblies, and many companies rely not on configuration software engines but instead use Product Lifecycle Management (PLM) in conjunction with Manufacturing Execution Systems (MES) all layered into production and planning systems to accomplish the same result at a much higher level of abstraction necessary for aircraft production.
The authors deserve credit for their foresightful analysis of the migration from rules-based to constraint-based web-based configuration and the need for included large nested object structures corresponding to highly structured and complex, interconnected configurations. Today this is called nested configuration logic, and is critical for the development of constraint-based logic in configuration engines now increasingly being used across the Internet. The authors also accurately call out of the need for more extensive reasoning components, support for explanation generation, and the critical need for knowledge management tools.
Critique of the Article
What is missing from the article are several key points, the two most glaring are the impact product configurators have on the financial performance of companies over time. What has since been proven from the growth of constraint-based configurators is the ability to tie back the financial performance of a company directly to the influences of their configuration strategy on customer satisfaction. The following table, derived by Columbus (2003) during his research of the impact of configurators on the global performance of companies adopting constraint-based configuration engines, shows that a company's entire value chain can be positively influenced by the growth of configurators as part of their online selling efforts. The authors, working in MIT, AT&T Bell Labs, and Vassar, concentrated only on telecommunications configuration challenges, yet if they would have opened up the scope of their research they may have found the correlation of configurator performance on financial results for a company.
Areas of Measurement
Baseline: What to Measure
Example of Benefits
Company-specific
Project costs and expenses
Use as a baseline for defining ROI
Number of orders per year
Determine configuration's impact on inventory turns
Current inventory and costs
Inventory turn savings
Customer Data
Lifetime cost per customer; avg. deal size by customer
Sales
Order cycle time
Order cycle times reduction of 65% or more recorded with mftrs contacted
Cost of Sales
Days Sales Outstanding reduction from 60 to 29 days on average
Cross-sell and up-sell revenue
Increase of 33% on aggregate
Average sales price per order
Increase from 9% to 26%
Quote and Order
Average costs to complete an order
95% reduction in cost per order
Special Pricing Requests
Over 100% ROI on automating Special Pricing Requests
Bad or incomplete orders
Incomplete order reductions of 20%
Customer Service
Number of customer complaints
98% reduction in cost of simple requests
Revenue lost to churn
60% when cross-selling is used with quote-to-order
Number of calls on order status
Median level of 500 per week to 70
Warranty and Returns
Reduction in warranty cost on customized products
10% reduction at a minimum
Labor cost reductions
Decrease order re-work from 15% to 2%
Enhancements to Readers' Knowledge
The article reviewed adds to the knowledge of readers interested in the progression of constraint-based configurators relative to their rules-based counterparts, and also provides a good foundation for seeing how telecommunications systems drove the development of nested configuration logic. The reader also get a good sense of where the authors see the growth trajectories of these technologies moving more into transactional workflows (they were right) and the need to have greater integration at the knowledge management level (also correct). The authors could have brought in more of the aspects of the use of the evolutionary role of rules-based configurators to the role of catalog and content management, which became the basis of guided selling and assemble-to-order, which led to the revolution in e-commerce mass customization.
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