Conjoint Analysis Technique

After processes are documented, they have to become as fast, efficient, and flawless as possible. This means you optimize the processes that generate all the value for your new solution. Several techniques will help you do this, but you should start with Measurement Systems Analysis, because it ensures the validity of any data you use in optimization studies (see the Design of Experiments, and Conjoint Analysis techniques). Then use Work Cell Design and Mistake Proofing to optimize the layout of people, machines, materials, and other factors in an office or factory. 

Conjoint Analysis is a simplified experimental technique for determining the best combination of attributes to include in a product or service design—Abased on the tradeoffs customers are willing to make. For example, you could have a new laptop computer that gives more benefits and costs less than what competitors offer. But before you release it you might want to find out what customers prefer in terms of the product s attributes, and what price they are willing to pay for them. 

InteUiQuest (1990), Conjoint Analysis A Guide for Designing and Integrating Conjoint Studies, Marketing Research Technique Series Studies, American Marketing Association, Market Research Division, TX. 

Conjoint analysis (CA) is one of the most powerful techniques available for qualifying patient or physician preference and satisfaction (Ryan and Farrar 2000 Ryan et al. 2008). It provides a structured framework to elicit preferences that consists of the following steps ... 

Apply appropriate forecast techniques for New Products (e.g., Regression, Market Research, Sales Forecast, Conjoint Analysis)... 

Conjoint analysis and related techniques are directly relevant to the marketing-operations interface because (1) they address the trade-off between customer satisfaction, which determines an upper-bound on product price, and the pro-duction/distribution cost of the product, and (2) they facilitate acquisition of empirical evidence to evaluate operational strategies. For instance, Lindsley et al., 1991 used conjoint analysis to quantify the tradeoffs that retailers are willing to make among price discoimt, speed of delivery, delivery reliability, number of titles carried in inventory, offered by book distributors. The customer satisfaction equation, estimated by the authors, suggests that a decrease in the discount rate of 0.38% offsets a one-day reduction in delivery time and an increase of 1% title filling rate saves 0.16% discount rate. The equation... 

The inclusion of external use/need knowledge is also one of the main issues of marketing science (Hauser et al. 2006), and remains a remarkable challenge for research and practice (Marketing Science Institute 2010). This task can be attributed to marketing research in organizations (McDaniel and Gates 2008). Many different methods have been developed to assess customer needs, which can be broadly divided Into quantitative (conjoint analysis, quality function deployment) and qualitative techniques (focus interviews, consumer workshops). All of these methods rely on the assumption that users or consumers have the ability to articulate or express their needs. Yet this is only possible for those needs, of which customers are aware themselves. Latent needs, which are crucial for the development of new product, cannot be acquired via these techniques, as they cannot be made explicit by users (Narver et al. 2004). 

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