M.J. Smith and G. Salvendy (Eds.): Human Interface, Part I, HCII 2009, LNCS 5617, pp. 227–232, 2009. © Springer-Verlag Berlin Heidelberg 2009 How to Learn from Intelligent Products; The Structuring of Incoherent Field Feedback Data in Two Case Studies Renate de Bruin, Yuan Lu, and Aarnout Brombacher Eindhoven University of Technology, Department of Industrial Design, Business Process Design Group, Den Dolech 2, 5600 MB Eindhoven, The Netherlands {R.d.Bruin,Y.Lu,A.C.Brombacher}@tue.nl Abstract. A growing number of products - particularly highly innovative and intelligent products - are being returned by customers, while analysis shows that many of these products are in fact functioning according to their technical specifications. Product developers are recognizing the need for information that gives more detail about the reason for these product returns, in order to find the root cause of the problems. Traditionally a lot of information from the field is stored in departments like sales and service (helpdesks and repair centers). Combining these data sources with new field feedback data sources, like cus- tomer experiences on the internet and product log files, could provide product developers with more in-depth and accurate information about the actual prod- uct performance and the context of use. Case studies were done at two different industries: a company from consumer electronic industry and a company from professional medical system industry. The Maturity Index on Reliability (MIR) method, a method to assess capability for businesses to respond to product reli- ability related issues, was combined with Contextual Design, a method for user context mapping and requirement definition, and explored as a means to ana- lyze the structure and capability of the current field feedback process in sup- porting the development of complex and innovative products . Keywords: Field Feedback Data, Product Failure, Root Cause Analysis, Busi- ness Information Flow, MIR Method, Contextual Design. 1 Introduction A vast and growing number of products are being returned by customers, while analy- sis shows that many of these products fully function according to their technical specifications [1, 2]. There are several trends in product development and user eman- cipation that may contribute here [1, 3, 4], the fact is that a lot has changed since the beginning of the digital era. First of all the products themselves have changed tre- mendously. What first were simple, mono-functional products have become complex, multi-functional and adaptive products (take for example the remote-less television of the 70s and compare this with the totally adaptive digital television of today). Sec- ondly the product development organizations have changed from having simple, monolithic business chains to complex, multi party chains as they have been driven by logistic efficiency [5].The consequences of these changes have been that;