Determining job complexity in an engineer to order environment for due date estimation using a proposed framework

Abstract

The engineer to order (ETO) environment is a common operating strategy found in industry today. ETO is a growing strategy as customers are increasingly demanding personalized solutions. In ETO, the engineering process is the largest controllable consumer of lead-time consuming one half of the total. A critical process is to determine engineering complexity for purposes of flow time prediction. One distinguishing factor of ETO is that each product is the culmination of a unique design prepared for a particular customer order. The only information available is limited to that which has been gathered during the quoting stage. Hence, the question becomes how does one determine the job difficulty in a complex transactional process when the job has not even been designed yet? This paper presents the results of a study that was conducted in conjunction with multiple ETO firms to identify factors which drive complexity in the engineering environment. One important application of these complexity factors is as a potential input to the accurate prediction of flow times. This paper presents a framework for using these complexity factors to predict ETO engineering flow times.