DSpace Collection: Virtual Customer (VC)

Metrics Thermostat

Thu, 28 Jun 2001 22:58:59 GMT

Title: Metrics Thermostat

Authors: Hauser, John

Abstract: The explosion of information and information technology has led many firms to evolve a dispersed product development process with people and organizations spread throughout the world. To coordinate such dispersed processes managers attempt to establish a culture that implicitly rewards product development teams based on their ability to perform against a set of strategic metrics such as customer satisfaction, time to market, defect reduction, or platform reuse. Many papers have focused on selecting the right metrics and establishing the culture. In this paper we focus on a practical method to fine-tune a firm's relative emphasis on the metrics that they have chosen. In particular, we seek to advise a firm whether to increase or decrease their emphasis on each metric such that the change in emphasis improves profits. Using a thermostat analogy we apply an adaptive control feedback mechanism in which we estimate the incremental improvements in priorities that will increase profits. Iterations of adaptive control seek to maximize profits even if the environment is changing. We demonstrate the metric thermostatâs use in an application to a firm with over $20 billion in revenue. In developing the metric thermostat we recognize that there are hundreds of detailed actions, such as the use of the house of quality and the use of robust design, among which the product development team must choose. We also recognize that they will act in their own best interests to choose the actions that maximize their own implicit rewards as determined by the metrics. Management need not observe or dictate these detailed actions, but rather control the process by establishing the culture that sets the implicit weights on the metrics. The thermostat works by changing those implicit weights. We define the problem, introduce the adaptive control mechanism, modify âagencyâ theory to deal with incremental changes about an operating point, and derive methods that are practical and robust in light of the data that firms have available. Our methods include statistical estimation and internal surveys. The mathematics identify the critical few parameters that need be determined and highlight how to estimate them. Both the measures and the estimation are illustrated in our initial application to a large officeequipment firm. The metrics thermostat suggests that this firm has about the right emphasis on timeto- market, but has overshot on platform reuse and has lost its focus on customer satisfaction. We describe how the firm reacted to the recommendations and changed its organization. We describe additional ongoing applications with the US Air Force, the US Navy, and a major automobile and truck manufacturer.

Fast Polyhedral Adaptive Conjoint Estimation

Tue, 29 Jan 2002 22:58:59 GMT

Title: Fast Polyhedral Adaptive Conjoint Estimation

Authors: Olivier, Toubia; Duncan, Simester; John, Hauser

Abstract: We propose and test a new adaptive conjoint analysis method that draws on recent polyhedral âinterior-pointâ developments in mathematical programming. The method is designed to offer accurate estimates after relatively few questions in problems involving many parameters. Each respondentâs ques-tions are adapted based upon prior answers by that respondent. The method requires computer support but can operate in both Internet and off-line environments with no noticeable delay between questions. We use Monte Carlo simulations to compare the performance of the method against a broad array of relevant benchmarks. While no method dominates in all situations, polyhedral algorithms appear to hold significant potential when (a) metric profile comparisons are more accurate than the self-explicated importance measures used in benchmark methods, (b) when respondent wear out is a concern, and (c) when product development and/or marketing teams wish to screen many features quickly. We also test hybrid methods that combine polyhedral algorithms with existing conjoint analysis methods. We close with suggestions on how polyhedral methods can be used to address other marketing problems.

Application and Test of Web-based Adaptive Polyhedral Conjoint Analysis

Sat, 29 Dec 2001 22:58:59 GMT

Title: Application and Test of Web-based Adaptive Polyhedral Conjoint Analysis

Authors: Dahan, Ely; Hauser, John; Simester, Duncan; Toubia, Olivier

Abstract: In response to the need for more rapid and iterative feedback on customer preferences, researchers are developing new web-based conjoint analysis methods that adapt the design of conjoint questions based on a respondentâs answers to previous questions. Adapting within a respondent is a difficult dy-namic optimization problem and until recently adaptive conjoint analysis (ACA) was the dominant method available for addressing this adaptation. In this paper we apply and test a new polyhedral method that uses âinterior-pointâ math programming techniques. This method is benchmarked against both ACA and an efficient non-adaptive design (Fixed). Over 300 respondents were randomly assigned to different experimental conditions and were asked to complete a web-based conjoint exercise. The conditions varied based on the design of the con-joint exercise. Respondents in one group completed a conjoint exercise designed using the ACA method, respondents in another group completed an exercise designed using the Fixed method, and the remaining respondents completed an exercise designed using the polyhedral method. Following the conjoint exer-cise respondents were given $100 and allowed to make a purchase from a Pareto choice set of five new-to-the-market laptop computer bags. The respondents received their chosen bag together with the differ-ence in cash between the price of their chosen bag and the $100. We compare the methods on both internal and external validity. Internal validity is evaluated by comparing how well the different conjoint methods predict several holdout conjoint questions. External validity is evaluated by comparing how well the conjoint methods predict the respondentsâ selections from the choice sets of five bags. The results reveal a remarkable level of consistency across the two validation tasks. The polyhe-dral method was consistently more accurate than both the ACA and Fixed methods. However, even better performance was achieved by combining (post hoc) different components of each method to create a range of hybrid methods. Additional analyses evaluate the robustness of the predictions and explore al-ternative estimation methods such as Hierarchical Bayes. At the time of the test, the bags were proto-types. Based, in part, on the results of this study these bags are now commercially available.

The Virtual Customer

Wed, 28 Nov 2001 22:58:59 GMT

Title: The Virtual Customer

Authors: Hauser, John; Dahan, Ely

Abstract: Communication and information technologies are adding new capabilities for rapid and inexpensive customer input to all stages of the product development (PD) process. In this article we review six web-based methods of customer input as examples of the improved Internet capabilities of communication, conceptualization, and computation. For each method we give examples of user-interfaces, initial applications, and validity tests. We critique the applicability of the methods for use in the various stages of PD and discuss how they complement existing methods. For example, during the fuzzy front end of PD the information pump enables customers to interact with each other in a web-based game that provides incentives for truth-telling and thinking hard, thus providing new ways for customers to verbalize the product features that are important to them. Fast polyhedral adaptive conjoint estimation enables PD teams to screen larger numbers of product features inexpensively to identify and measure the importance of the most promising features for further development. Meanwhile, interactive web-based conjoint analysis interfaces are moving this proven set of methods to the web while exploiting new capabilities to present products, features, product use, and marketing elements in streaming multimedia representations. User design exploits the interactivity of the web to enable users to design their own virtual products thus enabling the PD team to understand complex feature interactions and enabling customers to learn their own preferences for new products. These methods can be valuable for identifying opportunities, improving the design and engineering of products, and testing ideas and concepts much earlier in the process when less time and money is at risk. As products move toward pretesting and testing, virtual concept testing on the web enables PD teams to test concepts without actually building the product. Further, by combining virtual concepts and the ability of customers to interact with one another in a stock-market-like game, securities trading of concepts provides a novel way to identify winning concepts. Prototypes of all six methods are available and have been tested with real products and real customers. These tests demonstrate reliability for web-based conjoint analysis, polyhedral methods, virtual concept testing, and stock-market-like trading; external validity for web-based conjoint analysis and polyhedral methods; and consistency for web-based conjoint analysis vs. user design. We report on these tests, commercial applications, and other evaluations.